THE PSYCHOLOGY OF MODERN PREJUDICE
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THE PSYCHOLOGY OF MODERN PREJUDICE
MELANIE A. MORRISON AND
TODD G. MORRISON EDITORS
Nova Science Publishers, Inc. New York
Copyright © 2008 by Nova Science Publishers, Inc.
All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA The psychology of modern prejudice / Melanie A. Morrison, Todd G. Morrison (editors). p. cm. Includes bibliographical references and index. ISBN 978-1-60876-253-8 (E-Book) 1. Prejudices. I. Morrison, Melanie, 1949- II. Morrison, Todd G. BF575.P9P785 2008 303.3'85--dc22 2008023098
Published by Nova Science Publishers, Inc.
New York
CONTENTS Preface Chapter 1
Chapter 2
vii And So the Pendulum Swings: A Framework for Conceptualizing the Causes of Prejudice Becky L. Choma and Gordon Hodson Cognitive Consistency and the Relation between Implicit and Explicit Prejudice: Reconceptualizing Old-Fashioned, Modern and Aversive Prejudice Paula M. Brochu, Bertram Gawronski and Victoria M. Esses
1
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Chapter 3
Political Orientation and Contemporary Racism in America Helen C. Harton and Paul R. Nail
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Chapter 4
The Relationship between Modern and Implicit Prejudice John E. Edlund and Jeremy D. Heider
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Chapter 5
Measuring Racial Prejudice in A Multiracial World: New Methods and New Constructs Khaya D. Clark and Chuck Tate
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Assessing Implicit Cognitions with a Paper-Format Implicit Association Test Kristi M. Lemm, Kristin A. Lane, David N. Sattler, Saera R. Khan and Brian A. Nosek Feature-Based Gender Stereotyping: Beyond Categorization and Control? Sabine Sczesny and Sei Jin Ko Singlism – Another Problem that Has No Name: Prejudice, Stereotypes and Discrimination Against Singles Wendy L. Morris, Bella M. DePaulo, Janine Hertel and Lindsay C. Taylor Implicit Pride and Prejudice: A Heterosexual Phenomenon? Claire Cullen and Dermot Barnes-Holmes
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123
147
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vi Chapter 10
Chapter 11
Chapter 12
Contents Modern Heterosexism and Social Dominance Orientation: Do Subdomains of Heterosexism Function as Hierarchy-Enhancing Legitimizing Myths? N. Eugene Walls Modern Rape Myths: The Acceptance of Modern Myths about Sexual Aggression (AMMSA) Scale Friederike Eyssel and Gerd Bohner Old-Fashioned and Modern Prejudice toward Aboriginals in Canada Melanie A. Morrison, Todd. G. Morrison, Rebecca L. Harriman and Lisa M. Jewell
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About the Authors
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Index
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PREFACE The purpose of this volume is to highlight recent theoretical and methodological advances in the psychological study of stereotyping, prejudice, and discrimination. To this end, the first chapter by Becky Choma and Gordon Hodson (“And so the Pendulum Swings: A Framework for Conceptualizing the Causes of Prejudice”) details an innovative pendulum framework, which uses two relatively orthogonal dimensions (the perceived situational/personal determinants of prejudice and prejudice as a normal/pathological construct) to create four quadrants. Key theories and individual difference variables that fall into each quadrant are discussed. The second chapter (“Cognitive Consistency and the Relation between Implicit and Explicit Prejudice: Reconceptualizing Old-fashioned, Modern, and Aversive Prejudice”), written by Paula Brochu, Bertram Gawronski, and Victoria Esses, provides compelling evidence that perceptions of discrimination and the strength of nonprejudicial goals have implications for the association between implicit and explicit indicants of prejudice. In chapter three (“Political Orientation and Contemporary Racism in America”), Helen Harton and Paul Nail review some of the studies they have conducted which offer support for an integrated model of modern and aversive racism. In the next chapter written by John Edlund and Jeremy Heider (“The Relationship between Modern and Implicit Prejudice”), key findings from the authors’ research underscore the importance of taking into consideration individual difference variables such as internal and external motivations to control prejudice. Advances in measurement are provided by several contributors. Specifically, in chapter five, Khaya Clark and Chuck Tate (“Measuring Racial Prejudice in a Multiracial World: New Methods and New Constructs”) detail a measure of racial prejudice that moves beyond ingroup favoritism and outgroup derogation and, in so doing, is better able to capture the complexity of ingroup/outgroup attitudes. Kristi Lemm, Kristin Lane, David Sattler, Saera Khan, and Brian Nosek (“Assessing Implicit Cognitions with a Paper-Format Implicit Association Test” – Chapter 6) test the validity of various scoring procedures for paperformat IAT data and provide critical evidence suggesting that, when used with verbal stimuli, this method is a reasonable substitute for the computer-based IAT. The remaining chapters share the common feature of extending the psychological study of stereotyping, prejudice and discrimination to oft-neglected social categories (e.g., single people or Aboriginal Canadians) or to neglected elements of commonly studied groups. In reference to the latter point, Sczesny and Ko (Chapter 7: “Feature-based Gender Stereotyping: Beyond Categorization and Control?”) review a series of intriguing studies which demonstrate that gender-typed features such as hair length, scent, and vocal intonation exert
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greater influence on person perception than whether one is male or female. In a review of the literature, Wendy Morris, Bella DePaulo, Janine Hertel, and Lindsay Taylor (Chapter 8: “Singlism – Another Problem that has No Name: Prejudice, Stereotypes, and Discrimination against Singles”) document the negativity – both attitudinal and behavioural – that surrounds individuals who are single and stress the need for more research on this social group. Chapters 9 and 10 highlight some of the interesting work that is being conducted on attitudes toward sexual minorities. Claire Cullen and Dermot Barnes-Holmes (“Implicit Pride and Prejudice: A Heterosexual Phenomenon?”) summarise published research on implicit attitudes toward gay men and lesbian women and outline a promising new technique, the Implicit Relational Assessment Procedure (IRAP). Similarly, within the domain of explicit measurement, Eugene Walls (“Modern Heterosexism and Social Dominance Orientation: Do Subdomains of Heterosexism Function as Hierarchy-enhancing Legitimizing Myths?”) provides evidence attesting to the psychometric soundness of a multidimensional scale of homonegativity. The last two chapters also outline instruments that will prove advantageous to social scientists. Chapter 11 (“Modern Rape Myths: The Acceptance of Modern Myths about Sexual Aggression [AMMSA] Scale”), which is written by Friederike Eyssel and Gerd Bohner, describes the construction and validation of the AMMSA scale. The authors’ findings suggest that this instrument may be more appropriate for certain populations (e.g., college students) than measures that are more “old-fashioned.” Finally, in Chapter 12 (“Oldfashioned and Modern Prejudice Toward Aboriginals in Canada”), Morrison, Morrison, Harriman, and Jewell reveal that, despite being subject to extensive stereotyping, prejudice, and discrimination, Aboriginal Canadians have received scant attention from social psychologists. The authors then outline the development and preliminary validation of two scales designed to assess old-fashioned and modern prejudice toward this social group.
In: The Psychology of Modern Prejudice Editors: Melanie A. Morrison and Todd G. Morrison
ISBN 978-1-60456-788-5 © 2008 Nova Science Publishers, Inc.
Chapter 1
AND SO THE PENDULUM SWINGS: A FRAMEWORK FOR CONCEPTUALIZING THE CAUSES OF PREJUDICE Becky L. Choma and Gordon Hodson Brock University, Canada
ABSTRACT The goal of the present chapter is to propose a framework for conceptualizing the multifaceted causes of prejudice. We briefly review historical trends and dominant themes in the prejudice literature. We then present our Pendulum Framework, which conceptualizes the causes of prejudice along two relatively orthogonal dimensions (Normal vs. Abnormal; Person/Individual Differences vs. Situation/Group), partitioning theoretical camps into four main quadrants. Using this framework as a guide, we reflect on perspectives and empirical evidence of past and contemporary prejudice research within each quadrant. Rather than provide exhaustive or authoritative analyses, our discussion highlights examples of typical research and theory representative of each quadrant. Finally, we conclude with a critique of our framework and offer suggestions for future research in light of the Pendulum Framework. We argue that no particular perspective is inherently superior to others, instead recognizing that the goal of science is to understand phenomena.
“The pendulum of the mind oscillates between sense and nonsense, not between right and wrong.” Jung (1963)
INTRODUCTION Like a pendulum, themes emphasized by prejudice researchers concerning the causes of prejudice have shifted to reflect both societal and academic milieux. Previous researchers have offered in-depth historical analyses of the causes of prejudice and approaches adopted to
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study these intergroup biases (e.g., Dovidio, 2001; Duckitt, 1992), and will not be reiterated in detail here. According to Dovidio (2001), the study of prejudice may be classified into three “waves.” During the first wave, theorists conceptualized prejudice as pathological (e.g., Adorno, Frenkel-Brunswik, Levinson, and Sanford, 1950). That is, prejudice was seen as a consequence of unconscious, largely psychodynamic processes, such as projection and the displacement of hostility (Ackerman and Jahoda, 1950; Dollard, Doob, Miller, Mowrer, and Sears, 1939). During this period, prejudice was predominantly understood as a function of individual differences such as personality dimensions (e.g., authoritarianism; Adorno et al., 1950) and cognitive orientations (e.g., dogmatism; Rokeach, 1954). In contrast, the second wave emphasized normal processing as the root of prejudice (e.g., Tajfel and Turner, 1979). For instance, researchers in the 1960s emphasized adherence to social and cultural norms and interests; in the 1970s, focus shifted to intergroup relations and structural circumstances underpinning prejudice; and in the 1980s and early 1990s, prejudice was perceived as an unfortunate consequence of normal cognitive processes (see Duckitt, 1992). Finally, in Dovidio’s third wave – the contemporary framework for studying prejudice – intergroup bias has become increasingly operationalized as a multidimensional problem. These newer approaches capitalize on research tools that tap both implicit (e.g., implicit association task; IAT) and explicit processes, and devote greater attention to targets (vs. perpetrators) of prejudice (Dovidio, 2001). Overall, historical analyses reveal that the perceived causes of prejudice, and the approaches to understanding them in any given time or place, are greatly affected by social, political, and academic climates (Dovidio, 2001; Duckitt, 1992). It is presumably no coincidence that intergroup contact research flourished after the Civil Rights movement in the U.S., a time when many forms of institutionalized segregation were becoming outlawed. More recently, interest in terror management theory (Rosenblatt, Greenberg, Solomon, Pyszczynski, and Lyon, 1989) has grown exponentially following the terrorist attacks in the U.S. on September 11, 2001. A PsycINFO search reveals that in the 13 years leading up to and including 2001, 106 articles listed “terror management” as keywords. In the five years between 2002 and early 2007, 162 articles met this criterion. This 53% increase over onethird of the time interval prior to 9/11 is particularly remarkable considering publication delays. We believe this trend indicates that researchers have genuinely become more interested in the implications of mortality salience and terrorism for intergroup relations (e.g., Esses, Dovidio, and Hodson, 2002). Thus, not only does the expression of prejudice shift over time (Dovidio, 2001), but the theoretical and empirical themes pursued in the scientific literature reflect attempts to explain intergroup relations in ways that follow cultural events and zeitgeists. Similarly, scientific understandings can produce changes in our social environment (e.g., attitudes toward climate change). The finding that Blacks under-perform on intelligence tests presented as diagnostic of ability or when race is made salient (Steele, 1997) has influenced court rulings on the widely publicized University of Michigan affirmative action program (Lehrman, 2005). Therefore, a useful framework for conceptualizing the causes of prejudice will allow for reciprocal relations between social context and science, and will emphasize key dimensions underlying research efforts. In the next section, we present our framework for conceptualizing the causes of, and approaches to, understanding prejudice.
And So The Pendulum Swings
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Normal Quadrant 2: Threat-Sensitive and Cognitively Rigid People
Quadrant 3: Competitive Contexts and Status Quo Perpetuation
• Representative variables/theories: RWA, SDO, conservatism, intolerance of ambiguity, disgust sensitivity, dogmatism, PNS, Allport's authoritarianism
• Representative variables/theories: SIT, SCT, social cognition, RCT, ITTP, SJT, SDT, aversive, symbolic, & modern racism • Themes: identity, power, competition, system stability motivations, indirect resistance to intergroup egalitarianism
• Themes: individual variation in dominance, submission, cognitive rigidity • e.g., George W. Bush, Fidel Castro
• e.g., institutionalized US racism/sexism; residential desegregation
Person/ Individual Differences
Situation/ Group
• Representative variables/theories: psychodynamic authoritarianism (Adorno et al.), psychopathy, Machiavellianism, mental illness
• Representative variables/theories: TMT, Staub, deindividuation, frustration-aggression link, adverse social conditions, scapegoating
• Themes: personal maladjustment, dysfunctional personality, dysfunctional psychology
• Themes: dehumanization, collective crisis, historical tipping points
• e.g., Manson, Hitler, Kim Jong-il
• e.g., genocide, Rwanda, Nazi Germany, 9/11
Quadrant 1: Maladjusted People
Quadrant 4: Aggravated Conflict and Mortality Contexts Abnormal
Figure 1. A theoretical framework for conceptualizing the dominant themes and trends in prejudice research. ITTP = integrated threat theory of prejudice; PNS = personal need for structure; RCT = realistic group conflict theory; RWA = right wing authoritarianism; SCT = self-categorization theory; SDO = social dominance orientation; SDT = social dominance theory; SIT = social identity theory; SJT = system justification theory; TMT = terror management theory.
The Pendulum Framework As researchers, we should be cognizant of the social climate, both academic and cultural, within which we pose our questions and interpret our findings. As emphasis on the causes of prejudice shifts over time, a framework highlighting shifts in dominant themes would serve as
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a useful tool for discerning our understanding of prejudice. The framework is intended to serve multiple functions: 1) provide a descriptive organization of prejudice research and theory; 2) operate as a tool for conceptualizing how different areas of prejudice research and theory inform one another and our understanding of prejudice; and 3) orient prejudice researchers as a meta-cognitive tool by encouraging them to think about what prejudice researchers are thinking about in this research domain. The Pendulum Framework is organized along two relatively independent dimensions that capture dominant themes in the prejudice literature: Abnormal versus Normal and Person/Individual Differences versus Situation/Group. The first dimension, Abnormal versus Normal, represents the extent to which prejudice is conceptualized as a consequence of conditions or processes that are characterized as “pathological” or as falling within the “normal” range of functioning. For example, whereas Adorno et al. (1950) used a psychodynamic perspective to argue that prejudice can be conceptualized as displaced aggression resulting from repressed anger toward one’s punitive parents, Tajfel and Turner (1979) maintained that prejudice is an unfortunate outcome of normal group functioning (e.g., striving for positive self-esteem through positive group distinctiveness). The second dimension, Person/Individual Differences versus Situation/Group, represents the extent to which the theoretical roots of prejudice are person-based or emphasize group, situational, or contextual factors. Altemeyer’s (1981, 1996) Right-Wing Authoritarianism (RWA) construct emphasizes personality and ideology, wherein social factors play a more distal role in personality development. His analysis clearly places the person first as a prime cause of prejudice. Staub (1989, 1996), on the other hand, emphasizes adverse cultural and societal conditions as factors contributing to prejudice. He argues that adverse conditions (e.g., economic hardship) foster psychological processes such as scapegoating and dehumanization of outgroups that can, in turn, result in extreme intergroup discrimination including genocide. These cross-cutting dimensions categorize dominant themes into four quadrants that vary along the two dimensions. We have labeled these quadrants Maladjusted People, ThreatSensitive and Cognitively Rigid People, Competitive Contexts and Status Quo Perpetuation, and Aggravated Conflict and Mortality Contexts (see Figure 1). Within this framework, the “location” of a dominant prejudice explanation is designated by a pendulum. We propose that the location of the pendulum shifts in response to social and historical contexts, and also to academic trends and foci that are sometimes out of sync with social trends. In other words, the pendulum is perceived to be located within a three-dimensional space in which it can swing or flip from one quadrant to another, not necessarily in a linear manner. The pendulum is presumably in constant flux or swing, but is likely slow moving, requiring pressure or force to change direction. For instance, the pendulum may shift with the advancement or acceptance of statistical methods (e.g., Baron and Kenny, 1986; Spencer, Zanna, and Fong, 2005), technology (e.g., implicit measures, DNA testing), influential theoretical advances (e.g., Brewer, 1979; Gaertner and Dovidio, 1986; Tajfel and Turner, 1979), changes in social norms (e.g., IQ-race research), and “current” events (e.g., 9/11, WWII, Hurricane Katrina). In the following sections, we consider past and contemporary research and theory on prejudice characteristic of each quadrant. We first consider the notion that prejudice represents psychological dysfunction within particular individuals.
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Quadrant 1: Maladjusted People Early scientific thinking about prejudice emphasized psychopathologies, abnormalities, and maladjustments residing within the individual (e.g., Adorno et al., 1950; Jahoda, 1960). Many researchers adopted a clinical focus and concentrated on identifying dysfunctional characteristics of those individuals likely to be prejudiced. It is not surprising that psychodynamic theory played a dominant role in shaping prejudice research given its prominence in the field of psychology at the time. Borrowing from psychodynamic theory, unconscious processes such as defense mechanisms were forwarded as explanations for prejudice (e.g., Ackerman and Jahoda, 1950; Dollard et al., 1939). For example, prejudicial attitudes were posited to serve ego defensive functions by projecting unwanted thoughts or feelings about the self (e.g., lazy) onto outgroups such as Jews and African Americans (Jahoda, 1960). Some aspects of psychodynamic theory have provided successful explanations of particular prejudices. Adams, Wright, and Lohr (1996) investigated whether latent homosexuality (i.e., unrecognized, repressed, and denied homosexual arousal) can account for homophobic attitudes. In their study, homophobic men exhibited significantly greater sexual arousal, as measured physiologically, to a male homosexual erotic video than did nonhomophobic participants. These findings support the psychodynamic notion that homophobia serves as a defensive reaction to underlying homosexual arousal. Building on psychodynamic theory, Adorno et al. (1950) attempted to formalize the study of authoritarianism, and placed strong emphasis on individual differences. This approach characterized the authoritarian personality as a syndrome, with authoritarians being prone to conventionality, aggression, submission, destruction, cynicism, and prejudice. Adorno and colleagues asserted that an ‘authoritarian personality’ was the outcome of displaced hostility and aggression originating from repressed anger at a punitive parental authority. This pathological personality orientation, measured by the Fascism-Scale, predicted prejudice toward a variety of groups. The discovery of a generalized ethnocentrism represents a major contribution by this theoretical approach. Demonstrating that individuals who dislike one outgroup generally dislike other outgroups firmly established the importance of stable individual difference factors in generating prejudice. Although Adorno and his colleagues made significant contributions to the literature, their work has been widely criticized (e.g., Altemeyer, 1981; Christie and Jahoda, 1954). The Fascism-Scale, in particular, was criticized for its poor psychometric properties (Altemeyer, 1981). Overall, support for a psychodynamic explanation of prejudice and for approaches building on this theoretical framework is sparse, inconsistent, and inconclusive. Although these approaches offer rich and interesting accounts of prejudice, they are convoluted, lack parsimony, and suffer from unfalsifiability (Altemeyer, 1996). Psychodynamic and related clinical approaches also fail to account for institutionalized systemic prejudice or prejudice in the general population. That is, by focusing on individuals with psychopathologies and dysfunctions that represent only a small proportion of the population, their generalizability is limited. Despite some limitations, the Maladjusted People theme has advanced our understanding of prejudice. In particular, themes such as fearfulness, insecurity, and threat remain theoretically important to understanding prejudice (e.g., Altemeyer, 1996; Duckitt, 2005). In addition, recent research demonstrates that individuals denying unpleasant characteristics about the self project these traits onto other groups (Newman and Caldwell,
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2005). Further, individuals high in (largely irrational) interpersonal disgust sensitivity are higher in prejudice, mediated by ideological orientations rooted in authoritarianism (Hodson and Costello, 2007). Similarly, Compulsive-Dependent personality disorder affects prejudice through its relation to authoritarianism (Schlachter and Duckitt, 2002). Thus, the relation between clinical dysfunction and prejudice may be indirect, channeled through threatsensitive ideological variables such as authoritarianism and social dominance that are not clinical in nature (see Quadrant 2).
Summary: Themes and Interventions The dominant themes in this quadrant reflect personal maladjustment, dysfunctional personality, and dysfunctional psychology more generally. Here the roots of prejudice are situated within a specific minority of the population. Examples of such prejudiced and xenophobic individuals might include Charles Manson1, Adolf Hitler, and Kim Jong-il. Treatment programs based on this approach naturally emphasize therapeutic and clinical solutions. For instance, systematic desensitization has been used to treat highly prejudiced Whites, improving impressions of traits stereotypically associated with Blacks (Sappington, 1976).
Quadrant 2: Threat-Sensitive and Cognitively Rigid People Although early scientific explanations of prejudice focused heavily on pathological causes, contemporary approaches predominantly emphasize individual differences between people in the normal range of human functioning, including ideology (Altemeyer, 1998; Heaven and St. Quintin, 2003; Pratto, Sidanius, Stallworth, and Malle, 1994), personality (Duriez and Soenens, 2006; Ekehammar, Akrami, Gylje, and Zakrisson, 2004; Flynn, 2005), cognitive styles (Cornelis and Van Hiel, 2006; Hodson and Sorrentino, 2001; Neuberg and Newsom, 1993), and emotions (Hodson, 2008; Hodson and Costello, 2007; Smith and Mackie, 2005). The literature discussed in this quadrant represents theory and research that typically conceptualizes the causes of prejudice as a function of normal individual differences or person-based factors. Like Adorno et al. (1950), Allport (1954) proposed that personality can generate prejudice. However, his description of the prejudiced personality departed from the psychodynamic approach in noteworthy ways (for a contemporary analysis, see Duckitt, 2005). Allport suggested that authoritarianism encompassed beliefs that people are inherently bad and that the world is dangerous. The emphasis here is on fearfulness, insecurity, and threat-fuelled authoritarianism rather than displaced hostility and repression. An authoritarian’s fearfulness, insecurity, and threat were argued to result in cognitive traits such 1
Charles Manson, the cult leader on death-row for his role as a ring-leader in several murders, preached that a race war in the U.S. was imminent in the late 1960s and early 1970s. He and his followers planned to spark this race war while isolating themselves in the desert, expecting the Black population to be victorious but soon finding themselves in need of a strong White leader (such as Manson) to govern in the aftermath of war. Central to this plan was the prejudiced belief that Blacks are too violent and unintelligent to govern themselves.
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as rigidity and intolerance of ambiguity. Similarly, Rokeach (1954) maintained that a rigid cognitive orientation, particularly dogmatism, was a primary trait related to prejudice.2 Right-wing authoritarianism (RWA) and social dominance orientation (SDO) are probably the most widely studied, reliable, and strongest individual difference predictors of prejudice to date (Altemeyer, 1998; Duckitt, 2005). Therefore, we will focus on these individual differences as exemplars of this quadrant. Altemeyer (1981) defines RWA as an ideology characterized by three central traits: submission to legitimate authority, aggressiveness, and adherence to social norms and conventions. Whereas Allport (1954) considered authoritarianism the consequence of “underlying insecurity” and an “ego that is crippled” (p. 396), Altemeyer (1981, 1998) emphasizes basic social learning processes. Specifically, RWA is viewed as the result of “training in obedience, conventionalism, and aggression” (1998, p. 48) through basic socialization emphasizing danger and threat (Duckitt, 2005). Individuals high in RWA consistently hold prejudiced attitudes (Alteymeyer, 1981, 1988, 1996, 1998) toward women (Sibley, Wilson, and Duckitt, 2007a), gay and lesbian persons (Altemeyer, 1996; Whitley, 1999), individuals with mental illness (Ekehammar et al., 2004), and ethnic minorities (Esses and Hodson, 2006; Hodson and Esses, 2005). Social dominance orientation is a more recently developed individual difference construct strongly associated with prejudice. According to social dominance theory, evolutionary and societal variables promote ideologies in which people seek to minimize group conflict using legitimizing myths that rationalize the dominance of one group over another (Sidanius and Pratto, 1999). Individuals high in SDO prefer hierarchical (vs. egalitarian) intergroup relations (Pratto et al., 1994). Increased SDO is associated with hostile sexism (Sibley et al., 2007a), negative attitudes toward gay men and lesbian women (Sibley, Robertson, and Wilson, 2006), racism (Altemeyer, 1998; Pratto et al., 1994; Sibley et al., 2006; Sidanius and Pratto, 1999), and ethnic minority prejudice (Esses and Hodson, 2006; Hodson and Esses, 2005). Correlations between RWA and SDO have generally been modest, often ranging between .20 (Altemeyer, 1998; Whitley, 1999) and .40 (Heaven and Bucci, 2001; Hodson and Esses, 2005). This RWA-SDO association varies depending on social and cultural factors; a recent meta-analysis revealed stronger positive relations among RWA and SDO in countries with a strong ideological contrast – a left-right ideological distinction – compared to countries with weaker ideological contrast (Roccato and Ricolfi, 2005). Although there is some evidence that SDO scores may be influenced by strong situational pressures (e.g., Schmitt, Branscombe, and Kappen, 2003), RWA and SDO demonstrate considerable stability across time under normal and consistent testing circumstances (Sibley, Wilson, and Duckitt, 2007b). Moreover, current theorizing directly argues that “there should be systematic variability in SDO and RWA across situations” as motivational goals are sought and met (Sibley et al., 2007b, pp. 367-368 [italics in original]; see also Duckitt, 2001; Sidanius and Pratto, 1999; Sidanius, Pratto, van Laar, and Levin, 2004). Furthermore, it would seem unreasonable to expect ideological orientations, rooted in social attitudes and values, to be rigid and inflexible. First, ideological orientations clearly serve motivational functions for individuals (see Jost, Glaser, Kruglanski, and Sulloway, 2003). The functionality of these orientations would be compromised if operating in isolation from the situation or context. Second, evidence of systematic variation in ideological 2
It should be noted that Rokeach’s Dogmatism Scale has been widely criticized for lacking construct validity, suffering acquiescence bias, and generating questionable results (Altemeyer, 1996).
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orientation as a function of environmental factors or salient cues does not in itself invalidate constructs that are, under ordinary circumstances, fairly stable. For example, the finding that scores on intelligence measures can vary as a function of the instructional set given to participants (Steele, 1997) does not lead most researchers to conclude that the construct of intelligence is pointless, irrelevant, or seriously flawed. Just as most researchers and laypeople recognize that relatively stable individual differences in intelligence scores can be influenced by some random (e.g., amount of sleep) or non-random factors (e.g., cues presenting the test as diagnostic vs. non-diagnostic in an attempt to create or reduce anxiety), it is reasonable to expect ideological orientations such as RWA and SDO to be similarly affected. As with intelligence, this in no way implies that these constructs are seriously flawed or spurious, but rather that they are flexible and responsive to contextual cues, and that these relations warrant investigation. In this way, RWA and SDO walk the fine line between “the person” and “the situation” in their pure theoretical forms. Given that these constructs “are positioned at the interface between personality and social psychology” (Ekehammar et al., 2004, p. 468), it would indeed be surprising if RWA and SDO did not demonstrate both relative stability and some contextual variation. Why so much consideration of these variables? Together, RWA and SDO reliably predict prejudice, typically accounting for approximately 50% of the variance in intergroup attitudes (Altemeyer, 1998; Duckitt, 2005). Although correlated, these constructs are theoretically and empirically distinct.3 For a detailed analysis on the distinction between RWA and SDO, see Altemeyer (1998). Building on these findings, Duckitt (2001, 2005) proposed a dual-process model of personality, ideology and prejudice, in which RWA and SDO differentially predict prejudice from divergent motivational goals. Duckitt argues that personality factors and social conditions affect the adoption of worldviews. Specifically, individuals who strive (chronically or through situational inducement) to maintain security and order adopt a view that the world is dangerous and threatening (which predicts authoritarianism), whereas individuals who strive (chronically or through situational inducement) to maintain group dominance and superiority adopt a view that the world is competitive (which predicts social dominance) (Duckitt, 2001, 2005; Duckitt and Fisher, 2003). Thus, an individual’s worldview may be influenced by both chronic factors (e.g., socialization, personality) and by situational factors. As individuals high in RWA are characteristically motivated to maintain security and order, and view the world as a dangerous and threatening place (Duckitt, 2001), their prejudices are typically directed toward groups (e.g., drug dealers) perceived as threatening or disruptive of social stability (Duckitt, 2006). In contrast, because high SDOs are motivated to maintain group dominance and superiority and view the world as an unforgiving competitive place, their prejudices are directed toward competitive or low status groups (e.g., individuals with physical disabilities) who may challenge the balance of power (Duckitt, 2006). This research qualifies earlier conclusions that individual differences such as authoritarianism predict generalized prejudice (e.g., Allport, 1954). Such findings demonstrate the complex relation between individual differences and social factors as causes of prejudice characteristic of
3
Although SDO is typically a stronger predictor of prejudice than is RWA (Altemeyer, 1998; Whitley, 1999), there is one consistent exception: the prediction of attitudes toward gay men and lesbian women. Meta-analytic tests reveal that RWA is a stronger predictor of homonegativity than is SDO (Whitley and Lee, 2000, Study 1). However, even after controlling statistically for RWA, SDO remains a significant (albeit small) predictor of homonegativity (Whitley and Lee, 2000, Study 2; also re-analysis of Hodson and Costello [2007]).
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Dovidio’s (2001) third wave, factors not easily explained by a simple cause-and-effect model proposed by early researchers (Duckitt, 2005).
Summary: Themes and Intervention The dominant theme in this quadrant concerns individual variation within the normal range of human functioning. In particular, themes of dominance and submission form a “lethal union” (Altemeyer, 1998) fostering intergroup bias. Here the roots of prejudice are located within a sizeable minority of individuals who endorse authoritarian ideologies, with social learning during personality development (Altemeyer, 1996) and societal pressures (Duckitt, 2005; Sidanius and Pratto, 1999) perceived as contributing factors to person-based prejudices. Although we focused on several ideological variables (RWA, SDO), space permitting we would have included other variables related more directly to cognitive rigidity, such as the personal need for structure (Neuberg and Newsom, 1993). These variables are less directly related to prejudice and its correlates (Hodson and Esses, 2005), and may affect prejudice distally through RWA and SDO (Van Hiel, Pandelaere, and Duriez, 2004). Exemplars of such threat-sensitive and cognitively rigid individuals might include George W. Bush and Fidel Castro. Treatment programs are sorely needed to supplement causal theories emanating from this quadrant. Although interventions challenging core intergroup beliefs held by SDOs can backfire (Esses, Dovidio, Jackson, and Armstrong, 2001), focusing the attention of SDOs away from national identity and toward individual identity can eliminate their biases (Danso, Sedlovskaya, and Suanda, 2007). In addition, several studies indicate that increased intergroup contact between White and Black prison inmates is associated with less prejudice among high SDOs (Hodson, 2008). Intriguingly, the effect of contact on attitudes was mediated through elevated intergroup empathy among socially dominant individuals, suggesting that inducing empathy-related emotions might prove fruitful in reducing prejudice among such people. More research is needed to explore methods to reduce bias among authoritarian and socially dominant individuals that do not irritate their threat-sensitive predispositions.
Quadrant 3: Competitive Contexts and Status Quo Perpetuation Social psychologists studying prejudice have maintained a strong focus on the power of the social situation. In this quadrant, we consider two topics common in the literature: 1) groups perceive themselves in competition with one another, and 2) groups have vested interests in maintaining the structural status quo. We turn first to the topic of perceived intergroup competition. Realistic Group Conflict Theory (LeVine and Campbell, 1972; Sherif, 1966) emphasizes that groups compete over real and tangible resources, such as access to material assets, employment, and health care. Groups also can compete for power and money that grant access to tangible resources. Overall, an outgroup can pose “realistic” threats if seen to block access to resources or threaten the physical/mental welfare of ingroup members. When group-
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level goals are perceived to be incompatible4, intergroup tensions and hostility ensue, entrenching group boundaries and exacerbating prejudices. Social Identity Theory (Tajfel, 1969; Tajfel and Turner, 1979) introduced the concept that groups also may invest in social identity concerns. In particular, these theorists argue that groups compete for positive and distinct social identities. From this perspective, people identify themselves along a continuum ranging from personal (“me”) to social (“us”), using these identities to enhance positive esteem. Thus, group members enhance the evaluations and/or positive distinctiveness of their ingroup in ways that benefit the self or ingroup. Even in “minimal” or arbitrary groups with no history, group members have been shown to positively evaluate and favor ingroups over outgroups (see Brewer, 1979), although this is true for some individuals more than others (Hodson and Sorrentino, 2001). For instance, those strongly identifying with such ad hoc groups are more likely to allocate positive outcomes to ingroup than outgroup members (Hodson, Dovidio, and Esses, 2003). Self-Categorization Theory (Turner, Hogg, Oakes, Reicher, and Wetherell, 1987), an outgrowth of Social Identity Theory, de-emphasized motivational concerns. This approach stressed the role of categorization processes in group behavior, demonstrating that people act and think more in terms of group membership when group categories are salient, accentuating between-group differences and minimizing within-group differences. In short, social construals of self and others become activated and influence attitudes and behaviors such as prejudice and discrimination. These approaches have successfully explained prejudice and other group phenomena, and have provided the foundations for other theoretical perspectives (e.g., Gaertner and Dovidio, 2000). For the most part, the theories discussed above conceive of group behavior, including prejudice and discrimination, as natural, meaningful, and normal. Somewhat in contrast, the social cognition approach dominant in the 1980s often emphasized micro-level cognitive processes focusing on errors, including failures to attend to base-rates, attribution errors, overuse of schemas, expectancies, and construct accessibility (for reviews, see Fiske and Taylor, 1991; Kunda, 1999). For example, Hamilton and Gifford’s (1976) research on illusory correlations demonstrates that inaccurate negative impressions about numerical minority groups can form through basic cognitive processes having nothing or little to do with groups or intergroup history. Others suggest that stereotypes can serve as mental shortcuts or heuristics utilized when mentally taxed. For instance, Bodenhausen (1990) found increased intergroup bias among people who reportedly function best early in the day (“morningpeople”) when tested in the evening, and increased bias among “evening-people” when tested in the morning. Thus, stereotypes can assist a busy mind by providing group-level information that circumvents the need for mentally demanding individuated information. Regardless of the positive or negative emphasis placed on intergroup processes covered in this section, a common contemporary theme has emerged. Whether intergroup biases are conceptualized as resulting from faulty reasoning based on the limits of cognitive processing abilities, or from meaningful modes of processing information about social groups, these processes are argued to fall within the range of normal (vs. abnormal) processing (Dovidio, 2001; see also Nelson, 2006).
4
It should be noted that Realistic Group Conflict Theory stresses perceived (not actual) competition and goal incompatibility.
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Increasingly, researchers are recognizing that seemingly divergent approaches to understanding prejudice have much in common and can benefit when bridges stretch across theoretical camps. Indeed, social identity and social cognition approaches have become increasingly integrated (see Abrams and Hogg, 1999). In recent years, we also have witnessed a resurgence of interest in group threat, both realistic (tangible) and symbolic (non-tangible; e.g., values, cultural dominance, group worldview). Following the 9/11 attacks, perceived realistic and symbolic threats from immigrants (and physical safety threats from MiddleEasterners) predicted increased support for restrictive public policies to protect the national ingroup in Canada and the U.S., notably decreased immigration levels and use of stringent origin-restricted immigration rules (Hodson, Esses, and Dovidio, 2006). The Integrated Threat Theory of Prejudice (Stephan and Stephan, 2000) proposes that outgroups can pose not only realistic or symbolic threats, but also intergroup anxiety threats (feeling awkward or embarrassed when interacting with other groups) or stereotype threats (anticipated negative outcomes from outgroup interactions). A recent meta-analysis confirms the independent importance of these four group threats, in total accounting for one-third of the variance in intergroup attitudes (Riek, Mania, and Gaertner, 2006). Importantly, groups can objectively pose threats (realistic or symbolic), be perceived as posing threats, or both. Emphasizing the perception of group threat, some theorists may alternatively choose to situate intergroup threats at the personal (vs. situational) end of the continuum we propose. After all, compared to less prejudiced people in the same situation, high SDOs perceive heightened realistic and symbolic threats from other groups (e.g., Esses, Hodson, and Dovidio, 2003). However, we have situated group threats in this particular quadrant (Competitive Contexts and Status Quo Perpetuation) due to the clear social and intergroup implications of these constructs, and because the literature historically considers them to be situational variables (e.g., Riek et al., 2006). Other perspectives belonging to this quadrant concern the maintenance of the status quo and resistance to change at a macro level. Social Dominance Theory (Sidanius and Pratto, 1999) emphasizes both personal (e.g., SDO) and structural elements in promoting intergroup dominance and prejudice. From this perspective, human societies are hierarchically arranged according to cultural, political, and structural demands; support for these hierarchies takes the form of “legitimizing myths” that serve to perpetuate existing hierarchies, particularly among those in dominant group positions (Sidanius and Pratto, 1999; see also Esses and Hodson, 2006). A related but distinct approach is offered by System Justification Theory (Jost and Banaji, 1994; Jost, Banaji, and Nosek, 2004). Jost and colleagues similarly argue that dominant groups are interested in maintaining social hierarchies, but add an interesting twist: subordinate groups also endorse intergroup inequality, perhaps even more so than dominant groups (Jost et al., 2004). System justifications are believed to serve personal, group, and system-based goals relevant to esteem and maintaining perceptions that the existing social order is stable, fair and just. Rather than engaging in direct conflict, groups can co-exist and perpetuate systems of inequality. These effects can be quite subtle and, thus, are most detectable on implicit measures (Jost et al., 2004). Moreover, powerful motives underlie these effects. System justification is considered a motive akin to dissonance reduction: people most disadvantaged by “the system” are often the strongest advocates of the very processes that maintain it, presumably because these people “have the most to explain, justify, and rationalize” from a psychological standpoint given that they do not benefit personally (Jost,
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Pelham, Sheldon and Sullivan, 2003, p. 16). Impressively, System Justification Theory can therefore explain, at least in part, why groups often accept low status positions and why outgroup favoritism occurs, topics that have perplexed social psychologists for decades. Jackman (2005) also recognizes that intergroup strife is not necessarily based on hostility and hatred as traditionally assumed (e.g., Allport, 1954). Instead, intergroup behavior is based on “self-interested, rational, political motives” (p. 89) of a competitive nature, whereby dominant groups strive to control subordinate groups within the confines of institutional constraints. This, Jackman (2005) argues, is often best achieved through paternalism and positive outgroup attitudes and behaviors that maintain social systems and keep subordinate groups in disadvantaged positions. Recognizing their disadvantaged and relatively powerless role in this arrangement, low status groups often cooperate with the system to minimize personal costs. Also represented in this quadrant are theories of contemporary prejudice stressing that people are increasingly less willing or able to express their prejudices in social and cultural contexts that look unfavorably upon intergroup bias. Symbolic racists have been described as those who express negative intergroup attitudes indirectly, often via political attitudes that oppose help for minorities, such as affirmative action (Sears, 1988). Modern racists view minority groups as too “pushy” in their rush to equality, consequently getting an unfair share of benefits and resources (McConahay, 1986). Both of these forms of contemporary racism are expressed by people not prejudiced in obvious or direct ways, and are increasingly common among conservatives. In contrast, aversive racism is a form of bias most common among liberals (Gaertner and Dovidio, 1986; Hodson, Dovidio, and Gaertner, 2004). Aversive racists see themselves as unprejudiced and openly endorse egalitarian values of intergroup equality consistent with liberal values in Western democracies. However, personal biases, typically unconscious and unrecognized, often “leak out” in the form of prejudice and discrimination. These biases are more likely when: 1) the context is ambiguous (i.e., where socially correct or appropriate responses are not obvious), or 2) other explanations with non-racial implications can be forwarded. For instance, Dovidio and Gaertner (2000) found that when making hiring decisions about applicants with obviously strong or weak applications, where evidence of racial bias would be blatant, no racial bias emerged. However, when applications with “mixed” qualifications (i.e., some weak and some strong components) were assessed, racial biases in favor of White applicants and against Black applicants were expressed by White participants. In making university admission judgments, criteria are weighted by decisionmakers in these mixed qualification conditions in ways that mask or disguise prejudicial motives (Hodson, Dovidio, and Gaertner, 2002). Also consistent with the aversive racism framework, Whites in a simulated legal context showed no bias against Blacks generally; however, after the introduction of instructions by a judge to disregard questionable DNA evidence, participants gave the benefit of the doubt to a White defendant but strongly punished a Black defendant, presumably operating under the “honorable” auspices of not letting a guilty person go free (Hodson, Hooper, Dovidio, and Gaertner, 2005). In most cases, these racial biases operate independently of self-reported individual differences in prejudice (e.g., Dovidio and Gaertner, 2000; Hodson et al., 2005). Recently, researchers have begun to explore contemporary prejudices against other social groups. These advances are much welcomed in a field that arguably over-examines racial prejudice at the expense of other important intergroup biases. For instance, new scales
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assessing modern attitudes toward gay men and lesbian women demonstrate incremental validity beyond traditional explicit prejudice measures (e.g., Morrison, Kenny, and Harrington, 2005). These new scales also predict intergroup behavior. For example, one study found that participants obtaining higher scores on the Modern Homonegativity Scale sat further from a confederate presumed to be homosexual, but only when this decision could be rationalized by non-homonegative motives (Morrison and Morrison, 2002).
Summary: Themes and Interventions This quadrant is characterized by an emphasis on social and contextual influences falling within the normal range of everyday life. In particular, we have highlighted themes that center on intergroup competition and goal incompatibility, whether realistic (tangible), symbolic (intangible), or involving social identification and distinctiveness. In addition to considering exemplars of these approaches (e.g., Social Identity Theory and the Integrated Threat Theory of Prejudice), we highlighted theories emphasizing motivations for maintaining the status quo (e.g., Social Dominance Theory and System Justification Theory), and explored contemporary approaches (e.g., Aversive Racism) demonstrating that modern societal trends toward egalitarianism conflict with prejudicial thoughts and feelings well-entrenched in society historically. Overall, themes in this quadrant emphasize identity, power, competition, system stability motivations, and indirect resistance to intergroup egalitarianism. We see evidence of these social forces in institutionalized racism/sexism and residential segregation. Fortunately, social psychologists have devoted considerable time and energy to solutions based on the causes stressed in this quadrant. Research on the Contact Hypothesis (Allport, 1954) reveals that increased contact, particularly favorable contact under conditions of intergroup equality accompanied by institutional support, reduces prejudice toward a variety of groups (for a recent meta-analysis, see Pettigrew and Tropp, 2006). Other interventions focus on social identity and categorization processes. For example, the Common Ingroup Identity Model (Gaertner and Dovidio, 2000) emphasizes extending ingroup boundaries to include those formerly categorized as outgroup members by increasing the salience of shared superordinate social categories. This approach capitalizes on natural intergroup processes, harnessing basic psychological tendencies involved in group interactions and redirecting them toward bias reduction.
Quadrant 4: Aggravated Conflict and Mortality Contexts There are examples of extreme behavior by groups or collectives clearly affected by social and contextual influences generally considered outside the normal range. For instance, riots, lynchings, and arguably genocides can be categorized as extreme outcomes representing abnormal or maladaptive group interactions. In this quadrant, we discuss theory and research emphasizing social and contextual factors that facilitate abnormal or dysfunctional processes (e.g., violent scapegoating) in causing prejudice. Social psychologists have generally neglected the causes of prejudice characterizing this quadrant. An early exception is Hovland and Sears’ (1940) classic test of the frustrationaggression hypothesis, wherein frustration from deteriorating economic conditions was
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suggested to foster aggressive acts toward less powerful social scapegoats (i.e., disadvantaged groups). Harsh economic conditions were hypothesized to generate frustration, which then was displaced as aggression toward marginalized groups for whom irrational and underserved aggression is tolerated. On a group or societal level, such aggression often includes collective acts of violence such as riots, mass killings, or genocides. Although Hovland and Sears demonstrated increased lynching of Blacks in the southern U.S. following unfavorable economic trends, subsequent researchers have questioned these findings. For instance, Green, Glaser, and Rich (1998) re-analyzed the original data using more sophisticated statistical analyses and found no consistent support for the frustration-aggression link. Using contemporary data examining the relation between unemployment rates and the frequency of hate crimes (e.g., violence, vandalism, harassment) in New York from 1987 to 1995, Green and colleagues again found no consistent support for the theory. Additional research on lynching has demonstrated that, as the number of aggressors involved increases, the brutality escalates (Mullen, 1986). In his Deindividuation Theory, Zimbardo (1969) argues that social conditions (e.g., anonymity) encourage a state of decreased self-awareness and self-regulation (i.e., “getting lost in the crowd”), leading to behavior that under normal circumstances is considered anti-normative. However, metaanalytic results failed to support this postulation (Postmes and Spears, 1998). Specifically, this review found minimal evidence that deindividuation relates to lowered self-awareness, or that lowered self-awareness leads to anti-normative behavior. Instead, individuals in deindividuating contexts conform to norms of the situation, positive or negative. This pattern is consistent with the Social Identity model of Deindividuation Effects (SIDE; Reicher, Spears, and Postmes, 1995), in which deindividuating conditions facilitate the transition from personal to social identity and adherence to norms associated with that particular identity. In other words, as once unacceptable social beliefs and norms become accepted, attitudes and behaviors such as prejudice and discrimination – especially extreme forms – may become more probable. Importantly, situation- or group-specific norms may be considered antinormative in relation to more general cultural norms. Consequently, Postmes and Spears (1998) would likely propose that deindividuated behavior is better accounted for by theory characteristic of our third quadrant (i.e., deindividuated behavior explained as a normal [not abnormal] process). Insight on potential factors contributing to clearly abnormal social functioning is offered by Staub (1996; Staub and Bar-Tal, 2003). He suggests that extreme forms of prejudice and discrimination originate from adverse social conditions (e.g., economic hardship, political tension, social change, and failure to meet basic human needs) that “give rise to shared psychological reactions and social processes” that ultimately promote bias (Staub and BarTal, 2003, p. 718). Reactions such as scapegoating, strong group identification and dehumanization surface to help meet basic needs, instigating extreme forms of discrimination under certain social and cultural conditions. One prominent example articulated by Staub (1996) is Nazi Germany. After losing WWI, Germany was plagued by social and economic crisis, and in 1933 Hitler’s Nazi party was elected. In this new social context, Jews were devalued and dehumanized, deliberately targeted as scapegoats to account for adverse social conditions. This, in combination with the nationalistic Nazi ideology, fuelled gradually intensifying aggression toward the Jews which culminated in genocide. Thus, intergroup atrocities originate predominately from harsh and often persistent social and cultural conditions (Staub, 1996; Staub and Bar-Tal, 2003).
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One function of social beliefs or cultural worldviews, including irrational or maladaptive beliefs, may be to protect individuals from anxiety about their own death (Terror Management Theory, TMT; Greenberg, Pyszczynski, and Solomon, 1986). TMT research demonstrates that in response to mortality primes, people exhibit negative reactions toward those with opposing worldviews, and increased positive regard for those with similar cultural worldviews (e.g., Greenberg et al., 1990). In coping with their existential fear of death, mass populations often cling to their existing leaders. For instance, Landau et al. (2004) found that priming Americans with mortality salience or terrorism generated greater support for the incumbent George W. Bush prior to the 2004 election. Such effects may be particularly powerful among victimized individuals chronically primed with destitution and possible death resulting from exposure to extreme circumstances such as war and hunger (Staub, 2004). On a societal level, leaders may initiate certain beliefs, worldviews, or ideologies that lead to social or cultural conditions encouraging intergroup violence. In particular, individuals may adopt “destructive ideologies” (Staub and Bar-Tal, 2003, p. 724) to fulfill basic needs or manage existential angst (Greenberg et al., 1986), resulting in suboptimal and destructive consequences. For instance, increased support for Bush has enabled intergroup aggression in Iraq and Afghanistan, further fuelling intergroup hostility in the region.
Summary: Themes and Interventions Our discussion of research and theory in this quadrant was relatively brief because psychologists rarely approach prejudice from this perspective. Psychologists may shy away from this approach because it is virtually impossible to control extenuating variables necessary to infer cause and effect. Analyses of such extreme events also typically occur after the fact, leaving conclusions more open to interpretation. However, despite these limitations, examination of extreme social and contextual conditions certainly informs other areas of prejudice research. Thus, Staub and colleagues have offered valuable insights on the causes of prejudice at group, societal, and cultural levels (e.g., Staub and Bar-Tal, 2003). At this point, the field arguably needs more psychological research to shed light on causal and mediating mechanisms. Recent research encroaching on this domain has proven promising. For instance, SDO appears to affect prejudice via dehumanizing perceptions of outgroups (Esses, Veenviet, Hodson, and Mihic, 2008; Hodson and Costello, 2007). In a rare manipulation in this field, exposure to a media article dehumanizing refugees significantly increased prejudice among participants generally (Esses et al., Study 3, 2008), stressing the importance of dehumanizing portrayals of outgroups in exacerbating intergroup conflict. The dominant themes in this quadrant include dehumanization, societal crisis, and historical tipping points. Researchers and theorists possibly falling into this quadrant (e.g., Greenberg et al., 1986; Staub, 1996; Zimbardo, 1969) consider extreme and abnormal societal or contextual factors as causes of prejudice (but see Reicher et al., 1995). Examples characteristic of this quadrant include genocide (Rwanda in the 1990s, Nazi Germany) and the 9/11 terrorist attacks in the U.S. Treatment suggestions emanating from this perspective focus mainly on prevention. For instance, Staub (2004; Staub and Bar-Tal, 2003) emphasizes the importance of economic development, meeting basic human needs of individuals and groups, reconciliation among groups, pluralism, democracy, fostering inclusiveness, and selfawareness.
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CONCLUSION Utility of the Pendulum Framework The goal of the present chapter was to present a Pendulum Framework for conceptualizing the multifaceted causes of prejudice organized along two relatively independent dimensions (Abnormal vs. Normal; Person/Individual Differences vs. Situation/Group). The Abnormal versus Normal dimension represents the extent to which prejudice is conceptualized as an outcome of pathological conditions or processes, opposed to conditions and processes considered to be “normal.” The Person/Individual Difference versus Situation/Group dimension represents the extent to which theoretical origins of prejudice are person-based or situational. This framework highlights two dimensions that recur frequently and coincide with historical trends. Our intention was not to detail the evolution of prejudice research, but to capture the dominant themes and trends prominent in this area of inquiry. Rather than review the literature, we have followed Duckitt’s (1992) suggestion to provide a framework to integrate our understanding of the causes of prejudice. Intersection of these two dimensions partitioned prejudice research into four quadrants. In the first, Maladjusted People, we considered research and theory defining prejudice as a psychological abnormality within individuals. The dominant themes of this quadrant embodied personal maladjustment, dysfunctional personality, and dysfunctional psychology. The second quadrant, Threat-Sensitive and Cognitively Rigid People, similarly situated causes of prejudice within the individual yet within the normal range of human functioning. Individual variations in dominance, submission, and cognitive rigidity comprised the main themes of research. Our third quadrant, Competitive Contexts and Status Quo Perpetuation, viewed prejudice as originating from normal conditions and processes. In contrast to Quadrant 2, the emphasis here was on social and contextual influences, focusing on themes of identity, power, competition, system stability motivations, and indirect resistance to intergroup egalitarianism. Finally, the Aggravated Conflict and Mortality Contexts quadrant highlighted research and theory considering prejudice as a consequence of abnormal or maladjusted social and contextual influences. Relevant themes included dehumanization, collective crisis, and historical tipping points. A number of approaches to understanding the causes of prejudice are captured by the Pendulum Framework’s two dimensions and four quadrants. As stated earlier, we argue that no particular perspective or quadrant theme is inherently superior to others. The field does not share this view, as theorists continue to debate the particular value of specific approaches (e.g., Endler and Magnusson, 1976; Fiske, 2000; Funder and Ozer, 1983; Guimond, Dambrun, Michinov, and Duarte, 2003; Mischel, 1968; Nisbett, 1980; Verkuyten and Hagendoorn, 1998). Researchers are encouraged to consider how individual differences predict prejudice in varying contexts, and how individual differences operate in selecting and influencing situational contexts. These foci will necessitate more feedback loops in our models to capture the complex reciprocal nature of person- and situation-based factors. In keeping with the rationale underlying the Unified Instrumental Model of Group Conflict, “ideologies and situational factors that promote perceived group competition may be mutually reinforcing so that the ideologies heighten sensitivity to situational factors, and the situational factors reinforce and strengthen the ideologies” (Esses et al., 2005, p. 236). Empirical tests of
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such reciprocal models are sorely needed to address the complexity of intergroup behavior and prejudice in particular. In our opinion, studying individual differences is important because prejudice ultimately occurs within the individual, regardless of its origins. Further, person-based approaches account for generalized ethnocentrism, with new evidence demonstrating this phenomenon even at the implicit level (Cunningham, Nezlek, and Banaji, 2004). One particularly valid criticism of person-based approaches is the typical underestimation of situational influences on people’s reactions (e.g., Rubin and Hewstone, 2004). Another criticism is that situational factors can influence scores on individual differences measures (e.g., Schmitt et al., 2003). However, it is generally the case that those relatively high on measures such as SDO in one context will be relatively high in another (see Sidanius et al., 2004). Researchers utilizing situation-based approaches examine the effects of a specific social context on the responses of people in general, often manipulating situational variables and measuring the impact on prejudice (e.g., Tajfel and Turner, 1979; Turner et al., 1987). This approach is particularly useful in developing prejudice reduction strategies because these solutions apply to most people, and situations can be restructured. Unfortunately, many situation-based approaches ignore or greatly minimize the role of stable personal factors in people’s responses. Greater integration is needed, as person- and situation-based approaches possess approximately equivalent explanatory power for many psychological phenomena (Funder and Ozer, 1983; Richard, Bond, and Stokes-Zoota, 2003). In the context of prejudice, individual differences in RWA and SDO together account for 50% of the variance in prejudicial attitudes (Altemeyer, 1998; Duckitt, 2005), and group threats outlined by the Integrated Threat Theory account for 36% (Riek et al., 2006). It is clear that both person and situation approaches account for substantial variance in prejudice, and emphasis on one side of the equation to the exclusion of the other may not make optimal sense of the data at hand. An interactionist approach integrates the benefits of personal and situational approaches and their interplay (Endler and Magnusson, 1976; Swann and Seyle, 2005). Some researchers propose that interactionist approaches hold maximal explanatory power (Bowers, 1973; Endler and Magnusson, 1976). For instance, studying Nazi Germany by either failing to consider the influence of Hitler’s personality, or by ignoring the social norms and conditions in Europe after WWI, would drastically limit our understanding of prejudicial attitudes at that time. We are not proposing that person and situation factors always be considered simultaneously (i.e., in the same study) or in interaction. Instead, it can be fruitful and often preferable to focus on one type of factor or approach over another. For example, examining individual differences to better understand the Rwandan genocide may be suboptimal, as would a focus primarily on cultural factors to explain the racial biases held by Charles Manson. But to the extent that we invest in one approach over another, we should recognize the importance of other perspectives. Rarely are psychological phenomena exclusively the result of any single factor, and prejudice is no exception. In his seminal book on prejudice, Allport (1954) emphasized the role of the person and the situation in addition to their interaction, a theme reflected in some contemporary research (Sidanius and Pratto, 1999). Similarly, researchers may benefit from examining processes within the normal and abnormal range of study. It is encouraging to see researchers testing models that incorporate multiple causes of prejudice. Recently, Guimond and colleagues (2003) compared and contrasted three
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approaches to understanding the role of SDO in prejudice. They argue that a personality model suggests that high SDOs are prejudiced because they seek to dominate others. Further, because those high in SDO seek out particular situations, SDO should predict prejudice irrespective of the situation. In contrast, the person-by-situation interaction model asserts that SDO moderates the effects of situational variables on prejudice. Finally, according to the mediation model proposed by Guimond and colleagues, SDO should mediate the effects of the situation on prejudice. Although Guimond et al.’s findings provided the greatest support for their mediation model, support for the personality and person-by-situation models was also obtained, suggesting that prejudice is complex and multifaceted. The field would benefit from more of these types of analysis. From our perspective, any approach examining the causes of prejudice should be flexible. Almost all variables are predicted by other variables and, in turn, predict subsequent variables (i.e., most variables are both endogenous and exogenous, and our models only reflect theoretically derived start and end points). In addition, many variables can moderate the effects of other variables. Thus, we encourage flexibility in the designation of prejudice variables as predictors, moderators, mediators, or outcomes. These decisions will be affected by the research question at hand, other variables in the model, and our shared goal to make optimal “sense” of the data.
Future Directions and Reflections Although we argue that our two dimensions successfully capture dominant themes and trends in the prejudice literature, others may suggest alternatives. A strong candidate to consider may be an Implicit versus Explicit dimension. Such a dimension itself might lie across both personal and situational domains. That is, implicit processes may be, in part, driven by social constraints placed on the open expression of racial attitudes and, yet, clearly reflect processes located within the individual, such as the automatic association of semantically related constructs. Although research investigating implicit processes associated with prejudice is relatively new, over the next 20 years an Implicit versus Explicit dimension may become such a dominant theme that an effective framework will require this dimension to make maximal sense of the data. The “location” of a dominant or popular explanation for prejudice in the present framework is designated by a hypothetical pendulum. Obviously not all researchers “swing” with the force of the field, nor should they. As a consequence, some important research can be overlooked until the pendulum returns. For instance, both Altemeyer (1981, 1988, 1996, 1998) and Staub (1989, 1996) focus on causes of prejudice initially considered out of sync with dominant approaches. Their dedication to alternative perspectives has fostered major gains in prejudice research and advanced our understanding and theory-building. Even though our framework highlights dominant explanations for prejudice, it simultaneously recognizes and encourages alternative research and prejudice explanations that swim upstream, such as those proposed by Altemeyer and Staub. In summary, the Pendulum Framework can serve as a tool for conceptualizing the many explanations for prejudice. Although themes expressed in each quadrant provide rich and valuable insights on the causes of prejudice, limiting ourselves to one quadrant ultimately means we risk missing the bigger picture. After all, as prejudice researchers, we aim to
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address how and why individuals and groups express social prejudices and discriminatory actions that may reflect normal group processing or abnormal and extreme circumstances. We hope that the present framework will be useful as a meta-cognitive tool for researchers to step back and consider how different explanations inform each other. For example, research by Staub on the role of strong respect for authority at a societal or cultural level may inform Altemeyer’s work on personal authoritarianism and vice versa. In addition to recommending the integration of various theoretical approaches, we encourage some latitude and flexibility in choosing methodologies and theoretical positions, and in how we conceptualize variables as endogenous or exogenous. Creating bridges between theoretical camps will undoubtedly extend our understanding of prejudice in important ways. In keeping with the Jung quotation at the beginning of the chapter, the pendulum of science should oscillate between pursuits requiring relative judgments that maximize “sense” and minimize “nonsense” in our data, rather than between pursuits requiring rigid and dogmatic assertions about theoretical positions being “right” or “wrong.”
REFERENCES Abrams, D., and Hogg, M. A. (Eds.) (1999). Social identity and social cognition. Oxford: Blackwell Publishers. Ackerman, N., and Jahoda, M. (1950). Anti-Semitism and emotional disorders: A psychoanalytic interpretation. New York: Harper. Adams, H. E., Wright, L. W. Jr., and Lohr, B. A. (1996). Is homophobia associated with homosexual arousal? Journal of Abnormal Psychology, 105, 440-445. Adorno, T., Frenkel-Brunswik, E., Levinson, D., and Sanford, R. (1950). The authoritarian personality. New York: Harper. Allport, G. W. (1954). The nature of prejudice. Reading, MA: Addison-Wesley. Altemeyer, R. A. (1981). Right-wing authoritarianism. Winnipeg, MB: University of Manitoba Press. Altemeyer, R. A. (1988). Enemies of freedom: Understanding right-wing authoritarianism. San Francisco: Jossey-Bass. Altemeyer, R. A. (1996). The authoritarian specter. Cambridge, MA: Harvard University Press. Altemeyer, R. A. (1998). The other “authoritarian personality.” In M. P. Zanna (Ed.), Advances in experimental social psychology (Vol. 30, pp. 47-91). New York: Academic Press. Baron, R. M., and Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182. Bodenhausen, G. V. (1990). Stereotypes as judgmental heuristics: Evidence of circadian variations in discrimination. Psychological Science, 1, 319-322. Bowers, K. S. (1973). Situationism in psychology: An analysis and a critique. American Psychologist, 80, 307-336. Brewer, M. B. (1979). In-group bias in the minimal intergroup situation: A cognitivemotivational analysis. Psychological Bulletin, 86, 307-324.
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Christie, R., and Jahoda, M. (1954). Studies in the scope and method of the “authoritarian personality.” New York: Free Press. Cornelis, I., and Van Hiel, A. (2006). The impact of cognitive styles on authoritarianism based conservatism and racism. Basic and Applied Social Psychology, 28, 37-50. Cunningham, W. A., Nezlek, J. B., and Banaji, M. R. (2004). Implicit and explicit ethnocentrism: Revisiting the ideologies of prejudice. Personality and Social Psychology Bulletin, 30, 1332-1346. Danso, H.A., Sedlovskaya, A., and Suanda, S. H. (2007). Perceptions of immigrants: Modifying the attitudes of individuals higher in social dominance orientations. Personality and Social Psychology Bulletin, 33, 1113-1123. Dollard, J., Doob, L., Miller, N. E., Mowrer, O., and Sears, R. (1939). Frustration and aggression. New Haven, CT: Yale University Press. Dovidio, J. F. (2001). On the nature of prejudice: The third wave. Journal of Social Issues, 57, 829-849. Dovidio, J. F., and Gaertner, S. L. (2000). Aversive racism and selection decisions: 1989 and 1999. Psychological Science, 11, 319-323. Duckitt, J. (1992). Psychology and prejudice: A historical analysis and integrative framework. American Psychologist, 47, 1182-1193. Duckitt, J. (2001). A dual process cognitive-motivational theory of ideology and prejudice. In M. Zanna (Ed.), Advances in experimental social psychology (Vol. 33, pp. 41-113). San Diego, CA: Academic Press. Duckitt, J. (2005). Personality and prejudice. In J. F. Dovidio, P. Glick, and L. A. Rudman (Eds.), On the nature of prejudice: Fifty years after Allport (pp. 395-412). Malden, MA: Blackwell Publishing. Duckitt, J. (2006). Differential effects of right-wing authoritarianism and social dominance orientation on outgroup attitudes and their mediation by threat from and competitiveness to outgroups. Personality and Social Psychology Bulletin, 32, 684-696. Duckitt, J., and Fisher, K. (2003). The impact of social threat on worldview and ideological attitudes. Political Psychology, 24, 199-222. Duriez, B., and Soenens, B. (2006). Personality, identity styles, and authoritarianism: An integrative study among late adolescents. European Journal of Personality, 20, 397-417. Ekehammar, B., Akrami, N., Gylje, M., and Zakrisson, I. (2004). What matters most to prejudice: Big five personality, social dominance orientation, or right-wing authoritarianism? European Journal of Personality, 18, 463-482. Endler, N. S., and Magnusson, D. (1976). Toward an interactional psychology of personality. Psychological Bulletin, 83, 956-974. Esses, V. M., Dovidio, J. F., and Hodson, G. (2002). Public attitudes toward immigration in the United States and Canada in response to the September 11, 2001 “Attack on America.” Analyses of Social Issues and Public Policy, 2, 69-85. Esses, V. M., Dovidio, J. F., Jackson, L. M., and Armstrong, T. L. (2001). The immigration dilemma: The role of perceived group competition, ethnic prejudice, and national identity. Journal of Social Issues, 57, 389-412. Esses, V. M., and Hodson, G. (2006). The role of lay perceptions of ethnic prejudice in the maintenance and perpetuation of ethnic bias. Journal of Social Issues, 62, 453-468. Esses, V. M., Hodson, G., and Dovidio, J. F. (2003). Public attitudes toward immigrants and immigration: Determinants and policy implications. In C. M. Beach, A. G. Green, and G.
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R. Jeffrey (Eds.), Canadian immigration policy for the 21st century (pp. 507-535). Kingston, ON: John Deutsch Institute, Queen’s University. Esses, V. M, Jackson, L. M., Dovidio, J. F., and Hodson, G. (2005). Instrumental relations among groups: Group competition, conflict, and prejudice. In J. F. Dovidio, P. Glick, and L. A. Rudman (Eds.), On the nature of prejudice: Fifty years after Allport (pp. 227-243). Malden, MA: Blackwell Publishing. Esses, V. M., Veenviet, S., Hodson, G., and Mihic, L. (2008). Justice, morality, and the dehumanization of refugees. Social Justice Research, 21, 4-25. Fiske, S. T. (2000). Stereotyping, prejudice, and discrimination at the seam between centuries: Evolution, culture, mind, and brain. European Journal of Social Psychology, 30, 299-322. Fiske, S., and Taylor, S. E. (1991). Social cognition (2nd edition). New York: McGraw-Hill. Flynn, F. J. (2005). Having an open mind: The impact of openness to experience on interracial attitudes and impression formation. Journal of Personality and Social Psychology, 88, 816-826. Funder, D. C., and Ozer, D. J. (1983). Behavior as a function of the situation. Journal of Personality and Social Psychology, 44, 107-112. Gaertner, S. L., and Dovidio, J. F. (1986). The aversive form of racism. In J. F. Dovidio and S. L. Gaertner (Eds.), Prejudice, discrimination, and racism (pp. 61-89). New York: Academic Press. Gaertner, S. L., and Dovidio, J. F. (2000). Reducing intergroup bias: The common ingroup identity model. Philadelphia, PA: Psychology Press. Green, D. P., Glaser, J., and Rich, A. (1998). From lynching to gay bashing: The elusive connection between economic condition and hate crime. Journal of Personality and Social Psychology, 75, 82-92. Greenberg, J., Pyszczynski, T., and Solomon, S. (1986). The causes and consequences of a need for self-esteem: A terror management theory. In R. F. Baumeister (Ed.), Public self and private self (pp. 189-212). New York: Springer-Verlag. Greenberg, J., Pyszczynski, T., Solomon, S., Rosenblatt, A., Veeder, M., Kirkland, S., and Lyon, D. (1990). Evidence for terror management theory: II. The effects of mortality salience on reactions to those who threaten or bolster the cultural worldview. Journal of Personality and Social Psychology, 58, 308-318. Guimond, S., Dambrun, M., Michinov, N., and Duarte, S. (2003). Does social dominance generate prejudice? Integrating individual and contextual determinants of intergroup cognitions. Journal of Personality and Social Psychology, 84, 697-721. Hamilton, D. L., and Gifford, R. K. (1976). Illusory correlation in interpersonal perception: A cognitive basis of stereotypic judgments. Journal of Experimental Social Psychology, 12, 392-407. Heaven, P. C. L., and Bucci, S. (2001). Right wing authoritarianism, social dominance orientation, and personality: An analysis using the IPIP measure. European Journal of Personality, 15, 49-56. Heaven, P. C. L., and St. Quintin, D. (2003). Personality factors predict racial prejudice. Personality and Individual Differences, 34, 625-634. Hodson, G. (2008). Interracial prison contact: The pros for (socially dominant) cons. British Journal of Social Psychology, 47, 325-351.
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In: The Psychology of Modern Prejudice Editors: Melanie A. Morrison and Todd G. Morrison
ISBN 978-1-60456-788-5 © 2008 Nova Science Publishers, Inc.
Chapter 2
COGNITIVE CONSISTENCY AND THE RELATION BETWEEN IMPLICIT AND EXPLICIT PREJUDICE: RECONCEPTUALIZING OLD-FASHIONED, MODERN, AND AVERSIVE PREJUDICE Paula M. Brochu, Bertram Gawronski and Victoria M. Esses The University of Western Ontario
ABSTRACT Research on modern, subtle manifestations of prejudice is currently characterized by the existence of diverse concepts that are not well integrated from a general perspective. The present chapter reviews a new framework that integrates several of these concepts from a cognitive consistency perspective, and the data collected to date that support this framework. Specifically, it is argued that the impact of immediate affective reactions toward stigmatized groups on evaluative judgments about these groups depends on the (in)consistency of this evaluation with other relevant beliefs reflecting the central components of old-fashioned, modern, and aversive forms of prejudice. This conceptualization makes unique predictions regarding the correspondence between implicit and explicit prejudice; namely, that the relation between the two should be moderated by the interaction of (a) egalitarianism-related nonprejudicial goals (i.e., the extent to which one believes that negative evaluations of stigmatized groups are wrong) and (b) perceptions of discrimination (i.e., the extent to which one believes that a specific social group is a target of systematic discrimination). The strength of the proposed framework is that it articulates specific relations among various forms of prejudice, can be applied to a variety of target groups, and provides new insights into the nature of and the relations between implicit and explicit prejudice.
INTRODUCTION Imagine for a moment that you have been raised in a society that holds negative emotions, beliefs, and values about Camarians, an immigrant group taking up residence in
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your country because of constant threat of natural disaster in their home region (see Maio, Esses, and Bell, 1994). Camarians affectively elicit discomfort, tension, disrespect, and anxiety from others, and are believed to be unfriendly, dishonest, lazy, and unintelligent. Further, Camarians are perceived as violating important values such as equality, law and order, economic development, and family. From a very young age, you have been bombarded with such negative messages about Camarians from a variety of sources, including your family, your neighbours, and the mass media. As a result, whenever you encounter a Camarian, you experience a negative reaction. Would you openly express this negative reaction? If so, how would it be expressed, and what factors would increase or decrease the likelihood that you would do so? In the present chapter, we review a new framework that aims at specifying the particular conditions under which negative affective reactions to social groups translate into negative judgments about these groups (see Gawronski, Peters, Brochu, and Strack, 2008). This framework integrates the central components of old-fashioned, modern, and aversive prejudice by attributing a significant role to the interplay of egalitarianism-related nonprejudicial goals and perceptions of discrimination in the expression of prejudice. In addition, the integrative framework provides new insights into the relation between implicit and explicit forms of prejudice by distinguishing between associative and propositional processes underlying group evaluations (see Gawronski and Bodenhausen, 2006; Strack and Deutsch, 2004). Specifically, we argue that the desire to maintain consistency within one’s system of beliefs determines whether spontaneous negative reactions toward a particular social group (implicit prejudice) will be reflected in negative evaluative judgments of that group (explicit prejudice). For this purpose, we will first review the concepts of old-fashioned, modern, and aversive prejudice in greater detail. Drawing on this discussion, we will illustrate the core concepts of the integrative model: the distinction between associative and propositional processes, along with the importance of cognitive consistency, and the interplay of egalitarianism-related nonprejudicial goals and perceptions of discrimination. These concepts then will be applied to formally conceptualize the relations among old-fashioned, modern, and aversive forms of prejudice. In the remainder of the chapter, we will review evidence in support of the integrative model and discuss implications for research on the expression of prejudice.
FORMS OF PREJUDICE Prejudice is commonly defined as an overall negative evaluation of a social group or its members based on one’s perceptions of and reactions to the group (Esses, Haddock, and Zanna, 1993). Historically, such negative evaluations have been studied in the form of direct, blatant expressions of negativity, which are often described as old-fashioned prejudice. Over the last few decades, researchers have proposed more subtle forms of prejudice, such as modern and aversive prejudice, due to observations of changing societal and personal norms regarding the overt expression of prejudice (Dovidio and Gaertner, 2004; Gaertner and Dovidio, 1986; McConahay, 1986; McConahay, Hardee, and Batts, 1981; Swim, Aiken, Hall, and Hunter, 1995). In addition, methodological concerns regarding the use of self-report measures have led to significant advances in the area of indirect attitude measurement (e.g.,
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Fazio, Jackson, Dunton, and Williams, 1995; Greenwald, McGhee, and Schwartz, 1998; Payne, Cheng, Govorun, and Stewart, 2005). These methodological advances have suggested potential dissociations between implicit and explicit prejudice, such that people may harbour negative implicit evaluations of social groups in the absence of negativity at the explicit level. For the most part, however, investigations into different forms and conceptualizations of prejudice have occurred relatively independently from each other. Old-fashioned prejudice may best be conceptualized in terms of non-egalitarian beliefs, such as the endorsement of negative stereotypes, support for segregation and open discrimination, and belief in the inferiority of particular social groups (McConahay, 1986; McConahay et al., 1981; Swim et al., 1995). This form of prejudice has been labeled oldfashioned because, although it used to be acceptable, it is no longer fashionable or acceptable in most social circles (McConahay, 1986; McConahay et al., 1981). In fact, public opinion polls in North America have shown a steady decline in the negative evaluations of racial minority groups after World War II, mirrored by a steady increase in the endorsement of the goals of racial integration and equal treatment (Bobo, 2001; Dovidio and Gaertner, 2004). Interestingly, despite the significant decline in overtly expressed negativity, racial conflicts during this time showed only a moderate reduction (Dovidio and Gaertner, 2004). This disconnect is often attributed to individuals’ inner conflict between egalitarian values and negative racial sentiments, which has given rise to theorizing of newer, more subtle forms of prejudice. Modern prejudice is one influential concept that has been used to explain the subtle expression of prejudice, reflecting the conflict between egalitarianism and underlying negativity toward particular social groups. According to the theory of modern prejudice, negativity is only expressed overtly when it can be justified on non-prejudicial grounds, as this allows for the maintenance of an egalitarian and non-prejudiced self-image (McConahay, 1983, 1986). According to McConahay, such nonprejudiced justifications are based upon contextual factors such as ideological or situational ambiguity. Modern prejudice is exemplified in the case where people deny the existence of discrimination in the first place, and thus do not support public policies aimed at reducing discrimination (e.g., affirmative action). Those who endorse this position claim that they are not prejudiced, but that it is an empirical fact that discrimination no longer exists and that such policies are unfair and violate egalitarian principles (McConahay, 1986; Swim et al., 1995). The concept of aversive prejudice also has been influential in explaining the subtle expression of prejudice, and is similarly based upon the conflict between egalitarianism and underlying negativity. The theory of aversive prejudice asserts that individuals generally acknowledge discrimination and believe that it is wrong, but nevertheless experience negative reactions toward particular social groups. This negativity is expressed, however, only when it can be justified on non-prejudicial grounds in order to protect one’s egalitarian image (Dovidio and Gaertner, 2004; Gaertner and Dovidio, 1986). Despite its resemblance to modern prejudice, there are two important differences between these constructs (Dovidio and Gaertner, 2004). First, aversive prejudice is theorized to describe those who are politically liberal, whereas modern prejudice tends to describe those who are politically conservative. Second, although both modern and aversive prejudice are theorized to characterize those who endorse egalitarian, nonprejudiced beliefs, only modern prejudice is associated with a deliberate denial of discrimination.
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Old-fashioned and modern prejudice are typically assessed via self-report. However, due to the susceptibility of such direct measures to socially desirable responding and introspective inaccessibility of attitudes, indirect measures have been developed to overcome issues of monitoring and control (e.g., Fazio et al., 1995; Greenwald et al., 1998; Payne et al., 2005). Whereas self-reported attitudes are expressed consciously with awareness and intent, indirectly assessed attitudes have been described as implicit in the sense that they may reflect “introspectively unidentified (or inaccurately identified) traces of past experience that mediate favorable or unfavorable feeling, thought, or action toward social objects” (Greenwald and Banaji, 1995, p. 8). Based on this definition, implicit prejudice is often conceptualized as an automatic association between social groups and negative valence (Rudman, 2004; see also Fazio, 1995). As such, implicit evaluations often dissociate from explicitly endorsed evaluations, in that people may show negative responses at the implicit level despite the absence of negativity at the explicit level. This claim is consistent with the findings of a recent meta-analysis, showing that the mean population correlation between implicit and explicit measures of group attitudes was only modest with an average, error-corrected correlation of 0.25 (Hofmann, Gawronski, Gschwendner, Le, and Schmitt, 2005). Such dissociations have been incorporated into the theory of aversive prejudice, such that indirect measures are assumed to tap the negative affective component of aversive prejudice, whereas direct measures are assumed to reflect the conscious, egalitarian component (Dovidio and Gaertner, 2004; Son Hing, Li, and Zanna, 2002). Although each of the three forms of prejudice is concerned with the experience, expression, and consequences of prejudice, the conceptual and empirical relations between these different concepts has not been well specified. That is, to date, there has been no integrative model that incorporates all of these concepts into a general prejudice framework. In the present chapter, we review a new integrative model which hypothesizes that oldfashioned, modern, and aversive forms of prejudice share central components concerning spontaneously experienced negativity, egalitarianism-related nonprejudicial goals, and perceptions of discrimination (see Gawronski, Peters, et al., 2008). In integrating these forms of prejudice, however, it is important to first consider the general mechanisms underlying evaluations, namely the roles of associative (implicit) and propositional (explicit) processes, along with the notion of cognitive consistency.
PROCESSES UNDERLYING EVALUATION Associative Versus Propositional Processes In the integrative framework, two types of mental processes that underlie tendencies to respond positively or negatively to social groups are distinguished: associative and propositional processes (see Gawronski and Bodenhausen, 2006; Strack and Deutsch, 2004). The first kind of evaluative tendency is best described as a spontaneous affective reaction toward a given group, which depends on the particular associations that are activated in response to that group. The notion of affective reactions endorsed in this research is similar to Russell’s (2003) notion of core affect, in which affective reactions vary only in terms of valence (i.e., positivity or negativity) and arousal, but do not involve additional qualitative
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distinctions (e.g., distinct emotions). The defining feature of such associative activation processes is that they are independent of what people believe to be true or false. That is, associations can be activated irrespective of whether a person considers the evaluations implied by these associations to be accurate or not. For example, being exposed to African Americans may activate negative associations even though an individual regards these associations to be inadequate or false (Devine, 1989). The second type of evaluative tendency is reflected in endorsed evaluative judgments about a given social group, which represent the outcome of propositional validation processes. According to Gawronski and Bodenhausen (2006), processes of propositional reasoning aim to determine the validity of evaluations and beliefs by assessing their consistency with other relevant propositions (Jones and Gerard, 1967; Quine and Ullian, 1978). Drawing on a central assumption of Strack and Deutsch (2004), Gawronski and Bodenhausen (2006) proposed that people typically translate their spontaneous affective reaction to a given social group into propositional format (e.g., a negative affective reaction to a social group is translated into the proposition “I dislike that social group”). According to Gawronski and Bodenhausen (2006), the resulting proposition is then subject to syllogistic inferences that assess its validity. This assumption is in line with Zajonc’s (1980) claim regarding the primacy of affect, in that affective responses are assumed to precede a cognitive appraisal of these responses (see also Russell, 2003). However, the most significant feature that distinguishes propositional from associative processes at a conceptual level is their dependency on truth values. Whereas the activation of associations can occur regardless of whether a person considers these associations to be true or false, processes of propositional reasoning are generally concerned with the validation of evaluations and beliefs. Moreover, whether or not the propositional evaluation implied by an affective reaction will be explicitly endorsed depends on the subjective validity of that evaluation, as determined by the consistency of this proposition with other salient, relevant propositions (Gawronski and Bodenhausen, 2006).
Cognitive Consistency One of the most important aspects of the present model is the notion of cognitive consistency. Gawronski and Bodenhausen (2006) argued that the desire to maintain a consistent system of beliefs determines whether people base their evaluative judgment of a social group on their spontaneous affective reaction to that group. According to Festinger (1957), two cognitions are inconsistent if one follows from the opposite of the other. Conversely, two cognitions are consistent if one does not follow from the opposite of the other. Since the logical relations presupposed in Festinger’s (1957) definition require an assignment of truth values, cognitive (in)consistency can be regarded as inherently propositional (Gawronski and Strack, 2004; Gawronski, Strack, and Bodenhausen, in press). There is no logical relation between two cognitions unless they are regarded as either true or false. Such logical relations in conjunction with a given set of accepted propositions provide the basis for the (subjective) truth or falsity of other propositions, such as the evaluation implied by one’s spontaneous affective reaction (Jones and Gerard, 1967; Quine and Ullian, 1978).
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The perceived validity of a proposition—and thus of the evaluation implied by a spontaneous affective reaction—depends on the consistency of this proposition with other propositions that are considered to be relevant to the judgment at hand (Kruglanski, 1989). If the evaluation implied by a spontaneous affective reaction is consistent with other relevant propositions, it may be considered valid and thus may serve as the basis for an evaluative judgment. If, however, the evaluation implied by a spontaneous affective reaction is inconsistent with other relevant propositions, it may be considered invalid and thus may be rejected as a basis for an evaluative judgment. Most important, simply rejecting a spontaneous affective reaction for an evaluative judgment does not necessarily deactivate the associations that have led to this reaction (Deutsch, Gawronski, and Strack, 2006; Gawronski, Deutsch, Mbirkou, Seibt, and Strack, 2008; Gawronski and Strack, 2004). Accordingly, negative affective reactions to a particular social group tend to be unaffected by deliberate rejections of these reactions as a basis for evaluative judgments (see Butler et al., 2003; Gross, 1998). Hence, inconsistency-related rejections of spontaneous affective reactions often lead to dissociations, such that spontaneous affective reactions to a social group may be negative despite the absence of negativity in evaluative judgments (Gawronski and Strack, 2004; Gawronski et al., in press).
RECONCEPTUALIZING FORMS OF PREJUDICE The distinction between associative and propositional processes, along with the notion of cognitive consistency, is central to the general framework integrating different forms of prejudice (see Gawronski, Peters, et al., 2008). We equate explicit prejudice, as assessed through direct self-report measures, with the outcome of propositional processes (i.e., endorsed evaluative judgments of a social group). In contrast, implicit prejudice, as assessed by indirect attitude measures, is equated with the outcome of associative processes (i.e., spontaneous affective reactions to a social group). In addition, we argue that egalitarianismrelated nonprejudicial goals and perceptions of discrimination—two integral components of old-fashioned, modern, and aversive prejudice—reflect propositions relevant to the endorsement of evaluative judgments about social groups. This theorizing allows us to integrate old-fashioned, modern, and aversive forms of prejudice, as outlined below. Let us begin with the assumption that an individual is experiencing a negative affective reaction toward a member of a particular social group, which is driven by the valence of associations that are activated in response to this group. According to Gawronski and Bodenhausen’s (2006) theorizing, whether this affective reaction results in a negative judgment about the social group member should depend on the consistency of this evaluation with other propositions that are considered to be relevant, such as egalitarianism-related nonprejudicial goals and perceived discrimination.1
1
For the purpose of the present framework, nonprejudicial goals and perceived discrimination are viewed to be the most significant propositions relevant to the evaluation of social groups and their members. However, it is conceivable that there are other prejudice-related propositions that may contribute to (in)consistency within a person’s system of beliefs in addition to the ones discussed in the present chapter.
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More precisely, the resulting set of judgment-relevant propositions may include the following components (see Figure 1, Panel A): 1) “I dislike members of this social group”, 2) “Negative evaluations of disadvantaged social groups are wrong”, and 3) “Members of this social group are disadvantaged because of their group membership”. These three propositions are inconsistent with each other in that they cannot be endorsed simultaneously without violating the basic notion of cognitive consistency (Festinger, 1957). Proposition 1 is inconsistent with the joint implication of Propositions 2 and 3; Proposition 2 is inconsistent with the joint implication of Propositions 1 and 3; and Proposition 3 is inconsistent with the joint implication of Propositions 1 and 2. Thus, in order to avoid uncomfortable feelings arising from cognitive dissonance (Festinger, 1957), cognitive consistency may be maintained by rejecting (i.e., changing the truth value of) at least one of the three propositions (Gawronski and Strack, 2004; Gawronski et al., in press).2 The three possible cases are illustrated in Figure 1 (Panels B, C, and D). First, people may reject the proposition representing nonprejudicial goals (e.g., “I don’t care about disadvantaged social groups”). In this case, people may still agree that the social group is disadvantaged. However, this belief does not result in a rejection of negative affective reactions as a basis for evaluative judgments, as negative judgments of disadvantaged social group members are considered acceptable. Thus, negative affective reactions to members of this social group may directly translate into negative judgments (see Figure 1, Panel B). This case represents central components of the theory of old-fashioned prejudice: people do not endorse nonprejudicial values and openly support discriminatory practices, resulting in overt negative evaluations (e.g., McConahay, 1986; Swim et al., 1995). Second, people may reject the proposition representing perceptions of discrimination (e.g., “Members of this social group are not disadvantaged because of their group membership”). In this case, people may still hold strong nonprejudicial goals. However, these goals do not result in a rejection of negative affective reactions to members of disadvantaged social groups as a basis for evaluative judgments, as they are not considered to be targets of discrimination (e.g., Franco and Maass, 1999). Accordingly, negative affective reactions may directly translate into negative judgments (see Figure 1, Panel C). This case represents central components of the theory of modern prejudice: people deny the continued discrimination of disadvantaged social groups, thereby rationalizing negative reactions despite the endorsement of nonprejudicial goals (e.g., McConahay, 1986; Swim et al., 1995).
2
An alternative strategy to resolve inconsistency is to “search for consonant information” (Festinger, 1957), which implies the addition of a new proposition rather than the rejection of an old proposition (Gawronski and Strack, 2004). This strategy is discussed in more detail in the section on Implications of the Model.
Figure 1. Interplay between spontaneous affective reactions (i.e., implicit prejudice), nonprejudicial goals, and perceptions of discrimination in the endorsement of negative evaluations of social groups (i.e., explicit prejudice). Panel A depicts the case of an inconsistent belief system resulting from negative affective reactions toward members of a social group; Panels B, C, and D depict consistent belief systems whereby the proposed components of the model reflect central components of the theories of old-fashioned, modern, and aversive forms of prejudice.
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Third, people may reject their negative affective reactions as a valid basis for an evaluative judgment (e.g., “I like members of this social group”). Such a rejection may occur when people hold strong nonprejudicial goals and, at the same time, agree that members of this social group are disadvantaged by virtue of their group membership. In this case, negative affective reactions to members of this social group will not translate into negative judgments about this group (see Figure 1, Panel D). Rather, people’s evaluative judgments should be relatively neutral (or even positive), irrespective of the valence of their affective reactions. Importantly, the mere rejection of affective reactions as a basis for evaluative judgments does not necessarily change their affective quality (Deutsch et al., 2006; Gawronski and Strack, 2004; Gawronski, Deutsch, et al., 2008; see also Butler et al., 2003; Gross, 1998). That is, even though negative affective reactions may not be reflected in evaluative judgments, affective reactions may still be negative. This case represents central components of the theory of aversive prejudice: people hold strong nonprejudiced values and believe that particular social groups are disadvantaged, but nevertheless experience negative feelings toward these groups even though these feelings are not reflected in negative judgments (e.g., Dovidio and Gaertner, 2004; Gaertner and Dovidio, 1986).
EMPIRICAL EVIDENCE Aside from integrating different forms of prejudice, the integrative model implies new predictions regarding the relation between implicit prejudice as assessed by indirect measures and explicit prejudice as assessed by direct measures. In particular, the model predicts that the endorsement of nonprejudicial goals and perceptions of discrimination interactively moderate the correspondence between implicit and explicit prejudice. More precisely, implicit and explicit prejudice should be highly correlated when either nonprejudicial goals or perceptions of discrimination are low. In these cases, negative affective reactions to a particular social group should serve as a basis for direct evaluative judgments of that group, resulting in high correlations between the two. Such direct translations should occur when people perceive a particular social group as facing discrimination, but do not care about disadvantaged social groups (central components of old-fashioned prejudice), or when people believe it is wrong to negatively evaluate disadvantaged social groups, but do not perceive members of a particular social group as facing discrimination (central components of modern prejudice). However, when both nonprejudicial goals and perceived discrimination are high, implicit and explicit prejudice should be unrelated (or perhaps negatively related). In this case, negative affective reactions to a particular social group should not serve as a basis for direct evaluative judgment of that group. Such dissociations between spontaneous affective reactions (implicit prejudice) and evaluative judgments (explicit prejudice) should occur when people believe it is wrong to negatively evaluate disadvantaged social groups and, at the same time, perceive the particular social group as facing discrimination (central components of aversive prejudice). In summary, the integrative model implies that people should base their evaluative judgments about a particular social group on their spontaneous affective reactions toward this group when either (a) they do not endorse nonprejudicial goals, or (b) they do not believe that this group is a target of discrimination. In contrast, spontaneous affective reactions should not
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be reflected (or may be negatively reflected) in evaluative judgments when people (a) hold strong nonprejudicial goals, and at the same time, (b) believe that the group is a target of discrimination. Thus far, these predictions have been tested and supported in a series of three studies, using three different indirect attitude measures and two referent social groups. The first two studies tested the model within the domain of racial prejudice, utilizing two different indirect attitude measures: the Implicit Association Test (IAT; Greenwald et al., 1998; Olson and Fazio, 2004), and the Affect Misattribution Procedure (AMP; Payne et al., 2005). The third study extended the model to the domain of weight prejudice, utilizing a variant of Wittenbrink, Judd, and Park’s (1997) sequential priming task (SPT) to assess implicit weight prejudice. In the following sections, we review the central findings of these studies.
Application to Racial Prejudice Using the Implicit Association Test The main goal of the first study (Gawronski, Peters, et al., 2008, Study 1) was to provide a test of the integrative framework by examining the interactive effects of nonprejudicial goals and perceptions of discrimination on the relation between implicit and explicit prejudice against Black people. In this study, implicit prejudice, or negative affective reactions resulting from spontaneously activated associations, was assessed with two variants of the Implicit Association Test (IAT): the standard variant proposed by Greenwald and colleagues (1998), and the personalized variant proposed by Olson and Fazio (2004). Explicit prejudice, or direct evaluative judgments, was assessed with a feeling thermometer scale (Esses et al., 1993). Both IAT scores and difference scores of the feeling thermometer ratings were calculated such that higher values indicated a stronger preference for Whites over Blacks. Nonprejudicial goals were assessed with Dunton and Fazio’s (1997) Motivation to Control Prejudiced Reactions Scale (e.g., “I get angry with myself when I have a thought or feeling that might be considered prejudiced”). Perceptions of discrimination were assessed with McConahay’s (1986; Table 2) Modern Racism Scale (e.g., “How many Black people in Canada do you think miss out on jobs or promotions because of racial discrimination?”). Both nonprejudicial goals and perceptions of discrimination were scored such that higher values indicated stronger nonprejudicial goals and higher perceived discrimination, respectively.3 As described earlier, the integrative model proposes that nonprejudicial goals and perceived discrimination of Blacks interactively determine whether negative affective reactions to Blacks (implicit prejudice) lead to the endorsement of negative evaluations of Blacks (explicit prejudice). More precisely, it is predicted that implicit prejudice should be directly related to explicit prejudice when either nonprejudicial goals or perceptions of discrimination are low. However, implicit prejudice should be unrelated, or possibly negatively related, to explicit prejudice when both nonprejudicial goals and perceptions of discrimination are high. In other words, the integrative framework implies a three-way interaction in the prediction of feeling thermometer scores, such that IAT scores should predict feeling thermometer scores when nonprejudicial goals or perceptions of 3
Note that the present coding of perceived discrimination is opposite to the standard coding of the Modern Racism Scale, in which high scores typically reflect a low level of perceived discrimination.
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discrimination are weak. IAT scores should be unrelated (or potentially negatively related) to feeling thermometer scores when nonprejudicial goals are strong, and, at the same time, perceived discrimination is high. To test these predictions, explicit preference for Whites over Blacks was regressed on implicit preference for Whites over Blacks, nonprejudicial goals, perceived discrimination, and all of their possible interactions.
Figure 2. Relation between implicit racial prejudice assessed by the Implicit Association Test and explicit racial prejudice as a function of nonprejudicial goals and perceptions of discrimination (Gawronski, Peters, et al., 2008, Study 1).
This regression analysis revealed a significant three-way interaction, which is shown in Figure 2. Consistent with predictions, implicit prejudice was positively related to explicit prejudice when perceived discrimination was high but nonprejudicial goals were weak, reflecting the central components of old-fashioned prejudice. Moreover, implicit prejudice was positively related to explicit prejudice when nonprejudicial goals were strong but perceived discrimination was weak, reflecting the central components of modern prejudice. In contrast, implicit prejudice showed a tendency for a negative relation to explicit prejudice when perceived discrimination was high and, at the same time, nonprejudicial goals were strong, reflecting the central components of aversive prejudice. Unexpectedly, participants low in perceived discrimination and holding weak nonprejudicial goals showed independence between their levels of implicit and explicit prejudice. That is, participants’ implicit preference for Whites over Blacks was not significantly related to their explicit preference for Whites over Blacks. The pattern of findings did not differ between the standard and personalized variants of the IAT.
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Application to Racial Prejudice Using the Affect Misattribution Procedure The main goal of Gawronski, Peters, and colleagues’ (2008) second study was to determine whether the findings of their first study would replicate with a different measure of implicit prejudice. This goal was stimulated by two issues. First, it seemed important to determine whether the obtained independence of implicit and explicit prejudice for participants with low scores on both nonprejudicial goals and perceptions of discrimination was simply a random effect or a replicable, systematic effect. Second, even though similar effects using the standard and personalized IAT were obtained in Study 1, the general procedure of the IAT has been criticized on several grounds (e.g., Brendl, Markman, and Messner, 2001; Mierke and Klauer, 2003; Rothermund and Wentura, 2004), suggesting that replication with an alternative implicit measure would be beneficial. In this study, implicit prejudice was assessed with Payne and colleagues’ (2005) Affect Misattribution Procedure (AMP). For this task, participants were briefly presented with a Black or White face, which was followed by a Chinese character of neutral valence that was backward masked. Participants then indicated whether they considered the presented Chinese character as more pleasant or less pleasant than the average Chinese character (see also Murphy and Zajonc, 1993). Affective priming effects in this task are reflected in higher proportions of more pleasant responses after priming with positive (e.g., White face) as compared to negative (e.g., Black face) stimuli, and in higher proportions of less pleasant responses after priming with negative as compared to positive stimuli. AMP scores were calculated such that higher values indicated a stronger implicit preference for Whites over Blacks. Explicit prejudice, nonprejudicial goals, and perceived discrimination were assessed with the same measures as employed in the first study. Explicit preference for Whites over Blacks was regressed onto implicit preference for Whites over Blacks, nonprejudicial goals, perceived discrimination, and all of their possible interactions. This regression analysis again revealed a significant three-way interaction. The specific pattern of this interaction is depicted in Figure 3. Replicating the pattern obtained in Gawronski, Peters, et al.’s (2008) first study, implicit prejudice was positively related to explicit prejudice when perceived discrimination of Blacks was high but nonprejudicial goals were weak, reflecting the central components of oldfashioned prejudice. Implicit prejudice was positively related to explicit prejudice when nonprejudicial goals were strong but perceived discrimination of Blacks was low, reflecting the central components of modern prejudice. In contrast, implicit prejudice was unrelated to explicit prejudice when perceived discrimination of Blacks was high and, at the same time, nonprejudicial goals were strong, reflecting the central components of aversive prejudice. Replicating the unexpected pattern obtained in the first study, explicit and implicit prejudice were not significantly related for participants with low perceived discrimination of Blacks and weak nonprejudicial goals.
Application to Weight Prejudice Using the Sequential Priming Task The main goals of our third study (Brochu, Esses, and Gawronski, 2008) were to test whether the obtained results would replicate using another indirect measure of implicit
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Figure 3. Relation between implicit racial prejudice assessed by the Affect Misattribution Procedure and explicit racial prejudice as a function of nonprejudicial goals and perceptions of discrimination (Gawronski, Peters, et al., 2008, Study 2).
prejudice, and to extend the model to other prejudicial domains. The theories of oldfashioned, modern, and aversive prejudice were all stimulated and tested primarily within the domain of race relations. Nonetheless, it is important to test the generalizability of the integrative framework to other targets of prejudice. In this instance, we examined weight prejudice because subtle forms of prejudice exhibited toward this social group have not been widely examined (for a notable exception, see Brochu, 2007), and weight bias may be considered one of the last acceptable forms of discrimination (Puhl and Brownell, 2001). In this study, implicit weight prejudice was assessed using a variant of Wittenbrink and colleagues’ (1997) sequential priming task (SPT). In this paradigm, participants were subliminally presented with the terms OVER-WEIGHT or NORMAL-WEIGHT, which were then backward masked. After the masking stimulus, participants were presented with a letter string which was a positive, negative, or neutral word, or a meaningless non-word. Participants were instructed to indicate as quickly as possible whether the presented letter string was a meaningful word or not. Priming effects in this task are reflected in faster response times in indicating that a negative word is a word, and slower response times in indicating that a positive word is a word, after being primed with OVER-WEIGHT than after being primed with NORMAL-WEIGHT. Scores on this task were calculated such that higher values indicated more negative implicit evaluations of the overweight. Explicit prejudice was assessed with Crandall’s (1994) Anti-fat Attitudes Questionnaire – Dislike subscale (e.g., “I really don’t like overweight people much”), with the term fat replaced by overweight. Nonprejudicial goals were again assessed with Dunton and Fazio’s (1997) Motivation to Control Prejudiced Reactions Scale. Perceptions of discrimination were assessed with 11 items developed for the purpose of this study (e.g., “Overweight people are victims of discrimination”; see Brochu et al., 2008). Higher scores on these scales indicate
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greater endorsement of explicit negative evaluations of the overweight, nonprejudicial goals, and perceived discrimination of the overweight, respectively. In order to test the model within the domain of weight prejudice, explicit evaluations of the overweight were regressed on implicit evaluations of the overweight, nonprejudicial goals, perceived discrimination, and all of their possible interactions. This analysis again revealed a significant three-way interaction (see Figure 4). Replicating the pattern of the first two studies, implicit evaluations were positively related with explicit evaluations when nonprejudicial goals were low and perceived discrimination was high, reflecting the central components of old-fashioned prejudice. Implicit evaluations tended to be positively related to explicit evaluations when nonprejudicial goals were high and perceived discrimination was low, reflecting the central components of modern prejudice. In addition, implicit evaluations were negatively related with explicit evaluations when both nonprejudicial goals and perceived discrimination were high, reflecting the central components of aversive prejudice. Finally, replicating the unexpected finding of the previous studies, implicit evaluations were not significantly related to explicit evaluations when both nonprejudicial goals and perceived discrimination were low.
Figure 4. Relation between implicit weight prejudice assessed by the Sequential Priming Task and explicit weight prejudice as a function of nonprejudicial goals and perceptions of discrimination (Brochu et al., 2008).
SUMMARY In support of the integrated framework of prejudice (Gawronski, Peters, et al., 2008), the findings indicate that the correspondence between implicit and explicit prejudice is
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determined by the interplay between (a) egalitarianism-related nonprejudicial goals (i.e., the extent to which one believes that negative evaluations of social groups are wrong) and (b) perceptions of discrimination (i.e., the extent to which one believes that a specific social group is a target of systematic discrimination). The primary predictions of this framework were supported across three studies employing three different indirect measures of attitudes and assessing prejudice toward two different social groups. Further, one unexpected finding involving participants who do not endorse nonprejudicial goals or perceive discrimination consistently revealed itself across the three studies. Taken together, the reviewed evidence indicates that: (1) explicit evaluations of a social group reflect implicit evaluations when nonprejudicial goals are weak and, at the same time, perceived discrimination is high; (2) explicit evaluations of a social group reflect implicit evaluations when nonprejudicial goals are strong and, at the same time, perceived discrimination is low; (3) explicit evaluations of a social group do not reflect, or may negatively reflect, implicit evaluations when nonprejudicial goals are strong and perceived discrimination is high; and (4) explicit evaluations of a social group do not reflect implicit evaluations when nonprejudicial goals are weak and perceived discrimination is low. Each of these four response patterns has interesting theoretical implications and relations to different forms of prejudice. In the first case, the positive relation between implicit and explicit evaluations of a social group when nonprejudicial goals are weak and, at the same time, perceived discrimination is high, represents central components of old-fashioned prejudice, which is an overt and blatant form of prejudice that dictates open support for discrimination and segregation (McConahay, 1986; McConahay et al., 1981; Swim et al., 1995). In the second case, the positive relation between implicit and explicit evaluations when nonprejudicial goals are strong and perceived discrimination is low, represents central components of modern prejudice, which is a covert and subtle form of prejudice that denies discrimination while maintaining an image of egalitarianism (McConahay, 1986; Swim et al., 1995). In the third case, the unrelated or negative relation between implicit and explicit evaluations when nonprejudicial goals are strong and perceived discrimination is high, represents central components of aversive prejudice, which is a covert and subtle form of prejudice characterized by a conflict between negative affective reactions and egalitarian beliefs (Dovidio and Gaertner, 2004). According to Dovidio and Gaertner’s theorizing, “aversive racists either will treat Blacks and Whites equally, or they will respond even more favorably to Blacks than to Whites” (p. 7), which is reflected in the tendency for negative relations between implicit and explicit prejudice in the current studies. However, when a justification is available that allows for the expression of the affective negativity on nonprejudicial grounds, it is expected that implicit and explicit prejudice will relate positively with each other, which is discussed further in the next section. Finally, the nonsignificant relation observed between implicit and explicit prejudice when nonprejudicial goals are weak and perceived discrimination is low does not directly map onto a previously described form of prejudice. Implications of this fourth case are also discussed in more detail in the next section.
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IMPLICATIONS OF THE MODEL The reconceptualization of old-fashioned, modern, and aversive prejudice in terms of their underlying associative and propositional processes has many implications for prejudice research. Perhaps most interesting is the interactive influence of nonprejudicial goals and perceptions of discrimination on the relation between implicit and explicit evaluations, which integrates central components of the theories of old-fashioned, modern, and aversive forms of prejudice. However, the integrative framework also has many potential implications for research conducted in the areas of motivation to control prejudice, weight bias, and prejudice reduction. In addition, the model suggests other potential avenues for avoiding cognitive inconsistency in social group evaluation, and sheds light on the controversy surrounding theorizing regarding different forms of prejudice.
Motivation to Control Prejudice Previous studies using Dunton and Fazio’s (1997) Motivation to Control Prejudiced Reactions Scale have demonstrated that implicit and explicit prejudice are significantly correlated only for participants low in motivation to control prejudice, but not for participants high in motivation to control prejudice (e.g., Fazio et al., 1995; Gawronski, Geschke, and Banse, 2003; Payne et al., 2005). The studies described in the present chapter extend such findings by focusing on the interactive impact of motivation to control prejudice, conceptualized here as nonprejudicial goals, and perceived discrimination on the relation between implicit and explicit prejudice. Most notably, we failed to replicate the simple moderation of motivation to control prejudice in all three studies reviewed in this chapter. Given the integrative framework of prejudice, however, this failed replication is not all that surprising. A central assumption of the model is that nonprejudicial goals and perceptions of discrimination interactively determine the relation between implicit and explicit prejudice. Specifically, the model suggests that high levels of motivation to control prejudice, or strong nonprejudicial goals, are not sufficient to reduce the impact of negative affective reactions on the overt endorsement of negative evaluations. Rather, this reduction requires high levels of both nonprejudicial goals and perceptions of discrimination. As such, the moderating influence of motivation to control prejudice found in previous studies may have depended on contingent characteristics of the sample, namely high levels of perceived discrimination.
Alternative Strategies for Maintaining Cognitive Consistency In the present chapter, we focused primarily on the maintenance of cognitive consistency by rejecting relevant propositions. However, as alluded to earlier, inconsistency also can be resolved by searching for consonant information (or an additional proposition) that resolves the inconsistency (Festinger, 1957). In research on cognitive dissonance, additional information of this kind is often represented by situational explanations for counterattitudinal behavior (e.g., Festinger and Carlsmith, 1959; Gawronski and Strack, 2004). In the current case of prejudice, one could argue that people may resolve the inconsistency between
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negative evaluations, nonprejudicial goals, and perceived discrimination by searching for a situational explanation that could justify a negative evaluation. Indeed, situationally-based justification processes are theorized to play a crucial role in research on modern expressions of prejudice (Crandall and Eshleman, 2003; Dovidio and Gaertner, 2004; Gaertner and Dovidio, 1986; McConahay, 1983, 1986). These theories suggest that people are most likely to express their underlying negative attitudes toward various social groups when there is a readily available justification for doing so. For example, Dovidio and Gaertner (2000) found that Black and White job applicants were similarly recommended for a job when their qualifications were strong or weak; when their qualifications were ambiguous, however, Black job applicants were recommended significantly less strongly than White job applicants. In other words, participants in this study only expressed their negative reaction to Blacks when it could be justified on non-discriminatory grounds (i.e., ambiguous qualifications that could be interpreted in a variety of ways). Applied to the integrative framework, the possibility of resolving cognitive inconsistency via consonant information should result in a correspondence between spontaneous affective reactions and direct evaluative judgments. That is, implicit negativity should result in explicit negativity when a potential inconsistency between negative affective reactions, nonprejudicial goals, and perceived discrimination can be resolved by means of another proposition (i.e., a justification that appears to be non-prejudicial is available). For example, in the case of weight bias, this framework suggests that implicit negativity is likely to be expressed explicitly when nonprejudicial goals and perceptions of discrimination are high, and, at the same time, the belief that overweight individuals are responsible for their excess weight is endorsed (an additional relevant proposition). However, negative affective reactions should be unrelated (or negatively related) to evaluative judgments about the group when such a proposition is not available or accessible, and inconsistency is resolved by rejecting the negative affective reaction.
The Fourth Case One unexpected finding revealed across all three studies was an observed independence between spontaneous affective reactions and endorsed evaluative judgments for participants who reported weak nonprejudicial goals and weak perceptions of discrimination. For this group of participants, implicit and explicit prejudice were generally unrelated. One immediate question raised by this finding is what may distinguish this group of participants in evidencing levels of implicit and explicit prejudice that did not correspond with each other. In the third study reviewed in this chapter—which examined the integrative prejudice framework within the domain of weight prejudice (Brochu et al., 2008)—we had the opportunity to relate the observed dissociation to several other variables that may possibly account for this effect. However, none of the variables included in these analyses showed significant relations to this pattern, including social dominance orientation (Pratto, Sidanius, Stallworth, and Malle, 1994), right-wing authoritarianism (Altemeyer, 1996), Protestant work ethic (Katz and Hass, 1988), belief in a just world (Rubin and Peplau, 1975), and religious fundamentalism (Altemeyer and Hunsberger, 1992). Thus, future research is needed to examine additional features of this group of participants that may contribute to the observed dissociation.
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One promising avenue of inquiry is to examine the structure of participants’ attitudes, in particular whether they are more cognitively- or affectively-based. Huskinson and Haddock (2004) have demonstrated that there is wide variability in the relations between evaluations of attitude objects and affective and cognitive responses to the same attitude objects. Further, they demonstrated that this variability could be at least partially explained by individual differences in the Need for Affect (Maio and Esses, 2001) and the Need to Evaluate (Jarvis and Petty, 1996). That is, participants who evidenced a strong relation between their evaluative and affective responses tended to score higher on the Need for Affect, whereas participants who evidenced a strong relation between both their evaluative and affective responses, and evaluative and cognitive responses, tended to score higher on the Need to Evaluate. Thus, based upon this research, it is possible that our fourth group of participants, who showed a dissociation between their implicit and explicit attitudes, are characterized by low Need for Affect and/or Need to Evaluate. Future research should examine this possibility.
Modern Weight Prejudice The overt expression of weight bias is often described as the last socially accepted form of discrimination (Crandall, 1994; Puhl and Brownell, 2001). Although the pervasive and profound nature of weight bias is well-demonstrated (Brownell, Puhl, Schwartz, and Rudd, 2005; Puhl and Brownell, 2001, 2003), recent evidence has shown that the expression of weight bias may be fading (Brochu and Morrison, 2007; King, Shapiro, Hebl, Singletary, and Turner, 2006). For example, using a customer service paradigm, King and colleagues (2006) demonstrated that formal discrimination against overweight shoppers did not occur. That is, both average weight and overweight shoppers were greeted by sales representatives and offered help in searching for items in the store. However, interpersonal discrimination (operationalized as less smiling, eye contact, and friendliness, greater rudeness, and shorter interaction time) was only observed toward overweight shoppers who provided information that allowed the sales representatives to hold them responsible for their weight (e.g., not on a diet, did not exercise). This research demonstrates that people may need to justify the expression of weight prejudice, suggesting that its expression may not be as socially acceptable as it once was. The model outlined in the present chapter further suggests that nonprejudicial goals and perceptions of discrimination may play a significant role in this process. This assumption is consistent with Brochu and colleagues’ (2008) findings which showed patterns of prejudicial responses corresponding to those obtained for racial prejudice.
A New Perspective on Subtle Forms of Prejudice Throughout this chapter, the constructs of interest were described as reflecting “different forms of prejudice.” It is important to note, however, that this interpretation has been the subject of serious controversy in social psychology. For example, research in the tradition of modern prejudice has been criticized for inferring prejudice from measures that may simply reflect conservative political opinions (Sniderman and Tetlock, 1986). In a similar vein, research on implicit prejudice has been criticized for inferring prejudice from measures that may reflect cultural stereotypes rather than “personal animus” (Arkes and Tetlock, 2004). The
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present framework offers a new perspective on these controversies by specifying the relation between several different concepts. The integrative model agrees with previous criticism by arguing that measures of implicit prejudice and modern variants of prejudice do not tap the endorsement of negative evaluations of social groups. That is, measures of implicit prejudice and modern variants of prejudice do not directly assess individuals’ evaluations of social groups and, thus, may be considered indirect in nature. In keeping with definitions proposed by De Houwer (2006), such an endorsement can only be assessed with measures implying a direct evaluation of these groups (e.g., attitude thermometers or likeability ratings). The present conceptualization also agrees with the previous criticism that neither the denial of discrimination nor implicit negativity is sufficient for the endorsement of negative evaluations. However, the present conceptualization disagrees with the previous criticism in arguing that both perceived discrimination and implicit negativity systematically contribute to the endorsement of negative evaluations of social groups. More precisely, the results of the research described in this chapter indicate that negative affective reactions (as assessed by measures of implicit prejudice) directly translate into negative judgments of social groups when either nonprejudicial goals are weak or perceived discrimination is low. Negative affective reactions do not translate into negative judgments when nonprejudicial goals are strong and, at the same time, perceived discrimination is high. Thus, theoretical controversies regarding the ontological nature of different forms of prejudice could possibly be resolved by focusing on the specific relations between the proposed concepts. In addition, incorporating the notion of cognitive consistency (Festinger, 1957; Gawronski et al., in press) and recent theorizing on associative and propositional processes (Gawronski and Bodenhausen, 2006; Strack and Deutsch, 2004) may provide deeper insights into the underlying dynamics of different forms of prejudice.
Strategies for Prejudice Reduction The integration of old-fashioned, modern, and aversive forms of prejudice also has important implications for prejudice reduction. The primary implication of the model is that attempts to reduce prejudice need to target three components simultaneously. That is, they should try to (a) enhance nonprejudicial goals, (b) increase awareness of discrimination, and (c) reduce automatic negative reactions. Strategies certainly exist that independently seek to directly or indirectly accomplish these goals. For example, work on the common ingroup identity model, which encourages individuals to see the common human bonds that connect people, may serve to foster growth of nonprejudicial goals (Gaertner et al., 2000). Further, providing individuals with information regarding the experiences of particular social groups may reduce ignorance about the existence of discrimination (Stephan and Stephan, 2000). Moreover, research has demonstrated the malleability of implicit attitudes by means of extended training in counterstereotypical responding (e.g., Gawronski, Deutsch, et al., 2008; Kawakami, Dovidio, Moll, Hermsen, and Russin, 2000) and evaluative conditioning (e.g., Olson and Fazio, 2006). However, the model indicates that a caveat must be taken into consideration when employing such strategies. The findings reviewed in the present chapter suggest that attempts to reduce prejudice may be unsuccessful as long as they ignore the underlying dynamics of
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associative and propositional processes (Gawronski and Bodenhausen, 2006; Strack and Deutsch, 2004). For example, simply enhancing nonprejudicial goals may leave negative judgments of social groups unaffected when these groups are not considered to be targets of discrimination. In a similar vein, enhancing people’s awareness of the continued discrimination of particular social groups may be unsuccessful in reducing the endorsement of negative evaluations when nonprejudicial goals are weak. Attempts to change evaluative associations—and thus spontaneous affective reactions—may leave the endorsement of negative evaluations unaffected when nonprejudicial goals are weak and perceived discrimination is low. Thus, strategies that are directed at all of the relevant components simultaneously may be most successful in reducing prejudice (e.g., Rudman, Ashmore, and Gary, 2001).
CONCLUSION Research on prejudice is currently characterized by the existence of diverse concepts (e.g., implicit prejudice, old-fashioned prejudice, modern prejudice, aversive prejudice) that are not well integrated from a theoretical perspective. In this chapter, we reviewed a new theoretical framework that reconceptualizes these forms of prejudice in terms of their underlying associative and propositional processes (Gawronski, Peters, et al., 2008). A central implication of this model is that the correspondence between implicit and explicit prejudice is determined by the consistency between direct evaluative judgments, nonprejudicial goals, and perceptions of discrimination. A significant advance of this reconceptualization is that it (a) articulates the specific relations among various forms of prejudice, (b) can be applied to a variety of target groups, and (c) contributes to our understanding of the nature of, and the relations between, implicit and explicit prejudice. Needless to say, these issues are crucial when it comes to interpreting the findings of basic research so that they can be effectively applied to reduce the various forms of prejudice that are still prevalent in modern societies. Based on this conclusion, we hope that our theorizing will prove practical in reducing different forms of prejudice.
REFERENCES Altemeyer, B. (1996). The authoritarian specter. Cambridge: Harvard University Press. Altemeyer, B., and Hunsberger, B. (1992). Authoritarianism, religious fundamentalism, quest, and prejudice. The International Journal for the Psychology of Religion, 2, 113133. Arkes, H. R., and Tetlock, P. E. (2004). Attributions of implicit prejudice, or “Would Jesse Jackson ‘fail’ the Implicit Association Test?” Psychological Inquiry, 15, 257-278. Bobo, L. D. (2001). Racial attitudes and relations at the close of the twentieth century. In N. J. Smelser, W. J. Wilson, and F. M. Mitchell (Eds.), America becoming: Racial trends and their consequences (Vol. 1, pp. 264-301). Washington: National Academy Press.
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Brendl, C. M., Markman, A. B., and Messner, C. (2001). How do indirect measures of evaluation work? Evaluating the inference of prejudice in the Implicit Association Test. Journal of Personality and Social Psychology, 81, 760-773. Brochu, P. M. (2007). Old-fashioned and modern prejudice against the overweight: Scale development and validation. Unpublished master’s thesis, University of Western Ontario, London, Ontario, Canada. Brochu, P. M., Esses, V. M., and Gawronski, B. (2008). Cognitive consistency in prejudice against the overweight: The interplay of implicit evaluations, nonprejudicial goals, and perceived discrimination. Manuscript in preparation. Brochu, P. M., and Morrison, M. A. (2007). Implicit and explicit prejudice toward overweight and average weight men and women: Testing their correspondence and relation to behavioural intentions. Journal of Social Psychology, 147, 681-706. Brownell, K. D., Puhl, R. M., Schwartz, M. B., and Rudd, L. (2005). Weight bias: Nature, consequences, and remedies. New York: Guilford Press. Butler, E. A., Egloff, B., Wilhelm, F. H., Smith, N. C., Erickson, E. A., and Gross, J. J. (2003). The social consequences of expressive suppression. Emotion, 3, 48-67. Crandall, C. S. (1994). Prejudice against fat people: Ideology and self-interest. Journal of Personality and Social Psychology, 66, 882-894. Crandall, C. S., and Eshleman, A. (2003). A justification-suppression model of the expression and experience of prejudice. Psychological Bulletin, 129, 414-446. De Houwer, J. (2006). What are implicit measures and why are we using them? In R. W. Wiers and A. W. Stacy (Eds.), The handbook of implicit cognition and addiction (pp. 1128). Thousand Oaks, CA: Sage. Deutsch, R., Gawronski, B., and Strack, F. (2006). At the boundaries of automaticity: Negation as reflective operation. Journal of Personality and Social Psychology, 91, 385405. Devine, P. G. (1989). Stereotypes and prejudice: Their automatic and controlled components. Journal of Personality and Social Psychology, 56, 5-18. Dovidio, J. F., and Gaertner, S. L. (2000). Aversive racism and selection decisions: 1989 and 1999. Psychological Science, 11, 315-319. Dovidio, J. F., and Gaertner, S. L. (2004). Aversive racism. In M. P. Zanna (Ed.), Advances in experimental social psychology (Vol. 36, pp. 1-52). New York: Elsevier. Dunton, B. C., and Fazio, R. H. (1997). An individual difference measure of motivation to control prejudiced reactions. Personality and Social Psychology Bulletin, 23, 316-326. Esses, V. M., Haddock, G., and Zanna, M. P. (1993). Values, stereotypes, and emotions as determinants of intergroup attitudes. In D. M. Mackie and D. L. Hamilton (Eds.), Affect, cognition, and stereotyping: Interactive processes in group perception (pp. 137-166). San Diego: Academic Press. Fazio, R. H. (1995). Attitudes as object-evaluation associations: Determinants, consequences, and correlates of attitude accessibility. In R. E. Petty and J. A. Krosnick (Eds.), Attitude strength (pp. 247-282). Mahwah, NJ: Erlbaum. Fazio, R. H., Jackson, J. R., Dunton, B. C., and Williams, C. J. (1995). Variability in automatic activation as an unobtrusive measure of racial attitudes: A bona fide pipeline? Journal of Personality and Social Psychology, 69, 1013-1027. Festinger, L. (1957). A theory of cognitive dissonance. Evanston: Row Peterson.
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Jones, E. E., and Gerard, H. B. (1967). Foundations of social psychology. New York: Wiley. Katz, I., and Hass, R. G. (1988). Racial ambivalence and American value conflict: Correlational and priming studies of dual cognitive structures. Journal of Personality and Social Psychology, 55, 893-905. Kawakami, K., Dovidio, J. F., Moll, J., Hermsen, S., and Russin, A. (2000). Just say no (to stereotyping): Effects of training in the negation of stereotypic associations on stereotype activation. Journal of Personality and Social Psychology, 78, 871-888. King, E. B., Shapiro, J. R., Hebl, M. R., Singletary, S. L., and Turner, S. (2006). The stigma of obesity in customer service: A mechanism for remediation and bottom-line consequences of interpersonal discrimination. Journal of Applied Psychology, 91, 579593. Kruglanski, A. W. (1989). Lay epistemics and human knowledge: Cognitive and motivational bases. New York: Plenum Press. Maio, G. R., and Esses, V. M. (2001). The need for affect: Individual differences in the motivation to approach or avoid emotions. Journal of Personality, 69, 89-130. Maio, G. R., Esses, V. M., and Bell, D. W. (1994). The formation of attitudes toward new immigrant groups. Journal of Applied Social Psychology, 24, 1762-1776. McConahay, J. B. (1983). Modern racism and modern discrimination: The effects of race, racial attitudes, and context on simulated hiring decisions. Personality and Social Psychology Bulletin, 9, 551-558. McConahay, J. B. (1986). Modern racism, ambivalence, and the Modern Racism Scale. In J. F. Dovidio and S. L. Gaertner (Eds.), Prejudice, discrimination, and racism (pp. 91-125). Orlando: Academic Press. McConahay, J. B., Hardee, B. B., and Batts, V. (1981). Has racism declined in America? It depends on who is asking and what is asked. Journal of Conflict Resolution, 25, 563-579. Mierke, J., and Klauer, K. C. (2003). Method-specific variance in the Implicit Association Test. Journal of Personality and Social Psychology, 85, 1180-1192. Murphy, S. T., and Zajonc, R. B. (1993). Affect, cognition, and awareness: Affective priming with optimal and suboptimal stimulus exposure. Journal of Personality and Social Psychology, 64, 723-739. Olson, M. A., and Fazio, R. H. (2004). Reducing the influence of extra-personal associations on the Implicit Association Test: Personalizing the IAT. Journal of Personality and Social Psychology, 86, 653-667. Olson, M. A., and Fazio, R. H. (2006). Reducing automatically activated racial prejudice through implicit evaluative conditioning. Personality and Social Psychology Bulletin, 32, 421-433. Payne, B. K., Cheng, C. M., Govorun, O., and Stewart, B. D. (2005). An inkblot for attitudes: Affect misattribution as implicit measurement. Journal of Personality and Social Psychology, 89, 277-293. Pratto, F., Sidanius, J., Stallworth, L. M., and Malle, B. F. (1994). Social dominance orientation: A personality variable predicting social and political attitudes. Journal of Personality and Social Psychology, 67, 741-763. Puhl, R., and Brownell, K. D. (2001). Bias, discrimination, and obesity. Obesity Research, 9, 788-805. Puhl, R. M., and Brownell, K. D. (2003). Psychosocial origins of obesity stigma: Toward changing a powerful and pervasive bias. Obesity Reviews, 4, 213-227.
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Quine, W. V. O., and Ullian, J. S. (1978). The web of belief (2nd ed.). New York: McGrawHill. Rothermund, K., and Wentura, D. (2004). Underlying processes in the Implicit Association Test: Dissociating salience from associations. Journal of Experimental Psychology: General, 133, 139-165. Rubin, Z., and Peplau, L. A. (1975). Who believes in a just world? Journal of Social Issues, 31, 65-89. Rudman, L. A. (2004). Social justice in our minds, homes, and society: The nature, causes, and consequences of implicit bias. Social Justice Research, 17, 129-142. Rudman, L. A., Ashmore, R. D., and Gary, M. L. (2001). “Unlearning” automatic biases: The malleability of implicit prejudice and stereotypes. Journal of Personality and Social Psychology, 81, 856-868. Russell, J. A. (2003). Core affect and the psychological construct of emotion. Psychological Review, 110, 145-172. Sniderman, P. M., and Tetlock, P. E. (1986). Symbolic racism: Problems of motive attribution in political analysis. Journal of Social Issues, 42, 129-150. Son Hing, L. S., Li, W., and Zanna, M. P. (2002). Inducing hypocrisy to reduce prejudicial responses among aversive racists. Journal of Experimental Social Psychology, 38, 71-78. Stephan, W. G., and Stephan, C. W. (2000). An integrated threat theory of prejudice. In S. Oskamp (Ed.), Reducing prejudice and discrimination (pp. 23-45). Mahwah: Erlbaum. Strack, F., and Deutsch, R. (2004). Reflective and impulsive determinants of social behavior. Personality and Social Psychology Review, 8, 220-247. Swim, J. K., Aikin, K. J., Hall, W. S., and Hunter, B. A. (1995). Sexism and racism: Oldfashioned and modern prejudices. Journal of Personality and Social Psychology, 68, 199214. Wittenbrink, B., Judd, C. M., and Park, B. (1997). Evidence for racial prejudice at the implicit level and its relationship with questionnaire measures. Journal of Personality and Social Psychology, 72, 262-274. Zajonc, R. B. (1980). Feeling and thinking: Preferences need no inferences. American Psychologist, 35, 151-175.
In: The Psychology of Modern Prejudice Editors: Melanie A. Morrison and Todd G. Morrison
ISBN 978-1-60456-788-5 © 2008 Nova Science Publishers, Inc.
Chapter 3
POLITICAL ORIENTATION AND CONTEMPORARY RACISM IN AMERICA Helen C. Harton1 and Paul R. Nail2 1 2
University of Northern Iowa University of Central Arkansas
ABSTRACT We describe a line of research that tests predictions derived from the integrated model of racism (Dovidio and Gaertner, 1998). This model proposes that White political conservatives are more likely to show modern-symbolic racism, and White liberals, aversive racism. In support of the model, we found that White conservatives tend to be biased against minorities and justify their discrimination and negative feelings about outgroups based on their stereotypes about these groups. White liberals, on the other hand, are more variable in their response to minorities. They tend to evaluate racial and other minorities more favorably than non-minorities in some situations, but more negatively in others, such as when they can attribute their unfavorable evaluations of minorities to something besides race or group membership. These findings are consistent with the hypothesis that liberals experience significant intra-psychic conflict over race as a result of a strongly non-prejudiced self-image that coexists with automatic, negative race-based feelings beyond their control. We found little evidence of racism among political moderates, suggesting that racism may not necessarily be an inescapable consequence of the human condition.
INTRODUCTION Like many social psychologists, we have always been interested in topics such as intergroup relations, social perception, stereotypes, and prejudice. In our view, in social psychology, there are probably few topics that are as interesting theoretically or as important practically as the study of prejudice and racism. We were never involved in systematic research focusing directly on any of these topics, however, until the aftermath of two legal cases that more or less dominated the United States media for a number of months beginning
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in March of 1991 and, again, in June of 1994. We speak of the beating of African-American Rodney King by White members of the Los Angeles Police Department and of the murders of Nicole Brown Simpson and Ronald Goldman, two Caucasians, allegedly by the AfricanAmerican ex-football star, O. J. Simpson. In this chapter, we describe our research that sprang from these two cases. Much of this research has been published, but we also present findings that appear for the first time. Overall, our research is consistent with the general thesis that, although racism in the United States has changed considerably over the last several decades, it continues to exist, is relatively widespread, and has changed primarily in the manner in which it is expressed. We also present evidence that the ways in which this racism is manifested tend to differ for political conservatives versus liberals—specifically, we suggest, following Dovidio and Gaertner (1998, 2004), that modern-symbolic racism is linked to conservatism, and aversive racism to liberalism.
THE KING AND SIMPSON CASES From a purely academic point of view, the King and Simpson cases included many variables of interest to social psychologists and social scientists in general: race, gender, socioeconomic class, social status, and society’s laws and norms—variables that can and frequently do divide us as people. The event in each of these cases that eventually got us interested in doing research on racism, however, was that after being acquitted in a California State Court, the defendants were put on trial a second time. Specifically, the police officers involved in the Rodney King beating were subsequently indicted and convicted in Federal Court of violating Mr. King’s civil rights. In a somewhat similar manner, O. J. Simpson was sued in civil court by the Brown and Goldman families and found responsible for the murders of Nicole Brown Simpson and Ronald Goldman. As observant social psychologists, our attention was not so much on the cases themselves, but rather, the reactions of our friends, colleagues, and associates to them. In the case of the police officers in the Rodney King beating, it was our impression that it was our politically conservative friends who complained the loudest after the officers’ guilty verdict was announced. These friends frequently raised the issue of double jeopardy with regard to the officers’ second indictment. For example, they would argue, “I don’t know how that prosecutor can try those officers a second time when they were already acquitted by a jury. Doesn’t double jeopardy in the Constitution protect citizens from being tried twice for the same crime? Activist judges and prosecutors are ruining this country. Doesn’t the plain language in the Constitution mean anything any more?” In the O. J. case, however, it seemed to be our politically liberal friends who were doing most of the complaining, saying things such as “I realize that there is a difference between criminal court and civil court, but it seems wrong to me that it can be legal to sue a person in civil court for alleged crimes after they have already been acquitted in a criminal court. The double jeopardy clause should apply in these types of cases.” For our part, we found it most interesting that our conservative friends seemed not to notice the issue of double jeopardy when it came to O. J., whereas in the Rodney King case, it was our liberal friends who seemed not to care about the L. A. police officers and possible double jeopardy. We wondered if our casual observations might have any basis in fact. Would conservatives and liberals in general perceive these cases differently
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with respect to double jeopardy? Were our friends’ political orientations and biases systematically influencing their perceptions?
OUR INITIAL STUDY The verdict in the O. J. civil case was announced on February 4, 1997 (Chronology of the O. J. Simpson Trials, n.d.). Within a few days of the verdict, we began planning an empirical study to examine whether political orientation might play a role in perceptions of double jeopardy for Black versus White defendants. We created a scenario modeled most directly on the Rodney King case describing an alleged legal case in which a White male police officer was caught on videotape physically assaulting a Black male motorist. The officer was acquitted of assault and battery charges in state court but was later tried and convicted in federal court of violating the motorist’s civil rights. A second scenario was identical to the first except that the roles were reversed; the indicted police officer here was described as a Black male and the motorist as a White male. The dependent variable was the extent to which participants perceived that the case had violated the U.S. Constitution’s protection against double jeopardy (1 = No, not at all to 7 = Yes, definitely).1 On the next page, we constructed a questionnaire to collect demographic data and, most importantly, to measure each participant’s self-reported political orientation (liberal, moderate, or conservative). A research assistant approached randomly chosen individuals from the local university and business phone directories at their office or place of work and asked if they had a few minutes to help with a student research project. If they agreed, the assistant simply read the scenario to them (presented as being modeled on an actual case that had not gotten much attention in this part of the country) and asked them to provide their reactions to the case, along with their demographic information. Sixty-nine White2 participants (47 male, 22 female) from a small southwestern American college town agreed to complete the measures. They ranged in age from 18 to 65, with 94% reporting an age between 35 and 65 years. The findings supported our original, informal impressions regarding political orientation and bias (Nail, Harton, and Decker, 2003, Experiment 1, Sample 1; Figure 1). Conservative participants showed a clear bias in favor of the White officer. In the White officer-Black motorist condition, conservatives gave the officer a double jeopardy rating that was significantly greater than that in the Black officerWhite motorist condition. In sharp contrast, the bias of liberals was in favor of the Black officer. Liberals in the White officer-Black motorist condition gave the officer a rating that was significantly lower than that of liberals in the Black officer-White motorist group. So, our informal observations regarding political orientation and bias were supported. 1
2
Double jeopardy is a constitutional right that prohibits a defendant from being tried twice for the same crime within the same jurisdiction. It was perfectly legal, therefore, for the officers in the Rodney King case to be tried twice because assault charges against the officers were brought under the jurisdiction of the state of California, whereas the civil rights violation charges were brought under the jurisdiction of the federal government. It was also legal for the Brown and Goldman families to sue O. J. in civil court because double jeopardy in the constitution only prohibits the government from prosecuting someone twice for the same crime. As our interest was only in detecting potential White racism and because we did not have sufficient numbers of minority participants for comparisons, we do not present the results of any non-White participants in this chapter.
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Double jeopardy ratings
7 6 5
Black Officer
4
White Officer
3 2 1
Liberal
Moderate
Conservative
Political Orientation Figure 1. Double jeopardy ratings as a function of officer race and participant political orientation (Nail et al., 2003, Study 1, Sample 1).
White conservatives displayed bias against the Black officer relative to the White officer, whereas White liberals showed bias in favor of the Black officer relative to the White officer. Interestingly, political moderates were not biased one way or the other as a function of race; they gave mean double jeopardy ratings very near the midpoint of our 7-point scale regardless of condition. But what did these findings mean? It is hardly news that human beings tend to be biased or that conservatives and liberals generally see the world differently. How might these findings be interpreted?
THE INTEGRATED MODEL OF RACISM Much contemporary research indicates that White Americans rarely show blatant or “oldfashioned” prejudice anymore (see Dovidio and Gaertner, 1998, 2004); instead, psychologists now focus on and discuss concepts such as modern-symbolic (McConahay, 1986; Sears, 1988, 1998) and aversive (Dovidio and Gaertner, 1998, 2004; Gaertner and Dovidio, 1986) racism. These theories are similar in several respects.3 Both propose that racism can result as a byproduct of normal social and cognitive processes (cf., Sherif, Harvey, White, Hood, and Sherif, 1961 as cited in Sherif and Sherif, 1969) and de-emphasize earlier approaches that had focused on abnormal personality processes (e.g., Adorno, Frenkel-Brunswik, Levinson, and Sanford, 1950). These contemporary theories also maintain that, although the expression of racism has changed, it remains relatively widespread.
3
While some researchers have suggested very minor differences between modern and symbolic racism (e.g., Dovidio and Gaertner, 2004), the concepts originated as part of the same line of theory development and are considered to be essentially the same by their developers (e.g., Sears and Henry, 2005).
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To elaborate, there was a time in the United States when blatant, direct discrimination against minorities was the norm in many parts of the country. This type of racism is known as traditional or old-fashioned racism (Dovidio and Gaertner, 1986). But those days are largely gone. With changes in social norms, and in the American people themselves over the last seven decades, blunt and direct expressions of racism are simply no longer acceptable in most contemporary social settings. These changes do not mean that racism has vanished or been eliminated, however. Rather, racism has only changed in the forms it can assume. Whereas old-fashioned racism was blatant, conscious, and direct, contemporary racism tends to be subtle, nonconscious, and indirect. The theories of modern-symbolic and aversive racism maintain that White Americans tend to see themselves as nonracist (see also Kinder, 1986); at the same time, many still hold negative feelings toward Black people and other minorities that activate automatically in interracial settings and about which they may not be fully aware. Due to these negative feelings, the theories all hold that White Americans continue to discriminate against minorities, but such discrimination is much more limited and guarded than in the days of oldfashioned racism. Specifically, contemporary discrimination tends to occur only under conditions where it can be justified, explained away, or rationalized as nonracist. For example, someone may say that she is not a racist, but that she does not like Mexicans because they have too many babies and do not take care of their lawns. Another person might evaluate a Black employee especially harshly (and more harshly then he would a White employee) when the employee makes a mistake. Despite their similarities, the theories of modern-symbolic and aversive racism are not identical. The differences are important because taken together they provide a compelling and parsimonious account for the overall pattern of results of our double jeopardy study described above. One difference between the theories is that aversive racists are hypothesized to have internalized a nonracist self-image to a higher and more genuine degree than modernsymbolic racists (Dovidio and Gaertner, 1998, 2004; Frey and Gaertner, 1986). Aversive racists apparently do genuinely desire a society with greater and more equal opportunities and outcomes for all. As an indication of this greater internalization, consider the following self-report items that appear on both the Modern Racism Scale (McConahay, 1986) and the Symbolic Racism Scale (Henry and Sears, 2002; Sears and Henry, 2003): “Discrimination against Blacks is no longer a problem in the United States,” and “Blacks are getting too demanding in their push for equal rights” (1 = Strongly disagree to 5 = Strongly agree). Modern-symbolic racists, but not aversive racists, are likely to endorse these and similar items, at least to a moderate degree (see below in reference to Nail et al., 2003, Experiment 1, Sample 2), despite the fact that these individuals tend to see themselves as non-prejudiced. Apparently, it is the modernsymbolic racists’ beliefs in traditional values and the Protestant work ethic that allow them to reject overt, old-fashioned racism while at the same time endorsing such items and supporting social policies that result in continued de facto discrimination and inequality (Emerson, Smith, and Sikkink, 1999; McConahay, 1986; Monteith, 1996). The label “symbolic racism,” in fact, resulted from the tendency of such individuals to transfer their negative, race-based feelings to abstract race-related symbols such as affirmative action and school bussing. Aversive racists, in contrast, would be less likely to endorse such items from the Modern Racism and Symbolic Racism Scales because they are too much at odds with their
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internalized, nonracist attitudes and values. To do so would pose too direct a threat to their non-prejudiced, egalitarian self-image.4 Another difference between the theories is that because aversive racists have a more strongly internalized non-prejudiced self-image, they are hypothesized to experience greater intra-psychic conflict over race than modern-symbolic racists (Dovidio and Gaertner, 1998, 2004). This conflict is hypothesized to be extremely unpleasant and threatening, which is the origin of the label “aversive racism.” One consequence of this greater conflict is that aversive racists are more likely than modern-symbolic racists to defend their fiercely nonracist selfimage by going overboard in the other direction. Specifically, aversive racists may try to prove to themselves that they are nonracist by sometimes showing favoritism toward minorities. Reminiscent of Freud’s reaction formation, such favoritism is known in the literature as the amplification effect (e.g., Dovidio, Smith, Donnella, and Gaertner, 1997; Fein, Morgan, Norton, and Sommers, 1997; see also Katz, 1981). Dovidio and Gaertner have proposed that amplification is most likely to occur in situations were (a) race and (b) social cues against race-based discrimination are both salient. Perhaps the most important difference between the theories for our purposes is Dovidio and Gaertner’s (1998) suggestion that the modern-symbolic model is more likely to apply to political conservatives, while the aversive model applies more to political liberals. The authors state that “whereas symbolic and modern racism are subtle forms of contemporary racism that seem to exist among political conservatives, aversive racism seems to be more strongly associated with liberals” (p. 8). We refer to Dovidio and Gaertner’s theorizing in this regard as the integrated model of racism. In effect, this view suggests that the modernsymbolic and aversive models of racism are both correct. The caveat is that they apply to different types of people. The data from our double jeopardy study support this model nicely. As race was manipulated in a between-participants design, our participants had no way of knowing that their racial attitudes were under surveillance. Accordingly, conservatives were free to let their true negative feelings toward African Americans show without having to worry about being seen as a racist. Conservatives showed sympathy toward a twice-tried White officer in the form of elevated double jeopardy ratings but not toward a twice-tried Black officer, even though the officers were in mirror-image positions. With respect to conservatives, Dovidio and Gaertner’s integrated model is consistent with the numerous studies that have found a link between conservatism and various self-report measures of prejudice (e.g., Fazio, Jackson, Dunton, and Williams, 1995; Kinder and Sears, 1981; Lambert and Chasteen, 1997; McConahay and Hough, 1976; Meertens and Pettigrew, 1997). Further, given the association between political conservatism and traditional values (e.g., Kerlinger, 1984; Sniderman, Piazza, Tetlock, and Kendrick, 1991), the integrated model also fits nicely with Sears’ (1988) original contention that symbolic racism results from a blend of traditional values (i.e., individualism and self-reliance) and anti-Black affect (see also Sears and Henry, 2005). Using the term from Crandall and Eshleman’s (2003) justification-suppression model of prejudice, political conservatives justify their genuine prejudice—they can rationalize their negative
4
There is no corresponding scale that measures aversive racism directly. Gaertner and Dovidio (1986) have questioned whether the development of a conventional aversive racism scale is possible (but for nonconventional measures, see Son Hing et al., 2002, 2008).
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feelings about minorities as being due to some other characteristic the group holds (e.g., laziness or unworthiness; see also Reyna, Henry, Korfmacher, and Tucker, 2006). Regarding the liberal participants in our double jeopardy study, race was salient because the conflict was always between a White man and a Black man. Further, given that a courtroom is the quintessential setting for American fairness, cues against racial or unfair discrimination of any kind were likely salient as well. Considering these factors together, the conditions for an amplification effect (Dovidio and Gaertner, 1998) were present. The data are consistent with the hypothesis that liberals in our study discriminated in favor of the Black officer relative to the White officer as a means of bolstering their non-prejudiced self-image while at the same time defending against their non-conscious, negative race-based feelings. Dovidio and Gaertner’s integrated model also is consistent with the finding that an amplification effect tends to be found among samples that are known to be relatively liberal such as college students (Duncan, 1976), and particularly northeastern college students (e.g., Dovidio and Gaertner, 1986; Dovidio et al., 1997; Fein et al., 1997). Liberals, then, tend to suppress their prejudiced feelings, which may lead, in turn, to overcompensation (Crandall and Eshleman, 2003). In proposing the integrated model, Dovidio and Gaertner (1998) did not mention political moderates. By this omission, the implication was that moderates were neither modernsymbolic nor aversive racists. Thus, in an experiment where race was manipulated, one might expect moderates to not discriminate on the basis of race, which is precisely what we found (Figure 1). Despite noting the potential links between political orientation and types of prejudice, to our knowledge, Dovidio and Gaertner did not directly include political orientation as a variable in subsequent research, and there has been surprisingly little research at any time linking political orientation to different expressions of prejudice. One of the few studies examining these variables was by Gaertner (1973) as a test of the aversive racism model. A male caller with a noticeable Black or White accent telephoned randomly selected liberals or conservatives (determined from voting registration records) claiming car trouble. The caller said that he had dialed the number accidentally with his last dime, and asked the participant to make a call for him to his mechanic. Conservatives were significantly less likely to help the Black caller than the White caller. Conservatives could justify not helping based on their stereotypic beliefs about race (e.g., that the Black caller was less deserving). Age-matched liberals, however, helped both callers equally (in this study there was no amplification effect, likely because helping was all or none—there was no way to help the Black caller to a greater extent than the White caller). Thus, when the cues for helping were strong but the need to conceal one’s bias was low, conservatives favored a White target whereas liberals did not. When there was something to attribute not helping to besides race, however, liberals were actually more likely than conservatives to discriminate against the Black caller. Liberals were more likely to hang up on a Black caller before the request for help was made (presumably with the excuse “I don’t know this person, so the call is not for me”) than they were to hang up on a White caller. Conservatives, in contrast, were equally likely to hang up on both callers early in the conversation. Consistent with the aversive racism model, when no specific request for help had been made, there were no strong norms for treating people equally regardless of race. Thus, liberals could justify not helping the Black caller as not constituting racism.
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Similarly, Sniderman et al. (1991) examined racial attitudes among liberal and conservative participants, this time in the context of modern-symbolic racism, and, again, found results mostly consistent with Dovidio and Gaertner’s (1998, 2004) integrated model. Neither Sniderman et al. nor Gaertner (1973), however, directly investigated both modernsymbolic and aversive racism explanations in the same study. To more fully test the integrated model and follow-up on our original study, we conducted additional research investigating conservatives’ and liberals’ reactions to a Black versus White target: would we, again, find that conservatives and liberals both showed biases, but in different directions?
OUR SUBSEQUENT STUDIES We replicated our original study with a second sample drawn from the same population as our original (M age = 40; N = 68). The replication (Nail et al., 2003, Experiment 1, Sample 2) addressed two limitations of the original. One shortcoming of our initial study was our operational definition of political orientation. Following their ratings of double jeopardy, participants simply indicated on a single item whether they were liberal, moderate, or conservative. But how valid were these self-assessments? Did our participants accurately understand and faithfully report their political orientations? To address this concern, we added a political attitude scale to our measures, based on a similar scale developed by Lambert and Chasteen (1997). Participants rated their attitudes toward stereotypically conservative issues (e.g., increasing military spending) and stereotypically liberal issues (e.g., government-funded health care; reverse scored) on a -5 (very unfavorable) to +5 (very favorable) scale. The scale was administered following the double jeopardy ratings and immediately following the demographic questions, which were the same as used in Sample 1. Again, the demographic questions included a single-item measure of political orientation wherein participants circled whether they were liberal, moderate, or conservative. The correlation between the scale scores and the single-item measure of political orientation (from 1 = extremely liberal to 5 = extremely conservative) was strong and statistically significant (r = .76, p < .0001) suggesting that the single-item used with Sample 1 was valid. In addition, self-reported liberals had a mean political attitude scale score that was negative, moderates’ scores were close to 0, and conservatives’ scores were positive. A second shortcoming of our original double jeopardy study was that we did not include a self-report measure of racism. Including such a measure would have allowed us to examine Dovidio and Gaertner’s (1998) assertions regarding links between (a) aversive racism and liberalism on the one hand and (b) modern racism and conservatism on the other. Thus with Sample 2 we administered the Modern Racism Scale (MRS; McConahay, 1986) at the very end of each participant’s data collection, immediately following the political attitude scale. In line with Dovidio and Gaertner’s theorizing, we expected that self-reported liberals would score very low on the MRS and significantly lower than self-reported conservatives. This expectation was based on the idea that liberals, as aversive racists, would have a very nonprejudiced self-image and, therefore, would be unwilling to endorse any item that might suggest that they are even the least bit racist. In contrast, conservatives would have fewer problems endorsing such items because they have rationalized negative attitudes toward African Americans as nonracist. Our expectations were supported. Liberals reported a very
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low degree of modern racism (M = 1.70 on a 1 to 5 scale), and significantly less modern racism than both moderates (M = 2.76) and conservatives (M = 2.91). Regarding the primary dependent variable, the ratings of double jeopardy, the results from Sample 2 followed the theoretical predictions derived from Dovidio and Gaertner’s (1998) integrated model, as well as the results from Sample 1 (see Figure 2). Once more, conservative participants showed a bias in favor of the White officer. In contrast, the bias of liberals was in favor of the Black officer. Again, moderates did not differ one way or the other. In this and the original study, officer race and motorist race were always confounded. That is, participants either read about a Black officer/White motorist, or a White officer/Black motorist, making it impossible to separate out the race effects of the two. In a second replication (Nail et al., 2003, Experiment 2), again drawn from the same college town population (M age = 39; N = 130), we systemically de-confounded these variables by having participants read one of four scenarios using each combination of officer and victim race. Once again we repeated our basic double jeopardy findings, with conservatives and liberals showing opposite biases—given a Black victim, conservatives showed favoritism toward a White officer, liberals, a bias against a White officer. That is, the White officer/Black motorist condition was the only one in which ratings for conservatives or liberals were significantly different from the White officer/White motorist control group (Figure 3). Conservatives were much more likely to perceive double jeopardy when the case involved a White officer with a Black motorist, whereas liberals were much less likely to see double jeopardy in this scenario. So, for both conservatives and liberals, making race salient by portraying an interaction between a White high-authority figure and a Black low-authority citizen led to more divergent evaluations. The absence of significant differences among both liberals and conservatives with respect to the White officer/White motorist control groups versus the Black officer/Black motorist experimental groups can be explained by the fact that race was not salient within these conditions. What about the other predictions of the aversive racism model for liberals? Do liberals really experience a conflict between their self-image and attitudes? Can liberals sometimes show even greater discrimination than conservatives?
LIBERALS AND AVERSIVE RACISM Physiological Arousal Thus far, we have presented strong evidence for White liberals’ amplification, but have not addressed the intra-psychic conflict that aversive racism suggests leads to their occasional favoritism for Black over White targets. One of the central ideas of our research is that liberals, as aversive racists, experience a conflict between automatic negative race-based feelings and a very strong desire to be nonracist. This conflict then leads to the amplification effect and favoritism toward minorities. This type of attitude–behavior inconsistency in cognitive dissonance experiments results in both psychological discomfort (Elliot and Devine, 1994) and physiological arousal (e.g., Croyle and Cooper, 1983; Elkin and Leippe, 1986; see also Cooper, Zanna, and Taves, 1978; Rokeach, 1973).
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Double jeopardy ratings
6
5
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White Officer
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2
1
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Moderate
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Political Orientation Figure 2. Double jeopardy ratings as a function of officer race and participant political orientation (Nail et al., 2003, Study 1, Sample 2).
Double jeopardy ratings
7 6 5 Black Officer 4
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White Victim
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Black Victim
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Black Victim
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Political Orientation Figure 3. Double jeopardy ratings as a function of officer race, motorist race, and participant political orientation (Nail et al., 2003, Study 2).
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If the discomfort experienced by aversive racists is similar to that experienced by dissonance study participants, we should expect aversive racists (liberals) to show greater physiological arousal when interacting with another person who is Black as compared to White. The presence of a Black person should prime and make salient liberals’ conflicting values and feelings, thus resulting in discomfort and increased arousal. Modern-symbolic racists, in contrast, should feel little discomfort when interacting with a Black target. Despite their prejudice, they have rationalized their negative beliefs on the basis of traditional values and thus have little or no internal conflict over race (Emerson et al., 1999; McConahay, 1986; Monteith, 1996). Modern-symbolic racists (conservatives), therefore, should not differ in their physiological arousal as a function of another’s race. Consistent with this idea, White students, especially those with higher scores on a modern racism measure, show more negative affect toward Black than White targets as assessed by facial electromyography, but no difference in heart rate (Vanman, Paul, Ito, and Miller, 1997). As we predict for conservatives, they show negative feelings toward Black targets but no apparent discomfort or arousal because of these feelings. To test whether liberals, but not conservatives or moderates, would experience this hypothesized dissonance in interactions with a Black person, we recruited college students for a study of “perceptions of pictures” (Nail et al., 2003, Experiment 3; N = 168). A White female assistant escorted participants into a small room, helped them attach galvanic skin response sensors to their fingers, and seated them in front of a computer monitor. She asked them to relax until the experimenter came in to begin the study. One minute later, a Black or White same-sex experimenter entered the room. The experimenter introduced him or herself and seemingly made some adjustments on the computer for 30 seconds. At this point, the experimenter, unannounced, reached out and took hold of the participant’s wrist to “check your pulse” before the “study” began. Based on the integrated model and our previous results, we expected that White liberals, but not White conservatives, would have an increase in physiological arousal to the Black experimenter, and this is exactly what we found. Liberals showed faster pulse rates and an increase in galvanic skin response from baseline (indicating an increase in physiological arousal) when touched by a Black versus White experimenter, whereas conservatives and moderates did not (Figure 4). Evidence that these observed differences among liberals represent conflict rather than negative affect alone is provided by the lack of arousal effects among conservatives. Although conservatives are expected to have negative affect toward the Black target, because they are comfortable with these thoughts and emotions (through their justifications/ rationalizations), they should not have increased arousal in his/her presence. Further, these results do not seem to be due to previous experience with Black people. Another sample drawn from the same population showed no differences in White liberals’ and conservatives’ contact or number of friendships with Black peers (Harton and Petersen, 2001). As the experimenters were always the same sex as the participants, and because we used several experimenters for each condition (except for the Black male condition, in which we only had one), it is also unlikely that the results were due to sexual attraction or the characteristics of a particular experimenter. Thus the findings suggest that, as we predicted, liberals experience internal conflict in interactions with Black targets, and this conflict may explain their amplification effect. But what about when liberals can respond negatively toward Black targets without feeling that their reaction is race-related?
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43 41 39
Pulse rate
37 35
Black Experimenter
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White Experimenter
31 29 27 25
Liberal
Moderate
Conservative
Political Orientation Figure 4. Pulse rate as a function of experimenter race and participant political orientation (Nail et al., 2003, Study 3). Note. A very similar pattern of results arose for skin conductance (controlling for baseline skin conductance).
Excuses One way that liberals can resolve conflict between their unconscious attitudes and their desire to be non-prejudiced is through suppression and amplification, as we have demonstrated thus far. When there is an “excuse” or another non-racial reason to evaluate a minority member negatively, however, liberals may instead justify and directly express their prejudice. Suppression of prejudice is effortful, and liberals should be anxious to vent their negative feelings in the form of direct discrimination against Black targets when possible (Crandall and Eshleman, 2003). To do so, they need a good excuse so they can discriminate without challenging their non-prejudiced self-image (Frey and Gaertner, 1986; Son Hing, Chung-Yan, Grunfeld, Robichaud, and Zanna, 2005; Son Hing, Chung-Yan, Hamilton, and Zanna, 2008). One excuse, to return to the double jeopardy paradigm, would be to have a non-race-related reason to blame the Black officer. To test whether liberals would show bias against a Black target when there was an alternative, plausible reason to which the bias could be ascribed, Nail, Harton, and Barnes (2008) replicated our original paradigm with another community sample (M age = 46; N = 193). This time, however, we added a sentence to half our scenarios stating that the officer threw the first punch and thus initiated the physical aspects of the conflict. When the punch was unspecified, we replicated our original findings—liberals showed a bias in favor of the
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Black officer5 When the liberals had an excuse to discriminate, however—when the officer seemed to be at fault—they evaluated the Black officer more negatively than the White officer. Thus, liberals, as aversive racists, may sometimes show a bias in favor of minorities and sometimes a bias against minorities, depending on whether showing bias would threaten their non-prejudiced self-image (see also Son Hing et al., 2005, 2008). It is important to note that the “excuses” that free aversive racists to show biases are not related to the target’s group membership. For example, in this case, the Black officer started the fight, so one could blame him without it having anything to do with race. Aversive racists then can feel they have upheld their egalitarian values, as their reaction is not (they believe) based on race. Modern-symbolic racists, on the other hand, use their stereotypes about groups to justify their negative reactions. For example, a modern-symbolic racist may justify blaming the Black officer more regardless of whether the scenario suggests that he started the fight, based on the assumption that Black people are more hostile. Modern-symbolic racists then can feel they are not prejudiced toward the person’s race; increased hostility in Black Americans is “just the way it is.”
WHY ARE CONSERVATIVES AND LIBERALS DIFFERENT? We have shown evidence through a number of studies that conservatives and liberals tend to have negative race-based feelings, but express these feelings in different ways. To ensure that these differences were due to political orientation and not some confounding variable, we examined and systematically ruled out a variety of potential alternative explanations for our findings. In Nail et al. (2003), we ruled out sex, age, education level, occupation, and size of hometown. Socioeconomic status of family of origin, political involvement, and motivation to suppress prejudice likewise do not explain conservative versus liberal biases (Cullum, Harton, and Nail, 2005; Nail, Harton, and Barnes, 2007). Harton and colleagues (2006) also eliminated current socioeconomic status as an alternative explanation. These data suggest that our findings are not merely due to demographic differences between conservatives and liberals. So why do conservatives and liberals tend to express their prejudices in different ways? We contend that those with opposing ideological viewpoints embrace different values. Liberals strongly value egalitarianism (Kerlinger, 1984), and we suggest that it is this desire for equality that sometimes leads them to be hypersensitive with respect to race. They experience a conflict between their desire to be non-prejudiced and their unconscious negative race-based feelings that lead them to discriminate in favor of minorities in some situations and against them in others. Conservatives, on the other hand, highly value individual responsibility (Crandall, Eidelman, and Hellmund, 2004); thus, it is easier for them to “blame the victim” and justify any status differences as based on deservingness (Jost, Glaser, Kruglanski, and Sulloway 2003; Reyna et al., 2006; Skitka, Mullen, Griffin, Hutchinson, and Chamberlin, 2002). As they justify any negative feelings they have as being deserved—that is, due not to the person’s racial category, but to characteristics they believe 5
We should note that in this study we did not replicate our findings for conservatives. We suggest in the article that the lack of an effect may have been due to the relative temporal closeness of our data collection to the 9/11 terrorism events and conservatives’ greater likely defensiveness to such situations (Pyszczynski et al., 2006).
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people of that category just happen to hold—they are comfortable with their feelings and confident in their image of themselves as non-prejudiced. If individual responsibility and background are central motivators of conservatives’ modern-symbolic racism, then having a more “respectable” Black target may lead them to evaluate that target more favorably, or at least equally, to a similar White target. Consistent with this idea, Sniderman et al. (1991) found that conservatives, who clearly had negative attitudes about Black people based on other interview responses, were more sympathetic than liberals to a Black laid off worker if he violated their stereotypes by being described as “married” and “dependable.” To more fully test this hypothesis that conservatives will react to a person’s character as well as his or her racial background, Harton et al. (2006) created a “news article” describing a 17-year-old boy who had been caught with a small amount of illegal drugs. A community sample of participants (M age = 41; N = 98) read the article describing the local court case and gave a suggested reformatory sentence for the perpetrator. Pictures accompanying the articles showed a White or Black male, and the story itself included several details manipulating the target’s socioeconomic status and background— suggesting either a poor youth with a disadvantaged home life, or an upper middle class youth from a “good home.” We expected that liberals would be more forgiving of the youth’s indiscretion, especially if he were from a racial minority group or from a disadvantaged background. Liberals generally want to make sure that all citizens have an equal chance in life (Jost et al., 2003) and try hard not to show any biases, especially toward stigmatized groups. In fact, liberals in this study tended to be more punitive toward the White upper middle class adolescent than the disadvantaged White adolescent or the upper middle class Black adolescent (Figure 5). As predicted by the integrated model, liberals may respond to a conflict between unconscious negative, race-based feelings and their non-prejudiced self-image by being overly favorable toward minorities. This overcorrection does not occur, however, when the person is able to point to a reason or excuse for making the attribution other than race (Gaertner, 1973; Son Hing et al., 2005, 2008). In this study, when the Black adolescent was from a disadvantaged background and had already committed other negative behaviors (e.g., dropping out of school, having a child out of wedlock), liberals were just as punitive as conservatives.
Figure 5. Sentence as a function of perpetrator characteristics and political orientation (Harton et al., 2006).
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Conservatives, on the other hand, were predicted to pay more attention to background, being more forgiving of those from “good” backgrounds who may be more “deserving.” As expected, conservatives were more punitive toward the White and Black adolescents from disadvantaged backgrounds than toward the upper middle class, successful White adolescent. Surprisingly, however, they were highly punitive toward the upper middle class Black adolescent. This finding may provide evidence of a backlash effect, whereby conservatives judge minorities whom they believe have had more opportunities yet still commit negative stereotypical behaviors more harshly than those from less advantaged backgrounds who commit the same behavior—basically Sniderman et al.’s (1991) finding in reverse. The types of racism that liberals and conservatives tend to express do seem to be, at least partly, explained by value differences, as we expected. But do liberals and conservatives differ in automatic responses to others as well?
IMPLICIT VERSUS EXPLICIT ATTITUDES Based on our findings thus far, we expected that while liberals would score lower than conservatives on explicit measures of racism, they also would have a greater discrepancy between their implicit (unconscious associations among concepts; e.g., Black targets and bad versus good) and explicit (self-report) attitudes toward Black people. Conservatives, as modern-symbolic racists, are hypothesized to be comfortable with their negative feelings because they have justified them as nonracist. Meanwhile, liberals have a conflict between their negative feelings and a desire not to be prejudiced that make them particularly sensitive about race. To test this notion, Cullum, Harton, and Nail (2003) had White college student participants (N = 125) complete the Black-White Implicit Association Test (IAT; Greenwald, McGhee, and Schwartz, 1998) as well as various self-report measures of racism (and filler items to disguise the nature of the study). Conservatives and liberals (and moderates for that matter) did not differ on their levels of implicit racism as measured by the IAT (Figure 6), suggesting that the participants shared similar, relatively negative automatic associations with Black versus White targets. Political orientation was not a significant predictor of implicit attitudes, even when controlling for gender and motivation to control prejudice. On our explicit measure, however, liberals showed less prejudice than both moderates and conservatives. Further, only liberals showed a significant difference between their levels of implicit and explicit racism. These results are consistent with recent research that has defined aversive racists as those high in implicit but low in explicit racism (Son Hing, Li, and Zanna, 2002; Son Hing et al., 2005, 2008).
WHAT ABOUT THE MODERATES? In this chapter, we have focused primarily on conservatives and liberals, but in most of the studies reported here, we also assessed the responses of moderates. As one might expect, it turns out that moderates are, well, moderate. Their ratings on modern racism scales fell between those of conservatives and liberals (Cullum et al., 2003; Nail et al., 2003), their evaluations of Black targets were generally equivalent to their evaluations of White targets
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(Harton et al., 2006; Nail et al., 2003, 2008), and they did not show a discrepancy between their relative levels of implicit and explicit racism (Cullum et al., 2003) or any physiological arousal in response to a Black experimenter (Nail et al., 2003). In sum, moderates generally neither showed the anti-Black biases of modern-symbolic racists (conservatives), nor the arousal or amplification of aversive racists (liberals). Political moderates, then, may actually be less prejudiced than conservatives and liberals.
WHAT ABOUT PREJUDICE TOWARD OTHER GROUPS? Most research on modern-symbolic and aversive racism in the United States has focused on White participants’ attitudes, behaviors, or perceptions toward Black targets, but there are obviously other groups that suffer prejudice and discrimination in our society as well. In a recent study (Harton, Kochurka, and Nail, 2008; see also Kochurka, 2007), we examined whether the integrated model might apply to prejudice against homosexuals (viz., homonegativity). Conservative and liberal heterosexual college students (as identified in a mass testing session; N = 79) participated in a study of “online impressions.” A female experimenter escorted participants individually to a room where they were told that they would discuss topics over the computer with a participant in another room. They received demographic information about their partner indicating that he was a 19-year old in-state sophomore who was either homosexual or heterosexual. They then chatted with their partner, who was actually an experimental confederate, for 20 minutes about their attitudes on various political issues (e.g., the war in Iraq). The confederate was randomly assigned to either agree with the participants (based on their pretest answers) on most of the issues, or disagree on most issues.
Figure 6. Implicit and explicit levels of racism for liberals, moderates, and conservatives (Cullum et al., 2003). Note. Racism is shown as standardized levels, standardized within the current study.
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Figure 7. Helping intentions as a function of participant political orientation, confederate sexual orientation, and degree of agreement with confederate (Harton et al., 2008).
After the chat, the participants rated how much they would be willing to help their chat partner on various school-related tasks such as loaning him notes or tutoring him in a class. As expected by the model, we found a marginally significant 3-way interaction of participant political orientation, confederate sexual orientation, and the degree of agreement on helping intentions (Figure 7). Consistent with the concept of modern-symbolic prejudice, conservatives tended to be less likely to help the attitudinally similar gay confederate than the heterosexual one. Likewise, consistent with the aversive racism model, liberals tended to be more willing to help the gay confederate than conservatives if the confederate had similar attitudes. Liberals, however, tended to be more negative toward the gay confederate than conservatives when there was an “excuse” for their lack of helping intentions (i.e., when the confederate was attitudinally dissimilar to the participant; Figure 7), mirroring our findings in Nail et al. (2008). Liberals’ hypothesized unconscious conflict between a desire to be egalitarian and negative attitudes may lead them to overcompensate and rate minorities more favorably than non-minorities except when they can attribute their negative attitudes to something besides prejudice. Further, these results held when controlling for gender, participant age, self-reported attitudes toward homosexuals, and religious fundamentalism. The effects were reduced, however, when social dominance orientation (SDO) was controlled. Contrary to previous research suggesting that SDO is a core part of conservatism (Jost et al., 2003), we found that
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conservatives were not higher in social dominance orientation than liberals and, in fact, that SDO was more predictive of (not) helping for liberals than for conservatives. Interestingly, in this study, conservatives tended to react in a surprisingly positive manner toward the gay man with whom they disagreed—the same group that liberals showed the most negative reaction toward. This tendency also shows up in Harton et al. (2006), where conservatives tended to suggest less harsh sentences for the Black juvenile who had dropped out of school and gotten his girlfriend pregnant than for a more “upstanding” Black youth, and in Nail et al. (2008), where conservatives tended to rate double jeopardy higher for a Black officer who had started a fight with a motorist than for one who had not. Although these are not statistically significant differences, the fact that the trend has emerged across several studies suggests that there may be a real effect. Perhaps conservatives are actually less biased toward minorities who fulfill the conservatives’ negative stereotypes of their group than of those who do not and thus seem more similar to them.
CONCLUSION We have described a systematic program of research that tests the integrated model of racism (Dovidio and Gaertner, 1998, 2004), a model that links modern-symbolic racism to political conservatives and aversive racism to liberals. Together these studies provide strong, converging evidence that White conservatives generally have negative feelings toward Black people that they rationalize as not due to prejudice but based instead on important and consequential differences between Blacks and Whites (e.g., Black people are lazy or violent). These perceptions help White conservatives see race-related status differences as deserved. Liberals, on the other hand, have similar negative feelings, but they also have a strong desire not to be prejudiced. This conflict between their feelings and self-image frequently leads them to experience conflict and respond (when they can not attribute discrimination to a nonracial factor) with more favorable evaluations and responses to Black than White targets. We also presented some preliminary evidence that these tendencies may hold when evaluating gay men and, by extension, other stigmatized groups. Finally, we suggested that moderates may be neither modern-symbolic nor aversive racists and may be less prejudiced than liberals or conservatives, at least as prejudice was measured in these studies. We have suggested that the differences noted in the ways conservatives and liberals express prejudice are linked to their core values. These core values may lead them (especially liberals) to use motivated social cognition to change their perceptions. Crandall et al. (2004) have suggested that conservatism may be our human “default.” That is, many of the errors that humans make in judgment, such as the fundamental attribution error (Ross, 1977), are essentially conservative in origin (they emphasize individual responsibility over group equality). In fact, conservatives are much more likely to make the fundamental attribution error in a variety of types of judgments than are liberals (Skitka et al., 2002). When under cognitive load, however, liberals commit the fundamental attribution error to the same extent as conservatives, suggesting that they are motivated to overcome or adjust for their initial (conservative) responses.
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Future Research We have several studies currently underway to address other aspects of Dovidio and Gaertner’s (1998, 2004) integrated model and the limitations of our previous studies. For example, our measures of arousal were somewhat ambiguous in the study in which we found that only liberals showed higher physiological arousal in response to a Black experimenter as compared to a White (Nail et al., 2003, Experiment 3). Pulse rate and galvanic skin response are two of the most reliable physiological measures of prejudice (Guglielmi, 1999) and can indicate intra-psychic conflict (as we believe they did in our study, for reasons detailed in that section). However, they also can indicate other emotional responses, such as attraction, guilt, and fear (Guglielmi, 1999). One possibility for these results, sometimes suggested by academics who hear about our research, is that liberals may show increased arousal because they are particularly concerned about not showing racism when interacting with Black targets. On the one hand, our physiological data can not differentiate between this innocent, nonracist interpretation and the one that we favor in this chapter—that White liberals show increased arousal to Blacks because they tend to be aversive racists and thus experience intra-psychic conflict over race. On the other hand, unlike the aversive racism model, the nonracist interpretation can not explain why White liberals (a) show discrimination against Blacks when it can be justified as nonracist (Frey and Gaertner, 1986; Nail et al., 2008; Son Hing et al., 2005, 2008) and (b) reveal so much greater implicit racism than explicit racism (Figure 6). Blascovich and colleagues (e.g., Blascovich and Mendes, 2000; Blascovich, Mendes, Hunter, Lickel, and Kowai-Bell, 2001) have used cardiovascular indices to differentiate between threat and challenge responses. They found that White participants with little interracial contact tended to show a threat response when interacting with a Black partner on a task, whereas individuals with more contact displayed a challenge response. The use of more refined indices of arousal such as those of Blascovich et al. may allow us to better differentiate modern-symbolic and aversive racism and to conclude more confidently that the arousal of White liberals to Blacks is due to conflict/dissonance over race. We are currently in the planning stages of research that will measure cardiac output as well as a variety of other physiological measures during a laboratory interaction between White participants and Black versus White confederates. Another limitation of our research is that we have examined the amplification effect of aversive racism for liberals (whether they will overcompensate for their negative feelings about Black people by showing a bias toward a Black target) and our proposed cause of this effect (their increased physiological arousal when interacting with a Black target) in separate studies. A much stronger case could be made that the two are connected if we could show that arousal mediated subsequent amplification in the same study. An initial attempt to do this (Weipert, Close, Nguyen, Strouse, and Harton, 2006), by having heterosexual participants imagine dating other-sex White, Black, and filler targets and rating those targets while their heart rate was being continuously recorded, produced mixed results. We believe that these inconclusive findings may have been due, however, to the sterility of our constructed, laboratory situation. Imagining dating someone (if participants even did as we requested) may not have been a strong enough situation to induce conflict in liberals. They may also have been able to easily devise other “excuses” that were nonracial for why they might be less interested in a particular Black target as a dating partner. In future research, we plan to
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measure physiological arousal during actual White-White and White-Black interactions that also include evaluations of the White or Black target. We conducted an initial study that examined whether a target’s background (traditional versus nontraditional upbringing) affected participants’ evaluations of a Black versus White youth who was caught with a small amount of illegal drugs. We found some support for our contention that background would matter, but in different ways, for conservatives versus liberals. Conservatives were least punitive toward the White adolescent from a “good” background, whereas the liberals tended to be more punitive toward this boy than toward a Black adolescent from a good background or a White adolescent from a disadvantaged background. In this study, however, the youths were all allegedly guilty of a crime. In future research, we plan to examine how background affects reactions of conservatives and liberals in a more positive setting such as the evaluation of a job or scholarship application. Although we have found strong evidence that conservatives and liberals show different types of racism, we know little about potential mediators of these effects. In our most recent double jeopardy research examining evaluations of the police officer accused of beating a motorist, sympathy for the officer, but not anger or sympathy for the motorist, partially explained participants’ ratings of double jeopardy (Nail et al., 2007). That is, conservatives were more likely to feel sympathy for the White officer (and liberals, the Black), and more sympathy was related to higher ratings of double jeopardy. When participants rated the juvenile perpetrator in Harton et al. (2006), anger, but not sympathy, partially mediated the relationship between political orientation and evaluations. Participants who reported more anger toward the perpetrator tended to give more punitive responses. Further analyses and additional research are needed to better understand how emotions may relate to modernsymbolic and aversive racism. Finally, these results may or may not apply to interactions with group members other than Black Americans or to locations outside the United States. Due to slavery and past systematic discrimination, Black and White Americans have a unique history that may lead to different associations with racism (and on the part of liberals, potential feelings of guilt) than in other ethnic groups or countries. However, one study from our laboratories suggests that White American conservatives and liberals may show similar biases toward gay men. There is also evidence that some Canadians demonstrate aversive racism toward people of Asian descent (Son Hing et al., 2002), and that this aversive racism may be linked to political liberalism (Son Hing et al., 2008). Fiske and colleagues (Fiske, Cuddy, Glick, and Xu, 2002) suggest that people stereotype others along two dimensions: warmth and competence. Black people and gay men, the two categories that we have tested thus far, typically fall in the middle on both dimensions (although some subtypes of gay men are seen as higher or lower on each dimension; none are seen as high in both; see Clausell and Fiske, 2005). We suspect that while the integrated model will apply to all out-groups to an extent, it likely will be strongest for groups that are relatively low on competence, regardless of how warm Americans tend to feel toward the group. That is, we would expect conservatives to react more negatively toward groups Fiske et al. (2002) identified as low competence/low warmth such as the homeless and the poor, but also to low competence/high warmth groups such as the disabled. To the extent that negative stereotypes exist toward these groups, the conservative tendency toward individual responsibility and justification of status differences (Crandall et al., 2004) would likely lead them to be evaluated more negatively. Liberals, on the other hand, would have a tendency to
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overcorrect their initial negative feelings toward these groups, leading to more favorable evaluations and responses. High competence but disliked groups such as the rich and men (Fiske et al., 2002) may actually engender an opposite response from conservatives and liberals. They should not induce conservatives’ justification—these groups have an advantaged position, and by conservative ideology, they must deserve it, leading potentially to higher evaluations. They also should not induce liberals’ overcorrection—although liberals may have negative feelings toward these groups, there is no threat to their self-image in identifying these feelings as justified.
Final Note The research in this chapter may not seem very hopeful—both White conservatives and liberals generally showed very different yet still racist reactions toward Black targets relative to White targets. Yet, we believe there is reason for guarded optimism. Conservatives tend to justify their beliefs as not being race-based but character-based. Interventions and experiences that show conservatives that their stereotypes of minority groups are incorrect would potentially lead them to decrease their bias. Liberals’ concern about racism and desire for a non-prejudiced society are also hopeful—the more attention that can be brought to bear on these issues, the better the potential for change. Further, even if liberals do show biases in favor of minorities in some situations, these biases may help reverse the negative effects of biases against the same minorities in other situations (see Leiber, 2003). Finally, the relative non-bias of moderates suggests that decreasing, perhaps even eliminating, racism is not an impossible task.
REFERENCES Adorno, T. W., Frenkel-Brunswick, E., Levinson, D. J., and Sanford, R. N. (1950). The authoritarian personality. New York: Harper and Row. Blascovich, J., and Mendes, W. B. (2000). Challenge and threat appraisals: The role of affective cues. In J. Forgas (Ed.), Feeling and thinking: The role of affect in social cognition (pp. 59-82). Cambridge, UK: Cambridge University Press. Blascovich, J., Mendes, W. B., Hunter, S. B., Lickel, B., and Kowai-Bell, N. (2001). Perceiver threat in social interactions with stigmatized others. Journal of Personality and Social Psychology, 80, 253-267. Chronology of the O. J. Simpson Trials. (n.d.). Retrieved December 6, 2006 from http://www.law.umkc.edu/faculty/projects/ftrials/Simpson/Simpsonchron.html. Clausell, E., and Fiske, S. T. (2005). When do subgroup parts add up to the stereotypic whole? Mixed stereotype content for gay male subgroups explains overall ratings. Social Cognition, 23, 161-181. Cooper, J., Zanna, M. P., and Taves, P. A. (1978). Arousal as a necessary condition for attitude change following induced compliance. Journal of Personality and Social Psychology, 36, 1101-1106.
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Crandall, C. S., Eidelman, S., and Hellmund, S. (2004, May). Natural psychological advantage of conservative ideology. Invited paper presented at the Midwestern Psychological Association conference, Chicago, IL. Crandall, C. S., and Eshleman, A. (2003). A justification-suppression model of the expression and experience of prejudice. Psychological Bulletin, 129, 414-446. Croyle, R., and Cooper, J. (1983). Dissonance arousal: Physiological evidence. Journal of Personality and Social Psychology, 45, 782-791. Cullum, J., Harton, H. C., and Nail, P. R. (2003, February). Political orientation and the nature of prejudice. Poster presented at the meeting of the Society for Personality and Social Psychology, Los Angeles, CA. Cullum, J., Harton, H. C., and Nail, P. R. (2005). Implicit and explicit racial attitudes [raw data]. University of Wyoming, Laramie. Dovidio, J. F., and Gaertner, S. L. (1986). Prejudice, discrimination, and racism: Historical trends and contemporary approaches. In J. F. Dovidio and S. L. Gaertner (Eds.), Prejudice, discrimination, and racism (pp. 1-34). New York: Academic Press. Dovidio, J. F., and Gaertner, S. L. (1998). On the nature of contemporary prejudice: The causes, consequences, and challenges of aversive racism. In J. L. Eberhardt and S. T. Fiske (Eds.), Confronting racism: The problem and the response (pp. 3-32). Thousand Oaks, CA: Sage. Dovidio, J. F., and Gaertner, S. L. (2004). Aversive racism. In M. P. Zanna (Ed.), Advances in experimental social psychology (Vol. 36, pp. 1-52). San Diego, CA: Academic Press. Dovidio, J. F., Smith, J. K., Donnella, A. G., and Gaertner, S. L. (1997). Racial attitudes and the death penalty. Journal of Applied Social Psychology, 27, 1468-1487.
Duncan, B. L. (1976). Differential social perception and attribution of intergroup violence: Testing the lower limits of stereotyping of African-Americans. Journal of Personality and Social Psychology, 34, 590-598. Elkin, R. A., and Leippe, M. R. (1986). Physiological arousal, dissonance, and attitude change: Evidence for a dissonance-arousal link and a “Don’t remind me” effect. Journal of Personality and Social Psychology, 51, 55-65. Elliot, A. J., and Devine, P. G. (1994). On the motivational nature of cognitive dissonance: Dissonance as psychological discomfort. Journal of Personality and Social Psychology, 67, 382-394. Emerson, M. O., Smith, C., and Sikkink, D. (1999). Equal in Christ, but not in the world: White conservative Protestants and explanations of black-white inequity. Social Problems, 46, 398-417. Fazio, R. H., Jackson, J. R., Dunton, B. C., and Williams, C. J. (1995). Variability in automatic activation as an unobtrusive measure of racial attitudes: A bona fide pipeline? Journal of Personality and Social Psychology, 69, 1013-1027. Fein, S., Morgan, S. J., Norton, M. I., and Sommers, S. R. (1997). Hype and suspicion: The effects of pretrial publicity, race, and suspicion on jurors’ verdicts. Journal of Social Issues, 53, 487-502. Fiske, S. T., Cuddy, A. J., Glick, P., and Xu, J. (2002). A model of (often mixed) stereotype content: Competence and warmth respectively follow from perceived status and competition. Journal of Personality and Social Psychology, 82, 878-902.
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Frey, D. L., and Gaertner, S. L. (1986). Helping and the avoidance of inappropriate interracial behavior: A strategy that perpetuates a non-prejudiced self-image. Journal of Personality and Social Psychology, 50, 1083-1090. Gaertner, S. L. (1973). Helping behavior and racial discrimination among liberals and conservatives. Journal of Personality and Social Psychology, 25, 335-341. Gaertner, S. L., and Dovidio, J. F. (1986). The aversive form of racism. In J. F. Dovidio and S. L. Gaertner (Eds.), Prejudice, discrimination, and racism (pp. 61-89). Orlando, FL: Academic Press. Greenwald, A. G., McGhee, D. E., and Schwartz, J. L. K. (1998). Measuring individual differences in implicit cognition: The implicit association test. Journal of Personality and Social Psychology, 74, 1464-1480.
Guglielmi, R. S. (1999). Psychophysiological assessment of prejudice: Past research, current status, and future directions. Personality and Social Psychology Review, 3, 123-157. Harton, H. C., and Petersen, A. K. (2001). [Demographic and personality predictors of attitudes toward ethnic groups.] Unpublished raw data, University of Northern Iowa, Cedar Falls. Harton, H. C., Kochurka, K., and Nail, P. R. (2008). Political orientation and sexual prejudice: A test of Dovidio and Gaertner’s (1998) integrated model. Manuscript in preparation, University of Northern Iowa, Cedar Falls. Harton, H. C., Weipert, R., Close, A., Bumgarner, J., Johnson, K., and Banwart, S. (2006, January). Political orientation, race, and the violation of traditional values. Poster presented at the meeting of the Society for Personality and Social Psychology, Palm Springs, CA. Henry, P. J., and Sears, D. O. (2002). The symbolic racism 2000 scale. Political Psychology, 23, 253-283. Jost, J. T., Glaser, J., Kruglanski, A. W., and Sulloway, F. J. (2003). Political conservatism as motivated social cognition. Psychological Bulletin, 129, 339-375. Katz, I. (1981). Stigma: A social psychological analysis. Hillsdale, NJ: Erlbaum. Kerlinger, F. N. (1984). Liberalism and conservatism: The nature and structure of social attitudes. Hillsdale, NJ: Erlbaum. Kinder, D. R. (1986). The continuing American dilemma: White resistance to racial change 40 years after Myrdal. Journal of Social Issues, 42, 151-171. Kinder, D. R., and Sears, D. O. (1981). Prejudice and politics: Symbolic racism versus racial threats to the good life. Journal of Personality and Social Psychology, 40, 1141-1147. Kochurka, K. J. (2007). Sexual prejudice and political orientation online: A test of Dovidio and Gaertner’s integrated model of racism. Unpublished Masters Thesis, University of Northern Iowa, Cedar Falls. Lambert, A. J., and Chasteen, A. L. (1997). Perceptions of disadvantage versus conventionality: Political values and attitudes toward the elderly versus AfricanAmericans. Personality and Social Psychology Bulletin, 23, 469-481. Leiber, M. J. (2003). The contexts of juvenile justice decision making: When race matters. Albany, NY: State University of New York Press. McConahay, J. B. (1986). Modern racism, ambivalence, and the modern racism scale. In J. F. Dovidio and S. L. Gaertner (Eds.), Prejudice, discrimination and racism (pp. 91-125). Orlando, FL: Academic Press.
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McConahay, J. B., and Hough, J. C., Jr. (1976). Symbolic racism. Journal of Social Issues, 32, 23-45. Meertens, R. W., and Pettigrew, T. F. (1997). Is subtle prejudice really prejudice? Public Opinion Quarterly, 61, 54-71. Monteith, M. J. (1996). Contemporary forms of prejudice-related conflict: In search of a nutshell. Personality and Social Psychology Bulletin, 22, 461-473. Nail, P. R., Harton, H. C., and Barnes, A. (2007). Further tests of the integrated model [raw data]. University of Central Arkansas, Conway. Nail, P. R., Harton, H. C., and Barnes, A. (2008). A test of Dovidio and Gaertner’s Integrated Model of Racism. North American Journal of Psychology, 10, 197-220. Nail, P. R., Harton, H. C., and Decker, B. P. (2003). Political orientation and modern versus aversive racism: Tests of Dovidio and Gaertner’s integrated model. Journal of Personality and Social Psychology, 84, 754-770. Pyszczynski, T., Abdollah, A., Solomon, S., Greenberg, J., Cohen, F., and Weise, D. (2006). Mortality salience, martyrdom and military might: The great Satan versus the axis of evil. Personality and Social Psychology Bulletin, 32, 525-537. Reyna, C., Henry, P. J., Korfmacher, W., and Tucker, A. (2006). Examining the principles in principled conservatism: The role of responsibility stereotypes as cues for deservingness in racial policy decisions. Journal of Personality and Social Psychology, 90, 109-128.
Rokeach, M. (1973). The nature of human values. New York: Free Press. Ross, L. (1977). The intuitive psychologist and his shortcomings: Distortions in the attribution process. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 10, pp. 173-220). Orlando, FL: Academic Press. Sears, D. O. (1988). Symbolic racism. In P. A. Katz and D. A. Taylor (Eds.), Eliminating racism: Profiles in controversy (pp. 53-84). New York: Plenum. Sears, D. O. (1998). Racism and politics in the United States. In J. L. Eberhardt and S. T. Fiske (Eds.), Confronting racism: The problem and the response (pp. 76-100). Thousand Oaks, CA: Sage. Sears, D. O., and Henry, P. J. (2003). The origins of symbolic racism. Journal of Personality and Social Psychology, 85, 259-275. Sears, D. O., and Henry, P. J. (2005). Over thirty years later: A contemporary look at symbolic racism. In M. P. Zanna (Ed.), Advances in experimental social psychology (Vol. 37, pp. 95-150). San Diego, CA: Elsevier Academic Press. Sherif, M., and Sherif, C. W. (1969). Social psychology. New York, NY: Harper and Row. Skitka, L. J., Mullen, E., Griffin, T., Hutchinson, S., and Chamberlin, B. (2002). Dispositions, scripts, or motivated correction?: Understanding ideological differences in explanations for social problems. Journal of Personality and Social Psychology, 83, 470-487. Sniderman, P. M., Piazza, T., Tetlock, P. E., and Kendrick, A. (1991). The new racism. American Journal of Political Science, 35, 423-447. Son Hing, L. S., Chung-Yan, G. A., Grunfeld, R., Robichaud, L. K., and Zanna, M. P. (2005). Exploring the discrepancy between implicit and explicit prejudice: A test of aversive racism theory. In J. P. Forgas, K. D. Williams, and S. M. Laham (Eds.), Social motivation: Conscious and unconscious processes (pp. 274-293). New York: Cambridge University Press.
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Son Hing, L. S., Chung-Yan, G. A., Hamilton, L. K., and Zanna, M. P. (2008). A twodimensional model that employs explicit and implicit attitudes to characterize prejudice. Journal of Personality and Social Psychology, 94, 971-987.
Son Hing, L. S., Li, W., and Zanna, M. P. (2002). Inducing hypocrisy to reduce prejudicial responses among aversive racists. Journal of Experimental Social Psychology, 38, 71-78. Vanman, E. J., Paul, B. Y., Ito, T. A., and Miller, N. (1997). The modern face of prejudice and structural features that moderate the effect of cooperation on affect. Journal of Personality and Social Psychology, 73, 941-959. Weipert, R., Close, A., Nguyen, D., Strouse, S., and Harton, H. C. (2006, May). Race, politics and dating: A test of the Integrated Model of Racism. Poster presented at the meeting of the Midwestern Psychological Association, Chicago, IL.
In: The Psychology of Modern Prejudice Editors: Melanie A. Morrison and Todd G. Morrison
ISBN 978-1-60456-788-5 © 2008 Nova Science Publishers, Inc.
Chapter 4
THE RELATIONSHIP BETWEEN MODERN AND IMPLICIT PREJUDICE John E. Edlund and Jeremy D. Heider Northern Illinois University, USA Stephen F. Austin State University, USA
ABSTRACT Two studies investigated the relationship between modern prejudice (assessed using the Pro-Black/Anti-Black Attitudes Questionnaire [PAAQ; Katz and Hass, 1988] and Quick Discrimination Index [QDI; Ponterotto, Burkard, Rieger, and Grieger, 1995]), implicit prejudice (assessed using a racial Implicit Association Test [IAT; Greenwald, McGhee, and Schwartz, 1998]), political conservatism, and motivation to control prejudice. The key findings were: (a) modern and implicit prejudice exhibited a positive – albeit weak – relationship; (b) political conservatism was positively related to both modern and implicit prejudice; (c) externally-induced motivation to control prejudice was associated with greater modern prejudice; (d) internally-induced motivation to control prejudice was associated with lower modern prejudice; and (e) internally-induced motivation to control prejudice was a stronger predictor of prejudice-related attitudes than externally-induced motivation to control prejudice.
INTRODUCTION Prejudice comes in many forms. A key distinction that can be made among these forms is between old-fashioned prejudice, modern prejudice, and implicit prejudice. Old-fashioned prejudice is generally considered the “traditional” form of prejudice, involving beliefs about the biological superiority of one group over another. Modern prejudice, on the other hand, is a set of beliefs regarding the moral superiority of a group, particularly in terms of characteristics such as work ethic (Whitley and Kite, 2006). Due to the present societal climate, one is much more likely to see expressions of modern prejudice than old-fashioned prejudice. Finally, implicit prejudice refers to automatically activated associations between a
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social group and negativity (or positivity), with many researchers arguing that these associations, for the most part, operate outside conscious awareness (e.g., Greenwald, McGhee, and Schwartz, 1998).1
Measures of Modern Prejudice Instruments have been designed to assess modern prejudice in a number of domains, including prejudice toward women (Glick and Fiske, 1996), Jews (Gale, 2004), individuals with intellectual disabilities (Akrami, Ekehammar, Claesson, and Sonnander, 2006), and lesbian women and gay men (Morrison, Kenny, and Harrington, 2005). However, the majority of the research on modern prejudice has been conducted in the domain of racial and/or ethnic prejudice, particularly in the context of Black-White relations in America. Throughout the 1970s and 1980s, numerous researchers noted that the contemporary racial attitudes of White Americans were markedly different than those expressed in the 1940s (e.g., Lipset and Schneider, 1978; Schuman, Steeh, and Bobo, 1985; Smith and Sheatsley, 1984). Specifically, attitudes toward Blacks had become more favorable over time. However, the fact that many Whites were still opposed to policies such as mandatory school busing and job quotas suggested that the changes in opinion may have been superficial and that Whites still harbored prejudice toward Blacks (e.g., Feagin, 1980; Hsu, 1972; Jackman, 1978; Jones, 1977; Jones, 1972).2 Similar ideas had emerged in theories about symbolic racism (e.g., McConahay, 1986). Although McConahay (1986) developed the most widely utilized measure of modern racial prejudice, the Modern Racism Scale (MRS), the present research employed the Quick Discrimination Index (QDI; Ponterotto, Burkard, Rieger, and Grieger, 1995), a measure with a more reliable factor structure (i.e., clearer cognitive and affective components). These studies also used a measure of ambivalence, or attitudinal conflict. Katz (1981) proposed that a hallmark of modern racial attitudes may be the presence of such ambivalence. Based on this proposition, Katz and Hass (1988) asserted that both a “pro” and an “anti” attitude toward Blacks may exist within any given White individual. They developed the Pro-Black/AntiBlack Attitudes Questionnaire (PAAQ), which separately assesses pro-Black (sympathetic) and anti-Black (prejudiced) attitudes. In addition, the product of the pro-Black score and the anti-Black score can be used as an index of attitudinal ambivalence (see Katz and Hass, 1988).
1
2
Others have suggested a greater degree of conscious awareness of implicit associations (e.g., Gawronski, Hofmann, and Wilbur, 2006); however, these researchers still acknowledge the tendency for implicit prejudice to influence other non-conscious processes that are not influenced by old-fashioned or modern prejudice. On the other hand, Schuman et al. (1985) pointed out that there were observable changes in Whites’ public behavior toward Blacks, such as Whites’ endorsement of integration policies. Such public endorsements suggested that Whites did currently have a more genuine commitment to civil rights than they did in years past.
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Measures of Implicit Prejudice Although one is more likely to observe modern prejudice than old-fashioned prejudice in contemporary society, many individuals may be reluctant to express even modern forms of prejudice. Much of the research on old-fashioned and modern prejudice has employed traditional explicit measures that attempt to assess attitudes by directly asking individuals to report their personal beliefs. However, measures that rely on self-report are frequently subject to unwanted influences. One of these influences is the desire to appear socially appropriate, which is particularly likely to be problematic when assessing attitudes in a socially sensitive domain (Whitley and Kite, 2006). For example, an individual who holds a negative attitude toward African Americans (even a “modern” one, such as opposition to affirmative action programs) may be reluctant to admit to this attitude on a questionnaire because contemporary society generally frowns upon such negative beliefs. The past two decades have seen the development of a new, alternative approach to attitude assessment. A number of researchers have developed indirect, unobtrusive techniques to measure attitudes. These implicit measures examine phenomena such as evaluative associations in memory which, in turn, are believed to be indicative of an individual’s attitude (see Greenwald et al., 1998). These unobtrusive measures quickly rose to prominence in social psychological research, not only because they avoid issues of social desirability and self-presentation, but because they have been shown to reveal unique components of attitudes that lie outside conscious awareness and control (Banaji, 2001). In addition, some researchers have argued that implicit and explicit attitude measures assess independent knowledge structures, and therefore should be only weakly related, if not unrelated (e.g., Greenwald and Banaji, 1995; Greenwald et al., 1998). A variety of techniques to measure implicit attitudes have been employed by social cognition researchers, many of which focus on the assessment of implicit racial attitudes and/or stereotypes. These include word-fragment completion tasks (e.g., Dovidio, Kawakami, Johnson, Johnson, and Howard, 1997; Sinclair and Kunda, 1999), the extent to which descriptions of African Americans’ positive and negative behaviors use abstract versus concrete language (e.g., von Hippel, Sekaquaptewa, and Vargas, 1995, 1997), and the extent to which completion of a sentence explains a described behavior (as opposed to simply continuing the sentence without explaining the behavior; von Hippel et al., 1997; Sekaquaptewa, Espinoza, Thompson, Vargas, and von Hippel, 2002). However, despite the success of these approaches, the vast majority of research on implicit attitudes has used one of two primary techniques. The first of these techniques is the evaluative priming paradigm and its variants (Fazio, Sanbonmatsu, Powell, and Kardes, 1986). In an evaluative priming procedure, individuals are asked to indicate the connotation of an evaluative adjective (e.g., is this word good or bad?) after exposure to a prime. Primes can be presented either supraliminally (e.g., Fazio, Jackson, Dunton, and Williams, 1995) or subliminally (e.g., Dovidio et al., 1997; Dovidio, Kawakami, and Gaertner, 2002). For the assessment of implicit racial attitudes, the primes are typically photographs of the faces of African Americans and Caucasians. Implicit negativity is indicated by facilitated responding to negative adjectives following an African American face relative to a Caucasian face (and, to some extent, inhibited responding to positive adjectives following an African American face; see Fazio et al., 1995).
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The second frequently employed implicit technique – and the one utilized in the present research – is the Implicit Association Test, or IAT (Greenwald et al., 1998).3The IAT is a computer-based measure that assesses the strength of an individual’s association between a target concept and an attribute dimension by comparing response latencies to attitudeconsistent and attitude-inconsistent judgments. The underlying theory behind the IAT is that individuals should find it easy to provide the same response to two concepts that are similar in evaluative connotation. On the other hand, it should be relatively difficult to execute the same response to concepts that are of contrasting evaluative connotations. For example, if an individual associates positivity with Whites and negativity with Blacks, that individual should have little difficulty making the same response to stimuli from the categories “White” and “pleasant,” and the same response to stimuli from the categories “Black” and “unpleasant.” However, if the evaluative pairings were reversed (i.e., “White” paired with “unpleasant” and “Black” paired with “pleasant”), the increased difficulty of responding is typically reflected in increased latencies and possibly commission of more errors (See Nosek and Banaji [2001] for discussion of a variant of the IAT that does not require a contrast category).
The Relationship between Modern and Implicit Prejudice A number of researchers have provided reviews of the literature examining the relationship between modern and implicit prejudice (e.g., Dovidio, Kawakami, and Beach, 2001). As one might expect from previous theoretical treatments (e.g., Greenwald and Banaji, 1995), correlations between the two types of measures are often weak – at least within socially sensitive domains such as racial and ethnic attitudes (e.g., Devine, Plant, Amodio, Harmon-Jones, and Vance, 2002; Dovidio et al., 2002; Fazio et al., 1995; Greenwald et al., 1998; Kawakami and Dovidio, 2001; Ottaway, Hayden, and Oakes, 2001). Exceptions to this pattern certainly exist (e.g., McConnell and Liebold, 2001), but generally speaking, strong correlations between implicit and explicit attitude measures tend to emerge only with attitudes toward non-social objects. Obviously, these explicit attitudes cannot be considered part of the domain of modern prejudice as such prejudice only exists toward social groups. Based on these and other similar findings, Fazio and Olson (2003) have suggested it is more fruitful to ask when we might expect to observe a relationship between modern and implicit prejudice as opposed to if we might observe such a relationship. In other words, what are the conditions under which one might see significant relationships between the two types of prejudice? The data that have accumulated thus far support a perspective based on Fazio’s (1990) MODE (motivation and opportunity as determinants) model. In more socially sensitive domains, motivational mechanisms are induced that influence conscious responses on explicit measures. It is in these domains that one would expect some divergence between implicit and modern prejudice. In less sensitive domains, such motivation is not induced, leaving explicit responses more “pure” and thus more likely to correlate with implicit responses.
3
There is some debate in recent literature as to the psychometric quality of the IAT (see Blanton, Jaccard, Christie, and Gonzales, 2007; Blanton, Jaccard, Gonzales, and Christie, 2006). We continue to use the IAT in our own research largely because we find these arguments less than compelling in the face of a wealth of evidence in favor of the measure’s reliability and validity (see Nosek and Sriram, 2007; Poehlman, Uhlmann, Greenwald, and Banaji, 2006).
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At the same time, Fazio and Olson (2003) note that this pattern does not mean implicit attitudes are somehow “real,” whereas explicit attitudes are “fake.” To the contrary, they are qualitatively different types of attitudes that are each subject to numerous influences – some shared and some unique. If the two types of attitudes are formed and maintained in somewhat different ways, we should not be surprised when they diverge in socially sensitive domains. This is exactly the case with a social category such as race – modern prejudice is based primarily on personal feelings of morality; implicit prejudice derives in large part from cultural-level associations (e.g., media influences; see Whitley and Kite, 2006).4 Moreover, it should be noted that both modern and implicit prejudice have considerable value as predictors of behavior – albeit different types of behavior. Modern prejudice is especially well-suited to predict overt, deliberative behaviors, whereas implicit prejudice is better suited to predict more subtle, spontaneous behaviors (e.g., Dovidio et al., 1997; Fazio et al., 1995; Heider and Skowronski, 2007).
STUDY 1 One potential influence on prejudiced attitudes – be they modern or implicit – is one’s political preferences. Specifically, individuals with politically conservative attitudes often report higher levels of prejudice than those with politically liberal attitudes (see Agnew, Thompson, and Gaines, 2000; Morrison and Morrison, 2002). The primary goal of Study 1 was to assess the relationship between modern prejudice, implicit prejudice, and political conservatism. As part of a larger study investigating the relationship between modern prejudice, implicit prejudice, and interracial interaction behaviors (Heider and Skowronski, 2007), participants completed a series of self-report measures. One of these measures was the Pro-Black/Anti-Black Attitudes Questionnaire (PAAQ; Katz and Hass, 1988), and one was the Political Support Scale (PSS; Muller and Jukam, 1977). All participants also completed an IAT as a measure of implicit racial attitudes. These measures were completed in a single session; a separate session (the results of which are not reported herein; see Heider and Skowronski, 2007) assessed behavioral manifestations of prejudice.
METHOD Participants Two hundred and ninety-eight undergraduates enrolled in an introductory psychology course at a Midwestern American university participated in partial fulfillment of a course requirement. Of these 298, 30 were excluded from all statistical analyses for failing to complete the session of the study in which attitude data were collected. Therefore, 268 4
We do not mean to imply that modern and implicit prejudice derive only from feelings of morality and culturallevel associations, respectively, because clearly cultural associations can be one source of an individual’s sense of morality. (Many thanks to an anonymous reviewer who pointed us to this possibility.) However, a good deal of literature does suggest these two constructs (morality and culture) are the primary influences on the two types of prejudice.
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participants were included in the analyses reported below. Among these participants, there were 114 men (42.5%), 153 women (57.1%), and one participant (0.4%) who did not specify a sex. There were 163 Caucasians (60.8%), 60 African Americans (22.4%), 26 Hispanics (9.7%), 10 Asian Americans (3.7%), eight participants of other ethnicities (3.0%), and one participant (0.4%) who failed to indicate ethnicity. These demographic characteristics were representative of the participant pool.
Implicit Association Test Seventy-two words were used as stimuli for the IAT: 18 stereotypically White first names (e.g., Barry, Crystal), 18 stereotypically Black first names (e.g., Darnell, Latisha), 18 pleasant-meaning words (e.g., rainbow, paradise), and 18 unpleasant-meaning words (e.g., disaster, poison). The majority of these stimuli were taken from Greenwald et al. (1998). The IAT was administered in five steps using a computer program written by Farnham (1998): (1) Participants distinguished target concepts by pressing the right key on the keyboard (“5” on the number pad) for African American names and the left key (“a”) for Caucasian names; (2) Participants distinguished evaluative dimensions by pressing the right key for unpleasant words and the left key for pleasant words; (3) The stimuli from steps 1 and 2 were presented within the same step – here, participants responded to African American names and unpleasant words with the right key, and Caucasian names and pleasant words with the left key; (4) Step 1 was repeated, but with the response key assignments reversed (i.e., the right key was now used to respond to Caucasian names); and (5) Step 3 was repeated, but with new evaluative pairings: the right key was pressed in response to Caucasian names and unpleasant words, and the left key was pressed in response to African American names and pleasant words. The order in which participants executed Steps 3 and 5 was counterbalanced, as was key assignment. The primary dependent variable, the IAT effect, was obtained by computing the difference between the mean response latencies in Steps 3 and 5. All participants’ IAT latencies were scored such that a positive score reflected a relative implicit preference for Whites over Blacks (i.e., the IAT only allows for hierarchical conclusions; see Brendl, Markman, and Messner, 2001). For this sample, the average response latency during compatible blocks was 927 ms (SD = 237) and the average response latency during incompatible blocks was 1126 ms (SD = 275). This yielded an average IAT effect of 199 ms (SD = 257).5 This effect was statistically significant, t (267) = -12.68, p < .001.
Pro-Black/Anti-Black Attitudes Questionnaire The PAAQ (Katz and Hass, 1988) consists of 10 Pro-Black (e.g., “Black people do not have the same employment opportunities that whites do”) and 10 Anti-Black (e.g., “On the whole, black people don’t stress education and training”) items, and was administered using 5
For simplicity of presentation, the results reported in this chapter utilize untransformed IAT latencies. Analyses utilizing transformed latencies and the IAT scoring algorithm recommended by Greenwald, Nosek, and Banaji (2003) yielded remarkably similar correlations with all other variables in both studies.
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MediaLab experimental software (Jarvis, 2004b). Participants indicated their agreement with each statement by responding on a scale of 1 (strongly disagree) to 7 (strongly agree). Scores on each subscale could range from 10 to 70, with higher totals indicating a higher level of the corresponding attitude (either pro- or anti-Black). In addition, the product of the pro- and antiBlack scores was computed as an index of attitudinal ambivalence. The mean score on the pro-Black subscale was 35.06 (SD = 6.12), and it exhibited an acceptable level of scale score reliability (Cronbach’s α = .78, 95% CI = .74 - .82). The mean score on the anti-Black subscale was 31.45 (SD = 5.82), and it also exhibited acceptable reliability (α = .77, 95% CI = .73 - .81). The mean score of the ambivalence index was 1097.30 (SD = 253.09).
Political Support Scale The PSS (Muller and Jukam, 1977) consists of eight items (e.g., “The courts in the [United States] guarantee everyone a fair trial regardless of whether they are rich or poor, educated or uneducated”), and also was administered using MediaLab (Jarvis, 2004b). As this measure was originally developed in West Germany, the phrase “Federal Republic” in the original items was changed to “United States” to better suit the American participants in the present sample. Participants indicated their agreement with each statement by responding on a scale from 1 (strongly disagree) to 7 (strongly agree). Scores could range from 8 to 56, with higher totals indicating greater political conservatism. The mean score on the PSS was 35.06 (SD = 6.12), and, surprisingly, it only exhibited a modest level of scale score reliability (α = .67, 95% CI = .61 - .73).
Procedure All participants completed the study individually in private, sound-attenuated cubicles. The order in which participants completed the implicit (IAT) and self-report (PAAQ, PSS) measures was counterbalanced. Participation in this portion of the original study (Heider and Skowronski, 2007) took approximately 30 minutes, although all of the tasks were self-paced. After data collection was complete, participants were debriefed, thanked, and dismissed.
RESULTS AND DISCUSSION Zero-order correlations were computed among the primary measures of concern in Study 1: the IAT, the Pro-Black and Anti-Black subscales of the PAAQ, the Ambivalence Index of the PAAQ, and the PSS. The IAT exhibited a statistically significant negative correlation with the Pro-Black subscale of the PAAQ, r (268) = -.22, p < .001, and the PAAQ Ambivalence Index, r (268) = -.15, p = .018. These results suggest that as relative preferences for White over Black on the IAT increased: (a) explicit pro-Black attitudes decreased; and (b) attitudinal ambivalence decreased. Although this pattern of data might seem at odds with previous null findings
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regarding the relationship between modern and implicit prejudice, one should note that the overall magnitude of the correlations is quite modest. The PSS exhibited a statistically significant positive correlation with the IAT, r (268) = .15, p = .016, and significant negative correlations with the Pro-Black subscale of the PAAQ, r (268) = -.38, p < .001, and the PAAQ Ambivalence Index, r (268) = -.32, p < .001. These results suggest that as political conservatism increased: (a) implicit relative preferences for White over Black increased on the IAT; (b) explicit pro-Black attitudes decreased; and (c) attitudinal ambivalence decreased. These findings are consistent with previous research suggesting that politically conservative attitudes are associated with greater prejudice. No other statistically significant associations of relevance to the current study were noted.
STUDY 2 Another potential influence on prejudiced attitudes – be they measured implicitly or explicitly – is one’s motivation to control prejudice (Devine et al., 2002). The primary goal of Study 2 was to assess the relationship between modern prejudice, implicit prejudice, and motivation to control prejudice. Akrami and Ekehammar (2005) investigated the relationship between implicit (measured by an IAT) and explicit forms of prejudice (measured by an adapted MRS) and motivation to control prejudice. However, to our knowledge, no studies have used other measures of explicit forms of modern prejudice (e.g., a measure of attitudinal ambivalence such as the PAAQ) in this context. As part of a larger study, participants completed a series of measures including the PAAQ, the QDI, the Internal and External Motivation to Control Prejudice Scales (Plant and Devine, 1998), and a racial attitudes IAT. All of the measures were administered following the presentation of a case file, which assessed juror attitudes and decisions (the results of which are not reported here).
METHOD Participants Five hundred and fifty-two undergraduates enrolled in an introductory psychology course at a Midwestern American university participated in partial fulfillment of a course requirement. Of the 552 participants, 16 were excluded from all statistical analyses due to computer malfunctions, experimenter error, and extremely unusual data patterns (e.g., all measures were answered with a response of “1”, including age). Therefore, 536 participants were included in the analyses reported below. There were 218 men (40.7%) and 318 women (59.3%), with a mean age of 19.18 years (SD = 2.23).6 There were 337 Caucasians (62.9%), 104 African Americans (19.4%), 45 Hispanics (8.4%), 41 Asian Americans (7.6%), and nine participants of other ethnicities (1.7%). These demographic characteristics were representative of the participant pool. 6
Age data were not collected from the participants in Study 1; hence, data related to this demographic characteristic are only reported for the Study 2 sample.
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Quick Discrimination Index The QDI (Ponterotto et al., 1995) consisted of 30 items designed to assess generalized racial (e.g., “I really think affirmative action programs constitute reverse discrimination”), multicultural (e.g., “In the past few years there has been too much attention directed toward multicultural or minority issues in education”), and gender attitudes (e.g., “I do think it is more appropriate for the mother of a newborn baby, rather than the father, to stay home with the baby [not work] during the first year”), and was administered using DirectRT experimental software (Jarvis, 2004a). Participants indicated their agreement with each statement by responding on a scale from 1 (strongly disagree) to 5 (strongly agree). Scores on the total scale could range from 30 to 150, with higher totals indicating a greater sensitivity and receptivity towards racial, multicultural, and gender equality issues. The mean score on this scale was 98.08 (SD = 14.07), and it exhibited acceptable scale score reliability (α = .86, 95% CI = .84 - .88).
Motivation to Respond without Prejudice The Motivation to Respond without Prejudice measure (Plant and Devine, 1998) consists of five items designed to measure external motivations to control prejudice (e.g., “Because of today’s PC [politically correct] standards I try to appear non-prejudiced towards Black people”) and five items designed to measure internal motivations to control prejudice (e.g., “I attempt to act in non-prejudiced ways towards Black people because it is personally important to me”), which were administered using DirectRT experimental software (Jarvis, 2004a). Participants indicated their agreement with each statement by responding on a scale from 1 (strongly disagree) to 9 (strongly agree). Scores on each scale could range from 5 to 45, with higher totals indicating a desire to control prejudiced responses for the particular reason in question (either external or internal motivation). The mean score for internal motivation to respond without prejudice was 34.1 (SD = 9.24), and it exhibited acceptable scale score reliability (α = .83, 95% CI = .80 - .85). The mean score for external motivation to respond without prejudice was 24.55 (SD = 9.68), and it also exhibited acceptable reliability (α = .77, 95% CI = .74 - .80).
Procedure All participants completed the study individually in private, sound-attenuated cubicles. Participants did the juror task followed by the attitudinal measures. The implicit measure (IAT) was given first, then the modern prejudice measures (QDI and PAAQ), which were followed by the Motivation to Respond without Prejudice scale. Two key modifications were made to the IAT procedure: (1) photographs of White and Black faces were used as stimuli for the racial categories instead of stereotypical names; and (2) the measure was administered using DirectRT precision timing software (Jarvis, 2004a). For this sample, the average response latency during compatible blocks was 726 ms (SD = 181) and the average response latency during incompatible blocks was 835 ms (SD = 211). This yielded an average IAT
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effect of 109 ms (SD = 200). This effect was statistically significant, t (537) = -4.14, p < .001. This attenuation of the IAT effect (compared to Study 1) when using facial stimuli is similar to the one reported by Dasgupta, McGhee, Greenwald, and Banaji (2000). The entire procedure took approximately 30 minutes, although all of the tasks were selfpaced. After data collection was complete, participants were debriefed, thanked, and dismissed.
RESULTS AND DISCUSSION Zero-order correlations were computed among the primary measures of concern in Study 2: the IAT, the Pro-Black and Anti-Black subscales of the PAAQ, the Ambivalence Index of the PAAQ, the QDI, and the Motivation to Control Prejudice (both Internal and External) measures (see Table 1 for all correlations).7 The IAT exhibited a statistically significant negative correlation with the Pro-Black subscale of the PAAQ, r (536) = -.10, p = .02, a significant positive correlation with the AntiBlack subscale of the PAAQ, r (536) = .10, p = .024, and a significant positive relationship with the QDI, r (536) = .09, p = .042. These results suggest that as relative preferences for White over Black on the IAT increased: (a) explicit pro-Black attitudes decreased; (b) explicit anti-Black attitudes increased; and (c) explicit generalized discrimination attitudes increased. Again, although this pattern of data might seem at odds with previous null findings regarding the relationship between modern and implicit prejudice, one should note that the overall magnitude of the correlations is quite small and the sample size is quite large. External motivation to respond without prejudice had statistically significant positive correlations with the Anti-Black subscale of the PAAQ, r (536) = .12, p = .007, the PAAQ Ambivalence Index, r (536) = .16, p < .001, and internal motivation to respond without prejudice, r (536) = .16, p < .001. This suggests that as an externally-induced desire to control prejudice increased: (a) anti-Black attitudes increased; (b) attitudinal ambivalence increased; and (c) internal desire to control prejudice increased. Internal motivation to control prejudice had a statistically significant positive correlation with the Pro-Black subscale of the PAAQ, r (536) = .31, p < .001, the QDI, r (536) = .47, p < .001, and a significant negative correlation with the Anti-Black subscale of the PAAQ, r (536) = -.33, p < .001. This suggests that as an internally-induced desire to control prejudice increased: (a) pro-Black attitudes increased; (b) people had more egalitarian attitudes across races and gender; and (c) people had weaker anti-Black attitudes. Based on the correlations reported above, it should be noted that internally-induced motivation to control prejudice was a stronger predictor of prejudice-related attitudes than externally-induced motivation to control prejudice (although internal and external motivation were significantly correlated with one another). This suggests that internal motivations to combat prejudiced attitudes may have more of an impact on the expression of those attitudes than external motivations. This may be the case because the internalized nature of the former makes this type of motivation more personal and genuine. 7
We also explored the possibility of gender differences in both of our samples. We did not find any statistically significant differences between males and females in the magnitude of correlations. As such, we report all correlations collapsed across sex.
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Table 1. Relationships among all variables assessed in Study 2 IAT Effect IAT Effect Pro-Black Anti-Black Ambivalence QDI External Motivation Internal Motivation
ProBlack
AntiBlack
Ambivalence
QDI
-.100* .097* -.033 .088* -.043
-.159* .618** .505** .074
.049
.313**
External Motivation
.645** -.429** .117**
.051 .164**
-.068
-
-.332**
-.003
.471**
.160**
Internal Motivation
-
-
Note. *Significant at p < .05. **Significant at p < .01. Pro-Black = Pro-Black subscale of ProBlack/Anti-Black Attitudes Questionnaire (PAAQ); Anti-Black = Anti-Black subscale of PAAQ; Ambivalence = Ambivalence Index of PAAQ; QDI = Quick Discrimination Index; External Motivation = External Motivation to Control Prejudice; Internal Motivation = Internal Motivation to Control Prejudice.
CONCLUSION In Study 1, we investigated the relationship between political conservatism, implicit prejudice, and modern prejudice. We found that lower levels of pro-Black attitudes (measured via the PAAQ) were associated with a relative preference for White names over Black names on the implicit measure, and higher levels of political conservatism. Lower levels of attitudinal ambivalence on the PAAQ were associated with a greater preference for White over Black on the IAT and higher levels of political conservatism. Political conservatism also was associated with an increased implicit relative preference for White over Black on the IAT. In Study 2, we investigated the relationship between motivation to control prejudice, implicit prejudice, and modern prejudice. We found that lower levels of pro-Black attitudes (measured via the PAAQ) were associated with lower levels of internal motivation to control prejudice and a greater relative preference for White faces over Black faces on the IAT. We found that higher levels of anti-Black attitudes were associated with a greater relative preference for White over Black on the IAT, greater levels of external motivation to control prejudice, and lower levels of internal motivation to control prejudice. Attitudinal ambivalence on the PAAQ also was associated with higher levels of external motivation to control prejudice. Higher levels of prejudice on the generalized discrimination measure (the QDI) were associated with a greater relative preference for White over Black on the IAT, and lower levels of internal motivation to control prejudice. Taken together, these studies paint a consistent picture of the relationship between modern forms of explicit prejudice, implicit forms of prejudice, and other individual difference constructs that are related to prejudice. Across both studies, we found a consistent relationship between the PAAQ and the IAT, in which lower levels of pro-Black attitudes
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were associated with a greater relative implicit preference for White over Black. Importantly, this pattern emerged with different variants of the IAT: one using stereotypically White and Black names as the racial stimuli, the other using White and Black faces. In Study 2, we also found a relationship between anti-Black attitudes and the IAT, whereby higher levels of antiBlack attitudes were associated with a greater relative preference for White over Black on the IAT. In Study 2, the additional modern prejudice measure (the QDI) also showed the predicted pattern (i.e., scores correlated positively with a greater preference for White over Black on the IAT). This pattern of results is typical, such that the relationship between explicit and implicit prejudice is weak, if it is present. Perhaps more interesting is the association between the explicit measures of modern racism and the individual difference variables. In Study 1, political conservatism was associated with lower levels of explicit pro-Black attitudes and less attitudinal ambivalence. The statistically significant results with the ambivalence index (which has not been assessed in previous research) suggests that not only are politically conservative individuals more prejudiced in their attitudes, they are more certain of their beliefs and feel no psychological tension as a result. In Study 2, we investigated the relationship between motivation to control prejudice and the modern forms of prejudice. Whereas other studies (Akrami and Ekehammar, 2005; Devine et al., 2002) have used singular forms of modern prejudice adapted from the Modern Racism Scale and the Attitudes toward Blacks Scale, respectively, we employed two novel forms of modern prejudice (the PAAQ and the QDI). We obtained complementary findings suggesting that modern forms of prejudice are related to one’s motivations to control prejudice. Future research should investigate all of these individual difference measures along with measures of modern and implicit prejudice. We anticipate the need for comprehensive studies investigating political conservatism, motivation to control prejudice, need for cognition, social desirability, and the modern forms of prejudice. This research could then use the techniques offered by structural equation modeling (Kline, 2005), and investigate the relationships between these variables. These techniques could allow for detection of moderators, mediators, and perhaps antecedents of modern prejudice. Of particular interest would be a more careful examination of relationships involving pro-Black attitudes, antiBlack attitudes, and racial ambivalence (whether measured by the PAAQ or some similar instrument). Since the two types of attitude (pro- and anti-Black) tend to be only weakly related (if not unrelated), it would be fruitful to assess whether ambivalence is more often the result of increased pro-Black attitudes or increased anti-Black attitudes. There is also some evidence suggesting pro-Black attitudes are more valuable predictors of behavior than either anti-Black attitudes or ambivalence (e.g., Heider and Skowronski, 2007), but this pattern should be replicated with a wider variety of behaviors. One of the limitations to the studies reported in this chapter is that the studies were not designed specifically to assess relationships between modern and implicit prejudice. However, we feel what some might suggest is a weakness in the design of the studies is one of their strengths. As the studies were from different paradigms (behavioral research and jurybased decision making research), yet yielded remarkably similar outcomes, we believe the similarities are not due to similarities in research design. Instead, the results of Study 2 should be considered a compelling replication of the results of Study 1.
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Banaji, M. R. (2001). Implicit attitudes can be measured. In H. L. Roediger, J. S. Nairne, I. Neath, and A. M. Surprenant (Eds.), The nature of remembering: Essays in honor of Robert G. Crowder (pp. 117-150). Washington, DC: American Psychological Association. Blanton, H., Jaccard, J., Christie, C., and Gonzales, P. M. (2007). Plausible assumptions, questionable assumptions, and post hoc rationalizations: Will the real IAT, please stand up? Journal of Experimental Social Psychology, 43, 399-409. Blanton, H., Jaccard, J., Gonzales, P. M., and Christie, C. (2006). Decoding the Implicit Association Test: Implications for criterion prediction. Journal of Experimental Social Psychology, 42, 192-212. Brendl, C. M., Markman, A. B., and Messner, C. (2001). How do indirect measures of evaluation work? Evaluating the inference of prejudice in the Implicit Association Test. Journal of Personality and Social Psychology, 81, 760-773. Dasgupta, N., McGhee, D. E., Greenwald, A. G., and Banaji, M. R. (2000). Automatic preference for White Americans: Eliminating the familiarity explanation. Journal of Experimental Social Psychology, 36, 316-328. Devine, P. G., Plant, E. A., Amodio, D. M., Harmon-Jones, E., and Vance, S. L. (2002). The regulation of explicit and implicit race bias: The role of motivations to respond without prejudice. Journal of Personality and Social Psychology, 82, 835-848. Dovidio J. F., Kawakami, K., and Beach, K. R. (2001). Implicit and explicit attitudes: Examination of the relationship between measures of intergroup bias. In R. Brown and S. L. Gaertner (Eds.), Blackwell handbook of social psychology: Intergroup processes (pp. 175-197). Malden, MA: Blackwell. Dovidio, J. F., Kawakami, K., and Gaertner, S. L. (2002). Implicit and explicit prejudice and interracial interaction. Journal of Personality and Social Psychology, 82, 62-68. Dovidio, J. F., Kawakami, K., Johnson, C., Johnson, B., and Howard, A. (1997). On the nature of prejudice: Automatic and controlled processes. Journal of Experimental Social Psychology, 33, 510-540. Farnham, S. D. (1998). The Farnham Implicit Association Test (FIAT; Version 2.3) [Computer program]. Fazio, R. H. (1990). Multiple processes by which attitudes guide behavior: The MODE model as an integrative framework. In M. P. Zanna (Ed.), Advances in experimental social psychology: Vol. 23 (pp. 75-109). San Diego, CA: Academic Press.
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Fazio, R. H., Jackson, J. R., Dunton, B. C., and Williams, C. J. (1995). Variability in automatic activation as an unobtrusive measure of racial attitudes: A bona fide pipeline? Journal of Personality and Social Psychology, 69, 1013-1027. Fazio, R. H., and Olson, M. A. (2003). Implicit measures in social cognition research: Their meaning and use. Annual Review of Psychology, 54, 297-327. Fazio, R. H., Sanbonmatsu, D. M., Powell, M. C., and Kardes, F. R. (1986). On the automatic activation of attitudes. Journal of Personality and Social Psychology, 50, 229-238. Feagin, J. R. (1980). School desegregation: A political economic perspective. In W. S. Stephan and J. R. Feagin (Eds.), School desegregation: Past, present, and future (pp. 2550). New York: Plenum Press. Gale, J. D. (2004). The effects of aversive anti-Semitism on selection decisions regarding Jewish workers in the United States. Unpublished doctoral dissertation, Alliant International University. Gawronski, B., Hofmann, W., and Wilbur, C. J. (2006). Are ‘implicit’ attitudes unconscious? Consciousness and Cognition: An International Journal, 15, 485-499. Glick, P., and Fiske, S. T. (1996). The Ambivalent Sexism Inventory: Differentiating hostile and benevolent sexism. Journal of Personality and Social Psychology, 70, 491-512. Greenwald, A. G., and Banaji, M. R. (1995). Implicit social cognition: Attitudes, self-esteem, and stereotypes. Psychological Review, 102, 4-27. Greenwald, A. G., McGhee, D. E., and Schwartz, J. L. K. (1998). Measuring individual differences in implicit cognition: The Implicit Association Test. Journal of Personality and Social Psychology, 74, 1464-1480. Greenwald, A. G., Nosek, B. A., and Banaji, M. R. (2003). Understanding and using the Implicit Associations Test: I. An improved scoring algorithm. Journal of Personality and Social Psychology, 85, 197-216. Heider, J. D., and Skowronski, J. J. (2007). Improving the predictive validity of the Implicit Association Test. North American Journal of Psychology, 9, 53-76. Hsu, F. L. K. (1972). American core values and national character. In F. L. K. Hsu (Ed.), Psychological anthropology (pp. 241-262). Cambridge, MA: Schenkman. Jackman, M. R. (1978). General and applied tolerance: Does education increase commitment to racial integration? American Journal of Political Science, 22, 302-324. Jarvis, B. (2004a). DirectRT Precision Timing Software (Version 2004.1.0.2) [Computer software]. Empirisoft Corporation. Jarvis, B. (2004b). MediaLab v2004 (Version 2004.1.39) [Computer software]. Empirisoft Corporation. Jones, F. C. (1977). The changing mood in America: Eroding commitment? Washington, DC: Howard University Press. Jones, J. M. (1972). Prejudice and racism. Reading, MA: Addison-Wesley. Katz, I. (1981). Stigma: A social psychological analysis. Hillsdale, NJ: Erlbaum. Katz, I., and Hass, R. G. (1988). Racial ambivalence and American value conflict: Correlational and priming studies of dual cognitive structure. Journal of Personality and Social Psychology, 55, 893-905. Kawakami, K., and Dovidio, J. F. (2001). The reliability of implicit stereotyping. Personality and Social Psychology Bulletin, 27, 212-225. Kline, R. B. (2005). Principles and practice of structural equation modeling. New York: Guilford Press.
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Lipset, S. M., and Schneider, W. (1978). The Bakke case: How would it be decided at the bar of public opinion? Public Opinion, 1, 38-44. McConahay, J. B. (1986). Modern racism, ambivalence, and the Modern Racism Scale. In J. F. Dovidio and S. L. Gaertner (Eds.), Prejudice, discrimination, and racism (pp. 91-126). New York: Academic Press. McConnell, A. R., and Leibold, J. M. (2001). Relations among the Implicit Association Test, discriminatory behavior, and explicit measures of racial attitudes. Journal of Experimental Social Psychology. Morrison, M. A., and Morrison, T. G. (2002). Development and validation of a scale measuring modern prejudice toward gay men and lesbian women. Journal of Homosexuality, 43, 15-37. Morrison, T. G., Kenny, P., and Harrington, A. (2005). Modern prejudice toward gay men and lesbian women: Assessing the viability of a measure of modern homonegative attitudes within an Irish context. Genetic, Social, and General Psychology Monographs, 131, 219-250.
Muller, E. N., and Jukam, T. O. (1977). On the meaning of political support. American Political Science Review, 71, 1561-1595. Nosek, B. A., and Banaji, M. R. (2001). The Go/No-go Association Task. Social Cognition, 19, 625-666. Nosek, B. A., and Sriram, N. (2007). Faulty assumptions: A comment on Blanton, Jaccard, Gonzales, and Christie (2006). Journal of Experimental Social Psychology, 43, 393-398. Ottaway, S. A., Hayden, D. C., and Oakes, M. A. (2001). Implicit attitudes and racism: Effects of word familiarity and frequency on the Implicit Association Test. Social Cognition, 19, 97-144. Plant, E. A., and Devine, P. G. (1998). Internal and external motivation to respond without prejudice. Journal of Personality and Social Psychology, 75, 811-832.
Poehlman, T. A., Uhlmann, E., Greenwald, A. G., and Banaji, M. R. (2006). Understanding and using the Implicit Association Test: III. Meta-analysis of predictive validity. Manuscript submitted for publication. Ponterotto, J. G., Burkard, A., Rieger, B. P., and Grieger, I. (1995). Development and initial validation of the Quick Discrimination Index (QDI). Educational and Psychological Measurement, 55, 1016-1031.
Schuman, H., Steeh, C., and Bobo, L. (1985). Racial attitudes in America. Cambridge, MA: Harvard University Press. Sekaquaptewa, D., Espinoza, P., Thompson, M., Vargas, P., and von Hippel, W. (2002). Stereotype explanatory bias: Implicit stereotyping as a predictor of discrimination. Journal of Experimental Social Psychology, 39, 75-82. Sinclair, L., and Kunda, Z. (1999). Reactions to a black professional: Motivated inhibition and activation of conflicting stereotypes. Journal of Personality and Social Psychology, 77, 885-904. Smith, T. W., and Sheatsley, P. S. (1984). American attitudes toward race relations. Public Opinion, 7, 14-15, 50-53. von Hippel, W., Sekaquaptewa, D., and Vargas, P. (1995). On the role of encoding processes in stereotype maintenance. In M. P. Zanna (Ed.), Advances in experimental social psychology: Vol. 27 (pp. 174-255). San Diego, CA: Academic Press.
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von Hippel, W., Sekaquaptewa, D., and Vargas, P. (1997). The linguistic intergroup bias as an implicit indicator of prejudice. Journal of Experimental Social Psychology, 33, 490509. Whitley, B. E., and Kite, M. E. (2006). The psychology of prejudice and discrimination. Belmont, CA: Thomson Wadsworth.
In: The Psychology of Modern Prejudice Editors:Melanie A. Morrison and Todd G. Morrison
ISBN 978-1-60456-788-5 © 2008 Nova Science Publishers, Inc.
Chapter 5
MEASURING RACIAL PREJUDICE IN A MULTIRACIAL WORLD: NEW METHODS AND NEW CONSTRUCTS Khaya D. Clark and Chuck Tate1 University of Oregon California State University, Bakersfield
ABSTRACT This chapter argues for the use of new methods to assess racial prejudice because existing methods only provide a piecemeal understanding of the phenomenon, leading to an under-assessment of key constructs (e.g., ingroup favoritism, outgroup derogation) and provide no precision to assess new constructs, such as generalized outgroup derogation (negativity directed at all outgroups equally) and selective outgroup derogation (negativity directed at a specific outgroup or specific outgroups). The use of new response options, multiple targets, and multiple perceivers integrated into a single instrument is encouraged. The multidimensional architecture of the proposed instrument will allow researchers to uncover new constructs (e.g., selective or generalized outgroup derogation) and improve the assessment of existing constructs (e.g., ingroup favoritism, outgroup derogation) associated with racial prejudice. This chapter concludes by arguing that the methodological and theoretical clarity offered by these new methods in a single instrument will supplement and advance our understanding of racial prejudice, and that the approach is equally applicable to both the child and adult literatures.
INTRODUCTION Several theorists, including Biernat and Crandall (1999), have argued that “[r]ace...is one of the most complex and powerful dimensions of American political thought” (p. 297). It is 1
Correspondence may be sent to either author: Khaya D. Clark, Department of Sociology, 1555 Emory University, Atlanta, GA, USA 30322, e-mail:
[email protected] or Chuck Tate, Department of Psychology, California State University, Bakersfield, Antelope Valley Campus, 43909 30th St. West, Lancaster, CA, USA 93536, email:
[email protected]. This chapter was written with support from a National Science Foundation Social and Economic Sciences dissertation improvement grant (SES #0618886) awarded to Khaya D. Clark.
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no doubt also a powerful dimension of social perception in various countries, and sometimes has different definitions across cultures (see Davis, 1991). Throughout its ascendancy and current decline in the biological sciences (see Cavalli-Sforza and Cavalli-Sforza, 1995; Haga and Venter, 2003; Lewontin, 1972; Marks, 1995; Smedley and Smedley, 2005; Tate and Audette, 2001) and philosophy (Goldberg, 1993; Zack, 2003), the concept of “race”2 has been prominent in the social sciences largely because of its social consequences (American Anthropological Association, 1998; Jones, 1997; Smedley and Smedley, 2005; Tate and Audette, 2001). The most well researched social consequence of the belief in race is racism. Racism has various forms, notably racial prejudice, racial discrimination, racial ideology (Blumer, 1958), and structural relations (Bonilla-Silva, 1997), and the phenomenon is very much a part of many societies even if the concept of race lacks any biological validity (Smedley and Smedley, 2005; Tate and Audette, 2001). The study of racism, therefore, is an integral part of social science to the extent that most people participate in the project of making “human races” (Hirschfeld, 1996; Teo, 2004; see also Banton, 1977; Jones, 1997) and concomitantly develop attitudes about, and engage in behaviors toward, ascribed racial groups, including the one to which they claim membership. Given the psychological depth and social importance of racism, this chapter explores current approaches to racial prejudice, which usually characterize the phenomenon as involving only two groups (the ingroup and one outgroup), and offers new insights into how racial prejudice might be studied given that the scientific and social conceptions of humans races have always posited multiple (i.e., three or more) racial groups (Smedley and Smedly, 2005; Tate and Audette, 2001). Consequently, the current approaches have difficulty capturing racial prejudice in a multiracial world.
CHAPTER OVERVIEW This chapter is divided into three interrelated parts. The first is a review of the current racial prejudice literature with special attention to the various methods that are used to assess it and the shortcomings of these methods. The second part explicates an overarching method that can provide a holistic assessment of racial prejudice; namely, developing a single instrument that uses multiple response options, multiple targets and multiple perceivers simultaneously. The third part delineates the new constructs that would be possible from the use of a single instrument with the proposed multidimensional architecture (concerning response options, targets and perceivers) and also shows how such an instrument would provide clarity to existing constructs in the literature while generating new ones.
2
We refer to the term “race” with quotes to underscore our stance that the construct is a cognitive representation of the social world with no meaningful biological referent (Smedley and Smedley, 2005; Tate and Audette, 2001). The use of the term without quotes invites misinterpretations of our meaning. Nevertheless, we do not use these quotes around the term in the remainder of the paper in order to improve readability, with the hope that our stance remains clear.
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HIGHLIGHTS FROM PAST APPROACHES TO RACIAL PREJUDICE Social scientific studies of prejudice can be found as early as the 1920s when Bogardus (1928) began discussing ideas of social distance and racial groups in the United States. Bogardus (1933, 1959) developed social distance scales and wrote extensively about racerelations and associated social perceptions, encouraging other theorists to explore this issue as well. One notable study from that era relevant to this chapter was conducted by Thistlethwaite (1950) and examined how participants (identified as “Caucasian”) interpreted syllogisms concerning two target racial groups: “Negroes” (modern term “African-Americans”) and “Jews” (who were at that time considered a racial group).3 Thistlethwaite (1950) recruited two samples of males: (a) those from southern states in the U.S., presumed to have “ethnocentric” attitudes, and (b) those from northern states in the U.S., presumed to have less ethnocentric attitudes. In modern terms, Thistlethwaite was trying to recruit high and low prejudiced individuals. Thistlethwaite (1950) assumed that the high-prejudiced participants would make more errors when judging the correctness of the syllogisms that featured African-Americans or Jews as the target group than would the low-prejudiced individuals. Yet, Thistlethwaite found that the regions – the proxy for high and low prejudiced individuals – differed in the amount of errors made when the syllogisms referred to “AfricanAmericans;” however, no difference was noted when the syllogisms referred to “Jews.”4 Although statistical analysis and our understanding of racial prejudice and discrimination have advanced considerably since 1950, Thistlethwaite’s method is important to consider because it was one of the first (and one of the only to this day) to use multiple racial outgroups as targets in a single study using the same measurement tool. Since the 1950s, there has been consistent interest in both sociology and social psychology to develop scales and other instruments to measure the amount of racial prejudice that a given populace shows from one group to another based on the social concept of race. The current state of social science research includes a range of approaches—largely methodological (as opposed to theoretical)—concerned with the assessment of racial prejudice and discrimination. The breadth of research has produced a bevy of papers, informal schools of thought, and new phenomena, but there has been little apparent interest in integrating the existing knowledge base into one instrument. This chapter focuses primarily on racial prejudice5 and argues for the creation of a single instrument to measure it. The logic and merits of this proposal (including uncovering new constructs and improved precision for 3
In the interest of completely describing the study, we note that participants were also asked to rate patriotic arguments (in addition to the syllogisms). Also, as a control comparison for the racial categories, participants responded to syllogisms about the target group “women” (a non-racial group). 4 Given the statistical techniques widely available at that time, Thistlethwaite (1950) did not compare the responses directly; instead, he showed that there was significant difference (at p < .05) across the regions for one target, “African-Americans” but not the other, “Jews.” 5 We conceive of racial prejudice as a “rational” negative evaluation of a member of a racial group. We use the term “rational” to acknowledge that some theorists have offered compelling evidence regarding the internal coherence and non-pathological nature of racialized belief systems (e.g., Goldberg, 1993). The logic that inheres in racialized belief systems is counter to positions – in both sociology and psychology – that frame racial prejudice as pathological or “irrational” (see, for example, Allport [1954] describing “the pathology of bigotry” [p. 425] and the “tolerant personality” [p. 427]). Addressing this debate is beyond the scope of this paper; however, it is important to acknowledge that some sociologists have pointed out that the study of racial prejudice often serves to obfuscate issues of the structural racialized relations and the non-ideological aspects of racial matters by attempting to pathologize it (e.g., Bonilla-Silva, 1997). Of course, despite the internal coherence of racialized beliefs, they are deleterious to social cohesion and, therefore, should be ameliorated.
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existing constructs) are detailed as the main arguments of this chapter. The eventual creation of such a measure is offered as a project for interested social scientists.
THE CURRENT RESEARCH LANDSCAPE ON RACIAL PREJUDICE The landscape of historical and current research on racial prejudice has three general forms: (a) explicit scales, (b) tasks, and (c) implicit measures. Explicit scales are constructed to measure attitudes based on participants’ overt responses (of which they are presumably aware) using questionnaire methodology. The tasks involve participants responding to hypothetical or actual interactions or making choices that implicate ingroup and outgroup targets. Implicit measures are constructed to discern participants’ aconscious racial attitudes via button-presses to computer-presented stimuli or as physiological responses to presented stimuli. Each form is described in detail below to better acquaint the reader with the underlying assumptions and limits of each.
Explicit Racial Prejudice Scales Racial prejudice scales have existed since Bogardus’ (1928) Social Distance Scale. Excellent and detailed summaries of racial attitudes scales can be found in Biernat and Crandall (1999; adults) and in Cameron, Alvarez, Ruble, and Fuligni (2001; children). Thus, it is not our intention to further detail what others have so well documented. Instead, we wish to make clear the theoretical assumptions underpinning the scales since the 1920s and highlight the methodological procedures used to illustrate or support these assumptions. As Biernat and Crandall (1999, pp. 301-302) argue, existing scales that measure racial attitudes in adults can be classified as focusing on: (a) “old fashioned” measures of out-group directed attitudes (e.g., Ard and Cook, 1977; Brigham, 1977, 1993; Sidanius, Pratto, Martin, and Stallworth, 1991; Woodmansee and Cook, 1967), (b) “modern” measures of out-group directed attitudes (e.g., Bogardus, 1959; Jacobson, 1985; I. Katz and Hass, 1988; Kinder and Sanders, 1996; Lepore and Brown, 1997; McConahay, 1986; Ponterotto et al., 1995), (c) hybrid measures of old-fashioned and modern racism (e.g., Meertens and Pettigrew, 1997), (d) measures of racial stereotypes (e.g., Farley, Steeh, Krysan, Jackson, and Reeves, 1994; Peffley, Hurwitz, and Sniderman, 1997), and (e) prejudice-related world views, such as social dominance-orientation (Pratto, Sidanius, Stallworth, and Malle, 1994; Sidanius and Pratto, 1993) and nonprejudice (e.g., Universal Orientation; Phillips and Ziller, 1997). The distinction between old-fashioned and modern racist attitudes is roughly the distinction between harboring (and usually expressing) overtly racist attitudes (old-fashioned; e.g., supporting the use of racial slurs, believing that outgroups have lower abilities, deeming physical violence against outgroups to be acceptable, etc.) and comparatively more covert or subtle racist attitudes (modern; e.g., not wanting to associate with outgroup members, deeming obstructionism when dealing with racial outgoups to be acceptable, blaming minorities for structural inequality, etc.). There also has been renewed interest in assessing participants as high or low in their expression of racial prejudice (e.g., Lepore and Brown,
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1997), as well as assessing participants’ motivation to control prejudiced reactions or responses (e.g., Dunton and Fazio, 1997; Plant and Devine, 1998). Scales also have been developed to assess children’s racial prejudice, such as the Preschool Racial Attitudes Measure II (PRAM II) (Williams, Best, and Boswell, 1975; Williams, Morland, and Associates, 1975), the Katz-Zalk Projective Prejudice Test (KZPP) (P. Katz and Zalk, 1978; Zalk and Katz, 1976), and the Multi-response Racial Attitude Measure (MRA) (Doyle and Aboud, 1995). Given the participants, the scales for children do not distinguish between old-fashioned and modern forms of racism; instead, they focus on racial bias (PRAM II), ingroup pride and outgroup prejudice (Doyle and Aboud, 1995; P. Katz and Zalk, 1978), or on positivity or negativity attributed to both the ingroup and outgroup simultaneously (Doyle and Aboud, 1995). Developmental differences notwithstanding, both the adult and child scales ultimately measure positivity and negativity toward racial groups, as assessed by patterns of responses to standardized items.
Tasks Designed to Assess Racial Prejudice In addition to the explicit scales, one can find tasks designed to reveal racial prejudice in both the child and adult social cognition literature. These tasks are grouped and discussed here because they do not rely on rating or agreement scales in response to evaluative statements in the same way as do the explicit scales summarized above. Biernat and Crandall (1999) identify the Racial Reconciliation test (Doyle and Aboud, 1995) as one task measuring prejudice for children.6 In this task, children are asked to solve hypothetical disagreements between the self and fictitious same-age, same-sex peers of (a) a different racial group and (b) the same racial group. Children are shown their arrangement of pictures and then one of the other children’s arrangements and asked, “Are you both right or is someone wrong?” (Doyle and Aboud, 1995, p. 215). Choosing “both right” is considered reconciliation and (without the child’s knowledge) he or she receives a point for each such response. (Thus, scores can range from 0 [no reconciliation] to 2 [reconciliation for both targets].) While an assessment of prejudice might be extractable from this task, Aboud believes the Racial Reconciliation Test is “not a measure of prejudice, but rather of the young child's inability to reconcile different perspectives (e.g., of a white person and a black person who might have different preferences)” (F. E. Aboud, personal communication, August 30, 2007). This belief is based on the pattern of findings for this task reported in Doyle and Aboud (1995, footnote 1). Only 2 of the 47 children in their sample showed a pattern of responding that could be construed as prejudiced (i.e., saying that the other-race peer was wrong but a same-race peer was right when each peer showed the same arrangement to the child). One task for children that is universally considered a racial prejudice measure is the perceptual discrimination task (P. Katz and Zalk, 1978). In this task, children attempt to differentiate individuals in the racial ingroup and a racial outgroup (or sometimes just the latter) by remembering their names. P. Katz and Zalk (1978) found that children harboring negative intergroup attitudes had more difficulty discriminating faces of racial outgroup 6
It should be noted that the Racial Reconciliation Test is a modified version of the original Reconciliation Test used in Aboud (1981). This modified version appears in the Doyle and Aboud (1995) investigation along with the Multi-response Racial Attitude Measure.
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members. This lack of perceiving differences within an outgroup can promote inappropriate generalizations (Robinson and Hall, 1999). To counteract such tendencies, the use of exercises to increase perceptual differentiation, such as learning to observe more carefully, or to associate names to stimuli, has been shown to reduce children’s negative racial attitudes (e.g., Aboud and Fenwick, 1999; Hohn, 1973; P. Katz, 1973a, 1973b, 1976; P. Katz and Zalk, 1978). This task has an admittedly applied focus (i.e., to identify and reduce racial prejudice), but it, nonetheless, can be used to ascertain a child’s level of racial prejudice. Adult tasks are more varied. In some tasks, participants are asked to give their impressions of their actual interactions with racial outgroups in the laboratory setting (e.g., Shelton, Richeson, Salvatore, and Trawalter, 2005b), while others involve coding actual behaviors during interactions (e.g., McConnell and Leibold, 2001). Still other tasks involve measuring the activation of stereotypes via lexical decisions and the subsequent use of those activated constructs on decisions or hypothetical behavior (e.g., Gaertner and McLaughlin, 1983; Wittenbrink, Judd, and Park, 2001) or assessing whether activated stereotypes from the categorization of photographs affect decision-making (e.g., Correll, Park, Judd, and Wittenbrink, 2002). The above forms are not an exhaustive list; rather, they are used to illustrate the idea that many tasks involve a choice among a set of behaviors or associations – some of which indicate bias against a racial outgroup.
Implicit Measures of Racial Prejudice In response to some of the difficulties of directly asking participants to respond to statements on scales, many researchers have opted for implicit (presumably aconscious) or unobtrusive measures of prejudice (e.g., Fazio, Jackson, Dunton, and Williams, 1995; Wittenbrink, Judd, and Park, 1997). Such measures are currently used with children (e.g., Baron and Banaji, 2006) as well as adults. The hope of these measures is that they might provide a bonafide pipeline to participants’ true racial attitudes (Fazio et al., 1995), which may be concealed when they respond to items on explicit racial prejudice scales. The logic of implicit measures is to use behavioral responses (e.g., button-presses in response to supraliminal presentations; e.g., Fazio et al., 1995; Judd, Wittenbrink, and Park, 1999), heartrate (e.g., Blascovich, Mendes, Hunter, Lickel and Kowai-Bell, 2001; Mendes, Blascovich, Lickel, and Hunter, 2002), facial electromyography (EMG) (e.g., Brown, Bradley, and Lang, 2006; Vanman, Saltz, Nathan, and Warren 2004), or brain imaging using fMRI (e.g., Phelps et al., 2000; Richeson et al., 2003; Wheeler and Fiske, 2005) to assess prejudice because these responses are presumably not as easily concealable as responding to statements on a scale. While physiological data collection may be the most valid of the approaches, behavioral responses, such as the Implicit Association Test (IAT) (Greenwald, McGhee, and Schwartz, 1998) have become very popular (Ashburn-Nardo, Knowles, and Monteith, 2003; Cunningham, Preacher, and Banaji, 2001; Dasgupta, 2004; Richeson, Trawalter, and Shelton, 2005; Richeson and Shelton, 2003). The basic logic of the IAT is to measure both GOOD and BAD associations with different targets (e.g., “Black” and “White”). Thus, the assignment of evaluative attributes (e.g., “pleasant,” “good” [GOOD] or “unpleasant,” “bad” [BAD]) to target groups is the focus. The IAT has been criticized for its original, rather simplistic subtraction method (which may have created confounds; Greenwald, Nosek, and Banaji, 2003), for being too sensitive to supraliminal primes (e.g., Dasgupta and Greenwald, 2001; Foroni and Mayr,
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2005), and for not sufficiently dealing with other confounds such as cognitive skill (McFarland and Crouch, 2002) and the salience of response options (Rothermund and Wentura, 2004). Blanton and colleagues have recently called into question the use of the IAT based on statistical and criterion validity concerns (e.g., Blanton, Jaccard, Christie, and Gonzales, 2007; Blanton, Jaccard, Gonzales, and Christie, 2006). Briefly, Blanton et al. (2006) argued, in part, that the theoretical model of the IAT is causally restrictive because it predicts an interaction between the evaluations of “White” and “Black” targets but this interaction is assessed using an additive statistical model (i.e., the difference score method). Additionally, in Blanton et al. (2006, Study 2) participants showed small, but significant, correlations between positive items across racial targets (i.e., “Black/positive” and “White/positive”) and between negative items across racial targets (i.e., “Black/negative” and “White/negative”). These correlations suggest that the underlying logic of complementary scores for the IAT (i.e., an implicit association is the function of the difference between compatible and incompatible trials) is belied by a tendency for participants to respond positively or negatively to any presented racial group. These substantive critiques have weakened an argument for this method providing a bonafide pipeline to “true” attitudes. The IAT scoring method was adjusted to lessen confounds (Greenwald et al., 2003) and to create a better measure of ingroup and outgroup constructs (e.g., bias, favoritism) (see Richeson et al., 2005), yet some theorists remain unconvinced as to the usefulness of the IAT even with these modifications (see Blanton et al., 2006, 2007). Despite the controversy, the most useful piece of information from the IAT may simply be the use of reaction times as an unobtrusive measure in the assessment of racial prejudice, which adds a new dimension of interpretation to the data by allowing researchers to focus on speed of response as well as choices. Reaction times may indicate the intensity or extremity of prejudice (when examined with respect to specific choices). Although different in the kind of data collected, the logic of the behavioral (versus physiological) implicit measures is not very different from the task assessments of racial prejudice summarized above. The implicit measure attempts to uncover who is prejudiced and to what degree by recording patterns of responses to pre-determined stimuli. In the interpretation of the data, some patterns indicate strong prejudiced attitudes, while other patterns indicate comparatively less prejudiced attitudes, using subtraction methods in the form of adjusted D scores (Greenwald et al., 2003), or subsequent task performance on unrelated measures, such as executive function (e.g., Richeson et al., 2003; Richeson and Shelton, 2003). Tasks also rely on recording the patterns of responses to pre-determined stimuli (usually without assessing response latency), and the patterns of responses are evaluated (given the structure of the presentation) as indicating varying degrees or different forms of racial prejudice.
Commonality Among Explicit, Task, and Implicit Approaches Aside from the obvious focus on the same topic and interest in deriving the same information about the direction and extent of prejudice, explicit, task, and implicit racial prejudice assessments to date have largely focused on prejudice in one dimension. Specifically, these approaches use a single target group and single perceiver group as the
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underlying method of assessment. That is, most of the scales concern “Black” individuals (e.g., “African-American,” “Black-Canadian,” etc.) as targets and “White” individuals (e.g., “European-American,” “White-Canadian,” etc.) as perceivers (see Shelton, 2000). Shelton (2000) recently argued that such a focus allows researchers to see only part of the picture when it comes to racial prejudice. A number of theorists have endeavored to include parameters other than “White” to “Black” comparisons (Bobo and Hutchings, 1996; Brigham, 1977, 1993; Shelton, 2000). For example, researchers have focused on the prejudice of “Whites” against: “Hispanics” (e.g., Weyant, 2005); Arabs (e.g., Dambrun, Guimond, and Michinov, 2003; Pratto et al., 1994); Aboriginal Australians (e.g., Pedersen and Walker, 1997); and “Asians” (Johnson, Terry, and Louis, 2005). Likewise, focusing largely on implicit measures, Richeson and Shelton and colleagues have recently endeavored to show that “Blacks” harbor prejudice against “Whites” (Richeson et al., 2003, 2005; Richeson and Trawalter, 2005; Shelton and Richeson, 2005, 2006; Shelton, Richeson and Salvatore, 2005a; Shelton et al., 2005b). Johnson and Lecci (2003) and Brigham (1977) also have investigated Black-to-White prejudice using questionnaire-based scales. Yet, as these citations indicate, the inclusion of more parameters besides “White” to “Black” prejudice was accomplished largely in the extant single-target group, single-perceiver group set-up, rather than as a multiple-target, multiple-perceiver configuration. Only occasionally (e.g., Lin, Kwan, Cheung, and Fiske, 2005) are multiple racial groups used as perceivers (e.g., “White” and “people of color”) to assess prejudice against one outgroup (e.g., “Asian-Americans”). A similarly small number of studies have examined prejudice from one racial group as perceivers to multiple outgroup targets (see Cummings and Lambert [1997] for an exploration of the prejudice of “African-Americans” toward both “Hispanics” and “Asian-Americans”; Walker [1994] for the prejudice of “White Australians” toward “Aborigines” and “Asians”; and Wilson [1996] for the prejudice of “Whites” against “Blacks,” “Hispanics,” “Asians,” and “Jews” in the United States). However, almost all of these studies use single items from public opinion research, not explicit scales, tasks, or implicit measures. Virtually no research, to date, has expanded existing methods of studying racial prejudice to a multiple-perceiver, multiple-target configuration.7
BENEFITS OF A MULTIPLE-PERCEIVER, MULTIPLE-TARGET CONFIGURATION It is clear that researchers are branching out and studying multiple, discrete configurations of pairwise prejudice. Yet, the very discrete, unidimensional assessment of perceivers and targets in most of the studies does not allow researchers to fully explore many important constructs in the prejudice literature.8 For example, concepts such as ingroup 7
While not focused on racial prejudice, it should be noted that Herek and colleagues have conducted research using the feeling thermometer to compare levels of prejudice toward bisexual men and bisexual women (targets) using heterosexual men and women as perceivers (Herek, 2002) and toward lesbians and gay men (targets) using heterosexual men and women as perceivers (Herek and Capitanio, 1999). This method can be viewed as a very rudimentary form of the method we endorse. 8 Certain concepts such as outgroup homogeneity, ingroup heterogeneity (e.g., Park and Rothbart, 1982) and ingroup homogeneity (e.g., Lee and Ottati, 1993, 1995) can be easily studied in the single-perceiver group,
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favoritism/preference and outgroup bias/derogation (e.g., Brewer, 1979) are difficult to study in this paradigm (see Cameron et al., 2001). Of course, these concepts have been studied using pairwise comparisons of one racial ingroup (perceiver) and one racial outgroup (target) for decades, but there is (and always has been) a flaw in the logic of interpretation. Strictly speaking, if one is able to demonstrate that “White” participants show derogation of “Blacks,” and the latter is the only outgroup included in the study, then the logical question becomes: Is this derogation selective to “Blacks” or generalized against all racial outgroups (including “Blacks”)? A generalized prejudice account would make the same predictions about patterns of results as the selective prejudice account. That is, if “White” participants have a generalized prejudice against all “Non-Whites” then they will downrate any outgroup. If only one racial group is included as a target, then a researcher cannot obtain affirmative evidence for either effect—selective or generalized derogation. It appears prudent to include multiple racial outgroups as targets in prejudice studies in order to answer this and other fundamental issues regarding possible differential perceptions of racial groups (see Bobo and Hutchings, 1996). For example, one could examine the repudiated hierarchical ordering of racial groups that some theorists posit (see Gold [2004] for a review). Additionally, implications from colorblind racism theory (Bonilla-Silva, 2003) also can be investigated by allowing researchers to examine multiple target groups simultaneously to explore to what extent those who endorse colorblind ideology actually show racial bias and toward whom.
A NEW MULTIDIMENSIONAL ARCHITECTURE AND APPROACH DELINEATED It should be noted that by 2010 in the United States the largest racial group after “European-Americans” (“Whites”) is projected to be “Hispanic-Americans” (“Latinos”). Moreover, the “Asian-American” (“Asian”) population is growing at a faster rate than the “African-American” (“Blacks”) population (U.S. Census Bureau, 2004). Ironically, most of the racial prejudice research continues to focus on prejudice from Whites-to-Blacks and the newest research focuses on prejudice from Blacks-to-Whites while prejudice toward the soonto-be second largest racial group in the U.S. is understudied. Our solution to this quandary is to not simply urge more research on “Hispanic-American” and “Asian-American” targets using familiar methods; instead, our proposed solution is to study the groups simultaneously as both targets and as perceivers. The multi-dimensional method that we propose can be organized as three separate but interrelated facets—response options, targets, and perceivers—all of which can (and should) be integrated into a single instrument, as outlined below.
single-target group paradigm because they theoretically rely on the perception of a single perceiver group and can be applied to any number of similar target groups. For instance, one could demonstrate that outgroup homogeneity happens for facial recognition using “Blacks” as the outgroup for “Whites” and imagine that this effect could extend to “Asians” as an outgroup (Bernstein, Young, and Hugenberg, 2007).
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The First Facet: Multiple Response Options Cameron et al. (2001) have noted the difficulty in the child literature with utilizing the familiar binary forced-choice response options. The KZPP and the PRAM II both ask children to attribute positive and negative attributes (separately) to either the ingroup or outgroup — there are no other options. This binary choice is flawed because it does not sufficiently disentangle ingroup favortism from outgroup derogation (Cameron et al., 2001). That is, children could choose the ingroup in the KZPP or PRAM II only because they want positive adjectives to be attributed to the ingroup and negative adjectives not to be attributed to the ingroup, thereby showing favoritism for one group not derogation of the other. Yet, in a binary choice situation, negative adjectives can only be attributed to the non-ingroup response option, the outgroup, even if the child has no particular negative feelings toward the outgroup. An analogous problem exists in the adult prejudice literature. As stated previously, the original IAT methodology used a simple subtraction method (between WHITE/DESIRABLE and BLACK/UNDESIRABLE responses), making it virtually impossible for older versions of the IAT to disentangle ingroup favoritism from outgroup derogation (Blanton et al., 2006). The improved scoring alogorithm of calculating D scores supposedly ameliorates this problem (e.g., Richeson et al., 2005). However, some confounds, such as salience asymmetry in response pairings, are not eliminated simply by using the modified D score method (see Greenwald, Nosek, Banaji, and Klauer, 2005; Rothermund and Wentura, 2004). Additionally, using the IAT and the modified scoring method, Blanton et al. (2006, Study 2) showed a significant, positive correlation between WHITE/NEGATIVE and BLACK/POSITIVE responses but a near zero correlation between WHITE/POSITIVE and BLACK/NEGATIVE responses. This pattern suggests that the argument for incompatible judgment as the assessment of prejudice only works for one set of responses (not both as the theory contends), and thereby may illustrate that the IAT cannot meaningfully disentangle favoritism and derogation. We agree with the Cameron et al. (2001) assessment of the methodological issues for children’s measures, argue that the same principles can be extended to adult work with the IAT, and propose that future work on racial prejudice provide and examine multiple, discrete response options. One of the only racial prejudice instruments to include more than two response options is the MRA for children (Doyle and Aboud, 1995, which was based on a previous version of an inter-ethnic prejudice assessment [Doyle, Beaudet, and Aboud, 1988]). The MRA allows children to choose either: (a) ingroup (provided that the child is identified as one of the presented groups), (b) outgroup, or (c) both groups. Cameron et al. (2001) have noted that even while the “both” response option is a good addition, a “none” (neither) response option also would be prudent to disentangle whether there really is favoritism or derogation. Interestingly, as Cameron et al. (2001) report, usages of the MRA and its prototype measure (Doyle et al., 1988) usually do not include the “both” response in analyses, opting instead to analyze the familiar difference score between ingroup-positive and outgroup-negative responses. To fully appreciate the argument made by Cameron et al. (2001), consider, for instance, that with three response options — ingroup, outgroup, and both — if a child is truly showing ingroup favoritism, the problem of interpretation remains for the negative attributions. As the “both” response option includes the ingroup this option may not be chosen for negative attributes when a child wants to show preference for the ingroup. Thus, the child would
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simply choose the outgroup for the negative attributes because it is the only option that does not include the ingroup. Yet, if a child were allowed to choose “neither” for negative attributes, researchers would be able to clearly interpret this result. In effect, ingroup favoritism would be a particular constellation of responses: only the positive items would be assigned to the ingroup and the negative items would be assigned to neither group (i.e., neither ingroup nor outgroup). This pattern would clearly show that children favor the ingroup but do not derogate the outgroup (by not assigning negative attributes to that group). In effect, in a four-option space (neither, ingroup, outgroup, both), a participant is allowed to not choose any group; a three-option space (using “both”) does not provide that option. Beyond the argument provided by Cameron et al. (2001), we believe that the “neither” option as part of a four-response set (neither, ingroup, outgroup, both) allows another layer of interpretation. As we noted earlier, virtually the only measure to assess nonprejudice among adults is Universal Orientation (Phillips and Ziller, 1997). Consequently, it appears that children are assumed to show some level of bias (either ingroup preference or outgroup derogation; see Cameron et al. [2001] for a review), as are adults using IAT methods or prejudice scales. It is possible, however, that some children and adults show no ingroup preference and no outgroup derogation. If such an attitude configuration existed, then the four-response space would allow researchers to see it as well. That is, participants who were nonprejudiced would likely show one of two response patterns. One pattern would include “both” responses for positive attributes and “neither” responses for negative attributes. This pattern might be a universal positive orientation toward people (ingroup and outgroup). The other pattern would include “neither” responses to both positive and negative items. In this case, the participant is reporting that neither the ingroup nor the outgroup is good or bad. While the second may not be the paradigmatic case of nonprejudice, it is a nonprejudiced pattern in that neither group is preferred nor derogated over the other, making it one kind of egalitarian perception. The merits of adding a “neither” (none) response notwithstanding, we propose another response option—one that provides yet another level of interpretive sophistication. A fourresponse forced-choice set has several merits, as we and Cameron et al. (2001) have argued. Nevertheless, the forced-choice nature of such a response set would provide interpretational problems of its own. It may be that a participant (especially a child) does not understand how to make such an assessment between or among targets, or the participant (especially an adult) does not see how to legitimately make such a choice given the information provided. Therefore, we believe that the participant should be given the option to state “I don’t know,” “I can’t tell” or something similar. Although some researchers may decry the use of an optout response, it seems prudent that children or adults be given this opportunity. If the interpretation of a response is that it reflects a child’s or adult’s actual beliefs or feelings, then it would be inadvisable to force a participant to make a decision when she or he does not feel comfortable with the question asked or the responses provided. In this case, the data quality is compromised because the participant was forced to respond. Consequently, a “don’t know” or “can’t tell” option theoretically allows a researcher to interpret the four other responses (neither, both, ingroup, outgroup) as statements of relative certainty because the participant has the option of not answering the question.
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The Second Facet: Multiple Targets As we discussed at the outset and as others have noted (e.g., Shelton, 2000), virtually all existing measures of racial prejudice for children and adults focus uni-dimensionally on one group as the target and another as the perceiver. However, we believe there is a serious problem with only using one group as the target—namely, one cannot really assess the locus of the negative or positive attitudes. For instance, once negative attributes have been assigned to the outgroup (e.g., via the KZPP or IAT) the question becomes, is this derogation specific to that particular outgroup? Or, would this participant show the same level of derogation toward all racial outgroups if given the opportunity? It is tempting but, ultimately, incorrect to interpret negativity toward the presented outgroup as negativity toward that specific group. The problem lay in the stimulus presentation. The KZPP, PRAM II and the IAT methods present only two targets: (a) the ingroup and (b) a single outgroup (and usually “White” and “Black”).9 With the binary forced-choice method that each type of measure uses, the participant must choose one or the other target. In this two-response, two-target space, the logical counterpart of the ingroup favoritism problem is at play. Focusing only on the outgroup choice, if a participant chooses negative attributes for the outgroup, there are (at least) two potential psychological causes: (a) the participant dislikes the specific racial outgroup presented, but not other racial outgroups, and (b) the participant dislikes all racial outgroups equally. In the second case, the presented racial outgroup is simply a “stand-in” for all racial outgroups. In effect, the participant uses an INGROUP/NOT-INGROUP logic to respond. Accordingly, the interpretation that the specific, presented racial outgroup is selectively disliked may or may not be the case. Notice, however, that adding the five-option response set to the two-target presentation does not resolve this problem. If only two targets are presented then even if the outgroup is chosen for a negative attribute (when the participants could have chosen “neither” or “both” as responses), then one only knows that there is definite outgroup derogation, but the specificity of derogation—selective or generalized—is unknown because there is not a comparison racial outgroup available to provide affirmative evidence for a specific derogation. Thus, like multiple response options, one needs multiple racial outgroups as targets to clearly argue for a specific bias against any one outgroup. Presenting multiple outgroup targets brings with it important methodological considerations. Two general classes of presentation architecture are possible with multiple targets: (a) exhaustive pairwise and (b) all groups simultaneously. The former allows the five response options to remain unchanged (i.e., neither, ingroup, outgroup, both, don’t know), but requires more presented items than the latter. The latter requires a change to the labels of the five response options (but their general meaning is the same) as well as new responses to capture all possible patterns (i.e., none [neither], ingroup, outgroup-1, outgroup-2, [etc.], all groups [both], all outgroups [new response], some subset of outgroups but not all [a set of new responses], and don’t know). While the simultaneous presentation method might be tempting, we argue that the exhaustive pairwise stimulus presentation should be preferred. The reasons rest on both the clarity of interpretation and the simplicity of the response category construction. Take, for 9
Of course this statement assumes that a participant self-identifies as one of the two presented groups, which is not always the case.
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example, the simultaneous presentation of one exemplar from 4 target groups — “White,” “Black,” “Asian,” and “Hispanic” — when the participant identifies as “White.” In this case, the response categories go from 5 (exhaustive pairwise) to 17 (simultaneous) to give all possible combinations and thus present no systematic bias in the provided responses. The 17 categories would be: (a) “none,” (b) “White” [ingroup], (c) “Black” [outgroup-1], (d) “Asian” [outgroup-2], (e) “Hispanic” [outgroup-3], (f) “all” [all four groups], (g) “Black, Asian, and Hispanic” [all outgroups], (h) “Black and Asian,” [outgroup pair-1], (i) “Asian and Hispanic” [outgroup pair-2], (j) “Black and Hispanic” [outgroup pair-3], (k) “White and Black” [ingroup/outgroup pair-1], (l) “White and Asian” [ingroup/outgroup pair-2], (m) “White and Hispanic” [ingroup/outgroup pair-3], (n) “White, Black, and Asian” [ingroup/outgroup trio1], (o) “White, Asian, Hispanic” [ingroup/outgroup trio-2], (p) “White, Black, and Hispanic” [ingroup/outgroup trio-3] and (q) “I don’t know.” Presenting 17 or more response categories is far too complex for either children or adults to fully comprehend and would probably result in the creation of response artifacts, such as participants using response heuristics (e.g., only viewing the first five options). Thus, the exhaustive pairwise presentation method would be preferred because it keeps the response space at 5 options. The exhaustive pairwise method requires similar diligence in the presentation of the total number of items. For the exhaustive pairwise presentation method, one needs to be mindful of presenting all combinations of targets in pairs (hence, the “exhaustive” title). As a result, there will be ingroup-outgroup pairs and outgroup-outgroup pairs. Nonetheless, the combinations of the exhaustive pairwise presentation are not complex. Using the four-target example from above — “Black,” “White,” “Asian,” and “Hispanic” — we can see that all pairwise comparisons would result in 6 initial pairings (i.e., Black-White, Black-Asian, Black-Hispanic, White-Asian, White-Hispanic, and Asian-Hispanic), see Figure 1. If a twodimensional valence factor (e.g., positive and negative) were added, then the initial stimulus set is multiplied by 2 for a total of 12 items. If one were interested in controlling for the specific content of valenced attributes across all the pairings, one need only multiply by the number of unique attributes. In the simplest case, let us use 2 unique attributes for each valence level — that is, 2 positive attributes (e.g., “easy-going” and “beautiful”) and 2 negative attributes (e.g., “violent” and “ugly”). In the case of two unique attributes for each valence level, we need only multiply 12 by 2 (because valence is also included in our 12-item running total) to get 24 items. Adding three unique attributes for each would make our total 36 items (12 x 3), adding four unique attributes would give us 48 items (12 x 4), and so forth. Recall, that each item only has 5 response options (not 17 or more), and even a 48-item measure might be easily administered to children. Finally, considering children in particular, it may be useful to simply present pictures of the actors to be judged without names and develop the response options consistent with a purely graphically presentation. This method avoids the problems of literacy levels and unwanted confounds, such as familiarity or other associations with names themselves.
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Target Groups
“Black”
“White”
“Asian”
“Hispanic”
Exhaustive Pairwise Presentation of the Target Groups “Black”
“White”
“Black”
“Asian”
“Black”
“Hispanic”
“White”
“Asian”
“White”
“Hispanic”
“Asian”
“Hispanic”
Figure 1. A graphical depiction of the exhaustive pairwise presentation strategy. Four targets are presented: “Black,” “White,” “Asian,” and “Hispanic.” The labels are meant to be broad enough to include any national instantiations (e.g., “African-American,” “Black-Canadian” for “Black”). The pairwise comparisons are depicted within the rows. As the figure indicates, any single target group is presented with every other target group. For research, order of presentations and position of targets (left, right) may be counterbalanced.
As we display in Figure 2, one might use a picture-story methodology (similar to the KZPP) to present the scenario and question via audio (“Here are two girls in the same class. Who will get a good grade on the next test?”), then use pictures as response options: each target singly, both targets, neither target (using a cross-out over both targets), and a question mark (?), see Figure 2.
The Third Facet: Multiple Perceivers Using a Single Instrument Our proposal of using multiple response options and multiple targets is also quite amenable to using multiple perceivers of different racial identities. If the five-response
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[Target 2]
[Both]
[Neither]
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[Don’t Know]
Figure 2. Possible stimulus and response option presentation for a single instrument with multidimensional architecture for children. Consistent with the mock display, one could present children with pictures of the response options (rather than providing words and names of characters to avoid any biases associated with remembering names, matching names to faces, and literacy). A question that might be asked for this presentation is, “Who will get a good grade on the next test?” In this case, (with the aid of pointers) “this girl” (i.e., target 1 or target 2), “both girls,” “neither girl,” and “I don’t know” all make logical and grammatical sense as answers.
options and use of multiple targets were integrated in a single instrument (as outlined above) the structure of the single instrument would allow the comparisons to be calibrated to the racial identity of the perceiver. Thus, a single instrument could provide a simultaneous measure of Black-to-White prejudice, White-to-Black prejudice, as well as any other form. This breadth of interpretation and use is possible because of the exhaustive pairwise stimulus presentation and nature of the response options. As described above, when a participant identifies as “White,” these targets become the ingroup and all other targets are racial outgroups. Likewise, when a participant identifies as “Black,” these targets are the ingroup, all other targets are racial outgroups, and so forth. The same response options can be used because they conceptually represent the ingroup and various outgroups (in addition to both, neither, and don’t know) for presented pairs and therefore require no adjustment (see Figure 2). One simply needs to record the participant’s racial self-identity to assess which group counts as the ingroup. The foregoing is a new concept when compared to traditional scales used to assess racial prejudice whose items indicate a single target group and assume that the perceiver does not identify with that group (e.g., Ard and Cook, 1977; Brigham, 1977, 1993; McConahay, 1986; Sidanius et al., 1991). Other methods of assessing racial prejudice such as the KZPP, PRAM II and IAT do not encounter the same problem because they present at least two target groups (usually “Black” and “White”). Yet, if participants identify as a race other than “Black” or “White,” no ingroup information can be assessed using the KZPP, PRAM II or the Black/White IAT versions.
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IS A SINGLE INSTRUMENT FOR ASSESSING RACIAL PREJUDICE USEFUL OR NEEDED? Despite the merits of the multi-faceted approach we outlined, one might question whether a single instrument designed to assess racial prejudice is useful or needed. Given the constructs uncovered by more than 70 years of racial prejudice research, can a single instrument hope to capture core aspects of this phenomenon? While taking nothing away from the variegation of constructs associated with racial prejudice and progress made to this point, we believe that a single instrument using a multidimensional architecture can capture and even refine many of the existing constructs associated with racial prejudice. This argument is developed in more detail in the next section. Here, we draw the reader’s attention to similar single-instrument projects already used to assess other types of prejudice (e.g., sexism and prejudice against homosexuality) to underscore the idea that a single instrument can capture various aspects of prejudice. For example, it is common for study protocols to have both men and women as participants complete the Ambivalence toward Men Inventory (AMI) (Glick and Fiske, 1999) or the Ambivalent Sexism Inventory (ASI) (Glick and Fiske, 1996), both complementary scales designed to measure a participant’s level of hostile and benevolent sexism toward men (AMI) and toward women (ASI). Each scale by itself uses multiple perceivers (in this case, men and women as participants) and assesses their endorsement of multiple constructs (in this case, hostile and benevolent sexism). Two complementary scales are needed because the contents of both benevolent and hostile sexisms differ based on the target group – men or women. Thus, the single-instrument aspect of these sexism measures is restricted to one instrument for measuring ambivalent sexism toward women or toward men (but not both simultaneously). Accordingly, the ASI and AMI lack multiple target groups in their singleinstrument approach. An example much closer to the proposal in this chapter is the Attitudes toward Lesbians and Gay Men Scale (ATLG) (Herek, 1988). The ATLG simultaneously assesses participants’ attitudes toward lesbian women and gay men as target groups (i.e., assesses multiple targets), making it possible to explore whether participants have equally prejudicial attitudes toward either target group, or whether one target group is viewed more negatively than another. Furthermore, any differences based on the gender of the participant (in this case, heterosexual men and women [multiple perceivers]) also can be examined. This method was used to argue that heterosexual men (as compared to heterosexual women) tend to have more favorable views of lesbian women versus gay men (Herek, 1988). (Heterosexual women tend to show equal levels of prejudice toward both target groups.) While the ATLG is not exactly comparable to the measure we propose creating for racial prejudice (e.g., the ATLG does not assess nonprejudice and the items concerning lesbians and gay men are not exactly the same, and thus not directly comparable), we urge social scientists interested in racial prejudice to take inspiration from the ATLG to explore direct comparisons among multiple target groups to more fully map the contours of racial bias and explore any differences in response profiles on the basis of participants’ ascribed racial identities. For instance, are “Whites” and “Blacks” similar in their prejudice toward “Asians”? Or does one group show more favoritism or derogation toward “Asians” than the other?
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One important difference between the analogous methods of the ASI, AMI, and ATLG and our method is that we propose a measure that is closer to the task and behavioral implicit measures rather than a questionnaire-based scale. We propose the development of inventory that is based on a task, such as responding to questions in a picture-story structure, which is also amenable to response latency measurement, rather than the development of a new scale or series of scales for racial prejudice. Below, we discuss the theoretical constructs that can be refined and uncovered by our proposed instrument to elucidate its position with respect to the current landscape of measuring racial prejudice.
ANTICIPATED OUTCOMES FROM A SINGLE INSTRUMENT WITH MULTIDIMENSIONAL ARCHITECTURE Integrating the three above-described facets (five response options, multiple targets, and multiple perceivers) into a single instrument would not be particularly difficult using extant computer technology. Aside from the methodological clarity that using such an instrument would provide (as argued above), new concepts would be at the disposal of theorists and researchers, while existing constructs would benefit from the added precision of measurement. These existing and new concepts are summarized in Table 1 and described in detail below in terms of response patterns on the multiple-response, multiple-target singleinstrument methodology proposed in this chapter. In order to clearly understand the constructs below, one should assume that participants must assign negative attributes and positive attributes separately to either a single target group, both target groups, neither target group, or else indicate that they “don’t know” to whom to assign an attribute.
Ingroup Favoritism This is a familiar construct, also known as ingroup preference, in both the child and adult literature on racial prejudice (e.g., Aboud, 2003; Brewer, 1979, 2001; Doyle and Aboud, 1995). As Cameron et al. (2001) have argued, this construct is ideally a preference for ingroup members with no negativity toward outgroup members. In terms of the stimulus presentation and response-option architecture presented in this chapter, this construct could be assessed unambiguously by examining the pattern of assigning most positive attributes to the ingroup and failing to assign negative attributes to any outgroup or to the ingroup (assigning them instead to the “neither” or “don’t know” response options).
Outgroup Favoritism This construct also is known as outgroup preference and has been identified within the implicit prejudice literature using the IAT (Ashburn-Nardo et al., 2003; Dasgupta, 2004; Rudman, Feinburg, and Fairchild, 2002). In terms of a response pattern, outgroup favoritism is the identical pattern of responding as ingroup favoritism but switching the ingroup and the
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Table 1. Theoretical Constructs Extractable from a Single Instrument that Presents Multiple Racial Groups to Multiple Perceiver Groups Construct Description 1. Ingroup favoritism 2. Outgroup favoritism 3. Generalized outgroup favoritism 4. Selective outgroup favoritism
5. Outgroup derogation
6. Generalized outgroup derogation 7. Selective outgroup derogation
8. Ingroup derogation 9. Traditional prejudice 10. Inverse prejudice 11. Ambivalence 12. Ingroup ambivalence 13. Generalized outgroup ambivalence 14. Selective outgroup ambivalence 15. Concomitant ingroup and outgroup 16. Ambivalence 17. Nonprejudice
A preference for the ingroup with little or no negativity toward at outgroups A preference for one outgroup (or multiple outgroups) with little or no negativity toward the ingroup An equal preference for all outgroups with little or no negativity toward the ingroup A preference for one outgroup (or a subset but not all outgroups) with little or no negativity toward the ingroup and the remaining outgroups A negativity toward one outgroup (or multiple outgroups) with little or no positivity toward the ingroup A negativity toward all outgroups with little or no positivity toward the ingroup A negativity toward one outgroup (or a subset but not all outgroups) with little or no positivity toward the ingroup and remaining outgroups A negativity toward the ingroup with little or no positivity toward any outgroup A combination of preference for the ingroup and derogation of one or more outgroups A combination of preference for one or more outgroups and negativity toward the ingroup Equal positivity and negativity to any group (including the ingroup) Equal positivity and negativity directed at the ingroup alone Equal positivity and negativity directed at all outgroups Equal positivity and negativity directed at one outgroup (or a subset of, but not all, outgroups) Equal positivity and negativity directed at the ingroup and at any or all outgroups No clear preference for any group (ingroup or outgroup) in the absence of derogation of any group
outgroup. Accordingly, this construct could be assessed by examining the pattern of assigning most positive attributes to the outgroups and failing to assign negative attributes to the outgroups or to the ingroup (assigning them instead to the “neither” or “don’t know” response options). Also, with the inclusion of multiple outgroups as targets in a single instrument,
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outgroup favoritism can be more precisely assessed as either generalized or selective. Each is described below. Generalized Outgroup Favoritism. This construct indicates that a participant favors all racial outgroups equally. The unambiguous pattern of responding that would indicate generalized outgroup favoritism would be assigning all positive attributes across the outgroups equally and the concomitant failure to assign negative attributes to any outgroups or to the ingroup (assigning them instead to the “neither” or “don’t know” response options). In this case, racial outgroups are not differentiated in terms of positive attributes. Selective Outgroup Favoritism. This construct indicates that a participant favors one outgroup (or a subset of, but not all, outgroups) over other outgroups. As a response pattern, participants would assign positive attributes to one outgroup or a subset of outgroups. The remaining outgroups are not assigned positive attributes and also are not assigned negative attributes. Finally, the ingroup is assigned neither positive nor negative attributes.
Outgroup Derogation Outgroup derogation is another familiar construct within the prejudice literature, also called outgroup bias or outgroup prejudice (e.g., Aboud, 1988, 2003; Brewer, 1979, 2001; Brigham, 1977, 1993; Cameron et al., 2001; McConahay, 1986; Tajfel, 1982). This construct is, as it sounds, negativity toward an outgroup. Yet, previous interpretations of this phenomenon, especially for children, were problematic due to the confounding of response categories with other constructs (e.g., ingroup favoritism) (Cameron et al., 2001). With the methods presented in this chapter, one can now more cleanly assess outgroup derogation as the response pattern wherein most negative attributes are assigned to outgroups while most positive attributes are assigned to neither outgroups nor to the ingroup. As with outgroup favoritism, if one includes multiple racial outgroups as targets, outgroup derogation can be further parsed into generalized or selective. Generalized Outgroup Derogation. As the name indicates, generalized outgroup derogation is equally derogating all racial outgroups. In terms of a response pattern, unambiguous generalized outgroup derogation would be assigning negative attributes equally to all presented outgroups while assigning positive attributes to neither the outgroups nor to the ingroup. Selective Outgroup Derogation. This construct is based on the specificity of derogation. The unambiguous response pattern indicating selective outgroup derogation would be: one outgroup or a subset of outgroups (but not all outgroups) is assigned negative attributes but the remaining outgroups are not assigned these negative attributes. Additionally, positive attributes are not assigned to the specific outgroup(s) that received negative attributes and also are not assigned to the remaining outgroup(s) or to the ingroup.
Ingroup Derogation This construct is the logical counterpart to ingroup favoritism. If it is possible to favor the ingroup while not derogating the outgroups, then it is theoretically possible to derogate the ingroup while not favoring outgroups. The unambiguous response pattern for such a construct
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would involve assigning most negative attributes to the ingroup, assigning no negative attributes to any outgroup, and finally assigning positive attributes to neither the ingroup nor the outgroups. Individuals who harbor negative attitudes toward ingroup members but show no preference for or bias against any racial outgroup would show this pattern.
Traditional Prejudice (or Pro-Ingroup/Anti-Outgroup Prejudice) This pattern of responding is a combination of ingroup favoritism and some form of outgroup derogation. That is, the ingroup is assigned positive attributes, while the outgroups are assigned negative attributes. In this way, traditional prejudice is distinguishable from ingroup favoritism and outgroup derogration (as described above) because it is the combination of these response sets, rendering the outcome ingroup favoritism together with outgroup derogation. Moreover, the anti-outgroup aspect of traditional prejudice can be further examined as generalized or selective. We term this construct “traditional prejudice” because it captures the paradigmatic scientific and non-scientific belief that prejudice is the combination of pro-ingroup attitudes and anti-outgroup attitudes.
Inverse Prejudice (or Anti-Ingroup/Pro-Outgroup Prejudice) The logical flipside of traditional prejudice is inverse prejudice. For this construct, participants would assign most positive attributes to outgroups and most negative attributes to the ingroup thereby inverting the pattern of traditional prejudice. This construct is reminiscent of the Clark and Clark (1947) investigation wherein the researchers found that children identified as “African-American” had negative attitudes toward dolls designed to represent “African-Americans” and positive attitudes toward dolls designed to represent “Whites.” With the methods proposed in this chapter, this phenomenon can be examined over a set of racial outgroups, not just one, to explore different expressions of pro-outgroup attitudes (e.g., generalized or selective).
Ambivalence Ambivalence refers to equally positive and negative attitudes toward particular attitude objects. In the case of racial prejudice, ambivalence has been examined with respect to at least one target group, “Blacks” (I. Katz and Haas, 1988), using a questionnaire-based explicit scale. However, with our proposed single instrument using a multidimensional architecture, ambivalence can be examined with respect to both the ingroup and outgroups as the attitude objects. Using the framework developed in this chapter, there can be at least four broad kinds of ambivalence: (a) ingroup ambivalence, (b) generalized outgroup ambivalence, (c) selective outgroup ambivalence, and (d) concomitant ingroup and outgroup ambivalence. Ingroup Ambivalence. This construct refers specifically to ambivalent attitudes directed only at the ingroup. As a result, an unambiguous response pattern indicating ingroup ambivalence would be assigning all the positive and all the negative attributes to the ingroup while not assigning any negative or positive attributes to any outgroup.
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Generalized outgroup ambivalence. This construct refers specifically to ambivalent attitudes directed equally at all outgroups. An unambiguous response pattern that would indicate generalized outgroup ambivalence is one in which all the positive and all the negative attributes are assigned to each and every outgroup while not assigning any negative or positive attributes to the ingroup. Selective Outgroup Ambivalence. This construct is a narrower application of generalized outgroup ambivalence to specific outgroups or to one outgroup (not equally toward all). A response pattern that would indicate selective outgroup ambivalence is one in which a specific outgroup or a subset of outgroups is assigned all the positive and all the negative attributes while not assigning any negative or positive attributes to the remaining outgroups or to the ingroup. Concomitant Ingroup and Outgroup Ambivalence. This construct is, in effect, the combination of each type of ambivalence, ingroup-directed and outgroup-directed. As such, it can encompass both generalized and selective outgroup ambivalence. Concomitant ambivalence involves both positive and negative attributes assigned to both the ingroup and to either a single outgroup, to multiple outgroups, or to all presented outgroups.
Nonprejudice It appears prudent that any measure of racial prejudice should also include the ability to assess its logical opposite, nonprejudice. As we noted earlier, most existing racial prejudice measures do not include such a possibility. However, the proposed construction of a single instrument using multiple response options and multiple targets does allow for the assessment of nonprejudice in addition to the various types of prejudice detailed above. As indicated previously, a nonprejudice response pattern could be of two kinds. One kind would be not assigning positive or negative attributes to any group — ingroup or outgroups. This pattern would essentially be a series of “neither” responses, indicating that the participant has no clear favoritism or derogation toward any group, including the ingroup. Another pattern would be responding with “neither” to any pair for negative attributes and responding “both” to any pair (i.e., ingroup-outgroup or outgroup-outgroup) for positive attributes. In this case, the participant appears to show only positivity toward any group and no negativity toward any group.10
SUMMARY The racial prejudice constructs presented above are purposefully listed as unambiguous or appear as non-overlapping because these are the logical possibilities that a single instrument constructed in the manner described can generate. Of course, combinations of the above constructs are also possible and we have detailed at least three instances of such combinations (i.e., traditional prejudice, inverse prejudice, and concomitant ingroup/outgroup 10
Because this pattern of responding is universal positivity, it is different from positive prejudice (i.e., assigning positive attributes based on group membership) because all groups are treated equally. In this case, group membership is a zero predictor of positive associations.
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ambivalence). Although complex and varied, these constructs represent the theoretical space possible for the assessment of racial prejudice. The actual patterns evinced by participants are an empirical question and researchers would need to define the specific criteria for the presence or absence of these constructs based on percentage of responses, extent of responses, or some other measure. Nevertheless, we wanted to detail that which is possible to underscore the idea that racial prejudice can be meaningfully assessed via a single instrument for any set of racial identities as perceivers using multiple response options and multiple targets simultaneously. Additionally, the multi-response, multi-target single-instrument architecture is completely amenable to the use of response latencies as a way to further assess levels of prejudice. The use of latencies with this instrument would make it parallel in some respects to existing behavioral implicit measures such as the IAT while the structure of response options and presented stimuli would allow for more precise differentiations between and among constructs using both overt choice and reaction time data. Reaction times could add a dimension of interpretability to the constructs listed above by allowing researchers to examine the extent or intensity of derogation, favoritism or ambivalence by measuring how quickly people respond when assigning positive or negative attributes to groups. Moreover, current multivariate statistical techniques can be employed to reduce the space of observed (vs. theoretical) constructs. Depending on the construction of the response scale (i.e., continuous vs. categorical), techniques such as profile analysis, multidimensional scaling, conjoint analysis and correspondence analysis can be used to provide a systematic picture of the actual response space and the appropriate constructs that can be derived.
CONCLUSION To date, the literature on racial prejudice has largely focused on the phenomenon as it relates to a single perceiver group and single target group. While the historical motivations for this situation are understandable, we argue that it is time to advance our knowledge of the processes underlying and constructs associated with racial prejudice by constructing new measures that allow researchers to assess multiple target groups via multiple response options. Moreover, the same methods can be used to assess prejudice in children and adults (with presumed content changes for developmentally appropriate-language). The thrust of this chapter is not to decry the existing techniques as much as supplement them with new ideas. While a single instrument designed to measure racial prejudice as delineated above is encouraged, the principles of the existing measures remain central to the proposed single instrument. The current focus of explicit scales, tasks and implicit measures on assessing negative attitudes toward a particular outgroup can be explored via the constructs of selective or generalized outgroup derogation, while positive attitudes can be explored via favoritism, and both can be explored via ambivalence. The reaction time methodology employed by behavioral implicit measures (e.g., IAT) can also be retained in the single instrument by recording latencies from initial stimulus presentation until a response is indicated (see Figure 2 for a template of the stimulus presentation we envision). Furthermore, if the merits of the single instrument are demonstrated empirically with respect to distinguishing the different forms of racial prejudice detailed in the previous section, then
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existing scales, tasks and implicit measures can be evaluated with reference to the constructs they assess. For example, using the single instrument proposed as a benchmark, one might find that the IAT can reliably assess outgroup favoritism (or lack thereof) but no other construct. In this case, researchers can use the IAT in the appropriate manner, knowing what construct(s) it can and cannot assess. Additionally, current measures that are not directly focused on racial prejudice, such as motivation to control prejudice (e.g., Dunton and Fazio, 1997; Plant and Devine, 1998) and social dominance orientation (Pratto et al., 1994) are completely amenable to use with the proposed single instrument to advance our understanding of prejudice. One can, for example, explore whether traditional prejudice (as we have termed and defined it) correlates with a social dominance orientation, or whether outgroup derogation by itself is more strongly correlated. Similarly, researchers can explore which constructs identified above correlate with high or low motivation to control prejudiced responses to further define how racial prejudice functions with motivation. The urgency of this issue is that as we continue to increase our understanding of what it means to live in a world in which people identify as different races, our methods to assess racial prejudice ought to become increasingly complex so that we may understand and explain the contours, nuances and associated motivations for racial prejudice in order to effectively address it. Therefore, it behooves us to figure out better ways to study racial prejudice in a multiracial world than we are currently using because the current methods only give a piecemeal picture of prejudice rather than a holistic view. We might take the lead from Thistlethwaite (1950) and other theorists of that era who intimated that what we now call “racial prejudice” is a system of attitudes and beliefs that connects all relevant groups. Yet, until we develop methods of studying these perceptions of multiple groups using a single, standardized instrument, we will be left with imprecise comparisons and imprecise conclusions. Even without constructing a single instrument to measure racial prejudice, it is our hope that this chapter provokes a deeper consideration of the constructs associated with racial prejudice (see Table 1). It is not a logical necessity that a single instrument be developed to discover and assess the constructs that we have described here. In principle, these constructs could be assessed using multiple instruments.11 In any event, we believe it prudent to explore these constructs and, in so doing, acquire a more sophisticated understanding of racial prejudice. In sum, we have provided a detailed outline of the theory and methods that we believe can supplement and advance our knowledge about processes involved in racial prejudice. It also should be noted that the ideas presented here are applicable to other forms of prejudice such as sexual orientation prejudice, gender prejudice, as well as ethnic prejudice. Concepts such as favoritism, derogation and ambivalence, and the selective or generalized nature of them for multiple outgroups, can logically be examined for other social categories besides race. Finally, we urge theorists who study other forms of prejudice to query the depth of assessment in their respective fields, using the constructs presented here as starting points to advance our understanding of attitudes and social perception in general. 11
The use of multiple instruments would, admittedly, present some difficulties such as length of the measures, participant fatigue, and possible carry-over effects from responding to 4 to 6 measures at one time (depending on the number of target groups assessed).
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Shelton, J. N. (2000). A reconceptualization of how we study issues of racial prejudice. Personality and Social Psychology Review, 4, 374-390. Shelton, J. N., and Richeson, J. A. (2005). Intergroup contact and pluralistic ignorance. Journal of Personality and Social Psychology, 88, 91-107. Shelton, J. N., and Richeson, J. A. (2006). Ethnic minorities’ racial attitudes and contact experiences with white people. Cultural Diversity and Ethnic Minority Psychology, 12, 149-164. Shelton, J. N., Richeson, J. A., and Salvatore, J. (2005a). Expecting to be the target of prejudice: Implications for interethnic interactions. Personality and Social Psychology Bulletin, 31, 1189-1202. Shelton, J. N., Richeson, J. A., Salvatore, J., and Trawalter, S. (2005b). Ironic effects of racial bias during interracial interactions. Psychological Science, 16, 395-402. Sidanius, J., and Pratto, F. (1993). The inevitability of oppression and the dynamics of social dominance. In P. M. Sniderman, P. E. Tetlock, and E. G. Carmines (Eds.), Prejudice, politics, and the American dilemma (pp. 173-211). Stanford, CA: Stanford University Press. Sidanius, J., Pratto, F., Martin, M., and Stallworth, L. M. (1991) Consensual racism and career track: Some implications of social dominance theory. Political Psychology, 12, 691-721. Smedley, A., and Smedley, B. D. (2005). Race as biology is fiction, racism as a social problem is real: Anthropological and historical perspectives on the social construction of race. American Psychologist, 60, 16-26. Tajfel, H. (1982). Social psychology of intergroup relations. Annual Review of Psychology, 33, 1-39. Tate, C., and Audette, D. (2001). Theory and research on 'race' as a natural kind variable in psychology. Theory and Psychology, 11, 495-520. Teo, T. (2004). The historical problematization of ‘mixed-race’ in psychology and human scientific discourses. In A. S. Winston (Ed.), Defining difference: Race and racism in the history of science (pp. 79-108). Washington, DC: American Psychological Association. Thistlethwaite, D. (1950). Attitude and structure as factors in the distorting of reasoning. Journal of Abnormal and Social Psychology, 45, 442-458. U.S. Census Bureau (2004). U.S. Interim Projections by Age, Sex, Race, and Hispanic Origin. Retrieved from http://www.census.gov/ipc/www/usinterimproj Vanman, E. J., Saltz, J. L., Nathan, L. R., and Warren, J. A. (2004). Racial discrimination by low-prejudiced whites. Psychological Science, 15, 711-714. Walker, I. (1994). Attitudes toward minorities: Survey evidence of Western Australians’ attitudes to Aborigines, Asians, and women. Australian Journal of Psychology, 46, 137143. Weyant, J. M. (2005). Implicit stereotyping of Hispanics: Development and validity of a Hispanic version of the implicit association test. Hispanic Journal of Behavioral Sciences, 27, 355-363. Wheeler, M. E., and Fiske, S. T. (2005). Controlling racial prejudice: Social-cognitive goals affect amygdala and stereotype activation. Psychological Science, 16, 56-63. Williams, J. E., Best, D. L., and Boswell, D. A. (1975). Children’s racial attitudes in the early school years. Child Development, 46, 494-500.
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Williams, J. E., Morland, J. K. and Associates (1975). Preschool racial attitudes measure II and color meaning test: General information and manuals of directions. Wake Forest: Wake Forest University Press. Wilson, T. C. (1996). Cohort and prejudice: Whites’ prejudice toward Blacks, Hispanics, Jews, and Asians. Public Opinion Quarterly, 60, 253-274. Wittenbrink, B., Judd, C. M., and Park, B. (1997). Evidence for racial prejudice at the implicit level and its relationship with questionnaire measures. Journal of Personality and Social Psychology, 72, 262-274. Wittenbrink, B., Judd, C. M., and Park, B. (2001). Evaluative versus conceptual judgments in automatic stereotyping and prejudice. Journal of Experimental Social Psychology, 37, 244-252. Woodmansee, J. J., and Cook, S. W. (1967). Dimensions of racial attitudes: Their identification and measurement. Journal of Personality and Social Psychology, 7, 240250. Zack, N. (2003). Philosophy of science and race. New York: Routledge. Zalk, R. S., and Katz, P. (1976). The Katz-Zalk Projective Prejudice Test: A measure of racial attitudes in children. JSAS Catalog of Selected Documents in Psychology, 6, 37.
In: The Psychology of Modern Prejudice Editors: Melanie A. Morrison and Todd G. Morrison
ISBN 978-1-60456-788-5 © 2008 Nova Science Publishers, Inc.
Chapter 6
ASSESSING IMPLICIT COGNITIONS WITH A PAPERFORMAT IMPLICIT ASSOCIATION TEST Kristi M. Lemm11, Kristin A. Lane2, David N. Sattler1, Saera R. Khan3, and Brian A. Nosek4 1. Western Washington University, USA 2. Bard College, USA 3. University of San Francisco, USA 4. University of Virginia, USA
ABSTRACT The Implicit Association Test (IAT; Greenwald, McGhee, and Schwartz, 1998) is a frequently used measure of implicit cognitions that is typically administered on computers. This chapter reports development of an IAT that can be administered on paper. First, it describes a suggested analytic procedure for paper IAT data. Next, two studies measuring implicit racial preferences are reported that suggest that the paperformat IAT elicits similar but somewhat weaker mean effects than the computer-format IAT, and shows test-retest reliability comparable to the computer-format IAT. The paper format IAT may be more sensitive to the type of stimuli used in the task. It performed better with all-verbal stimuli compared with pictures of faces. Use of the paper-format IAT with verbal stimuli may be a useful supplement to computerized data collections, or a viable approach when computer data collection is not feasible.
INTRODUCTION The assessment of attitudes has a long theoretical and methodological history in social psychology. One recent insight, that people may possess attitudes of which they are 1
Correspondence concerning this chapter should be addressed to Kristi M. Lemm, Department of Psychology, Western Washington University, 516 High Street, MS 9089, Bellingham, WA 98225; Email:
[email protected].
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consciously unaware, has spurred the development of measures to assess such cognitions without relying on verbal self-reports. Most of these measures use response latency as the dependent variable, and a computer for administration. Less conscious measures of attitudes typically reveal more negativity toward socially stigmatized outgroups than merely asking people how they feel (Nosek et al., 2007). Additionally, implicit and explicit measures explain unique variance in people's behavior (Greenwald, Poehlman, Uhlmann, and Banaji, in press). Sole reliance on computers to administer such tasks restricts researchers' ability to collect a large amount of data in a single setting and potentially to reach non-traditional populations (e.g., conference attendees, students on a camping retreat, beach-goers, people on the train). "Low-tech" means of assessing such attitudes may prove to be a useful supplement to computer-based measures (Vargas, Sekaquaptewa, and von Hippel, 2007). The Implicit Association Test (IAT; Greenwald et al., 1998) is a widely used tool for assessing implicit attitudes and beliefs (see Lane, Banaji, Nosek, and Greenwald, 2007; Nosek, Greenwald and Banaji, 2007 for reviews). The IAT measures the relative strength of association between concepts in different categories (e.g., flower/insect and pleasant/unpleasant) by measuring the amount of time it takes to categorize stimuli from the four categories with just two response options. In one condition, participants give one response (e.g., a key press on a computer) for both flowers and pleasant words and an alternate response for both insects and unpleasant words. In a second condition, participants give one response for both flowers and unpleasant words and the alternate response for insects and pleasant words. The difference in average response latency between the two pairings reflects the underlying relative strength of associations. In this example, most participants would be able to categorize the items faster in the first condition than the second, indicating relatively more positive associations toward flowers than insects. Response latency is typically assessed using computers. This provides maximal information about each response but restricts data collection to situations in which computers are readily available. Although computer-based data collection is optimal for response latency measures, we introduce a paper-format IAT for circumstances in which a computer is not available. We summarize previous uses of this task, provide a detailed description of the procedure for administering a paper-format IAT, and describe an algorithm that is effective for scoring a paper-format version. Additionally, we report two studies that demonstrate that the psychometric properties of a paper-format IAT, while not as consistent as computer versions, are reasonable for research uses of the IAT.
DESCRIPTION AND SOME SUCCESSFUL RESEARCH APPLICATIONS OF THE PAPER-FORMAT IAT When completing a paper-format IAT, participants see a page with two columns of stimuli and they are instructed to mark a circle to the left or right of each stimulus item to indicate its appropriate category. Two of the categories correspond with a left response, and the other two correspond with a right response. Each IAT consists of two conditions. For example, Figure 1 depicts one condition that requires participants to categorize names typical among Black people and pleasant words on the left side of the column and names typical among White people and unpleasant words on the right side.
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Figure 1. Sample page of paper-format IAT.
In a second condition on a new page, the category pairings switch, and White names and pleasant words are categorized on the left and Black names and unpleasant words on the right side.2 Participants receive a fixed time period (e.g., 20 seconds) to categorize as many items as possible starting from the top of the page and working down. The number of correct categorizations in one condition compared with the other is the key measure of relative association strength. This approach is different from computer-based IATs, in which the number of responses is fixed and the amount of time to complete them is the dependent variable. Even so, the procedural logic is the same: close association between the concepts 2
The order of the critical pages and the left-right location of the pairings are counterbalanced across participants.
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that share a response should make the task easier, leading to better performance (i.e., more correct responses). So, more categorizations in the second compared with the first condition above would be interpreted as an implicit preference for Whites compared with Blacks. The patterns of data obtained from paper-format IATs generally parallel those of conceptually similar computerized IATs. For example, studies using paper-format IATs have demonstrated strong pro-White (relative to Black) implicit preference (Lowery, Hardin, and Sinclair, 2001; Sinclair, Lowery, Hardin, and Colangelo, 2005) and strong pro-thin (relative to obese) implicit preference (Teachman and Brownell, 2001; Teachman, Gapinski, Brownell, Rawlins, and Jeyaram, 2003), just as is observed with computer administration (Nosek et al., 2007). Attitudes assessed with the paper-format IAT appear to be sensitive to the same kinds of situational cues as those assessed with the computerized IAT (Blair, 2002). For example, White (but not Asian American) participants showed weaker pro-White attitudes when the test was administered by a Black experimenter than by a White experimenter (Lowery et al., 2001); anti-fat attitudes were stronger after exposure to news stories emphasizing behavioral (versus genetic) causes of obesity but weaker after exposure to an empathy-inducing story (the latter effect was only observed among overweight participants; Teachman et al., 2003). Finally, paper-format IATs have been used to measure associations of self with good (selfesteem), self with one’s university (identity), and one’s university with good (attitude) providing evidence for cognitive consistency among these constructs (Lane, Mitchell, and Banaji, 2005), as predicted by recent conceptions of consistency among implicit cognitions, and observed with computer-based measures (Greenwald, Banaji, Rudman, Farnham, Nosek, and Mellott, 2002). These studies suggest that paper-format forms of the IAT may be a useful instrument for implicit social cognition research. Use of the paper-format IAT is predicated on the assumption that the computerized and paper-format versions of the IAT share the same underlying logic, and thus should measure the same construct. To date, this assumption has not been tested directly. The current research is the first to compare the results and psychometric properties of the paper-format IAT and its computer-based counterpart. In addition, because the dependent variable for the paper-format IAT is the number of responses completed in a fixed time, rather than the amount of time to complete a fixed number of responses, the recommended scoring procedures for the computer-based IAT (Greenwald, Nosek, and Banaji, 2003) do not apply. Through simulation and empirical tests, we investigated the validity of alternative analytic approaches for paperformat IAT data.
STUDY 1 The goal of Study 1 was to determine an appropriate method for analyzing paper-format IAT data. In a paper-format IAT, the dependent measure is based on the number of items completed in a fixed amount of time. Intuition may suggest using the difference between the number of items completed on the two blocks of the paper-format IAT as an index of the “IAT effect.” However, individual differences in response speed create an unwanted artifact in the use of difference scores in response latency comparisons in general (Sriram, Greenwald, and Nosek, 2007) and on the IAT in particular (Greenwald et al., 2003; Hummert,
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Garstka, O’Brien, Greenwald, and Mellott, 2002).3 This effect can be reduced by using the D algorithm that divides the average difference in response latency by the standard deviation of all the response trials (Cai, Sriram, Greenwald, and McFarland, 2004; Greenwald et al., 2003; Mierke and Klauer, 2003). As the paper format IAT does not provide response latencies to individual trials, this approach is not a viable strategy for the paper-format IAT. However, a number of mathematical transformations may reduce artifactual influences of individual differences in average response latency. Consider two participants who each complete a paper-format IAT measuring implicit preference for flowers, relative to insects. Participant 1 completes 20 items in the flower+good block and 10 items in the flower+bad block, and Participant 2 completes 30 items and 20 items in those blocks, respectively. Based on the simple difference in the number of items completed (difference = 10), these two participants exhibit the same implicit preference for flowers over insects. However, Participant 1 completes twice as many items in the flower+good pairing than in the flower+bad pairing, whereas Participant 2 completes only 50% more items in the flower+good pairing than in the flower+bad pairing. As a ratio, Participant 1 has a much larger effect than Participant 2. This example illustrates how individual differences in participant speed may mask or exaggerate the magnitude of implicit preferences as gauged by a simple difference score. Study 1 explores a variety of different procedures for analyzing paper-format IAT data. To evaluate the efficacy of these procedures, we first created a simulated data set of paperformat IAT data with individual differences in average response time. Next, we created a second data set designed to be correlated with the IAT score from the first and included random error. As the datasets were manufactured to be positively correlated, the validity of scoring procedures can be observed by identifying the approach that maximizes the correlation between the data sets.
METHOD Simulated Datasets We first generated a simulated dataset (D1) of 1000 data observations. Each observation consisted of two values (A1 and B1) that were drawn from a range similar to those that have been seen in actual paper-format IAT data sets (Lane et al., 2005; Lemm, 2000). For ease of presentation, we assumed that these data represent an attitudinal IAT in which blocks A1 and B1 denote the pairings A+good and B+good, respectively. Values of A1 greater than B1 would reflect implicit preference for A over B. A1 and B1 were randomly selected integers between 10 and 40. Thus, this simulated data set assumes that items completed on any given block are uniformly distributed between 10 and 40. (Simulated data sets with normally distributed data revealed a similar pattern of results.)
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The effect of overall response speed differs for the two versions of the task: on the computerized version, participants with slower responses overall show larger IAT effects for a measure based on difference scores; on the paper-pencil version, they would be expected to complete fewer items overall and show a smaller IAT effect based on a difference score calculation.
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Nine secondary data sets (D2) were then generated as a function of D1 with the following formulas: (1) A2 = r' * A1 + (1-r') * X and (2) B2 = r' * B1 + (1-r') * Z, where r' varied between 0.1 and 0.9, and X and Z were randomly selected integers between 10 and 40. That is, each new data point was a joint function of the original data set and a random value. Greater values of r' therefore reflect stronger relationships between the two data sets. In the extreme case, for example, where r' = 1.0, D1 would be isomorphic to D2. Finally, “extreme” data sets (D3) were generated that were a function of D1 but that consisted solely of extreme scores. The same formulas were used to generate values of data points of A3 and B3, with the additional requirement that for each observation, the larger value of the two blocks was increased by two standard deviations. These simulated data sets allowed us to explore each proposed analytic procedure’s ability to detect correspondence between the data sets even when one of the data sets consists of extreme scores.
POTENTIAL SCORING PROCEDURES An infinite number of approaches could be used in analyzing paper-format IAT data. In the current study, we examined the properties of seven scoring procedures. The procedures varied in their emphasis on the additive difference (A – B) versus the ratio difference (A/B) between the two IAT blocks. Additionally, common approaches for normalizing data (square root or inverse calculations) were included in some of the scoring approaches to test their ability to minimize the extraneous effects of extreme scores. In all cases, higher numbers reflect stronger implicit preference for A over B. Difference score. The difference score considers only the difference in number of items completed across the two blocks, and does not adjust for participant speed. The difference score is calculated as A – B. Simple ratio. The simple ratio is calculated as A/B – 1, and is sensitive to the relative speed of response on each block. The ratio approach provides an index of a subject’s performance on block A, relative to his or her performance on block B. One is subtracted from each ratio value in order to define the zero point as no difference in the number of correct responses between the two response conditions. Max/min ratio. The max/min ratio is calculated as X/Y – 1, where X is the greater of A or B, and Y is the smaller of A or B. (If A = B, the formula produces a result of 0 regardless of which original value is selected as X and which is selected as Y.) As with the simple ratio approach, this approach adjusts for overall speed by assessing performance on one block of the IAT relative to performance on the other block of the IAT. However, unlike the simple ratio, this approach minimizes the effects of larger difference scores from faster subjects, relative to slower ones. Resulting values should be multiplied by -1 if B is greater than A in order to preserve the directionality of the IAT score. Latency conversion. This approach calculates the difference in the average latency per item between the two blocks. The total number of items completed is first transformed into an average response latency per item (per second) by taking the reciprocal of the number of items completed on each block. Next, the difference between these two values is calculated. The formula for this approach is 1000 * ((1/B) – (1/A)).
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Simple product. This approach makes use of both the overall difference score and the ratio score by multiplying the difference score by the max/min ratio. It is calculated as (A – B) * (X/Y), where X is the greater of A or B, and Y is the smaller of A or B. Product: squared ratio. This approach also incorporates the overall difference and ratio scores. However, the relative performance on the two blocks is squared, and thus weighted more heavily than the difference score. It is calculated as (A – B)*(X/Y)2, where X is the greater of A or B, and Y is the smaller of A or B. Product: square root of difference. This approach includes both difference score and ratio information. In this case, the square root of the difference between the number of items completed between the two blocks is multiplied by the ratio of items completed. It is calculated as (X/Y)*Square Root of (X – Y), where X is the greater of A or B, and Y is the smaller of A or B. If B is greater than A, the resulting values are multiplied by -1 to retain the directionality of the IAT effect.
RESULTS Correlations among Simulated Data Sets IAT effects were calculated for the simulated data using each of the proposed transformations. Each scoring procedure was applied to the data sets D1 (original data set), D2 (non-extreme data set that was a function of D1), and D3 (extreme data set that was a function of D1) at varying levels of correspondence (r') between D1 and the secondary data sets D2 and D3. As D2 and D3 are direct functions of D1, there is a true relationship among them. Superior scoring procedures ought to reproduce this functional relationship, and thus maximize the correlation between the data sets D1 and D2 and between the data sets D1 and D3. The different scoring procedures did not affect correlations among IAT scores at low levels of correspondence between D1 and D2 (r' = 0.1, 0.2). However, at higher degrees of correspondence between the data sets, transformation selection did influence the observed correlation among the data. As illustrated in Figure 2, the simple ratio transformation was far inferior to the other transformations, and the product: squared ratio and max/min ratio transformations lagged behind the others in maximizing the observed correlations between D1 and D2. As these procedures were inferior for non-extreme data, they were not considered in the analysis of the extreme data set. We next examined the ability of the four remaining scoring procedures to maximize correspondence between D1 and D3, which was functionally related to D1 but consisted of extreme scores. As can be seen in Figure 3, at eight out of nine levels of r', the product: square root of difference approach outperformed the other scoring procedures. For the two highest levels of defined correspondence (r' = 0.8, 0.9) between D1 and D3, the product: square root of difference approach explained significantly more variance than the next-best transformation, zs > 2.00.
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DISCUSSION The ability of seven proposed scoring procedures to maximize the correlation between functionally related data sets was explored. Of the seven potential scoring procedures, the product: square root of difference approach evidenced the best performance, particularly when one of the data sets consisted of extreme scores. Consequently, we used this scoring approach in subsequent studies with data collected from human participants. Product: Square Root of Difference Difference Score Latency Simple Product Simple Ratio Max/ Min Ratio Product: Squared Ratio
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Value of r' Figure 2. Comparison of proposed procedures for analyzing paper-format IAT data. Figure shows the correlation between two functionally related data sets - D1 and D2 - at different levels of correspondence between the two (r'). Higher levels of r' indicate stronger initial relationships between D1 and D2.
STUDIES 2A AND 2B Paper-format IATs have been used in previous research with the tacit assumption that the psychometric properties of the measure are similar to computer-based IATs. The purpose of Studies 2a and 2b was to assess systematically whether results from a paper-format IAT would mimic those of a computer-based IAT when using the same stimulus items. Participants completed paper- and computer-based race IATs (Black-White/pleasantunpleasant) with names or pictures for the race dimension and words for the pleasantunpleasant dimension. Test-retest reliability was assessed after a one-week interval. If the paper-format IAT is to be a viable supplement to the computerized version, then they should show similar patterns of racial attitudes, be correlated with one another, and have comparable levels of test-retest reliability.
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Figure 3. Comparison of proposed procedures for analyzing paper-format IAT data for extreme scores. Figure shows the correlation between two functionally related data sets - D1 and D3 - at different levels of correspondence between the two (r'). Higher levels of r' indicate stronger initial relationships between D1 and D3. This data set consisted of extreme scores, with the larger value of the two data points increased by two standard deviations.
STUDY 2A Method Participants Fifty-three female and 20 male undergraduates (aged 18-40, M = 20.8, SD = 4.1; 75% White) completed Session 1 in exchange for partial course credit; 19 men and 50 women returned for Session 2. Data from two women who reported not being fluent in English were omitted from further analysis. Due to a printing error on the measure, paper IAT responses from three men and 19 women were unusable, and due to computer failure, computer IAT data were unusable for two men and 10 women, resulting in unequal Ns for different analyses. Materials Black and White names and pleasant and unpleasant word stimuli were selected from Greenwald et al. (1998). Race stimuli for the picture IATs were positive expression color photographs of African American and European American faces (four men and four women
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of each race).4 The individuals pictured all had similar hair color and were matched on attractiveness by a sample of college students.
PROCEDURE Experimenters were White undergraduate students. Participants were seated in individual laboratory rooms, with a maximum of three participants (in separate rooms) per session. Room doors were left open and the experimenter stood in the hall where participants could clearly hear him or her deliver verbal instructions for the paper-format IAT. Participants first completed a flower/insect training IAT followed by the critical race attitude paper IAT measures in counterbalanced order. The experimenter then instructed participants to begin working on the computer and closed the individual lab room doors. Participants completed a computer format flower/insect training IAT followed by the race attitude computer IATs in counterbalanced order. Following the first session, participants returned approximately one week later and completed the same measures again. At the end of Session 1 only, participants completed a demographic form that assessed their gender, race, and English fluency. Computer-based IATs. Each of the two race IAT measures consisted of two 60-trial blocks, one in which White was paired with pleasant and Black with unpleasant, and one in which Black was paired with pleasant and White with unpleasant. In a deviation from the standard IAT procedure (Nosek et al., 2006), there were no single-category practice blocks. This has the benefit of making the format of the computer IAT congruent with the format of the paper IAT, and the potential risk of undermining the computer IAT’s psychometric properties. The standard version is examined in Study 2. For analysis purposes, the first 20 trials of each block were considered practice trials and the remaining 40 trials were considered critical. Paper-based IATs. Each paper IAT consisted of two critical blocks. Each block was presented on a single page, with trials alternating between the race and valence dimensions (see Figure 1). The experimenter stood in a hallway outside the experimental rooms where he or she could be heard clearly but could not see the participants’ responses. Reading from a script, the experimenter orally instructed participants to categorize each stimulus item by making a check mark in the appropriate circle to the left or right of the item, beginning in the upper left and working down, then over to the second column. They were told to avoid making mistakes, but if they did make a mistake to keep going. Participants were given 20 seconds per page to make as many categorizations as possible. Prior to each page, the experimenter instructed participants to look at the category labels at the top of the page for three seconds. The experimenter then said, “Ready, set, go” and started a timer set for 20 seconds. The procedure was repeated for each block.
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Photos were senior year high-school photos used with permission from a 2000 high-school yearbook.
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RESULTS Preparation of Data for Analysis Computer IAT data. In accordance with the strategy described by Greenwald et al. (2003), differences between the two IAT blocks were divided by the standard deviation of all trials, separately for the practice and critical trials. Their average yielded a D score. Among the 18 men and 43 women in the final data set, the overall error rate was 5.8%, with slightly more errors recorded in Session 2 (6.1%), than Session 1 (5.4%), F(1, 58) = 3.76, p = .06, d = 0.25.5 As expected, collapsing across both sessions, participants made significantly more errors in the White+unpleasant pairing condition (7.0%) than the White+pleasant pairing condition (4.8%), F(1, 63) = 24.00, p < .001, d = 0.62. Paper IAT data. Although overall error rates were low, participants had a significantly higher error rate in Session 1 (3.4%) than Session 2 (0.7%), F(1, 44) = 4.07, p < .05, d = 0.30. Participants with more than 20% errors in any session (one White male and one Hispanic female) were omitted from further analysis. In addition, we set a criterion that only blocks with at least eight correct responses would be retained for analysis, which resulted in the deletion of one IAT for three participants. Among the remaining participants, collapsing across both sessions, participants made significantly more errors in the White+unpleasant pairing condition (1.5%) than in the White+pleasant pairing condition (0.7%), F(1, 42) = 6.62, p < .05, d = 0.39. IAT attitude scores were computed on correct responses for each participant using the product: square root of difference algorithm described in Study 1.
DEMONSTRATION OF IMPLICIT ATTITUDE Computer IATs with name and picture stimuli showed the same overall pattern of responses and were significantly correlated, r(58) = .54, p < .001 for Session 1 and Session 2, r(52) = .45, p < .001. As predicted, responses were significantly faster under the White+pleasant response pairing than the Black+pleasant pairing, indicating an implicit preference for White people relative to Black people. As shown in Table 1, the effect size for this difference was moderately strong, with Cohen’s d ranging from 0.51 to almost 0.77. The relationship between IATs with name and picture stimuli was weaker for paperformat IATs: r(43) = .28, p = .07 for Session 1 and r(42) = .45, p < .01 for Session 2. Importantly, the pattern of results for the name and picture versions was markedly different. On the paper IAT with name stimuli, participants demonstrated a pro-White attitude, but the effect size was smaller than that observed with the computer IAT and was only significant in Session 1. Unexpectedly, the predicted pro-White attitude was not observed on the paper IAT with picture stimuli. Participants showed no difference in their latency to respond when White was paired with pleasant versus when Black was paired with pleasant. This suggests that the paper format IAT may not be as powerful a measure for detecting effects as the computer format, and the paper format may be more sensitive to the type of stimuli used in the task.
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Effect sizes for all two-group, repeated-measures comparisons are reported as Cohen’s d, which is computed as d = t df . Cohen (1988) provides guidelines of d = .2 as a small effect, d = .5 as a medium effect, and d = .8 as a large effect for behavioral science research.
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Computer IAT
Name Stimuli Session 1 Session 2 Picture Stimuli Session 1 Session 2
IAT D score (SD)
t for difference from zero
.27 (.39) .24 (.33)
5.12 5.45
.000004 .000002
0.68 0.77
.21 (.42) .23 (.32)
3.86 4.85
.0003 .00002
0.51 0.69
IAT score (SD)
t for difference from zero
1.62 (2.52) .68 (2.31)
4.07 1.87
.0002 .07
0.64 0.29
-.28 (3.07) -.19 (2.14)
-0.57 -0.54
.57 .59
0.09 0.09
p
Cohen’s d
Paper IAT
Name Stimuli Session 1 Session 2 Picture Stimuli Session 1 Session 2
p
Cohen’s d
Note. Computerized IAT scores (D) are calculated according to the recommendations of Greenwald et al. (2003). Paper format IAT scores are computed using the Product: square root of difference algorithm. Cohen’s d for one-sample t-tests were computed as the absolute value of the sample mean divided by the sample standard deviation.
Test-Retest Reliability Reliability between sessions separated by one week was similar to that observed in previous, computer-based IAT research (e.g., Nosek et al., 2006). For the computer IAT, attitude scores for Session 1 and Session 2 were correlated, r(49) = .53, p < .001 for names and r(49) = .46, p < .001 for pictures. Test-retest reliability for the paper IATs was in line with that of the computerized task: r(41) = .62, p < .001 for names and r(40) = .49, p < .001 for pictures. These correlations, although small by standards for explicit measures, are consistent with reliability coefficients from administrations of the computerized IAT: In a summary of 23 data collections that have included IAT measurements on more than one occasion, mean and median test-retest reliabilities were .50 (Lane et al., 2007).
Relationship between Paper and Computer IAT For the session in which the IAT effect was strongest (Session 1), the correlation between the paper and computer IATs with name stimuli was also moderately strong, r(30) = .43, p < .05. However, in Session 2, in which the IAT effect with names was weaker, the correlation between the computer and paper versions was also weak, r(26) = .19, ns. For the IATs with
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picture stimuli, the paper-computer correlations were r(30) = .27, ns in Session 1 and r(26) = .48, p < .05 in Session 2.
Comparing Scoring Procedures We examined the efficacy of each of the proposed paper IAT scoring strategies. Results from actual data corroborated the analyses of simulated data sets, offering support for use of the product: square root of difference algorithm for analyzing paper IAT data. We assumed that a better scoring approach would maximize the relationship between computerized and paper-pencil measures of the same construct. For IATs with name stimuli, computer-paper correlations using the product: square root of difference algorithm were approximately equal or higher in both sessions than those using any of the six alternate algorithms (r = .43 versus .31 to .40 for other algorithms in Session 1 and r = .19 versus .11 to .20 for Session 2). For IATs with picture stimuli, computer-paper correlations in Session 1 were equal or higher using the product: square root of difference algorithm compared with all other algorithms (r = .27 versus .15 to .27 in Session 1). In Session 2, the product: square root of difference algorithm produced computer-paper correlations that were stronger than three of the other algorithms, r = .48 versus .43 to .47; correlations were higher using the simple difference (r = .50), simple product (r = .52) and product: squared ratio (r = .57) algorithms. However, of the candidate scoring procedures, no alternative was consistently superior to the product: square root of difference.
Effect of Potential Artifacts on Paper IAT Scores Order of IAT block presentation. The order in which participants complete the two IAT blocks (i.e., whether participants complete flower+good or flower+bad first) is one artifact of the procedure that has consistently been shown to influence the overall IAT effect with computer-based measures (Mierke and Klauer, 2003; Nosek, Greenwald, and Banaji, 2005). Contrary to most research with computer IATs, the typical IAT order effect was not observed with paper IAT measures in the present study. Order of presentation of the IAT block was not a significant factor for the paper IAT with name stimuli in Session 1, F(1, 38) = 0.44, ns, d = 0.11, or Session 2, F(1, 39) = 0.48, ns, d = 0.11. There was a significant order effect for the paper IAT with picture stimuli in Session 1, F(1, 38) = 15.78, p < .001, d = 0.64. Surprisingly, this strong order effect was in the opposite direction of what is commonly observed, with participants who completed the Black+pleasant pairing first demonstrating a strong pro-White attitude (M = 1.37, SD = 2.97) and participants who completed the White+pleasant pairing first demonstrating a strong pro-Black attitude (M = -1.92, SD = 2.22). This unexpected reverse order effect did not appear in Session 2, where there was no significant difference between the two order conditions, F(1, 39) = 0.00, ns.6 It is possible that 6
These artifacts were also tested for the computer IAT. Typical order effects were observed on the computer IAT, with significantly larger IAT effects observed when the White+pleasant block was completed first compared with when the Black+pleasant block was completed first, across both IAT measures and both sessions (all ps < .05). Correlations between average response latency and magnitude of IAT effect were non-significant. Similar results were observed in Study 2b.
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categorization of the faces was difficult initially, but became easier with repeated administrations. This may account for the lack of consistent effects with the picture version. Overall response speed. Original scoring procedures of the computerized version of the IAT were susceptible to differences in overall response speed: slower participants tended to exhibit larger overall IAT effects. This artifact of average response time was one of the motivations for developing newer scoring procedures for the computerized IAT (Greenwald et al., 2003). We examined whether overall differences in response speed would also influence the magnitude of IAT effects on the paper-format version. For each IAT in the study, the average number of items completed across the two blocks of each paper-format IAT was calculated to provide an index of general speed of response. This value was then correlated with participants’ calculated IAT scores. For the IATs with name stimuli, the total number of items completed was uncorrelated with the strength of the IAT effect in Session 1 (r = -.03, ns) and Session 2 (r = .08, ns). Similar results were observed for IATs with picture stimuli, with low and nonsignificant correlations in Session 1 (r =.08, ns) as well as Session 2 (r = .16, ns). The magnitude of the correlation between total number of items completed and IAT score was higher in most instances when alternate algorithms were used to compute IAT scores (rs ranging from .01 to .31). No single alternate algorithm consistently outperformed the product: square root of difference algorithm in minimizing the strength of this relationship.
SUMMARY Results of Study 2a provide support for the use of a paper IAT with all verbal stimuli; however, the paper IAT with picture stimuli for the race dimension was not effective. One concern is that the pictures that were used for the race stimuli, which were color photos of attractive young people with a positive expression, may not have been maximally effective for assessing racial attitudes, at least on the paper IAT. Although we cannot be certain that this is the case, it is possible that participants did not even need to process the pictures as human faces in order to categorize them as Black or White people – these categorizations could have been made entirely on the basis of ink color. In Study 2b, we replaced the color photos with black and white photos of people with neutral expressions, using the same stimulus items used in previous IAT research (e.g., Cunningham, Preacher, and Banaji, 2001; Nosek, Banaji, and Greenwald, 2002). As these pictures use similar ink colors for both categories (light and dark shades of gray), participants must process the faces more thoroughly to identify features that distinguish White and Black faces. In addition, practice blocks were added to the computer IATs to parallel the more typical design for computer IATs (Greenwald et al., 1998).
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STUDY 2B Method Participants Twenty-eight male and 57 female undergraduates (aged 18-26, M = 19.9, SD = 1.9; 92% White) completed Session 1 in exchange for partial course credit; 26 men and 54 women returned for Session 2. Data from two men who reported not being fluent in English were omitted from further analysis.
Materials IAT measures used the same word and name stimuli as Study 2a. Race stimuli for the picture IATs were neutral expression, closely cropped black and white photographs of adult African American and European American faces (three men and three women of each race).7
PROCEDURE Experiment 2b followed the same overall procedure as Experiment 2a. Experimenters for the study were White undergraduate students. Participants were placed in individual lab rooms, with a maximum of three participants in a session. Experimenters delivered verbal instructions for the paper-format IAT from the hall outside the lab rooms. Participants completed the paper-format IAT measures prior to the computer IAT measures. Both the paper- and computer-format IAT sets began with a flower/insect training IAT, followed by the critical race attitude IATs in counterbalanced order. Participants returned approximately one week after Session 1 and completed the same measures again. Demographic information (gender, race, and English fluency) was assessed following Session 1 only. Computer-based IATs. Each of the two critical IAT measures consisted of five blocks; only data from blocks 3 and 5 are used in the analysis. The first two blocks were 20-trial single-category practice blocks of Black-White and pleasant-unpleasant judgments. The third block was a 42-trial block with judgments from both categories using the key mappings previously practiced (e.g., Black+pleasant and White+unpleasant). A 20-trial block of pleasant and unpleasant judgments followed, with key mappings reversed relative to the preceding blocks. In the final 42-trial block, participants categorized stimuli from the two dimensions using response key mappings reversed from the previous critical block (e.g., Black+unpleasant and White+pleasant). In blocks 3 and 5, for analysis purposes, the first 14 trials are considered practice trials and the subsequent 28 trials are considered critical. Incorrect responses were indicated with a red X and participants were required to correct their response before advancing. Within the critical blocks, trials alternated between the pleasantunpleasant and Black-White dimensions.
7
The race photos used are identical to those employed in the race attitude task on the IAT website, available at https://implicit.harvard.edu/.
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Paper-based IATs. The paper IATs with name stimuli were identical to those used in Study 2a. The paper IATs with picture stimuli were modified to include the black and white photos described above.
RESULTS Preparation of Data for Analysis Computer IAT data. Data for the computer IATs were prepared following the same conventions used in Study 2a. The overall error rate was 5.4%. Replicating Study 2a, participants made significantly more errors in Session 2 (6.0%), than Session 1 (5.0%), F(1,78) = 8.30, p < .01, d = 0.33. Also replicating Study 2a, participants made significantly more errors in the White+unpleasant pairing condition (7.0%) than the White+pleasant pairing condition (4.3%), F(1, 84) = 62.12, p < .001, d = 0.86. Paper IAT data. Data for the paper IAT were prepared in the same way as Study 2a. Replicating Study 2a, participants had a significantly higher error rate in Session 1 (6.0 %) than Session 2 (1.7%), F(1, 78) = 14.71, p < .001, d = 0.43, partly due to several participants with unusually high error rates in Session 1 not returning for Session 2. Data from sessions in which participants made more than 20% errors were omitted from further analysis (resulting in deletion, from both sessions, of data provided by one White woman and Session 1 data only for three White men and four White women). Critical blocks in which fewer than 8 correct responses were made (8.1% of all critical blocks) were omitted from further analysis. Replicating Study 2a, participants remaining in the sample made significantly more errors across both sessions in the White+unpleasant pairing condition (3.2%) than in the White+pleasant pairing condition (2.3%), F(1, 70) = 5.55, p < .05, d = 0.28. Demonstration of Implicit Attitude Results from Study 2a were replicated for the computer IATs with name and picture stimuli, with participants indicating strong pro-White attitudes. As shown in Table 2, these effects were very strong, with Cohen’s d values near 1.0 for the picture IAT and in excess of 1.0 for the name IAT. The name and picture versions of the IAT were moderately correlated, r(80) = .43, p < .001 in Session 1 and r(80) = .26, p < .05 in Session 2. Pro-White implicit attitudes were also demonstrated on the paper IATs with both name and picture stimuli. As in Study 2a, the effect size was smaller with the paper IAT than with the computer IAT. However, in Study 2b, participants demonstrated significant pro-White implicit attitudes, with Cohen’s d ranging from 0.26 to 0.62. Correspondence between name and picture IATs was similar to the computerized task: r(68) = .38, p < .01 in Session 1 and r(74) = .36, p < .01 in Session 2. Test-Retest Reliability The computer IAT showed significant test-retest reliability, r(78) = .45, p < .001, for the name IAT, and r(78) = .41, p < .001 for the picture IAT. Reliability was similar for the paper IAT with name stimuli, r(64) = .49, p < .001. The paper IAT with picture stimuli, which showed the smallest overall IAT effect, was not significantly correlated between Sessions 1 and 2, r(64) = .21, p = .10.
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Table 2. Study 2b: Computer and Paper Format IAT Scores Computer IAT
Name Stimuli Session 1 Session 2 Picture Stimuli Session 1 Session 2
IAT D score (SD)
t for difference from zero
.46 (.38) .32 (.31)
11.07 9.00
6.09 x 10-18 1.17 x 10-13
1.22 1.02
.36 (.36) .29 (.32)
9.14 7.93
3.84 x 10-14 1.39 x 10-11
1.00 0.90
IAT score (SD)
t for difference from zero
1.55 (2.48) 1.38 (2.24)
5.18 5.23
.000002 .000002
0.62 0.62
.79 (2.48) .50 (1.92)
2.63 2.26
.01 .03
0.32 0.26
p
Cohen’s d
Paper IAT
Name Stimuli Session 1 Session 2 Picture Stimuli Session 1 Session 2
p
Cohen’s d
Note. Computerized IAT scores (D) were calculated according to the recommendations of Greenwald et al. (2003). Paper format IAT scores were computed using the Product: square root of difference algorithm. Cohen’s d for one-sample t-tests were computed as the absolute value of the sample mean divided by the sample standard deviation.
Relationship between Paper and Computer IAT Name-based paper and computer IATs were significantly correlated: r(70) = .36, p = .01 for Session 1 and r(73) = .40, p = .001 for Session 2. In contrast, with picture stimuli, papercomputer correlations were considerably weaker: r(68) = .17, p = .17 for Session 1 and r(76) = .23, p < .05 for Session 2. Comparing Scoring Procedures As in the prior study, results supported use of the product: square root of difference algorithm, which maximized the relationship between computerized and paper-based versions of the task. For IATs with name stimuli, correlations between computer and paper IATs were higher when the product: square root of difference algorithm was used compared with any of the six alternate algorithms (r = .36 versus .28 to .35 for other algorithms in Session 1 and r = .40 versus .34 to .39 for Session 2). For IATs with picture stimuli, all correlations were stronger with the product: square root of difference algorithm compared with other algorithms in Session 1 (r = .17 versus .12 to .14 for other algorithms). In Session 2, the product: square root of difference algorithm produced an equal or stronger paper-computer correlation (r = .23) than four of the alternate algorithms (rs from .20 to .23). The only exceptions were modestly stronger correlations in Session 2 using the max-min ratio conversion (r = .26) and the latency conversion algorithm (r = .30). As in Study 2a, no alternative was consistently superior to the product: square root of difference.
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The Paper-Format and Computer Versions of the IAT Assess a Single Construct Due to the relatively high degree of noise in response latency data, zero-order correlations with response-latency measures such as the IAT may be attenuated due to the low reliability of the measures. Cunningham et al. (2001) demonstrated that Structural Equation Modeling (SEM) can be used to separate variance due to latent attitude constructs from variance due to error inherent in response latency measurements, resulting in substantially improved correlations among measures. Analyzing IATs with name and picture stimuli separately, we fit latent variable models in which the paper IAT measures for Session 1 and 2 loaded onto a single latent factor that was correlated with a second latent factor assessed by computer IAT measures for Session 1 and 2. We then compared the two-factor models to models in which all IAT measures loaded onto a single latent factor. Model fit was assessed following guidelines proposed by Hu and Bentler (1999), who suggest that adequate model fit is indicated by standardized Root Mean Square Residual (sRMR) values less than .08, NonNormed Fit Index (NNFI) and Comparative Fit Index (CFI) greater than .95, and Root Mean Square Error of Approximation (RMSEA) less than .06. Name IATs. A model fitting paper and computer IAT scores onto separate, correlated latent factors was a moderately good fit to the data, χ2 (1) = 1.39, p = .24, sRMR = .026, NNFI = .943, CFI = .991, RMSEA = .08. The correlation between the latent factors was r = .78, indicating a very strong relationship between the paper and computer versions of the IAT. To determine whether scores on the paper IAT and computer IAT represent a single underlying factor, a second model was fit to the data in which all four measures (paper and computer IAT scores in Session 1 and 2) loaded onto a single latent factor. A nested chisquare test demonstrated that the fit of this model was not significantly different from the two-factor model described above, Δχ2 (1) = 1.95, ns, suggesting that the simpler and more parsimonious representation that the paper and computer measures assess the same construct can be retained. Picture IATs. Results for IATs with picture stimuli were similar to those with name stimuli. A model fitting paper and computer IAT scores onto separate, correlated latent factors was a very good fit to the data, χ2 (1) = .345, p = .56, sRMR = .019, NNFI = 1.000, CFI = 1.000, RMSEA = .000. The correlation between the latent factors was r = .51, indicating that the paper and computer versions of the IAT were related. A second model with all four measures loading onto a single latent factor did not provide significantly different fit from the two-factor model described above, Δχ2 (1) = 1.53, ns, consistent with the claim that the paper and computer IATs are assessing the same underlying construct. Effect of Potential Artifacts on Paper IAT Scores Order of IAT block presentation. Block order effects for the paper IAT were similar to those observed in Study 2a: implicit attitudes as measured by the IAT did not seem to be affected by the order of presentation of IAT blocks for name stimuli in Session 1, F(1, 71) = 1.63, ns, d = 0.15, or Session 2, F(1, 73) = 0.73, ns, d = 0.10. A significant order effect was observed for the paper IAT with picture stimuli in Session 1, F(1, 69) = 10.60, p < .01, d = 0.39. Surprisingly, this order effect was in the same reverse direction as that observed in Study 2a, with participants who completed the Black+pleasant pairing first demonstrating a larger IAT effect (M = 1.63, SD = 2.58) than participants who completed the White+pleasant
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pairing first (M = -.18, SD = 2.01). This unexpected reverse order effect did not appear in Session 2, where there was no significant difference between the two order conditions, F(1, 76) = 1.42, ns, d = 0.14. Overall response speed. Replicating Study 2a, the average number of items completed across the two blocks of each paper-format IAT was uncorrelated with participants’ calculated IAT scores. For the IATs with picture stimuli, the total number of items completed was uncorrelated with the strength of the IAT effect in Session 1 (r = .02) and Session 2 (r = -.02). IATs with name stimuli showed a similar pattern of weak correlations in both Session 1 (r = 15) and Session 2 (r = .17). Also replicating Study 2a, these correlations were generally higher when alternate algorithms were used to compute IAT scores (rs ranging from .001 to .22), and no single alternate algorithm produced consistently lower correlations compared with the product: square root of difference algorithm. To supplement the present finding that overall response speed did not produce a meaningful artifact on the paper-format IAT, we also examined the effect of overall response speed in another available data set (Lane et al., 2005). These results supported the conclusion that there was no systematic relationship between participants’ general response speed and their IAT scores. In this study, participants completed six paper-format IATs. Three measures of overall response speed were calculated: the average number of items completed in the two blocks of each IAT, the average number of items completed on all 12 blocks of the IATs in the study, and the number of items completed on the two blocks of a single, non-social (flower relative to insect) IAT.8 As seen in Table 3, IAT effects, as calculated by the suggested scoring procedure, were unrelated to the average number of items completed in the two blocks of the IAT (average r = .03) and the average number of items completed on all IATs in the study (average r = .02). Additionally, five social IATs (measures of university and school dormitory attitude and identity, and self-esteem) were unrelated to the number of items completed on the individual blocks of an unrelated, non-social (flower) IAT (average r = .01). Although these findings suggest that overall response speed does not produce a large artifact in paper-format IAT effects, it is worth noting that all of the participants were drawn from student populations and were likely familiar and comfortable with completing rapid or timed tasks. It is possible that an overall effect of speed may emerge among different populations that have notably slower overall response speeds (e.g., Hummert et al., 2002).
SUMMARY Study 2b largely replicated results of Study 2a, supporting use of a paper-format IAT with all verbal stimuli. This task was positively related to a computerized measure of the same task, and showed comparable patterns of attitudes and test-retest reliability to computerized IATs. Although the paper IAT with black and white, neutral expression pictures
8
These measures were highly correlated with one another, indicating that participants who were faster overall did tend to complete more items across all 12 blocks of the six IATs. For example, the average correlation between the mean number of items completed on the 12 IAT blocks and the mean number completed on each IAT was r = .80.
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Table 3. Effect of Overall Response Latency on Paper-Format IAT Effects: Correlations Between Four Measures of General Response Speed and Paper-Format IAT Effects (Reanalysis of Lane et al. [2005])
University Attitude University Identity Self Esteem Dorm Attitude Dorm Identity Flower Attitude (1) Average
Average on Relevant IAT -0.08 0.00 -0.03 -0.05 -0.01 0.34** 0.03
Average on All IATs -0.02 0.05 0.06 -0.12* -0.01 0.16* 0.02
Flower+ Good 0.02 -0.07 0.05 -0.05 -0.05 (1)
-0.02
Flower+Bad 0.00 0.06 0.09 0.08 0.00 (1)
0.05
Note. Participants completed six paper-format IATs, listed in the left-most column. IAT effects were calculated using the product: square root of difference scoring approach. Average on relevant IAT = Average number of items completed on that particular IAT. Average on All IATs = Average number of items completed on all 12 blocks of the six IATs. Flower+Good = Total number of items completed on the flower+good pairing of the flower/insect paper-format IAT. Flower+Bad = Total number of items completed on the flower+bad pairing of the flower/insect paper-format IAT. Ns ranged from 247 to 289. * p < .05. ** p < .0001. (1) The flower IAT was designed to familiarize participants with the task in a large group. As such, it was the only task not presented in a counterbalanced order: all participants completed the flower+good block prior to the flower+bad block of the IAT. Flower attitude effects were a direct function of number of items completed on each IAT block and should be highly correlated with the IAT effects.
showed more similar main effects to the computerized task than the version used in Study 2a, test-retest reliability and correspondence with the computerized IAT were still disappointingly small. The weak zero-order correlations between paper and computer IATs may be due, in part, to the substantial error variance associated with those scores. Error variance is a particular concern with any response latency measure, and the paper IAT is no exception. SEM analyses, which separate measurement error from latent construct variance, provided support that the computer and paper IATs are strongly correlated and they may be assessing the same underlying construct. At the same time, the data suggest that the paper-format IAT is not quite as effective at eliciting strong mean effects as the computer-format IAT. In addition, both verbal and picture versions demonstrated that the paper IAT is largely unaffected by common IAT artifacts such as task order and overall response speed.
CONCLUSION Study 1 compared several potential scoring procedures and demonstrated that the product: square root of difference approach, calculated as (X/Y)*Square Root of (X – Y), where X is the greater of A or B, and Y is the smaller of A or B, maximized the relationship
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between functionally related data sets. Data from human participants in Studies 2a and 2b also showed that this scoring approach was consistently superior at maximizing the relationship between computerized and paper-format versions of the same task. For the IAT with names, correlations between the computer and paper versions were equal to or higher using the product: square root of difference method compared with any of the six other proposed algorithms. For the IAT with pictures, computer-paper correlations were higher with the product: square root of difference algorithm in most instances, and it was the only algorithm that consistently outperformed the remaining algorithms. Studies 2a and 2b demonstrated that a paper-format IAT using names for the race categories exhibits similar psychometric properties to a traditional computer IAT with the same stimuli. Test-retest reliabilities for the paper format IAT with names were comparable to computer IAT reliabilities and the paper IAT with names was significantly correlated with the computer IAT in three of four replications. However, results with two versions of a paperformat IAT using pictures for the race dimension were equivocal. This version of the task did not show the expected strong pro-White implicit attitude (weak in Study 2b and absent in Study 2a), exhibited poor test-retest reliability and only weak correspondence with computerized versions of the same task. Although the paper IATs with picture stimuli showed weak or no effects, computer IATs with identical pictures showed robust pro-White/anti-Black bias. Thus, it appears that pictures are effective stimulus items for a computerized IAT but not for a paper-format IAT, at least in this particular context. Although speculative, one explanation for this may be the simultaneous visibility of all stimuli on a paper-format IAT. On the computer IAT, one stimulus item is shown at a time and a new item appears only after a participant has recorded a response. On the paper IAT, all of the stimuli are shown on the page simultaneously. Although participants are instructed to categorize each item individually, the presence of other stimuli in the visual field during categorization is unavoidable. This may not be a concern with word stimuli because participants most likely attend to each item individually since each word needs to be read and processed before it can be categorized. However, with pictures, participants are able to process multiple pictures in the visual field simultaneously; thus judgment of the target picture may be influenced by nearby pictures that are not the main focus of judgment (Mausfeld, 2003). This may have been a particular problem in Study 2a because the pictures were printed in color, thus emphasizing visual differences between Black and White faces. The current studies support the use of paper-format IATs with verbal stimuli, analyzed using the product: square root of difference algorithm. Our results replicated those of Lowery et al. (2001), who demonstrated anti-Black implicit attitudes using a paper IAT with name stimuli. They also parallel those of Teachman et al. (2003), who demonstrated anti-fat bias using a paper IAT with word stimuli, and Lane et al. (2005), who used paper IATs to measure college identity, attitude, and self-esteem using verbal stimuli for all dimensions. Paper-format IATs allow researchers to assess implicit attitudes under circumstances where traditional computer IAT data collection may be impractical or even impossible. We have administered it at beaches, where sand, sun and water pose risks to computers, and in large groups. Under circumstances such as these, where computerized data collection is not feasible, paper format IATs may provide a satisfactory supplement to traditional IATs. However, because the accuracy of timing is substantially less sensitive with paper IATs, and because the effects tend to be smaller than with computer data collection, paper format IATs
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are unlikely to serve as a substitute for computer IATs in most situations. Paper IATs also do not allow for trial by trial timing, thus it is not possible to compute split-half or alpha reliability. In addition, the computer IAT has been used extensively; numerous studies have explored its psychometric properties; and much more is known about its potential artifacts. Thus, researchers are advised to use computer IAT data collection for laboratory-based research. Although computer-based data collection is preferable, there are many circumstances in which it is not practical or even possible. When there is evidence that findings from a particular paper-format IAT converge with those of a computer-based counterpart, paper format IATs should prove useful.
AUTHORS’ NOTE This research was supported by R-01 MH68447 from the National Institutes of Health and REC-0634041 from the National Science Foundation to the last author. The authors thank Jonathan Dahl and Rebekah Mitchell for assistance with data collection.
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Hummert, M.L., Garstka, T.A., O'Brien, L.T., Greenwald, A.G., and Mellott, D.S. (2002). Using the Implicit Association Test to measure age differences in implicit social cognitions. Psychology and Aging, 17, 482-495. Lane, K.A., Banaji, M.R., Nosek, B.A., and Greenwald, A.G. (2007). Understanding and using the Implicit Association Test: IV. What we know (so far) about the method. In B. Wittenbrink and N. Schwarz (Eds.), Implicit measures of attitudes (pp. 59-102). New York: Guilford Press. Lane, K.A., Mitchell, J.P., and Banaji, M.R. (2005). Me and my group: Cultural status can disrupt cognitive consistency. Social Cognition, 23, 353-386. Lemm, K.M. (2000). Personal and social motivation to respond without prejudice: Implications for implicit and explicit attitude and behavior. Unpublished doctoral dissertation, Yale University. Lowery, B.S., Hardin, C.D., and Sinclair, S. (2001). Social influence effects on automatic racial prejudice. Journal of Personality and Social Psychology, 81, 842-855. Mausfeld, R. (2003). Conjoint representations and the mental capacity for multiple simultaneous perspectives. In H. Hecht, R. Schwartz, and M. Atherton (Eds.), Looking into pictures: An interdisciplinary approach to pictorial science (pp. 17-60). Cambridge, MA: MIT Press. Mierke, J., and Klauer, K.C. (2003). Method-specific variance in the Implicit Association Test. Journal of Personality and Social Psychology, 85, 1180-1192. Nosek, B.A., Banaji, M.R., and Greenwald, A.G. (2002). Harvesting implicit group attitudes and beliefs from a demonstration website. Group Dynamics, 6, 101-115. Nosek, B.A., Greenwald, A.G., and Banaji, M.R. (2005). Understanding and using the Implicit Association Test: II. Method variables and construct validity. Personality and Social Psychology Bulletin, 31, 166–180. Nosek, B.A., Greenwald, A.G., and Banaji, M.R. (2007). The Implicit Association Test at age 7: A methodological and conceptual review. In J.A. Bargh (Ed.), Social psychology and the unconscious: The automaticity of higher mental processes (pp. 265-292). Hove, UK: Psychology Press. Nosek, B.A., Smyth, F.L., Hansen, J.J., Devos, T., Lindner, N.M., Ranganath, K.A., Smith, C. T., Olson, K.R., Chugh, D., Greenwald, A.G., and Banaji, M.R. (2007). Pervasiveness and correlates of implicit attitudes and stereotypes. European Review of Social Psychology, 18, 36-88. Sinclair, S. Lowery, B.S., Hardin, C.D., and Colangelo, A. (2005). Social tuning of automatic racial attitudes: The role of affiliative motivation. Journal of Personality and Social Psychology, 89, 583-592. Sriram, N., Greenwald, A.G., and Nosek, B.A. (2007). Correlational biases in mean response latency differences. Unpublished manuscript. Teachman, B., and Brownell, K. (2001). Implicit associations toward obese people among treatment specialists: Is anyone immune? International Journal of Obesity, 25, 15251531. Teachman, B.A., Gapinski, K.D., Brownell, K.D., Rawlins, M., and Jeyaram, S. (2003). Demonstrations of implicit anti-fat bias: The impact of providing causal information and evoking empathy. Health Psychology, 22, 68-78.
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Vargas, P.T., Sekaquaptewa, D., and von Hippel, W. (2007). Armed only with paper and pencil: “Low-tech” measures of implicit attitudes. In B. Wittenbrink and N. Schwarz (Eds.), Implicit measures of attitudes (pp. 103-124). New York: Guilford Press.
In: The Psychology of Modern Prejudice Editors: Melanie A. Morrison and Todd G. Morrison
ISBN 978-1-60456-788-5 © 2008 Nova Science Publishers, Inc.
Chapter 7
FEATURE-BASED GENDER STEREOTYPING: BEYOND CATEGORIZATION AND CONTROL? Sabine Sczesny1 and Sei Jin Ko University of Bern Northwestern University
ABSTRACT This chapter discusses a body of research showing that gender stereotyping not only results from categorization by gender but also directly and independently from features or cues that vary more subtly within each gender category, such as hair length and shoulder size. Moreover, the findings indicate that feature-based, as compared with categorybased, gender stereotyping may be due to automatic information processing. Research examining the relationship between the two bases of stereotyping demonstrates the modern-day societal implications of stereotyping—social norms that encourage people to avoid the expression of category-based stereotyping may ironically end up increasing feature-based stereotyping. Finally, implications of the presented research in relation to stereotype reduction are discussed.
INTRODUCTION Categorization by gender evokes mental associations or expectations about women and men and, as research has demonstrated consistently, people hold remarkably different beliefs about women and men. In these group stereotypes, men are believed to be more agentic (e.g., competitive and individualistic) whereas women are assumed to be more expressive and communal (e.g., kind and nurturing – see Diekman and Eagly, 2000). People’s highly elaborated set of associations concerning men and women appears to be cross-culturally valid (Best and Thomas, 2003; Williams and Best, 1990). Moreover, gender-stereotypical contents 1
Correspondence to Dr. Sabine Sczesny, Institut fuer Psychologie, Universitaet Bern, Muesmattstr. 45, 3000 Bern 9, Schweiz;
[email protected].
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are automatically activated and serve as baseline judgments of men and women (e.g., Banaji and Hardin, 1996; Karylowski et al., 2001). This information processing, namely categorybased gender stereotyping, does not require extensive reasoning or thinking (Devine, 1989), and typically results in different evaluations of women and men (e.g., Bem, 1974; Broverman, Broverman, Clarkson, Rosenkrantz, and Vogel, 1970; Rosenkrantz, Vogel, Bee, Broverman, and Broverman, 1968; Spence, Helmreich, and Stapp, 1974). Nevertheless, in Western societies, a tremendous reduction in the overt expression of sexist attitudes and gender stereotyping has been observed (e.g., Diekman, Eagly, Mladinic, and Ferreira, 2005; Eagly and Sczesny, in press; Sczesny, Bosak, Diekman, and Twenge, 2007). Apparently, strong social norms have developed that often prevent people from openly expressing stereotypes and prejudice based on social categories (Klonis, Plant, and Devine, 2005).2 Besides the emergence of egalitarian social norms, other specific judgmental conditions also might contribute to a reduction of category-based gender stereotyping (see Figure 1). For example, people must be motivated to follow social norms, and they need sufficient cognitive capacity and time. When such conditions are fulfilled, stereotyping in the sense of emphasizing differences between gender groups is assumed to appear less likely due to controlled information processing (e.g., Devine, 1989). Moreover, if individuals overestimate the influence of a potential bias, even contrast or counter-stereotypic effects might occur because individuals overcorrect (Kunda and Spencer, 2003). A person’s categorization by gender is often considered to trigger gender stereotyping. Many influential models of the link between categorization and stereotyping suggest that category effects are so strong they leave little room for the influence of within-category variations in stereotyping (e.g., Bodenhausen and Macrae, 1998; Brewer, 1996; Fiske and Neuberg, 1990). In the following, we will present evidence for another form of gender stereotyping beyond categorization; namely, feature-based gender stereotyping. Although physical features such as long hair and broad shoulders can and definitely do trigger gendercategory membership, none of the “more masculine” or “more feminine” physical features is exclusively associated with one gender only. In fact, these features are associated with both genders so that it also is common to talk about a feminine looking man or to describe a woman's appearance as masculine (e.g., Zebrowitz, 1997). Hence, gender stereotyping may not only result from categorization by gender but also directly and independently from variation in features within each gender. In this chapter, we will first present empirical evidence for feature-based gender stereotyping from our own experimental work (which is based on student samples from the USA, the Netherlands, and Germany). We demonstrate that physical features of individuals that vary within each gender influence the way they are perceived and judged by others directly and independently of categorization by gender. Subsequently, we will provide evidence for a lack of control in feature-based gender stereotyping in contrast to categorybased gender stereotyping. Our analysis shows that both forms of gender stereotyping are independent and that feature-based gender stereotyping may be due to automatic information processing. Our findings also indicate that social norms that encourage people to avoid the expression of category-based stereotyping ironically end up increasing feature-based within2
Although research has indicated a reduction in overt expressions of sexist attitudes and gender stereotyping as mentioned above, implicit measurement of stereotypes and prejudice suggests there are still gender biases in the perception and evaluation of women and men (Dunning and Sherman, 1997; Glick and Fiske, 1996; Karylowski et al., 2001).
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category stereotyping. Finally, we will conclude the present chapter by discussing implications of our research for the reduction of stereotyping.
Empirical Evidence for Feature-Based Gender Stereotyping In person perception, there are at least three different sources of information used to sense variation in within-category features that might result in gender stereotyping; namely visual, vocal, and olfactory information.
VISUAL CUES Visual cues that allow people to readily identify a person’s gender include height, body shape, hair length, size and form of eyes, nose and chin. For example, more feminine features are a small nose and chin and large, round eyes whereas more masculine ones are a large nose, wide chin and small eyes. Such features, which are associated with masculinity and femininity, have been proven to influence the impression a person evokes in others (e.g., Berry and McArthur, 1985; Deaux and Lewis, 1983, 1984). For example, male business executives and career women were visualized with short/medium length hair and a tall stature (Green and Ashmore, 1998), indicating that leaders were imagined as rather more masculine. These sorts of leadership roles are usually associated with men and are believed to require agentic characteristics such as being assertive, ambitious, dominant, and prone to act as a leader (e.g., Deal and Stevenson, 1998; Schein, 2001; Sczesny, 2005). Following the lack-offit model by Heilman (1983) and the more recent role congruity theory by Eagly and Karau (2002), women’s unfavorable evaluation by others with respect to leadership may stem from an incongruity between the “required” agentic traits for leadership positions and the genderstereotypical belief that women lack these traits. Building on this research, Sczesny and colleagues (Sczesny, Dollmann, and Kühnen, under review; Sczesny, Spreemann, and Stahlberg, 2006) assumed that gender-related visual cues may prime gender-stereotypical associations and, thus, result in gender-stereotypical evaluations of leadership competence beyond categorization. In a series of studies, we systematically varied both targets’ gender and their within-gender visual features in photographs. Male and female participants evaluated targets from one of four groups varying in terms of their gender and their visual appearance (e.g., long versus short hair, large versus small nose, fine versus strong facial features): a feminine-looking man, a masculine-looking man, a feminine-looking woman, and a masculine-looking woman. The person on the respective photograph was named either Mr. Keller or Ms. Keller, in order to avoid any ambiguity. In a pre-test, the used photographs of the three masculine looking men (women) had been evaluated as significantly more masculine than the three feminine looking men (women). The evaluation of leadership competence was measured either directly on explicit trait rating scales or indirectly via an implicit recognition test (i.e., false recognition of leadership characteristics). In the direct measurement, participants were asked to evaluate the target on leadership characteristics (e.g., dominance, being able to make decisions, and possessing initiative) using rating scales. In the indirect measurement, participants were asked
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to memorize as many details as possible. Later on they had to decide whether certain characteristics had or had not been part of the materials. They also had to indicate how certain they felt in their judgment concerning the presence of the respective leadership characteristics. None of these relevant leadership characteristics (the same as in the trait ratings) had been included in the text. False recognition of a proposed leadership characteristic that had not been part of the original materials was expected more likely to occur when the target was male or had a more masculine appearance. In all experiments, participants attributed higher degrees of leadership competence to more masculine looking people than to more feminine looking ones (i.e., assimilation effects towards stereotypes were observed). This influence was independent of the target’s gender and the way in which leadership competence was assessed. In contrast, the influence of targets’ gender was moderated by the way in which leadership competence was measured. Participants attributed higher degrees of leadership competence to male targets than to female targets (assimilation effects) only when leadership competence was measured indirectly via a recognition test. If, however, explicit ratings were used, participants ascribed higher degrees of leadership competence to female targets than to male targets. Such contrast effects may stem, for example, from the awareness of political correctness norms (see the “women-arewonderful effect”: Eagly and Mladinic, 1994) or from a lower standard for women regarding leadership competence than for men (e.g., Biernat and Fuegen, 2001). To replicate and extend these findings, we conducted another experiment in which participants read two job advertisements varying in leadership requirements: one requiring task-oriented/agentic competence and the other person-oriented/communal competence (Sczesny et al., under review, Experiment 2). For example, the person-oriented position required a great sense of responsibility, the ability to work in teams, tolerance and fairness whereas the task-oriented position demanded a great sense of determination, a good sense of judgment, self-discipline and resilience. Participants then evaluated the suitability of the target (who, again, was either male or female and either had a masculine or feminine appearance) for both jobs based on their application papers. Participants then made a forced decision assigning the target to one of the two positions. The results indicated that masculinelooking persons were perceived as more competent than feminine-looking ones, independently of their gender. Furthermore, a better fit between masculine appearance and the task-oriented position as well as between feminine appearance and the person-oriented position was found. Female and male targets were not evaluated differently regarding their fit for the two different types of leadership positions. Neither attractiveness nor likeability of the targets accounted for the present findings.
VOCAL CUES The human voice is our predominant form of communication and the sound of someone’s voice may be one of the first salient cues that we encounter when meeting another person. Our fundamental need to make sense of the world quickly and efficiently (Fiske, 2004) dictates that such salient cues will form the basis for making stereotypic inferences. The inherent biological differences between men and women (Fitch and Giedd, 1999) means that men, on average, have more masculine voices than women, and hence a speaker’s gender can
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be easily determined on the basis of voice (Coleman, 1976; Smith, 1979). Nonetheless, voices within each gender category do not all sound the same; they also vary in the degree to which they sound masculine/feminine. Hence it stands to reason that one’s vocal qualities would play a role in how one is stereotypically perceived. Ko, Judd, and Blair (2006) first tested this idea by examining how variation in withincategory vocal femininity cues affects stereotypic inferences. We started by showing that listeners’ judgments of within-category “vocal femininity” were remarkably consensual as apparent by the high reliability scores of the voices’ femininity judgments, even though the listeners were never told what qualities of a voice to attend to when making these judgments (Study 1). We then investigated whether perceptions of vocal femininity led to spontaneous gender-stereotypic inferences (Studies 2 and 3). Participants were led to believe that the study was about accuracy in interpersonal judgments and, accordingly, they were asked to read several short self-descriptions and, following each description, to judge a series of voice clips on the probability that each speaker was the person who wrote the description. The voices were a subset chosen on the basis of the vocal femininity ratings. Specifically, the chosen male and female voices varied continuously from very feminine/not masculine to not feminine/very masculine. The voices read part of the “Rainbow Passage” (Fairbanks, 1940, p.127) whose content is stereotypically neutral and unvalenced (i.e., neither positive nor negative in meaning). The self-descriptions varied in the degree to which they depicted someone who was stereotypically female or male and in the person’s likeability (valence). For instance, one of the stereotypically female positive descriptions depicted an elementary school teacher who likes to create a caring environment where students learn to cooperate and build self-confidence. For each of the self-descriptions, we assessed the extent to which participants’ probability ratings of the voices were associated with the voices’ vocal femininity. Our prediction was that, within each gender, more feminine voices would be seen as more probable for the female-stereotypic self-descriptions and as less probable for the male-stereotypic self-descriptions just as more masculine voices would be seen as more probable for the male-stereotypic self-description and less probable for the female-stereotypic self-descriptions. Indeed, this “vocal femininity” effect occurred when all speakers were clearly categorized as females and when all speakers were clearly categorized as males (Study 2). Moreover, even under conditions where speakers’ gender category was made salient, the vocal femininity effect persisted over and above the stereotypic judgments due to vocal category differences (Study 3). The finding in Study 3 was all the more remarkable given the categorization literature suggesting that when stimuli can be categorized, between-category differences are accentuated while within-category differences are minimized (Corneille, Klein, Lambert, and Judd, 2002; Ford and Stangor, 1992; Tajfel and Wilkes, 1963). As mentioned above, many dominant models of the link between categorization and stereotyping also suggest that category effects may be potent enough to leave little room for within-gender variations to play a role in stereotyping (e.g., Bodenhausen and Macrae, 1998). Following this logic, vocal femininity in the face of potent categorical cues should have had little chance of affecting perceptions but that was certainly not the case in our Study 3. Having established that vocal femininity affects stereotypic inferences, what qualities of a voice might listeners use to judge its femininity in the first place? Some preliminary analyses of the voices’ acoustic characteristics showed that the cues that feature importantly in distinguishing whether a speaker is male or female (e.g., pitch, resonance, and variability in pitch) also are the ones that perceivers use to judge within-category vocal femininity. The full
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picture to emerge from this research was that the physical cues of category (derived from voice) and within-category vocal femininity are both judged on the basis of similar acoustic qualities and elicit the same stereotypes, but each of these cues may affect the stereotypes uniquely. In sum, variations in vocal femininity may be more subtle than differences in category (derived from voice) in that the former deals with finer grades of differences than the latter, but the role of vocal femininity in stereotypic judgments cannot be underestimated. Finally, Ko, Judd, and Stapel’s (under review) work examining the role of vocal cues in job hiring decisions found no evidence for applicants’ gender as a source of social discrimination. However, vocal femininity cues strongly affected social discrimination such that applicants with masculine voices were rated as more competent than those with feminine voices, regardless of the applicant’s gender.
OLFACTORY CUES As to olfactory cues, studies by Baron showed an influence of perfume on impression formation (Baron, 1981, 1983, 1986). Nowadays, perfume is used by women and men for the purpose of impression management during social interactions. Perfumes are even classified as “women's” and “men's” fragrances, with “flowery” or “fruity” fragrances being offered for women and “spicy” and “strong (musky)” fragrances for men. Do such gender-related olfactory cues also have a direct impact on gender stereotyping independent of gender categorization? In a series of experiments, Sczesny and colleagues investigated whether gender-related perfumes result in gender-stereotypical evaluations of applicants for a leadership position. We expected a more masculine perfume to result in a more favorable evaluation of leadership competence than a more feminine perfume (Sczesny, Bosak, and Woeber, 2005; Sczesny and Stahlberg, 2002). In these experiments, female and male participants were asked to take the role of a personnel manager evaluating a job applicant. Participants were provided with the application of a male or a female candidate for the position of a junior manager. In the first experiment, the application papers were prepared either with a more masculine perfume, a more feminine perfume, or no perfume (control group) (Sczesny and Stahlberg, 2002, Experiment 1). That is, the application papers were sprayed with the respective perfume or no perfume, and were then enclosed in an envelope. In addition, the perfume also was applied to a desk pad which the participants used while they were working on the papers. In another experiment, participants conducted a job interview with a female or male applicant (a confederate) who had applied the respective perfume or no perfume (Experiment 2). The participants’ task was to decide whether they would or would not employ the applicant and how certain they felt about their decision. Applicants who had used a masculine perfume were employed with a higher degree of certainty compared to those who had used a feminine perfume. The effect of perfume was not mediated by its pleasantness (analyzed in Experiment 2). Moreover, applicants’ gender had no impact on the employment decision, indicating the absence of category-based gender stereotyping or counteracting. In another experiment on the impact of olfactory cues, the procedure was as follows: male and female participants were, again, asked to take the role of a personnel manager and to decide whether they would employ a job applicant for a junior managerial position. This time
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they were tested in groups of four. They were asked to study the application papers after being handed them personally by a female applicant.3 The formal clothes of the female targets were, again, applied either with the respective perfume or no perfume. The favorable impact of masculine perfume on the employment decision was replicated, but only for female participants (Sczesny et al., 2005). Women employed female targets who had worn a masculine perfume with a higher degree of certainty than those who had worn a feminine perfume. In contrast, men employed female targets who had worn a masculine perfume to a lower degree of certainty than those who had worn a feminine perfume. These effects might be ascribed to the violation of different expectations. Women might have based their evaluation of the female applicant on the incongruity of a feminine perfume with the masculine-typed leadership role. Men might have been influenced by the incongruity of a masculine perfume with the female gender role. Taken together our research demonstrates that variations in within-gender visual, vocal, and olfactory features of individuals can influence person perception directly. The results also substantiate the assumption that categorization by gender and variations in within-gender features are independent sources of gender stereotyping. Finally, whereas within-gender variation in cues result in a gender-stereotypic evaluation irrespective of the direct or indirect judgment format, the influence of categorization depended on the way the judgment was assessed (e.g., Sczesny et al., 2006).
The Automaticity of Feature-Based Gender Stereotyping After demonstrating the occurrence of feature-based gender-stereotyping, the question arises as to why targets’ gender category and the variation in their within-category features have different degrees of influence. In other words, why do perceivers correct for the influence of targets’ gender (at least, when the judgment format is direct; Sczesny et al., 2006), but not for the impact of within-category features? Do people lack control over feature-based gender stereotyping? Is such within-category stereotyping due to automatic processing? As outlined above, there are specific judgment conditions which may contribute to a reduction of category-based gender stereotyping due to controlled information processing (see Figure 1). Also, meta-cognitive knowledge plays a critical role in this concern. Petty and Wegner (1993) argued that sometimes people attempt to correct their initial perceptions or judgments in light of potentially biasing factors. For example, when assessing the qualities of a person, people may realize that some factor in the judgment situation might have influenced their perception. If this influence is identified as inappropriate, people try to control and correct for it. Since gender is a frequently used social category (see, for example, Stangor, Lynch, Duan, and Glas, 1992), people likely possess meta-cognitive knowledge that their judgments might be gender-biased. In contrast, people might be less likely to possess metacognitive knowledge about the influence of within-category physical features on their judgments and, therefore, less likely to correct for this influence. Can the different impact of 3
Targets’ gender was not manipulated in this experiment as we only investigated the evaluation of female targets. Instead, participants’ cognitive capacity was an added factor in the design, which allowed us to investigate the underlying processes of their employment judgments.
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target gender and variation in within-gender features in our previous research be traced back to the disparate availability of meta-cognitive knowledge about both sources? To test this reasoning, Sczesny and Kühnen (2004; Study 1) asked participants to judge a series of potential influences with regard to their possible impact on the attribution of leadership qualification. Among the possibly biasing features, several physical characteristics that vary more subtly within gender such as hair length, hand size, and size of nose were provided.
Figure 1. Model of category-based and feature-based gender stereotyping.
For each characteristic, participants indicated the extent to which they might influence the overall rated qualification of job applicants. In addition, gender (female/male) and non-
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gender-related physical features (e.g., hair color and short sightedness) were included in the list of potential sources of judgment biases. Furthermore, the list included five commonly used personnel selection criteria (e.g., his or her final diploma grade). Results indicated that whereas individuals possess meta-cognitive knowledge about the influence of targets’ gender and commonly used personnel selection criteria on the assessment of leadership competence, no meta-cognitive knowledge about the influence of within-category physical features and non-gender-related physical features was available. In a second study we tested the prediction that feature-based stereotyping is independent of meta-cognitive knowledge and cognitive capacity (Sczesny and Kühnen, 2004, Study 2). The participants’ task was, again, to decide whether they would employ a male or a female target with either a masculine or feminine facial appearance and how certain they felt in their decision. Photographs presented the possible four combinations of gender and appearance. The available cognitive capacity was either high or low. In the low capacity condition, after reading the application papers, participants’ task was to memorize a 9-digit number within 20 seconds. Then they were asked to report their impression of the target. Thus, while judging the stimulus person, participants’ processing capacity was impaired by having to memorize the number (e.g., Gilbert and Osborne, 1989). In the high capacity condition, no such task was applied so that it was possible to become aware of potential biasing influences. Whereas the effects of targets’ gender were expected to be moderated by the available cognitive capacity, the effects of within-gender features should neither be moderated by the available cognitive capacity nor by the targets’ gender. In other words, masculine-looking targets should receive higher ratings of leadership ability than feminine-looking targets. The results provide additional evidence for our previous findings showing that both factors – targets’ gender and their within-gender features – contribute to gender stereotyping independently of each other. More importantly, the implications of the present results are that the cognitive underpinnings of gender category and variation in within-category features are not the same. Under conditions of high cognitive capacity, participants employed female targets with a higher degree of certainty compared to male targets. Conversely, under conditions of low cognitive capacity, male targets were employed with a higher degree of certainty than female targets. Thus, the influence of gender category underlies, at least sometimes, controlled information processing. In contrast, the impact of within-category cues was not moderated by the available cognitive capacity indicating automatic information processing. Targets with a more masculine appearance were attributed with a higher degree of leadership competence than targets with a more feminine appearance. To further investigate how far the information provided by within-category features is processed automatically, we conducted another study (see above: Sczesny et al., 2005). Instead of visual cues, the impact of within-category olfactory cues on leadership evaluation was investigated. (A pre-study confirmed that people possess no meta-cognitive knowledge about the influence of perfume on leadership evaluations.) As described above, in this experiment participants evaluated female applicants who had worn either a masculine or a feminine perfume or no perfume. (For details about the perfume effect see above.) Half of the participants received an application that certified “excellent” grades in the applicant’s final exams; the other half received an application with “good” grades. Applicants’ quality served as a standard of comparison (instead of participants’ gender) since it represents diagnostic information that should be taken into account when evaluating job applicants. Also, participants’ cognitive capacity was varied as in the previous study.
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Participants were expected to take the performance information into consideration as follows: under high cognitive capacity, “excellent” applicants should be employed with a higher degree of certainty than “good” applicants. This pattern should be less pronounced under low cognitive capacity because, in this case, it is more difficult to process the performance information correctly. Hence, the effects of the applicants’ performance were expected to be moderated by cognitive capacity. Applicants with a masculine perfume should be employed with a higher degree of certainty than those with a feminine perfume. This finding should not be moderated by applicants’ performance, participants’ cognitive capacity, or their gender. As expected, under high cognitive capacity, “excellent” applicants were employed with a higher degree of certainty than “good” applicants. Under low cognitive capacity, however, this pattern was not less pronounced. Unexpectedly, “good” applicants were employed with a higher degree of certainty than “excellent” applicants. This higher uncertainty with “excellent” performers might be due to the activation of the subtype “careerist” resulting in a devaluation or to the fact that participants felt that the applicant was over-qualified for the junior managerial position. Most importantly, compared to the performance information, the impact of perfume was not influenced by participants’ cognitive capacity or by applicants’ performance. Therefore, we can assume this information was processed in a rather automatic way. Taken together our present research supports the assumption that feature-based gender stereotyping happens not only beyond categorization but also seems to be beyond control (visual cues: Sczesny and Kuehnen, 2004; olfactory cues: Sczesny et al., 2005), due to a lack of meta-cognitive knowledge of the potential impact of within-gender features.
The Interplay of Category-Based and Feature-Based Gender Stereotyping One common way individuals attempt to reduce stereotyping is by trying to suppress their stereotypic thoughts. However, research has indicated that thought suppression can be counterproductive, helping to maintain the very state of mind one had hoped to avoid (Wenzlaff and Wegner, 2000). After all, active efforts to suppress a thought actually increase the thought’s activation and the probability that the suppressed thought may leak out in other forms (Macrae, Bodenhausen, Milne, and Jetten, 1994) or on other occasions (Wegner and Erber, 1992; Wenzlaff, Wegner, and Klein, 1991). The critical question is what are the consequences of the suppression of category-based gender biases with respect to featurebased gender stereotyping? Ko, Muller, Judd, and Stapel (2008) proposed that suppressing category-based stereotyping is so well practiced that it is unlikely to show rebound effects. However, the active suppression of category-based beliefs may mean that they leak out in more subtle and seemingly harder-to-control forms—namely, through rebound of stereotypes on the basis of the more subtle within-category features. The research reviewed above clearly indicates that people are quite capable of curbing blatant category-based stereotypes but not the more subtle feature-based ones. Building on this, Ko et al. (2008) examined whether there exists a relationship between category- and feature-based gender stereotyping. Specifically, we investigated whether the constant societal pressure to suppress category-based stereotyping may ironically lead to a rebound in feature-
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based stereotyping following (or even during) the active attempt to suppress category-based stereotyping. Our predictions relied on the fact that suppressing stereotypes is known to increase their accessibility (Macrae et al., 1994). Insofar as people continue to control their use of stereotypes, this increased accessibility remains unseen. However, once the pressure to control stereotypes is relaxed, this increased accessibility manifests itself in the form of the so-called rebound effect (Macrae et al., 1994). To the best of the researchers’ knowledge, this decrease in the pressure to control has always been presumed to take place sometime after suppression. We proposed, however, that stereotype suppression and rebound do not necessarily have to follow such a sequential timeline. Indeed, if people are unaware that they are using such stereotypes, as is the case with feature-based stereotyping, then they will not exert control over their use of these stereotypes. Hence, it follows that heightened accessibility could manifest itself (through rebound in features-based stereotyping) while people are simultaneously suppressing stereotypes (through control of category-based stereotyping). We argued that an examination of this topic is timely and important, given the dual presence of strong norms in our society not to discriminate and the strong and persistent experience that discrimination is alive and well. Perhaps the norms that dictate against category-based discrimination actually lead to stronger feature-based discrimination. To test this relationship between category- and feature-based stereotyping, we adopted a novel method where stereotype suppression and rebound were examined via two different modalities. Namely, we manipulated suppression of category-based stereotyping through the visual modality then measured its effects on stereotyping in the auditory modality. Traditionally, researchers have examined stereotype suppression and rebound as they relate to visual stimuli, which may represent an underlying presumption that suppression and rebound only occur within the same modality. Furthermore, past research has solely focused on category-based suppression and rebound (e.g., Macrae et al., 1994; Wyer, Sherman, and Stroessner, 2000). This represents a first demonstration that suppression originating from one modality not only affects judgments based on another modality but also that its effect can be dual, such that suppression of category-based stereotyping in the visual modality can affect both category-based and within-category cue-based stereotyping in the auditory modality. In this experiment, participants were told that they would be involved in a number of short unrelated tasks. The first was a writing task where participants were given 10 minutes to write about a day in the life of a male and female target depicted in two photographs. Those in the suppression condition were told that they should avoid the use of gender stereotypes and be careful that these not affect what they wrote. Those in the control condition were not given these extra instructions. Following this writing task, participants engaged in a probability judgment task (similar to that used by Ko et al., 2006, Study 3). This task was presented as an interpersonal accuracy task, where participants had to match the selfdescription of a target with the correct speaker. Participants were randomly assigned to read one of the 4 descriptions that differed on stereotypicality and valence (see Ko et al., 2006 for details) before listening to a set of male and female voices that varied continuously on vocal femininity. We were interested in whether the probability ratings on the basis of gender category and within-gender vocal femininity features were moderated by the suppression manipulation. Consistent with our reasoning that people may have become quite practiced at suppressing category-based stereotypes and that categorical cues are relatively simple to
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monitor, we found that participants who were told to suppress category-based stereotypes in the writing task continued to do so in the probability task. However, the suppression of category cues consequently lead participants to make more use of within-category vocal femininity as a basis for stereotypic judgments. A closer examination of the relation between category- and feature-based stereotyping revealed that, when participants were told to suppress the use of stereotypes, a relationship existed such that the less these participants used category cues the more they used within-category cues in their judgments, whereas these two cues were uncorrelated in the control condition. Hence, participants’ use of these two cues for stereotyping allowed us to demonstrate the predicted dual effect of category-based stereotype suppression; that is, participants’ stereotypic judgments showed both suppression (through the use of between-category cues) and rebound (through the use of within-category features) simultaneously. These findings provide new insight into our understanding of stereotype suppression and rebound by revealing a somewhat paradoxical effect. That is, suppressing stereotypes associated with a given category (e.g., stereotypes about females) can lead to rebound that not only affects members of that category (i.e., females) but, paradoxically, also affects members of the opposite category (i.e., males). The societal implications of this research are that the widely-shared and largely effective norms that encourage people to avoid the expression of category-based stereotypes may ironically end up increasing the extent to which individuals stereotype others based on those features that are associated with category membership but that vary within categories.
CONCLUSION In many influential models of the link between categorization and stereotyping, little room was left for an influence of within-category variations in stereotyping (e.g., Bodenhausen and Macrae, 1998). However, our own experimental work provided comprehensive empirical evidence for feature-based gender stereotyping within and beyond gender categories. Variation in targets’ within-gender category visual, vocal, and olfactory features or cues influenced the way perceivers judged them, over and above judgments made on the basis of the targets’ gender category. Specifically, regardless of targets’ gender: 1) more masculine looking people were attributed with higher degrees of leadership competence than more feminine looking ones; 2) applicants with masculine voices were rated as more competent than those with feminine voices; and 3) applicants with a more masculine perfume were employed with a higher degree of certainty compared to those with a more feminine perfume. (At least, female participants showed this pattern consistently in the three experiments.) Since these effects were found in a series of studies and in reaction to stimuli from different sources, feature-based gender stereotyping represents a robust phenomenon. The influence of features seems to be beyond individuals’ control. We observed that specific judgment conditions contributed to a reduction of category-based gender stereotyping due to correction processes, whereas feature-based gender stereotyping was unaffected (Sczesny et al., 2006; Ko et al., 2008). The decrease in category-based gender stereotyping that goes along with the occurrence of feature-based gender stereotyping corresponds with findings on the impact of race on decision-making. Archival data suggest a dramatic decrease
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in category-based biases; for example, race of offenders no longer seems to be predictive of sentencing length, as it was found to be the case in the past (Blair, Judd, and Chapleau, 2004a). In contrast, features affected sentencing; specifically, offenders with more afrocentric features received longer sentences, even when controlling for factors such as criminal record and race (Blair et al., 2004a; also see Eberhardt, Davies, Purdie-Vaughns, and Johnson, 2006). Other recent work on racial stereotyping showed that perceivers had little trouble suppressing category-based stereotyping but were unable to suppress stereotypes arising from variations in the degree to which targets, within race, had African American (afrocentric) characteristics (Blair, Judd, and Fallman, 2004b). Our investigation indicated that, in contrast to category-based stereotyping, feature-based gender stereotyping resulted from automatic information processing (i.e., people did not possess meta-cognitive knowledge of the potential impact of within-category features and, therefore, were unable to control for it). Research by Ko et al. (2008) investigated a possible relationship between feature-based and category-based stereotyping by assessing the consequences of suppressing categorybased stereotyping on the use of feature-based biases. Their findings indicated that social norms that encourage people to avoid the expression of category-based stereotyping ironically end up increasing feature-based stereotyping. The rationale for the negative relationship between these two bases of stereotyping lies in fact that the more perceivers’ attempt to curb their use of category-based stereotypes, the greater their accessibility. Hence, when perceivers are simultaneously exposed to category and within-category gender features and are actively suppressing the use of category, then the features may act as a channel through which the increased gender stereotype accessibility can find release, particularly because perceivers seem unable to control feature-based influences. To explain the lack of control over feature-based stereotyping, we argue that perceivers are largely unaware of these influences. Furthermore, suppressing the impact of withincategory features is complex because features are riddled with myriad shades of gray (e.g., think of variations in nose size). This complexity is further heightened by the fact that not one but many different physical cues (e.g., eye and nose size and curliness of hair for afrocentric characteristics) constitute features. Hence suppressing feature-based stereotypes would require monitoring the influence of the variation in all of these cues. Our research triggers a sobering question: if suppressing categorical differences does not reduce stereotyping and prejudice, what will? Perhaps the answer lies in a multicultural perspective where differences between categorical groups are recognized rather than ignored. This perspective may allow us to value and perceive different categories as more equal which, in turn, might contribute to the reduction of stereotyping and prejudice.
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Ko, S. J., Judd, C. M., and Stapel, D. A. (under review). What you hear may not be what you know: The impact of voice and individuating information on judgments of warmth and competence. Unpublished manuscript. Ko, S. J., Muller, D., Judd, C. M., & Stapel, D. A. (2008). Sneaking in through the back door: How category-based stereotype suppression leads to rebound in feature-based effects. Journal of Experimental Social Psychology, 44, 833-839. Kunda, Z., and Spencer, S. J. (2003). When do stereotypes come to mind and when do they color judgment? A goal-based theoretical framework for stereotype activation and application. Psychological Bulletin, 129, 522-544. Macrae, C. N., Bodenhausen, G. V., Milne, A. B., and Jetten, J. (1994). Out of mind but back in sight: Stereotypes on the rebound. Journal of Personality and Social Psychology, 67, 808-817. Petty, R. E., and Wegner, D. T. (1993). Flexible correction processes in social judgment: Correcting for context-induced contrast. Journal of Experimental Social Psychology, 29, 137-165. Rosenkrantz, P., Vogel, S., Bee, H., Broverman, I., and Broverman, D. M. (1968). Sex-role stereotypes and self-concepts in college students. Journal of Clinical and Consulting Psychology, 32, 287-285. Schein, V. E. (2001). A global look at psychological barriers to women’s progress in management. Journal of Social Issues, 57, 675-688. Sczesny, S. (2005). Gender stereotypes and implicit leadership theories. In B. Schyns and J. R. Meindl (Eds.), Implicit leadership theories: Essays and explorations (pp. 159-172). Greenwich, CT: Information Age Publishing. Sczesny, S., Bosak, J., Diekman, A., and Twenge, J. (2007). Dynamics of sex-role stereotypes. In Y. Kashima, K. Fiedler, and P. Freytag (Eds.), Stereotype dynamics: Language-based approaches to the formation, maintenance, and transformation of stereotypes (pp. 137-163). Mahwah, NJ: Lawrence Erlbaum. Sczesny, S., Bosak, J., and Woeber, M. (2005). The masculine smell of success – Automatic processing of gender-stereotypic olfactorial information. 14th General Meeting of the European Association of Experimental Social Psychology (EAESP), Würzburg/Germany. Sczesny, S., Dollmann, J., and Kühnen, U. (under review). A masculine looking face – a prospect for success? The impact of gender-stereotypic features on the ascription of leadership abilities. Unpublished manuscript. Sczesny, S., and Kühnen, U. (2004). Meta-cognition about biological sex and genderstereotypic physical appearance: Consequences for the assessment of leadership competence. Personality and Social Psychology Bulletin, 30, 13-21. Sczesny, S., Spreemann, S., and Stahlberg, D. (2006). Masculine = competent? The different impact of biological sex and physical appearance on the attribution of leadership competence. Swiss Journal of Psychology, 65, 15-23. Sczesny, S., and Stahlberg, D. (2002). The influence of gender-stereotyped perfumes on leadership attribution. European Journal of Social Psychology, 32, 815-828. Smith, P. M. (1979). Sex markers in speech. In K. R. Scherer and H. Giles (Eds.), Social markers in speech (pp. 109-146). Cambridge: Cambridge University Press. Spence, J. T., Helmreich, R. L., and Stapp, J. (1974). The Personal Attributes Questionnaire: A measure of sex-role stereotypes and masculinity and femininity. JSAS: Catalog of Selected Documents in Psychology, 4, 43-44.
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Stangor, C., Lynch, L., Duan, C., and Glas, B. (1992). Categorization of individuals on the basis of multiple social features. Journal of Personality and Social Psychology, 62, 207218. Tajfel, H., and Wilkes, A. L. (1963). Classification and quantitative judgement. British Journal of Psychology, 54, 101-114. Wegner, D. M., and Erber, R. (1992). The hyperaccessibility of suppressed thoughts. Journal of Personality and Social Psychology, 63, 903-912. Wenzlaff, R. M., and Wegner, D. M. (2000). Thought suppression. Annual Review of Psychology, 51, 59-91. Wenzlaff, R. M., Wegner, D. M., and Klein, S. B. (1991). The role of thought suppression in the bonding of mood and thought. Journal of Personality and Social Psychology, 60, 500-508. Williams, J. E., and Best, D. L. (1990). Measuring sex stereotypes. A multination study. Newbury Park, CA: Sage. Wyer, N. A., Sherman, J. W., and Stroessner, S. J. (2000). The roles of motivation and ability in controlling the consequences of stereotype suppression. Personality and Social Psychology Bulletin, 26, 13-25. Zebrowitz, L. A. (1997). Reading faces: Window to the soul? Boulder, CO: Westview Press.
In: The Psychology of Modern Prejudice Editors: Melanie A. Morrison and Todd G. Morrison
ISBN 978-1-60456-788-5 © 2008 Nova Science Publishers, Inc.
Chapter 8
SINGLISM – ANOTHER PROBLEM THAT HAS NO NAME: PREJUDICE, STEREOTYPES, AND DISCRIMINATION AGAINST SINGLES Wendy L. Morris1, Bella M. DePaulo2, Janine Hertel3, and Lindsay C. Taylor4 1
2
McDaniel College University of California, Santa Barbara, USA 3 TU Chemnitz, Germany 4 University of Virginia
ABSTRACT This chapter presents evidence that singles are targeted by singlism – stereotypes, prejudice, and discrimination based upon an individual’s actual or perceived marital or relationship status. Across four experiments, college students and an older community sample described single men and women more negatively than married men and women. Although the negative stereotypes of singles were stronger for older than younger singles, even college students without romantic partners were perceived more negatively than their coupled peers. We discuss several potential explanations for the negative stereotypes of singles and present evidence that singles face various types of discrimination. Compared to discrimination against other more recognized stigmatized groups, discrimination against singles is currently perceived as legitimate and the use of stereotypes is seen as unproblematic.
INTRODUCTION The study of stereotyping, prejudice, discrimination, and stigma has a longstanding and honorable place in social psychology. Scholars of these topics have produced an extensive and sophisticated literature, and interest and enthusiasm about these topics show no signs of abating. Still, of the myriad groups that have been studied by social psychologists, there is
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one that has mostly slipped under the radar. This group, numbered 90 million in 2005, is people who are single–adults who have always been single, as well as the widowed and divorced. In this chapter, we will present evidence that singles are the targets of stereotypes, prejudice, and discrimination based upon their marital or relationship status – a phenomenon we call singlism (DePaulo, 2006; DePaulo and Morris, 2005a). We will describe three complementary theories to explain why singles might be the targets of predominantly negative stereotypes. Then we will present data from a series of studies examining the content of these stereotypes and the extent to which different people believe the stereotypes or are targeted by them. Following this, we will discuss the accuracy of the negative stereotypes and their consequences, paying particular attention to discrimination against singles. Finally, we will show that people currently do not view discrimination against singles as problematic.
The Rise of Singlehood Prejudice toward singles in the United States exists, despite the fact that the demographic composition of the nation has changed in ways suggesting there should be little stigma directed toward those who are single. For example, in 1970, there were 38 million singles (representing 28% of the population of adults 18 years of age or older); in 2005, the number was 90 million (representing 41.5% of the adult population). The age of first marriage has crept steadily upward, from 23 and 21 years of age for men and women, respectively, in 1970, to 27 and 26 in 2005. The percent of adults who are divorced (and not remarried) has more than tripled since 1970, from 3% to 10%, and households consisting of married couples became a minority in 2005. There are now more 1-person households than households comprised of “mom, dad, and the kids” (U. S. Census Bureau, 1970, 2001, 2006). Changes in demography are often followed by changes in points of view. In recent decades, attitudes have become more accepting toward divorce, cohabitation, marrying and not having children, and having children and not marrying (Thornton and Young-DeMarco, 2001). Yet, despite the increasing numbers of singles, the research we will describe shows that single people in contemporary American society continue to be stigmatized. Some have explained prejudice against singles as a cultural lag in attitudes that have not yet caught up with demographic changes in society (Byrne and Carr, 2005). Although rapid social changes have made singlehood more sustainable, common, and even desirable over time, marriage is still considered the ideal status and the primary path to fulfillment. While this cultural lag in attitudes could conceivably disappear with singles no longer being stigmatized, DePaulo (2006) and Koropeckyj-Cox (2005) have both argued that the very fact that singlehood is becoming increasingly common may cause people to cling even more strongly to the belief that marriage is a uniquely and supremely valued status as well as an essential ingredient for a full life. To the extent that singles are perceived as a threat to a cultural worldview that endorses marriage, derogating singles serves as a means to maintain the importance of marriage.
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Why Might People Hold Negative Stereotypes of Singles? The ideology of marriage and family: The glorification of marriage. Despite demographic changes in the frequency of divorce, the committed romantic couple currently holds a place of prominence that it did not always have (Cancian, 1987; Coontz, 2005). The current presumption is that all adults will marry or at least want to marry. Based on this presumption, advertising companies tend to offer their best deals to coupled adults rather than singles, businesses and the U. S. Government offer benefits that extend only to married couples, and most long-term television situation comedies seem to end with a wedding, as if no other version of “happily ever after” is conceivable (DePaulo, 2006). Weddings and Valentine’s Day, which both used to honor the many loved ones in an adult’s life, now focus exclusively on the bond between romantic partners (Gillis, 2004). According to Gillis, “people live by a conjugal ideal that is instilled from childhood and structures adult horizons of expectation throughout life and even beyond. As other relations have come to be seen as incapable of perfectibility, the conjugal has become the repository of powerful utopian desires. The expectations that people place upon marriage have escalated, making it what has been called a ‘Super Relationship’” (Gillis, 2004, p. 989). However, the romantic couple was not always considered the most important adult relationship. In 19th century American families, for example, both husbands and wives maintained and valued relationships with adults other than one’s spouse such as friends, relatives, and members of sex-segregated clubs. In fact, relationships between friends and siblings often were considered more intense and intimate than the relationship between spouses (Gillis, 1996). While love and the pursuit of happiness had been the idealized criterion for choosing a partner since the Enlightenment, it was not until the 20th century that true intimacy between spouses became attainable (Coontz, 2005). Factors that increased intimacy between spouses included the decreasing rigidity of the separate spheres for men and women (i.e., they were no longer considered entirely “opposite” sexes), the end of the Victorian era of sexual repression, increased equality for women, availability of birth control, the greater opportunities for women to earn a living wage (thus making marriage a matter of choice rather than a financial necessity), and post-World War I prosperity enabling young couples to own their own private homes without extended family (Coontz, 2005). Because divorce was now viewed as an acceptable option for those who failed to find satisfactory intimacy, love, or companionship in their marriages, those couples who chose to remain married had to work at maintaining successful, intimate marriages. Happiness was increasingly linked, in people’s minds, to heterosexual coupling and adults felt they had to reject close relationships with same-sex peers and even their own birth families in order to protect the sanctity of their marital relationship (Coontz, 2005). By the middle of the 20th century, the relationship between spouses grew in importance, both within the family, and relative to other relationships in the spouses’ social networks. Social life became more oriented to other couples than to same-sex friendships and clubs and today the committed romantic relationship is valued far more than any other adult relationship (DePaulo, 2006; Fineman, 1995). The kind of relationship to which wives and husbands aspire also has changed. The classic sociological study of middle America in the 1920s (Lynd and Lynd, 1937) suggested that “an intimate emotional and sexual bond between two developing personalities was
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seldom achieved or even strongly desired” (Cancian, 1987, p. 35). By the late 1900s, such a bond was just what couples wanted. In a study of contemporary construals of romantic love, Illouz (1997) interviewed adults about their romantic relationships, and analyzed advertisements, women’s magazines, and self-help literatures. She concluded that the meaning of romantic love now includes “the glorification of the theme of love as a supreme value and the equation of love with happiness” (p. 28). Despite the increasing number of singles in society, the institution of marriage continues to be glorified (DePaulo, 2006; DePaulo and Morris, 2005a; Thornton and Young-DeMarco, 2001). The ideal marriage envisioned today is comprised of “soul-mates” who fulfill all of their partners’ physical, emotional, social, and financial needs – the all-purpose partner (DePaulo, 2006). The soulmate version of marriage implies a very simple and appealing path to fulfillment. We construe the glorification of marriage as an ideology in that it is widely held, generally unquestioned, and resistant to examples that might contradict it (DePaulo, 2006; DePaulo and Morris, 2005a; see also Byrne and Carr, 2005). When marriage is deemed the most important adult relationship, the lives of singles are perceived as lacking. As a single participant from one of our studies claimed “My glass is seen as half empty rather than half full. It would be very refreshing to hear that the reason I am single is because I enjoy my life as a single person, that I’m discriminating and careful, and independent, and smart enough to make it on my own. It is utterly disabling to have my family look at my life and think something is missing” (Morris, 2005, p. 82). Furthermore, similar to the protestant work ethic, the ideology of marriage and family presents marriage as a goal that anyone can achieve by exerting enough effort to find that special soul mate. Given that most people expect to marry at some point in their lives (Thornton and Young-DeMarco, 2001) and about 90% of people do (Connidis, 2001), combined with the perception that the institution of marriage is attainable to any heterosexual person who would like to enter it¸ the lives of singles then, particularly heterosexuals who have never married, appear counter-normative and in need of explanation. One way to explain why single people have not married is to assume that they must possess personality characteristics that have made them undesirable to others or that they lack the maturity to achieve or maintain a marriage, the cultural signifier of adulthood. As another single participant in one of our studies noted, “People think that people who are single may be weird or [that] there is something wrong with them” (Morris, 2005, p. 82). Marriage and dating as developmental life tasks. Unlike aspects of identity such as gender or race, marital status is changeable and, to some extent, controllable. Unlike other potentially controllable stigmas such as obesity, marital status has a special place in the developmental life course. There is a time at which adults are expected to be single, and therefore one might predict that little stigma should be attached to the status, and a subsequent time at which they are expected to be married (or part of a committed couple). At the latter time, adults who are single may well be stigmatized. As Neugarten (1976) noted decades ago, “Every society is age-graded, and every society has a system of social expectations regarding age-appropriate behavior...There exists a socially prescribed timetable for the ordering of major life events: a time...to marry, a time to raise children, a time to retire” (p. 16). Some argue that age-graded norms have become even stronger over the course of the 20th century in North America and Western Europe due to the rising life expectancy and the fact that bureaucrats, scientists, and doctors increasingly relied upon age as a criterion for classifying people (Chudacoff, 1989). Subsequently, scholars
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examined the implications of reaching developmental milestones too late (or too early), and based their work on the assumption that people whose life courses departed from the social clock would experience more social disapproval (Marini, 1984), feelings of personal inadequacy (Helson, Mitchell, and Moane, 1984), and stress (e.g., Rook, Catalano, and Dooley, 1989). Increasingly, however, the life cycle has become more fluid, and in later writings, Neugarten began to suggest that age norms are becoming irrelevant (e.g., Neugarten and Neugarten, 1986). Krueger, Heckhausen, and Hundertmark (1995) asked whether the timing of marrying and having children is still relevant to social perceptions. Based on pretesting, they created profiles of typical 30-year-olds (married a few years, with one young child), 45year-olds (married about two decades, with two teenagers), and 60-year-olds (married about 27 years, with children and a grandchild or two). In a control condition, only the profiles were provided, with no age specified. In the experimental conditions, all target persons were described as 45-years old. Consequently, the targets married just a few years with one young child would seem to be late in achieving those developmental life tasks, and the targets described as married 27 years with children and grandchildren would seem to have married and raised children rather early. Krueger et al. (1995) found that the timing of life events mattered. Perceivers rated the off-time targets as more surprising and more atypical than the on-time targets. The life situation of the delayed targets was regarded as more under their own control, and more attributable to their personalities, than that of the on-time or early targets. Perceptions of controllability are especially significant because potentially stigmatizing conditions such as obesity are likely to elicit disapproval when they are regarded as controllable (Crandall and Martinez, 1996; Whitley, 1990). The female targets who were late in marrying and having children were perceived more negatively than the on-time targets on a composite measure that included feelings of liking and respect for the target, and perceptions of the target’s satisfaction with life. Consistent with the ideology of marriage and family, women who married and raised children early were perceived more positively than the on-time targets and delayed targets. However, the male targets who were delayed or early were not perceived any differently than the on-time targets. This implies that people who marry late or remain single throughout their lives may be perceived quite differently depending upon their gender, a point to which we will return later. In the Krueger et al. (1995) study and other studies of the social clock (e.g., Rook et al., 1989), all of the targets had in fact married, and only differed in the timing of their marriage. In our studies, we examine perceptions of targets who are described as single or married/in a relationship. More importantly, we want to understand the particular ways in which singles are perceived differently than people who are married, as well as the moderators of those different perceptions. Since the timely accomplishment of developmental life tasks is often seen as a sign of maturity (e.g., Keith, 1980), we expect targets described as single – particularly the relatively older singles – to be seen as less socially mature than the same-age targets described as married. The Krueger et al. (1995) results suggest that perceivers attribute delays in marrying to the personalities of the targets. What might those personality characteristics be? People who have not become coupled on-time may be seen as too socially immature, poorly adjusted, or self-centered to attract a partner or maintain a romantic relationship.
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When people evaluate singles, they may be looking for the kinds of attributes we just described, those that answer the question of why the single person has not married. In addition, they also may contemplate the question of what people may be like as a consequence of not marrying. For example, singles might be perceived as self-centered and envious due to the lack of a committed partner. Some characteristics may seem to be plausible answers to either question. For example, independence and dedication to a career may be seen as either causes or consequences of remaining single. Consistent with the developmental life tasks model, the differences in perceptions between married and single people should be greater when they are described as relatively older. For example, a 25-year-old single person may be seen as only slightly less socially mature and well-adjusted than a 25-year-old married person, but when both people are described as 40-years old, the difference should be greater. In our own conception of developmental life tasks, we include not just marriage, but also indications of progress toward marriage. We think that young adults who are single will be perceived more negatively if they are not currently in a romantic relationship than if they are, and if they have never been in such a relationship than if they have. Relationship status as a cue to the mate value of men and women. It is possible that people view singles more negatively than coupled people because relationship status conveys important information about one’s value as a mate. According to Pillsworth and Haselton (2005), “In the ancestral past, reliable inferences could be made about the mate value of individuals who had either never formed a mateship or were unable to maintain one….finding an unpartnered woman of reproductive age probably indicated that she was of exceptionally low mate value” (p. 101). The fertility of women is limited both by age constraints and lengthy gestational periods; therefore, men must compete to gain sexual access to women who act as the gatekeepers (Buss, 2003). As such, unpartnered women have been more unusual than unpartnered men historically. Therefore, one might predict that relationship status might be a more accurate reflection of the mate value of women than of men (Pillsworth and Haselton, 2005). To the extent that this is true, one might expect that perceptions of single women compared to coupled women would be more negative than single men compared to coupled men. This prediction is consistent with the results of the Krueger et al. (1995) study which found that only women were perceived more negatively for marrying and having children later than expected. Pillsworth and Haselton note that because of changes in modern society such as the advent of contraception and the entry of women into the workforce which has enabled women to consider singlehood a viable option, relationship status may no longer provide reliable cues concerning mate value. However, they argue that people may still respond to those cues due to evolved adaptations that were successful in the ancestral past. Alternatively, one could argue that the stigma of being single will be worse for men than for women. According to Bernard’s (1972) “marriage gradient,” men marry socially downward with regard to education and status while women marry socially upward. Thus, according to this notion, men who remain single must be the “bottom of the barrel” while women who remain single may do so because they are the “cream of the crop,” highly educated and/or financially successful women who have few eligible men above them to marry. While evolutionary psychology would predict that single women would be perceived more negatively than single men, the marriage gradient suggests that single men would be perceived more negatively.
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OVERVIEW OF EXPERIMENTS AND SUMMARY OF PREDICTIONS When we began doing this research, the few existing studies of singles as targets of negative stereotypes had either focused on a limited number of traits (e.g., those related to risky sexual behavior; see Conley and Collins, 2002) or they had relied entirely on the ratings made by college students (Etaugh and Birdoes, 1991; Etaugh and Malstrom, 1981). In this chapter, we will describe our research demonstrating that singles are the targets of negative stereotypes along a broad range of traits and explore the extent to which these stereotypes depend upon the age and sex of the target. We also will explore the degree to which the negative stereotypes of singles are held by adults of all ages, both single and married. After documenting the negative stereotypes of singles, we will then discuss ways in which singles face discrimination in their lives. Finally, we will present singlism as an under-acknowledged form of prejudice that is often considered fair and legitimate. In the four experiments we will describe below, we predicted that single targets would generally be perceived more negatively than married targets. We also predicted that perceptions of singles would be especially more negative than perceptions of married targets when the targets were described as 40-years old instead of 25-years old. In Experiments 1 and 2, we tested these hypotheses by experimentally manipulating the marital status, age, and sex of the targets. We chose to compare single and married targets at 25- and 40-years old based on results of a previous data collection in which we found that although marriage is desirable at 25, people do not predict that they will feel badly about being single until they reach 40 (DePaulo and Morris, 2001).1 We also were interested in exploring whether the stereotypes of singles might be more negative for men or women. We have argued that marriage compared to singledom is the more valued and validated status. Should we then expect negative perceptions of singles to be specific to people who are married, raising the possibility that disparagement of singles is a way in which married people maintain their place of privilege? Or are negative perceptions likely to be shared even by people who are single, raising the possibility that the devalued place of singles in society is part of a widely accepted ideology? To find out, we recruited for Experiment 2 an older sample that included both married and single participants. We predicted that the stigma of being single would not be as strong for 25-year-olds as for 40 year-olds. In addition, we expected to find negativity toward young singles who do not appear to be making progress toward marriage. If marriage is viewed as a developmental life task, dating may be seen as the prerequisite. Therefore, in Experiment 3, we described all of the targets as (unmarried) college students with varying degrees of experience in romantic relationships. The main comparisons were between college students in a current romantic relationship versus those not in a current relationship (Experiment 3a) and college students who have had a past romantic relationship versus those who have not (Experiment 3b). We predicted that college students who did not have experience in romantic relationships (current or past) would be evaluated as less well-adjusted and more socially immature than college students who did have such experiences. 1
According to this data collection (N = 444 college students), 98% wanted to be married by 40 and 87% reported that they would feel badly if they were not married by 40. Only 36% said that they wanted to be married by 25 and 3% reported that they would feel badly if they were still single at 25. Therefore, we chose 25 as the age where marriage does not feel imperative and 40 as the age at which singlehood begins to be perceived as counternormative.
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Consistent with the conceptualization of marriage as a developmental life task that is considered normative only beyond a certain age, our operationalization of single versus coupled varied depending upon the age of the targets. When participants were asked to rate adults who were 25 or older, we manipulated the marital status of the targets – married versus single. When participants were asked to rate college students for whom dating, rather than marriage, is normative, we manipulated the romantic relationship status and relationship history of the targets – coupled versus uncoupled. (See Table 1 for a summary of the designs of Experiments 1, 2, and 3). Finally, in Experiment 4, we asked participants to describe single or married people in an open-ended format in order to discover how people spontaneously describe these targets when their responses are not limited to predefined scales. In all four experiments, we left the sexual orientation of the targets unspecified. In the experiments that involved legally married targets (Experiments 1, 2, and 4), it is probably safe to assume that our participants thought the targets (at least the married ones) were heterosexual because gay marriage is not legal in most of the United States. On the other hand, in Experiment 3, romantic relationship status and relationship history were manipulated rather than legal marital status. Therefore, the results of this experiment might be applicable to homosexual as well as heterosexual targets. However, because we did not indicate explicitly the sexual orientation of the targets, this remains a question for future research. Table 1. Overview of the design of Experiments 1, 2, and 3 Experiment Experiment 1
Experiment 2
Experiment 3
Independent/Attribute Variables Target marital status Target age Target gender Participant gender Target marital status Target age Target gender Participant gender Participant relationship status Target current relationship status Target prior relationship history Target gender Participant gender
Main Questions Addressed Are singles perceived negatively compared to married people? Do the perceived differences increase with age? Same questions as Experiment 1. Also, do perceptions of single and married targets depend upon the relationship status of the perceiver? Are currently single college students perceived negatively compared to currently coupled students (Exp. 3a)? Are college students without a prior romantic relationship history perceived negatively compared to those with a prior history (Exp. 3b)? Are perceptions of current status moderated by prior history?
Note. The dependent variables in all experiments included the following characteristics: well-adjusted, socially immature, exciting, self-centered/envious, independent/career-oriented.
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EXPERIMENTS 1, 2, AND 3 Method Participants. Undergraduates participated in Experiments 1 (N = 55; 22 men, 33 women) and Experiment 3 (N = 54; 21 men, 33 women) in return for partial fulfillment of a requirement for an introductory psychology course at the University of Virginia. A non-college sample was recruited outside of a discount store in Oxnard, California for Experiment 2. These participants (N = 150; 74 men, 76 women) were paid $5 for their participation. Participants ranged in age from 18 to 81 with the median age of 34. Most of the participants were either Caucasian (49%) or Latino (30%). Annual income ranged from 0 to $100,000 (10 were unemployed), with a median income of $35,000. Forty-one percent of participants had received a college diploma or higher degree while 51% reported a high school diploma as their highest degree. Experiment 2 was a replication of Experiment 1 with a demographically more diverse sample. With an older community sample, we were able to address the question of whether perceptions of single and married targets are linked to the perceivers’ own relationship status. We used participants’ reports of their romantic relationship status to classify them as either single or coupled.2 Procedure and Materials. After signing an informed consent form in a university lab room or outside of a discount store, each participant received an experimental packet containing brief descriptions of target people and accompanying rating scales. In Experiments 1 and 2, each target person was described as either male or female, single or married, and 25 or 40 years old. In Experiment 3, each target person was a college student described as either male or female, currently in a romantic relationship or not, and having had a past romantic relationship or not.3 Each profile also included three inessential details – the target person’s hometown, profession (or desired profession, in the case of the college students), and a hobby. Eight different combinations of hometown, profession, and hobby were created. Each of the profiles created by the crossing of the three theoretically significant details (sex, marital status, and age in Experiments 1 and 2; sex, current relationship status, and past relationship status in Experiment 3) was paired an equal number of times with each of the descriptions created from the inessential details so that the provided information was thoroughly counterbalanced. Two examples of profiles used in Experiments 1 and 2 are: 1. Dave is a 40-year-old artist living in Portland, Maine. He enjoys hiking and is married. 2
3
Sixty-eight singles were recruited. Of these, 54 had always been single, seven were divorced and not remarried, four were separated, and three were widowed. The 81 participants classified as coupled included 52 people who were married for the first time, 13 who were remarried, and 16 who were not married but were living with their romantic partners. In Experiment 1, all three factors (sex, marital status, and age) were fully crossed within-participant factors. In Experiment 2, sex was a between-participant factor and marital status and age were both within-participant factors. In Experiment 3, all three factors (sex, current relationship status, and past relationship history) were fully crossed within-participant factors. As such, participants in Experiments 1 and 3 read eight descriptions while participants in Experiment 2 read four descriptions. In all Experiments, the order of presentation was counterbalanced using a Latin Square.
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Wendy L. Morris, Bella M. DePaulo, Janine Hertel et al. 2. Kristen is a 25-year-old teacher living in Chapel Hill, North Carolina. She enjoys playing basketball and is single. Three examples of profiles used in Experiment 3 are: 1. Laura is a college student from Larame, Wyoming. She enjoys painting and wants to be a social worker. Laura is currently in a relationship for the first time. 2. Malik is a college student from Santa Barbara, California. He enjoys cooking and wants to be a writer. Malik is not currently in a relationship but has been in the past. 3. Carla is a college student from Chicago, Illinois. She enjoys reading and wants to be a computer programmer. Carla has never been in a relationship.
After reading each description, participants rated the target person on 18 traits using ninepoint rating scales (1 = very low endorsement of trait, 9 = very high endorsement of trait). Based on the results of factor analyses and correlation patterns across all three experiments, these 18 traits were reduced to five factors describing how well-adjusted, socially immature, exciting, self-centered/envious, and independent/career-oriented the targets were perceived to be.4 Upon completion of the rating task, participants were debriefed.
Results and Discussion Are perceptions of targets predicted by their marital or relationship status? Consistent across all of the experiments, coupled targets (compared to single targets) were perceived as better adjusted and more socially mature. These effect sizes were quite large (see the Tables). In all of the Tables, the results describing the college students in Experiment 3 are presented separately for the effects of current relationship status, labeled as Experiment 3a, and the effects of past relationship history, labeled as Experiment 3b. As shown in Table 2, unmarried adults, uncoupled college students, and college students with no previous romantic relationship history are all perceived more negatively than their married or coupled peers. In Experiments 1 and 2, in which targets were older than college students, singles also were thought to be more independent/career-oriented as well as more self-centered/envious than coupled people. Sometimes coupled targets were perceived as more exciting than single targets, but this pattern was less consistent across experiments. Are the perceived differences between college students who are or are not currently in a romantic relationship moderated by past relationship history? In Experiment 3, the perception that college students in romantic relationships are better adjusted, more exciting, and less self-centered/envious than those who are not currently in romantic relationships was 4
The well-adjusted factor included the traits happy, secure, fond of children, likes emotional closeness, fun-loving, spends time with friends, and attractive (Experiment 1: Cronbach’s α = .87, Experiment 2: α = .82, Experiment 3: α = .83). The socially immature factor included the traits immature, fearful of rejection, shy and lonely (Experiment 1: α= .70, Experiment 2: α = .66, Experiment 3: α = .59). The exciting factor included the traits interesting, adventurous, and spontaneous (Experiment 1: α = .89, Experiment 2: α = .75, Experiment 3: α = .87). The self-centered/envious factor included the two traits for which it was named (Experiment 1: r = .63, Experiment 2: r = .38, Experiment 3: r = .60) as did the independent/career-oriented factor (Experiment 1: r = .66, Experiment 2: r = .51, Experiment 3: r = .43).
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moderated by past relationship history. The perceived differences between currently single and currently coupled targets were larger when the targets were described as never having been in a prior relationship than when targets were described as having been in at least one past romantic relationship (See Table 3). However, past relationship status did not moderate the effect of current relationship status on ratings of social immaturity or independence/career-oriented. Table 2. Are perceptions of targets predicted by their marital or relationship status? Factor Well-adjusted Experiment 1 Experiment 2 Experiment 3a Experiment 3b Socially Immature Experiment 1 Experiment 2 Experiment 3a Experiment 3b Self-centered and envious Experiment 1 Experiment 2 Experiment 3a Experiment 3b Independent and careeroriented Experiment 1 Experiment 2 Experiment 3a Experiment 3b Exciting Experiment 1 Experiment 2 Experiment 3a Experiment 3b
Singlea
Coupledb
Difference
F
d
5.50 5.65 5.53 5.43
6.31 6.36 6.03 6.16
0.81 0.71 0.50 0.73
83.54*** 39.54*** 59.06*** 43.85***
2.51 1.07 2.13 1.84
5.06 5.26 5.01 5.17
4.02 4.30 4.61 4.45
-1.04 -0.96 -0.40 -0.72
69.02*** 57.45*** 9.14** 51.64***
2.28 1.29 0.84 1.99
5.12 5.11 4.96 4.80
4.41 4.59 4.70 4.85
-0.71 -0.52 -0.26 0.05
23.83*** 14.42*** 4.96* 0.19
1.34 0.65 0.62 0.12
6.65
6.21
-0.44
11.64**
0.94
6.70 6.14 6.21
6.39 6.06 6.00
-0.31 -0.08 -0.21
5.74* 0.32 2.35
0.41 0.16 0.43
5.34 5.51 5.42 5.05
5.74 5.81 5.53 5.89
0.40 0.30 0.11 0.84
7.49** 3.71 0.66 29.33***
0.75 0.33 0.23 1.50
Note. The degrees of freedom for the experiments were as follows: Experiment 1 (1, 53), Experiment 2 (1, 138), and Experiments 3a and 3b (1, 52). Difference = coupled minus single. In Experiments 3a and 3b, targets were described as college students. Experiment 3a compared the attribute of coupled versus single whereas Experiment 3b compared prior relationship history versus no prior relationship history. aIn Experiments 1 and 2, single = legally single. In Experiment 3a, single = not in a current relationship and in Experiment 3b, single = has not had a past relationship. bIn Experiments 1 and 2, coupled = married. In Experiment 3a, coupled = in a current relationship and in Experiment 3b, coupled = has had a past relationship. * p < .05. ** p < .01. *** p < .001.
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Do the perceived differences between single and married targets increase with age? In support of the developmental life task hypothesis, the perceived differences between single and married targets were even more dramatic for 40-year-olds than for 25-year-olds. The degree to which single targets were perceived as less well-adjusted, more socially immature, more self-centered/envious, less exciting, and more independent/career-oriented than married targets was greater when the targets were 40 years old than when they were 25. Although not all of these results reached statistical significance, the pattern was consistent across experiments with just a few exceptions. (See difference columns in Table 4). Table 3. Are perceived differences between currently coupled and currently single college students moderated by past relationship history?
Current status:
Single
Welladjusted Socially Immature Selfcentered/ envious Independent and careeroriented Exciting
Past relationship Coupled Difference
Single
No past relationship Coupled Difference
d
6.03
6.29
0.26
5.08
5.77
0.69
0.72a
4.65
4.26
-0.39
5.37
4.97
-0.40
0.00
4.86
4.85
-0.01
5.06
4.55
-0.51
0.67b
6.00
5.99
-0.01
6.29
6.13
-0.16
0.16
6.04
5.75
-0.29
4.79
5.30
0.51
0.77c
Note. Difference = coupled minus single. F and d concern the comparison of the difference scores. a F(1, 52) = 6.75, p < .05. b F(1, 52) = 5.81, p < .05. c F(1, 52) = 7.64, p < .01.
Table 4. Do perceived differences between single and married targets increase with age?
Factor Well-adjusted Experiment 1 Experiment 2 Socially Immature Experiment 1 Experiment 2 Self-centered/ envious Experiment 1 Experiment 2 Independent and career-oriented Experiment 1 Experiment 2 Exciting Experiment 1 Experiment 2
Single
25-years-old Married Difference
Single
40-years-old Married Difference
d
5.78 5.87
6.44 6.33
0.66 0.46
5.22 5.43
6.17 6.40
0.95 0.97
0.20 0.28a
5.00 5.23
4.17 4.27
-0.83 -0.96
5.12 5.29
3.87 4.33
-1.25 -0.96
0.28b 0.00
5.02 5.15
4.57 4.59
0.45 -0.56
5.23 5.07
4.25 4.58
-0.98 -0.49
0.30c 0.03
6.52 6.58
6.21 6.40
-0.31 -0.18
6.77 6.81
6.22 6.38
-0.55 -0.43
0.19 0.08
5.63 5.83
5.97 5.94
0.34 0.11
5.05 5.20
5.51 5.69
0.46 0.49
0.05 0.12
Note. Difference = married minus single. F and d concern the comparison of the difference scores. a F(1, 138) = 10.76, p = .001. b F(1, 53) = 4.06, p < .05. c F(1, 53) = 4.58, p < .05.
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Table 5. Do perceived differences between single and coupled targets (and the perception that differences increase with age) differ for same-sex and other-sex ratings? Same-Sex Ratings
Difference
Other-Sex Ratings
Difference
Men rating men Women rating women
0.33 0.81
Men rating women Women rating men
1.09 1.02
Men rating men Women rating women
0.58 0.44
Men rating women Women rating men
0.83 1.06
Well-adjusted Experiment 1a
Experiment 3bb
Socially immature Experiment 2c Men rating men 25 years 40 years Women rating women 25 years 40 years
-1.38 -0.83 -1.21 -0.96
Men rating women 25 years 40 years Women rating men 25 years 40 years
-0.70 1.08 -0.57 -0.99
Self-centered/ envious Experiment 2d Men rating men 25 years 40 years Women rating women 25 years 40 years
-1.26 -0.37 -0.76 -0.42
Men rating women 25 years 40 years Women rating men 25 years 40 years
0.09 -0.51 -0.33 -0.67
Note. Difference = coupled minus single. In Experiments 1 and 2, single = legally single and couple = married. In Experiment 3b, single = has not had a past relationship and coupled = has had a past relationship. Unlisted characteristics did not produce statistically significant differences. a F(1, 53) = 4.29, p < .05. b F(1, 52) = 3.85, p = .055. c F(1, 138) = 3.97, p < .05. d F(1, 138) = 5.89, p < .05.
Other-sex versus same-sex ratings. We did not find any evidence suggesting that the negative stereotypes of singles are applied differentially to men and women. Despite the belief that marriage is more central to women’s lives (e.g., Hochschild, 2003), the stigma of singlehood applied equally to male and female targets. Unexpectedly, we found that people are less critical of singles of their own sex than they are of singles of the other sex. Although people consistently thought that coupled people were better adjusted than single people, the perceived difference between coupled and single targets was magnified when participants in Experiments 1 and 3b rated people of the other sex. Similarly, in Experiment 2, single targets were rated as especially more socially immature and self-centered/envious than the married targets at age 40 than at age 25 but only when participants rated targets of the other sex. In fact, when participants rated targets of their own sex, the perceived difference between single and married targets decreased with age (see Table 5).
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Although our data cannot provide a definitive explanation for this finding, we will raise two possibilities. First, from an evolutionary perspective, adaptations for successful mating choices are essential to the survival of a species (Buss, 2003). For this reason, people pay close attention to the relationship status and history of others because it may provide information about the quality of a potential mate (Pillsworth and Haselton, 2005). Considering that most people are heterosexual, one could argue that people have evolved to pay more attention to the relationship status of people of the other sex and perhaps perceive greater differences between coupled and single people of the other sex than of their own. Another possibility is that perhaps people empathize more easily with their own sex. We might more easily understand why someone of our own sex would either choose to be single or remain involuntarily single. Those who like their single status (and, according to the 2005 Pew Internet and American Life Project survey, most single people do) can easily see why other people like themselves would, too. The single people who would like to be coupled, and who have an ideologically based view of coupling as an achievement that is deserving of status and privilege, may think that dating and marriage are more difficult for their own sex to achieve than it is for the other sex. This self-serving belief could enhance the self-esteem of singles who wish to be coupled by providing an external attribution for being single. This belief also could allow coupled people to feel particularly good about themselves, having achieved something that is considered difficult to achieve. To the extent that people do empathize more easily with singles of their own sex, then people would be more likely to attribute the single status of someone of their own sex to external circumstances but someone of the other sex to negative personality characteristics. Do some people believe the stereotypes more than others? In Experiment 3a, participants generally thought college students who were currently in a romantic relationship were better adjusted than those who were not. Women perceived this difference between single and coupled targets to be larger than men did.5 However, this gender difference was not found in the other experiments. The older sample of participants in Experiment 2 enabled us to learn whether the perceptions of single and married people depend upon the marital status of the perceiver. In general, married and single participants held the stereotypes to the same degree. However, when the gender of the participants was taken into account, an interesting pattern emerged. Although married targets were considered slightly more exciting than single targets overall, this difference was largest when the raters were married men and single women. In fact, married women thought that single targets were slightly more exciting than married targets. Similar patterns were found when participants made ratings of adjustment. Although participants generally evaluated married targets as better adjusted than single targets, this pattern was particularly true of married male participants and single female participants. Furthermore, married male participants and single female participants were most likely to think that the disparity in adjustment between married and single targets increased with age (25- versus 40-year-old targets). See difference columns in Table 6.
5
The mean difference for women was .64, and the mean difference for men was .31, F(1, 52) = 6.86, p = .012.
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Table 6. Do the perceived differences between single and coupled targets (and the perception that those differences increase with age) differ depending on the gender and relationship status of the raters? (Experiment 2) Factor
Type of participant
Difference
Type of Participant
Difference
Single Men Coupled Men
0.04 0.85
Single Women Coupled Women
0.43 -0.13
Excitinga
Well-adjustedb
Single Men 25 years 40 years Coupled Men 25 years 40 years
0.73 0.42 0.41 1.79
Single Women 25 years 40 years Coupled Women 25 years 40 years
0.33 1.17 0.35 0.50
Note. Difference = married minus single. Unlisted characteristics did not produce statistically significant differences. aF(1, 138) = 4.91, p < .05. bFour-way interaction between relationship status and age of target and relationship status and sex of participant: F(1, 138) = 14.48, p < .001.
Why might married men and single women in particular hold the beliefs that married people are more exciting and well-adjusted than singles? Might these beliefs be related to their actual experiences as single or married men or women? Bernard (1972) introduced the concept of “his and hers marriages” and, in short, claimed that marriage is better for men than for women. Wives are more likely than husbands to report marital dissatisfaction, marital problems, and negative feelings including frustration and fewer wives than husbands report positive companionship. Wives also are more likely to consider their marriages unhappy, regret their marriages, and consider divorce or separation. Bernard also maintained that single women fared better than married women. Subsequently, claims have been made that getting married benefits both men and women (e.g., Waite and Gallagher, 2000). So what do the data indicate? DePaulo (2006) recently reviewed and critiqued both cross-sectional and longitudinal evidence. In cross-sectional studies, there were only small differences in health or happiness between the currently married and the people who had always been single. Typically, the least happy or healthy were the previously married (divorced or widowed). When there were sex differences (and often there were not), they typically showed that men did better when they were married than unmarried. Other studies suggest ways in which marriage is more problematic for women than for men. For example, compared to men, women report lower satisfaction in their marriages, think about divorce more often, initiate divorce more often, and are more negatively affected by marital conflict (Antonucci and Akiyama, 1987; Horowitz, McLaughlin, and White, 1998). Thus, married men might be basing their ratings on their own relatively more positive experiences being married. This also could explain why married women did not perceive as much of a difference between the married and single targets – marriage is a more ambivalent experience for them. If people were in fact basing their ratings on their own experiences, then
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it makes sense that single women would assume the “grass is greener” on the other side, having never been on the other side (83% of the single women in this sample had not previously been married). The messages women hear about the importance of getting married – messages consistent with the ideology of marriage and family – also may be important. Marriage and family continue to be regarded as more central to women’s lives than to men’s (e.g., Hochschild, 2003). Relationship advice columns, self-help books, and wedding guides are written overwhelmingly for female readers (e.g., DePaulo, 2006; Hochschild, 2003). Thus single men may have less of a reason to think the grass is greener on the other side. Most important theoretically were the negative judgments of single targets by the perceivers from the community sample who were themselves single and generally older than the college students. For example, although married men believed that married people were better adjusted than single people to a stronger degree than did single men, single men held these stereotypes as well. The devaluing of single people is not a practice that is perpetuated solely by people who are married. As we will detail below, the negative perceptions of singles result in discrimination against them that is not even recognized as illegitimate. Why, then, do singles share in these perceptions? Although we cannot answer that question definitively on the basis of the data we have collected so far, it can be argued that cultural ideas about marriage are so ingrained that they can be usefully construed as ideological (DePaulo, 2006; DePaulo and Morris, 2005a).
EXPERIMENT 4 As there is little recent research on how singles are evaluated and all of that research has measured stereotypes using predefined scales, Experiment 4 assessed the stereotypes of singles and marrieds using an open-ended format. This method allowed participants to describe the two groups freely without limiting their responses to the scales we chose to include in the previously described experiments.
Method Nine hundred and fifty undergraduate students (305 men, 583 women, 62 unspecified) from the University of Virginia completed a web-based survey in return for partial fulfillment of a class requirement. The median age of the sample was 19 and the ethnic breakdown was as follows: 69% Caucasian, 12% Asian, 9% African-American, 2% Latino, and 8% unspecified. Half of the participants were asked to write about singles and half were asked to write about married people in response to the following questions:
–
Think about people who are single/married. Please list the characteristics that describe people who are single/married. These characteristics could include personality traits, things they do or like, their attitudes or opinions, or anything else that comes to mind.
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Results and Discussion We created a coding scheme by reading through the participants’ answers while making a list of all of the descriptive information that was mentioned. After a list of descriptive items was generated, two research assistants then coded the data by noting which of the descriptive items each participant mentioned. In this chapter, we will only present the results for descriptive items that were mentioned by at least five percent of our participants. Those results are presented in Table 7.6 Consistent with the results of the previous experiments, participants thought married targets were better adjusted than single targets. Specifically, married targets were more likely to be described as happy, fulfilled, stable, reliable, kind, giving, and loving, whereas single targets were more likely to be described as unhappy, insecure, and lonely (see Table 7). Single targets also were described as more socially immature (i.e., married targets were described as honest, compromising, and flexible while singles were described as stubborn and shy). Given the results of the previous experiments, we were not surprised that participants more often volunteered descriptors such as loving, kind, caring, and giving, when listing characteristics of people who are married than when listing characteristics of singles. But we did not expect the differences to be quite so stark. Of the 552 students who provided openended descriptions of people who are married, one out of every three described married people as loving. Of the 398 students who described people who are single, not one used that word. Of the students who listed thoughts about married people, nearly half (48.7%) described them as kind, caring, or giving. In contrast, only 2.3% of the students describing singles used any of those terms. More than a third of the students in the singles condition listed the term independent, compared to less than two percent who did so in the married condition. Although we have conceptualized independence as a positive personality characteristic, it is possible that participants considered this a negative consequence or cause of not having a romantic partner and a trait that interferes with attachment goals. There were a few positive characteristics ascribed differentially to singles; however, in some instances, the opposite of the same positive traits also were ascribed to them more often. For example, singles were more often described as being confident than were marrieds, but they also were more often described as insecure. Singles were more often described as being friendly and sociable with friends, but also were more often described as shy and lonely. It is possible that single targets are seen as more extreme (in positive as well as negative ways) than married targets (Seccombe and Ishii-Kuntz, 1994). Viewing singles as extreme can provide two contradictory but seemingly plausible explanations for why someone may not have married – they are too insecure or shy to develop a romantic relationship or they are so confident and sociable that they feel no need to do so. Extreme attributions also may capture perceivers’ explanations of the consequences of not marrying – for example, remaining single
6
Participants received a “1” if the coders noted that a particular descriptive item was mentioned and “0” if that item was not mentioned. Thus each descriptive item became a dependent variable and the means ranging between 0 and 1 represented the percentage of participants who mentioned each descriptive item. The average reliability between the two coders was 92%. Each of the descriptive items was entered into a one-way betweenparticipants ANOVA. A complete list of responses is available from the first author.
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Table 7. Percentage of participants who mentioned each characteristic when describing single or married targets (Experiment 4) Marital Status Characteristic Single Married Difference Characteristics used more often to describe married people Kind, caring, 2.3 48.7 46.4 giving Loving 0.0 32.2 32.2 Happy 7.3 28.1 20.8 Faithful, loyal 0.0 16.3 16.3 Compromising 0.0 15.9 15.9 Secure, stable 0.0 10.5 10.5 Reliable, careful 1.5 7.6 6.1 Honest, 2.8 8.5 5.7 trustworthy Dependent, 1.0 6.5 5.5 needy Fulfilled, 1.8 6.9 5.1 content Flexible, open3.8 6.9 3.1 minded Characteristics used more often to describe single people Independent 36.2 1.6 -34.6 Lonely 16.8 0.2 -16.6 Looking for a 11.3 0.0 -11.3 partner Social, friendly, 21.4 10.1 -11.3 fun Flirtatious 8.8 0.0 -8.8 Spends time 10.8 2.4 -8.4 with friends Shy 9.3 1.1 -8.2 Drinking, night 7.8 0.0 -7.8 life Insecure 7.3 0.0 -7.3 Inflexible, 6.8 1.6 -5.2 stubborn Unhappy 8.0 2.9 -5.1 Confident, self7.5 4.5 -3.0 assured
F
d
322.71
1.17
189.02 68.51 77.37 75.32 46.43 18.25 13.50
0.89 0.54 0.57 0.56 0.44 0.28 0.24
17.74
0.27
13.63
0.24
4.27
0.13
259.75 107.19 70.22
1.05 0.67 0.54
23.52
0.32
53.11 30.66
0.47 0.36
37.41 46.53
0.40 0.44
43.29 17.11
0.43 0.27
12.89 3.85
0.23 0.13
Note. Characteristics that were endorsed by fewer than 5% of participants are not included in this table. Degrees of freedom were (1, 948). Difference = married minus single. All differences were significant at p < .001 except the differences for insecure and fulfilled which were each p < .01 and confident and flexible which were each p < .05.
could cause loneliness and insecurity or it could increase self-confidence and the desire to be sociable with friends. It is possible that people’s views about marriage and singlehood or even their feelings about particular single people predict whether they view singles in extremely positive or extremely negative ways.
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CONCLUSION Across multiple experiments and methodologies, we have shown that both single men and women are the targets of many negative stereotypes. Consistent across all three scenario experiments, single targets were perceived as less well-adjusted, more socially immature, and more self-centered and envious than married or coupled targets. Singles were also thought to be less exciting and more independent and career-oriented than married people in many of the experiments. Notably, all of the effect sizes for the perceived differences between single and coupled people in terms of adjustment and social immaturity across the three scenario studies were remarkably large (Cohen, 1988). Although our results reveal some support for the developmental life task model – the perceived differences between single and married targets were larger for ratings of the 40 year-old targets than the 25-year-old targets – it is important to note that this pattern was not significant for all dependent variables and even 25-year-old singles were perceived more negatively than their married peers. Furthermore, college students were perceived negatively if they had not achieved their age appropriate version of marriage (i.e., dating). The fact that our results did not show more age differences suggests that singlism may transcend age to some degree. We have discussed some of the moderators of our effects, noting that the perceived differences between singles and couples were greater for some targets than for others and for some perceivers than for others. More striking than these shades of differences, however, were the similarities. We recruited men and women, people from the university and people from the community, people who were single and people who were married. We asked them to rate single and married 25-year-olds, single and married 40-year-olds, and college students who varied in their relationship experiences. We used rating scales as well as an open-ended methodology, and the results were mostly the same. Across all of the rating scale studies, for example, we found no significant reversals of our predictions and only a few very circumscribed trends in the unpredicted direction. Having demonstrated that singles are the targets of negative stereotypes, one important component of singlism, we will now address some remaining questions concerning these stereotypes such as whether certain singles are exempt from stigma. After addressing these questions, we will then discuss the other key component of singlism – discrimination. We will present evidence that singles are the victims of discrimination and we will discuss the perceptions people have about singlism.
Is Prejudice Against Singles a Uniquely American Phenomenon? To answer this question, we asked 267 German adults to rate descriptions of single and married men and women who were 25 and 40 years old (using the same methods described earlier). The results of this German study replicated those of the American samples. Singles were perceived as less warm and caring and more miserable and lonely than married people. Consistent with our previous results, the negative perceptions of singles relative to married people were more dramatic for the 40-year-olds but still appeared for the 25-year-olds as well (Hertel, Schütz, DePaulo, Morris, and Stucke, 2007).
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Another series of studies conducted in Germany compared perceptions of single and coupled (rather than married) adults along a different set of characteristics. Greitemeyer (2007) found that people thought singles had lower self-esteem and were less sociable, less agreeable, less physically attractive, less conscientious, less satisfied with their lives, and more neurotic than were coupled people. Not only did this study provide further evidence of negative perceptions of singles, it also assessed the degree to which the stereotypes of singles are accurate, a point to which we will return later.
Are Certain Types of Singles Perceived More Positively than Others? Perhaps the negative stereotypes of singles are based upon the assumption that because singles lack a spouse they lack the kind of intimate, supportive, stable relationship that allows people to fulfill the need to belong, defined by Baumeister and Leary (1995) as “the combination of frequent interaction plus persistent caring.” Although the assumption that singles lack close relationships is a faulty one (Adams, 1976; Connidis, 2001; DePaulo, 2006; Zettel, 2005), this misperception might conceivably explain why people hold negative stereotypes of singles. To test this hypothesis, we conducted an experiment similar to the stereotyping studies we have already described. However, this time, in addition to manipulating the target’s marital status and gender, we also described half of the targets as having a network of very close friends and the other half were described as having many acquaintances but not many close friends. Regardless of whether the targets were described as having close friends or not, single targets were still perceived more negatively than married targets (Morris, 2002). Thus, even singles with close, supportive friendships are perceived as less well-adjusted and mature than their married peers. Consistent with the ideology of marriage and family, the marital relationship is considered more important and influential than other close relationships. Perhaps singles can overcome their stigma by demonstrating extraordinary accomplishments in other domains. In order to answer this question, we conducted another study in which participants read about targets that were either described as married or single. This time we also varied how successful the targets were in several different domains. Half of the targets were described in ways that highlighted their extraordinary professional, financial, interpersonal, or altruistic success. The other targets were described as average in those four domains. Although success sometimes decreased the gap between how married and single targets were perceived, even these extraordinary successes did not cause that gap to disappear entirely (DePaulo and Morris, 2004). Consistent with the ideology of marriage and family, people seem to believe that regardless of how successful singles might be in many aspects of their lives, no amount of success can replace the romantic partner they do not have. The group we have been calling singles includes quite a heterogeneous collection of people including those who are divorced, widowed, and singles living with long term romantic partners – single in legal terms but coupled in every day life. In most of the experiments we described above, we did not differentiate between different types of singles because, in accordance with the ideology of marriage and family, all types of singles should be stigmatized to some degree (DePaulo and Morris, 2005b). In a different study, we sought to determine whether perceptions vary depending on the different subtypes of singles. We asked almost 400 people to describe their thoughts in response to different types of singles in
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a free-writing format (Morris and DePaulo, 2002). Each participant responded to one of fourteen different types of singles including divorced people, single parents, widows, singles living with romantic partners, and the more general categories of single men and single women. For the most part, there was a great deal of similarity in the thoughts elicited by the many different types of singles. The only singles that were described distinctively were widows and singles who were living with their romantic partners. This finding makes sense given that both of these groups could be considered closer to married persons on the relationship status spectrum. Widows were married but the marriage ended due to reasons outside of their control. Cohabiting romantic partners live as if they are married (minus the documents and all of the financial perks that go with it). However, although widows are viewed more positively than people who are divorced or have always been single, even widows are viewed significantly less positively than married people (Etaugh and Malstrom, 1981). Furthermore, research we will detail below shows that cohabiting committed romantic partners do not escape discrimination by virtue of being socially, but not legally, coupled.
Do People Hold Negative Stereotypes about Singles on an Implicit Level? So far, all of the research we have described has measured participants’ explicit or conscious attitudes about singles. We also have found evidence that people hold stereotypes about singles on an implicit or automatic level as well. We designed three different Implicit Association Tests (IATs) modeled after the work of Greenwald, McGee, and Schwartz (1998). These tests measure the degree to which people unconsciously associate certain groups with certain characteristics. Two hundred and fifteen undergraduates from the University of Virginia (104 men, 110 women, 1 gender unspecified) each completed one of three IATs. In each IAT, the groups compared were single and married people and the opposing characteristics included either mature-immature, pleasant-unpleasant, or independent-dependent. We found that people unconsciously associated married people with maturity, pleasantness, and dependence while they associated singles with immaturity, unpleasantness, and independence (Taylor, Morris, and Sinclair, 2007).7 Thus, the stereotypes that people hold of singles operate even without conscious awareness.
Are the Stereotypes of Singles Accurate? Earlier, we briefly described a study in which participants thought singles had lower selfesteem and were less sociable, less agreeable, less physically attractive, less conscientious, less satisfied with their lives, and more neurotic than coupled people (Greitemeyer, 2007). However, when the single and coupled participants in this study rated themselves along these same dimensions, their self-ratings were no different from each other. The results were replicated when the criterion for accuracy was not self-ratings but ratings made by other people who were unaware of the targets’ relationship status: again, no differences were found 7
Mature-immature: mean difference = .78, t(68) = 21.09, p < .001, d = 2.54. Pleasant-unpleasant: mean difference = .29, t(70) = 5.98, p < .001, d = .71. Independence-dependence: mean difference = .50, t(70) = 13.38, p < .001, d = 1.59. Participants included 140 Caucasians, 28 African-Americans, 19 Asian-Americans, and 28 who did not specify their ethnicity.
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between single and coupled people. Although the perceived differences in personality between single and coupled targets were quite significant, the actual differences between the two were nonexistent. The only real difference found between the single and coupled participants was not a personality characteristic but rather that singles were less satisfied with their current relationship status. There are other inaccurate or distorted perceptions of singles as well. For instance, when 444 undergraduates were asked to predict, on a 1 to 9 scale, how happy they would be if they got married or remained single, they projected a mean rating of 7.9 if they married (DePaulo and Morris, 2001). In fact, almost half predicted the highest level of happiness the scale would allow (a rating of 9). In contrast, they anticipated a mean happiness level of only 3.9 if they remained single, and more than half expected to experience the lowest level of happiness the scale would allow. Similarly, in Experiment 4 that we have just described, 28% of participants thought married people were happy whereas only 7% thought singles were. Likewise, 8% of participants thought single people were unhappy but only 3% of people thought that married people were. The common perception that married people gleefully live out their days at the height of happiness while singles experience the depth of misery is a far cry from the actual differences in happiness levels reported by married and always single adults in meta-analyses (for a review, see DePaulo and Morris, 2005a). In reality, when thousands of adults in a national sample were asked to indicate their level of happiness on a 4-point scale, the mean ratings for married and single people (particularly people who were always single) were very close together. The mean happiness ratings were 3.3 for married people, 3.2 for always single people, and 2.9 for both widows and divorcees (Gove and Shin, 1989). Similarly, an 18-year longitudinal study of German adults found that marital status only explained around 1% of the variance in happiness levels between individuals (Lucas, Clark, Georgellis, and Diener, 2003). Although college students think that marriage will make them happier than singlehood (DePaulo and Morris, 2001), Lucas et al. found that getting married does not make people happier, except for a very brief and very small honeymoon effect. When differences in health and happiness are found between single and married people, those differences tend to be found between the currently married and the previously married (divorced and widowed people) rather than between the currently married and the consistently single (DePaulo and Morris, 2005a; Rook and Zettel, 2005). Although it is informative to note that the large effect sizes for the perceived differences between single and married people do not accurately represent the actual differences between these groups, this point is somewhat irrelevant in determining whether singlism is a form of prejudice. Prejudice exists when people hold negative evaluations of a group or an individual based on group membership regardless of whether those evaluations do or do not have a grain of truth to them (Crandall and Eshleman, 2003).
Discrimination Against Singles The negative stereotypes of singles have far reaching implications. Singles experience negative interpersonal and economic outcomes due to their marital status. For instance, couples tend to withdraw from their friends as their romantic relationships become increasingly intimate (Johnson and Leslie, 1982; Wellman, Wong, Tindall, and Nazer, 1997),
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Table 8. Examples of singles’ descriptions of personal experiences of discrimination Negative Perceptions: Pity: Social Exclusion:
Financial Disadvantage:
Housing: Workplace:
“People think that people who are single may be weird or there is something wrong with them.” “There is not a family dinner I attend that does not include the conversation that sympathizes with my ‘plight’ as a single woman.” “They don’t want to hang out with me because they have a spouse.” “At my church, the women’s ministry consistently, favorably, and almost exclusively holds events that cater to the interests and schedules of stay at home mothers.” “Airline packages are priced for doubles, so I can never get a package.” “Less pay because they think singles don’t need as much money.” “Difficulty renting an apartment because single.” “Always expected to work on Christmas.” “Was often expected to work later hours than my married coworkers.”
Adapted from Morris (2005, Experiment 4).
and when they do socialize they prefer to do so with other married people (Verbrugge, 1983). Unsurprisingly, then, singles often report feeling abandoned by their married friends (Amador and Kiersky, 1998). We asked 38 single adults (median age = 40) to describe a time when they had been treated a particular way because they were single (Morris, 2005). Their responses to this question most often included descriptions of negative perceptions others held of their lives, social exclusion, financial disadvantages, and differential treatment in the workplace. (For a sample of representative comments, see Table 8.) The only ways in which our participants perceived singles more positively than married people was that singles were described as more independent and career-oriented (Experiments 1 and 2). However, even this seemingly positive stereotype can have important negative consequences in that employers expect singles to work longer hours and on holidays precisely because singles are assumed to have fewer outside obligations than their married peers (Burkett, 2000, Davis and Strong, 1977; DePaulo, 2006). Ironically, despite the perception that singles are more career-oriented, married men are rewarded more often in the workplace. Several studies have found that marriage is an asset to a man’s career in that it increases both his salary and his likelihood of receiving a promotion across a broad range of professions. This “marriage bonus” persists even when married and single men occupy the same level of seniority and perform at the same level of competence (Antonovics and Town, 2004; Bellas, 1992; Budig and England, 2001; Keith, 1986; Toutkoushian, 1998). Furthermore, most states do not have laws that prohibit employers from discriminating on the basis of marital status (Unmarried America, n.d.). Groups that suffer discrimination in one domain are often vulnerable in other domains as well. We decided to run a series of controlled experiments to learn whether singles might
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suffer discrimination when applying to rent a home. Rental agents as well as college students read brief descriptions of multiple applicants8 for a rental property and were then asked to make a choice and explain the rationale behind that choice (Morris, Sinclair, and DePaulo, 2007). In one experiment, the choices included a married couple, a single man, and a single woman. In two of the experiments, the choices each included pairs of people with two sources of income – a married couple, a cohabiting, romantic couple (unmarried and heterosexual), and a pair of opposite sex friends. In the final experiment, the choices included a married couple and a cohabiting, unmarried romantic couple; however, this time we manipulated the relative stability of the latter’s relationship. The cohabiting couple was either described as having been together the same amount of time as the married couple or for a much longer amount of time. In all four of these experiments, participants consistently chose the married couple over all types of single applicants including a cohabiting couple who had been together much longer than the newlyweds who were chosen. Furthermore, the effect sizes in these experiments were quite large demonstrating not only a preference for married couples over singles but a very strong preference at that (phi coefficients ranged from .30 to .99). Why did participants have such a strong preference for renting properties to married couples over singles? After participants made their choice, we asked them to assess the likelihood that each applicant would be a delinquent, troublesome kind of tenant who would damage the house, pay rent late, be noisy, and so forth. In many cases, the participants thought that the single applicants would be more delinquent than the married couple. However, this was not always the case. Certain types of singles were not perceived in more negative terms than married couples (e.g., single women and the cohabiting couple that had been together longer than the married couple), but even these responsible singles were still not chosen over the married targets. Upon what reasons, then, were participants basing their discriminatory decisions? When we asked participants to explain the reasoning behind their choice, the one most commonly stated was simply that the married couple was married (Morris et al., 2007). This kind of logic explains why people will even prefer married couples over singles who are perceived as equally responsible. When choices are based upon the wearing of visible wedding rings, all kinds of singles are disadvantaged.
Perceptions of Discrimination Against Singles After our participants unselfconsciously admitted that they based their choices on the marital status of the applicants, we began to suspect that, unlike other forms of prejudice that are denounced, singlism is perceived as acceptable. In another study, participants read about a blatant example of discrimination in which a landlord chose an applicant from a dominant group over an applicant from a subordinate group despite the fact that the unchosen applicant had offered more money to rent the property (Morris et al., 2007). Similar to the housing experiments we described above, the landlord openly stated that his choice was based upon the fact that he preferred renting to members from the dominant group. Some participants read about discrimination against a single person and others read about discrimination against a member of a more publicly recognized stigmatized group such as a woman, an AfricanAmerican, a gay person, an obese person, or an elderly person. In comparison to participants 8
Applicants were all described as being the same age.
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who read about other culturally acknowledged types of discrimination, those who read about discrimination against a single person were more likely to agree with the landlord’s decision and think it was legitimate. They also were less likely to think that the landlord’s choice was based upon prejudice or stereotyping. Interestingly, for the publicly recognized forms of discrimination, the more people thought the landlord’s decision was based upon prejudice or stereotyping, the less fair they thought the decision was. For discrimination against singles however, whether participants thought the landlords used stereotypes or not was completely unrelated to whether they thought the landlord’s decision was fair. Thus, it appears that stereotypes, prejudice, and discrimination against singles are perceived as unproblematic and acceptable. One could argue that people find discrimination against singles more legitimate than discrimination against other groups based upon the fact that discrimination against people with controllable stigmas, such as being single, is perceived as more legitimate than discrimination against people with uncontrollable stigmas (Rodin, Price, Sanchez, and McElligot, 1989). However, we have found that discrimination against singles is perceived as more legitimate than discrimination against obese people even though these stigmas are perceived as equally controllable (Morris, Sinclair, and DePaulo, 2005). Although we have found evidence of housing discrimination against singles, most singles are not aware of their predicament. When Byrne and Carr (2005) analyzed data from a nationally representative sample of adults, they found that singles were not any more likely than married people to think that they had ever experienced discrimination when applying to buy or rent a home. Similarly, when we asked a diverse sample of adults to list any social groups or categories they belonged to which are the targets of negative stereotypes and/or discrimination, only four percent of singles spontaneously mentioned their single status as such a category. When we specifically asked participants to indicate whether they thought singles were the targets of negative stereotypes and/or discrimination, only 30% of singles and 23% of married people did. This level of awareness of the stigma of being single was much lower than the awareness people had about other stigmatized groups. For example, 90% of obese people and 78% of nonobese people recognized the stigma associated with obesity. Similarly, 86% of African-Americans and 83% of people who were not African-American recognized the stigma associated with that group (Morris, 2005). Why is it that most single and married people do not think of singles as a stigmatized group? One answer to this question lies in the fact that behaviors are only labeled as discrimination if they are perceived as both unfair and group-based (Major, Quinton, and McCoy, 2002). The results of our research show that the differential treatment of single and married people is perceived as relatively fair and legitimate (Morris et al., 2007). Furthermore, it is quite possible that singles do not view themselves as a group given the impermanent nature of marital status.
Who Practices Singlism and Why? In all of our studies, we have compared the responses of our married (or coupled) and single participants to determine whether singlism is a form of outgroup bias or whether singles share the same prejudices. Across all of our studies, we have found that singles practice singlism to the same degree as their coupled counterparts. Singles are just as likely as married and coupled people to hold negative stereotypes about their group, to discriminate
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against singles, and to believe that discrimination against singles is legitimate (Morris et al., 2007). This pattern of results may reveal the unquestioned nature of the ideology of marriage and family (DePaulo, 2006; DePaulo and Morris, 2005a) as even singles perpetuate and justify a system that disadvantages them (Jost, Banaji, and Nosek, 2004). We cannot definitively know from our data whether singlism is due to a culturally held ideology or whether there might be some evolutionary basis for it. One way to shed light on these explanations would be to pursue the study of singlism cross-culturally. Although we have conducted research in two countries, the United States and Germany, it is possible that singlism is a function of culturally variant beliefs that happen to be shared in these two western cultures. Pillsworth and Haselton (2005) observed that “in most cultures around the globe, your spouse is not your best friend, or even your primary social partner” (p.102). Might singlism vary cross-culturally with the importance placed upon the spousal relationship and the expectation that a spouse is supposed to serve as a soul mate, simultaneously fulfilling most of our social, interpersonal, sexual, and economic desires? Perhaps singlism also exists in countries where the marital relationship is regarded as a path to economic security. Whether marriages are typically arranged or freely chosen in a society also may predict the prevalence or degree of singlism. Further, it is possible that singlism is a function of marriage rates or cultural expectations. In the United States, for example, the single status of an African-American woman is more acceptable within the African-American community than is the single status of a Caucasian woman within the Caucasian community (Staples and Johnson, 1993). We hope that future research will test whether singlism is universal, as evolutionary explanations would predict; whether it is directly related to cultural norms and beliefs about the significance of marriage as an institution, as a sign of adulthood, and as a path to fulfillment; or whether both play a part.
The Failure to Recognize Singlism as a Prejudice One of the most thought-provoking aspects of singlism is that, despite the large differences in perceptions of singles compared to married people, and the evidence of discrimination against singles (Morris et al., 2007), people generally perceive the negative stereotypes and differential treatment of singles as unproblematic and fail to acknowledge them as a form of prejudice (DePaulo and Morris, 2006). Perhaps people do not object to singlism as much as they do to other forms of prejudice because singlism does not have the violent and sometimes fatal consequences associated with other “isms” such as racism and heterosexism. Prejudice may not seem quite so objectionable without violent repercussions (DePaulo and Morris, 2005b). Crandall and Warner (2005) provide an insightful explanation for why people fail to acknowledge singlism as a form of prejudice. When prejudice is defined as “a negative evaluation of a social group, or a negative evaluation of an individual that is significantly based on the individual’s group membership” (Crandall and Eshleman, 2003, p. 414), singlism clearly fits the bill. However, Crandall and Warner argue that negative attitudes about groups are only considered prejudice by mainstream society (and social scientists) when those attitudes are counternormative and frowned upon by a culture. Given that the ideology of marriage and family is widely shared and largely unquestioned, it is perhaps not
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surprising that singlism is usually considered an acceptable attitude rather than labeled a prejudice. To illustrate the historical trends in recognizing and studying prejudice, Crandall and Warner name sexism and heterosexism as examples of attitudes that have shifted from normative acceptability to normative unacceptability and they further argue that social scientists tend to study “isms” only during that controversial period of change, the “normative window” as they call it. Just as sexism and the feminine mystique used to be problems that had no name (Friedan, 1963), prejudice against singles has gone under-acknowledged and nameless. We hope that providing a name for this form of prejudice will motivate people to question the normative acceptability of singlism and encourage other social scientists to explore this understudied and ever-growing group of people.
REFERENCES Adams, M. (1976). Single blessedness: Observations on the single status in married society. New York: Basic Books. Amador, X., and Kiersky, J. (1998). Being single in a couple’s world: How to be happily single while looking for love. New York: The Free Press. Antonucci, T. C., and Akiyama, H. (1987). An examination of sex differences in social support among older men and women. Sex Roles, 17, 737-749. Antonovics, K., and Town, R. (2004). Are all the good men married? Uncovering the sources of the marital wage premium. American Economic Review, 94, 317-321. Baumeister, R. F., and Leary, M. R. (1995). The need to belong: Desire for interpersonal attachments as a fundamental human motivation. Psychological Bulletin, 117, 497-529. Bellas, M. (1992). The effects of marital status and wives’ employment on the salaries of faculty men: The (house) wife bonus. Gender and Society, 6, 609-622. Bernard, J. (1972). The future of marriage. New Haven, CT: Yale University Press. Budig, M. J., and England, P. (2001). The wage penalty for motherhood. American Sociological Review, 662, 204-225. Burkett, E. (2000). The baby boon: How family-friendly America cheats the childless. New York: The Free Press. Buss, D. M. (2003). The evolution of desire: Strategies of human mating (2nd ed.). New York: Basic Books. Byrne, A., and Carr, D. (2005). Caught in the cultural lag: The stigma of singlehood. Psychological Inquiry, 16, 84-91. Cancian, F. M. (1987). Love in America: Gender and self-development. Cambridge, MA: Cambridge University Press. Chudacoff, H. P. (1989). How old are you? Age consciousness in American culture. Princeton, NJ: Princeton University Press. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum. Conley, T. D., and Collins, B. E. (2002). Gender, relationship status, and stereotyping about sexual risk. Personality and Social Psychology Bulletin, 28, 1483-1494. Connidis, I. A. (2001). Family ties and aging. Thousand Oaks, CA: Sage.
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Coontz, S. (2005). Marriage, a history: From obedience to intimacy, or how love conquered marriage. New York: Viking. Crandall, C. S., and Eshleman, A. (2003). A justification-suppression model of the expression and experience of prejudice. Psychological Bulletin, 129, 414-446. Crandall, C. S., and Martinez, R. (1996). Culture, ideology, and antifat attitudes. Personality and Social Psychology Bulletin, 22, 1165-1176. Crandall, C. S., and Warner, R. H. (2005). How a prejudice is recognized. Psychological Inquiry, 16, 137-141. Davis, A. G., and Strong, P. M. (1977). Working without a net: The bachelor as a social problem. Sociological Review, 25, 109-129. DePaulo, B. (2006). Singled out: How singles are stereotyped, stigmatized, and ignored, and still live happily ever after. New York: St. Martin’s Press. DePaulo, B. M., and Morris, W. L. (2001). [Undergraduate students' views on marriage and singlehood]. Unpublished raw data. DePaulo, B. M., and Morris, W. L. (2004). [Are the negative perceptions of singles attenuated when singles are successful?] Unpublished raw data. DePaulo, B. M., and Morris, W. L. (2005a). Singles in society and in science. Psychological Inquiry, 16, 57-83. DePaulo, B. M., and Morris, W. L. (2005b). Should singles and the scholars who study them make their mark or stay in their place? Psychological Inquiry, 16, 142-149. DePaulo, B. M., and Morris, W. L. (2006). The unrecognized stereotyping and discrimination against singles. Current Directions in Psychological Science, 15, 251-254. Etaugh, C., and Birdoes, L. N. (1991). Effects of age, sex, and marital status on person perception. Perceptual and Motor Skills, 72, 491-497. Etaugh, C., and Malstrom, J. (1981). The effect of marital status on person perception. Journal of Marriage and the Family, 43, 801-805. Fineman, M. A. (1995). The neutered mother, the sexual family and other twentieth century tragedies. New York: Routledge. Friedan, B. (1963). The feminine mystique. London: Penguin Books. Gillis, J. R. (1996). A world of their own making: Myth, ritual, and the quest for family values. New York: Basic Books. Gillis, J. R. (2004). Marriages of the mind. Journal of Marriage and Family, 66, 988-991. Gove, W. R., and Shin, H. (1989). The psychological well-being of divorced and widowed men and women. Journal of Family Issues, 10, 122-144. Greenwald, A., McGhee, D. E., and Schwartz, J. K. (1998). Measuring individual differences in implicit cognition: The implicit association test. Journal of Personality and Social Psychology, 74, 1464-1480. Greitemeyer, T. (2007). Stereotypes of singles: Are singles what we think? Manuscript submitted for publication. Helson, R., Mitchell, V., and Moane, G. (1984). Personality and patterns of adherence and non-adherence to the social clock. Journal of Personality and Social Psychology, 46, 1079-1096. Hertel, J., Schütz, A., DePaulo, B. M., Morris, W. L., and Stucke, T. S. (2007). She’s single, so what? How are singles perceived compared with people who are married? Journal of Family Research, 19, 139-158.
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Hochschild, A. R. (2003). The commercialization of intimate life: Notes from home and work. Berkeley: University of California Press. Horowitz, A. V., McLaughlin, J., and White, H. R. (1998). How the negative and positive aspects of partner relationships affect the mental health of young married people. Journal of Health and Social Behavior, 39, 124-136. Illouz, E. (1997). Consuming the romantic utopia: Love and the cultural contradictions of capitalism. Berkeley: University of California Press. Johnson, P., and Leslie, L. (1982). Couple involvement and network structure: A test of the dyadic withdrawal hypothesis. Social Psychology Quarterly, 45, 34-43. Jost, J. T., Banaji, M. R., and Nosek, B. A. (2004). A decade of system justification theory: Accumulated evidence of conscious and unconscious bolstering of the status quo. Political Psychology, 25, 881-920. Keith, P. (1980). Two models of singleness: Managing an atypical marital status. International Journal of Sociology of the Family, 10, 301-310. Keith, P. M. (1986). The social context and resources of the unmarried in old age. International Journal of Aging and Human Development, 23, 81-96. Koropeckyj-Cox, T. (2005). Singles, society, and science: Sociological perspectives. Psychological Inquiry, 16, 91-97. Krueger, J., Heckhausen, J., and Hundertmark, J. (1995). Perceiving middle-aged adults: Effects of stereotype-congruent and incongruent information. Journal of Gerontology: Psychological Sciences, 50B, 82-93. Lucas, R. E., Clark, A. E., Georgellis, Y., and Diener, E. (2003). Reexamining adaptation and the set point model of happiness: Reactions to changes in marital status. Journal of Personality and Social Psychology, 84, 527-539. Lynd, R. S., and Lynd, H. M. (1937). Middletown in transition: A study in cultural conflicts. New York: Harcourt Brace Jovanovich. Major, B., Quinton, W. J., and McCoy, S. K. (2002). Antecedents and consequences of attributions to discrimination: Theoretical and empirical advances. In M. P. Zanna (Ed.), Advances in experimental social psychology: Vol. 34 (pp. 251-330). San Diego, CA: Academic Press. Marini, M. M. (1984). Age and sequencing norms in the transition to adulthood. Social Forces, 63, 229-244. Morris, W. L. (2002). [Are singles perceived negatively because they are thought to have few friends?]. Unpublished raw data. Morris, W. L. (2005). The effect of stigma awareness on the self-esteem of singles. Unpublished doctoral dissertation, Department of Psychology, University of Virginia. Morris, W. L., and DePaulo, B. M. (2002). [Assessing the stereotypes of subtypes of singles]. Unpublished raw data. Morris, W. L., Sinclair, S., and DePaulo, B. M. (2005). [Does the perceived controllability over marital status influence how discrimination against singles is perceived?] Unpublished raw data. Morris, W. L., Sinclair, S., and DePaulo, B. M. (2007). No shelter for singles: The perceived legitimacy of marital status discrimination. Group Processes and Intergroup Relations, 10, 457-470. Neugarten, B. L. (1976). Adaptation and the life cycle. The Counseling Psychologist, 6, 1620.
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Neugarten, B. L., and Neugarten, D. A. (1986). Age in the aging society. Daedalus, 115, 3149. Pew Internet and American Life Project survey (2006, February 13). Romance in America. Retrieved April 2, 2007, from http://www.pewinternet.org/PPF/r/173/report_display.asp. Pillsworth, E. G., and Haselton, M. G. (2005). The evolution of coupling. Psychological Inquiry, 16, 98-104. Rodin, M., Price, J., Sanchez, F., and McElligot, S. (1989). Derogation, exclusion, and unfair treatment of persons with social flaws: Controllability of stigma and the attribution of prejudice. Personality and Social Psychology Bulletin, 15, 439-451. Rook, K. S., Catalano, R., and Dooley, D. (1989). The timing of major life events: Effects of departing from the social clock. American Journal of Community Psychology, 17, 233258. Rook, K. S., and Zettel, L. A. (2005). The purported benefits of marriage viewed through the lens of physical health. Psychological Inquiry, 16, 116-121. Seccombe, K., and Ishii-Kuntz, M. (1994). Gender and social relationships among the nevermarried. Sex Roles, 30, 585-603. Staples, R., and Johnson, L. B. (1993). Black families at the crossroads: Challenges and prospects. San Francisco: Jossey-Bass. Taylor, L. C., Morris, W. L., and Sinclair, S. (2007). Implicit attitudes about married and single people. Manuscript in preparation. Thornton, A., and Young-DeMarco, L. (2001). Four decades of trends in attitudes toward family issues in the United States: The 1960s through the 1990s. Journal of Marriage and Family, 63, 1009-1037. Toutkoushian, R. K. (1998). Racial and marital status differences in faculty pay. Journal of Higher Education, 69, 513-529. Unmarried America. (n.d.). Marital statutes prohibiting marital status discrimination in unemployment. Retrieved December 20, 2003 from http://www.singlesrights.com/msemployment-laws.htm. U.S. Census Bureau. (1970). Marital status of the population by sex, race, and Hispanic origin: 1970 to 1995 (Census of population, vol. 1, part 1, and Current population reports, P20-450). Washington, DC. U.S. Census Bureau. (2001). Marital status of the population by sex, race, and Hispanic origin: 1980 to 2000 (Current population reports, P20-491). Washington, DC. U.S. Census Bureau. (2006). American Community Survey. Washington, DC. Verbrugge, L. M. (1983). A research note on adult friendship contact: A dyadic perspective. Social Forces, 62, 78-83. Waite, L. J., and Gallagher, M. (2000). The case for marriage: Why married people are happier, healthier, and better off financially. New York: Doubleday. Wellman, B., Wong, T. Y., Tindall, D., and Nazer, N. (1997). A decade of network change: Turnover, persistence and stability in personal communities. Social Networks, 19, 27-50. Whitley, B. E. (1990). The relationship of heterosexuals’ attributions for the causes of homosexuality to attitudes towards lesbians and gay men. Personality and Social Psychology Bulletin, 16, 369-377. Zettel, L. A. (2005). Aging alone: Do the social support resources of never-married individuals place them at risk? Unpublished doctoral dissertation, Department of Psychology, University of California – Irvine.
In: The Psychology of Modern Prejudice Editors: Melanie A. Morrison and Todd G. Morrison
ISBN 978-1-60456-788-5 © 2008 Nova Science Publishers, Inc.
Chapter 9
IMPLICIT PRIDE AND PREJUDICE: A HETEROSEXUAL PHENOMENON? Claire Cullen1 and Dermot Barnes-Holmes National University of Ireland, Maynooth
ABSTRACT Findings from American poll data spanning the last two decades reveal that attitudes toward gay men and lesbian women are becoming more liberal. Despite these trends, however, self-report data may fall victim to a range of confounds including selfpresentational biases. Recently, researchers have begun to assess implicit homonegativity (i.e., attitudes toward gay men and lesbian women that are relatively unconscious and beyond volitional control) using a range of implicit measures. This chapter reviews the studies published to date in the area of implicit homonegativity. The findings show that implicit attitudes as measured by the Implicit Association Test, the Sequential Priming Procedure and the Implicit Relational Assessment Procedure differ as a function of group status (i.e., heterosexual versus non-heterosexual). Specifically, implicit in-group “pride” and out-group “prejudice” were repeatedly produced by heterosexual participants. In contrast, non-heterosexuals were relatively egalitarian in their expression of implicit attitudes. Furthermore, in many of the studies, a divergence in performance between implicit and explicit attitudes toward gay men and lesbian women was observed.
INTRODUCTION Negative attitudes toward gay men and lesbian women have a long history. Prior to the Stonewall riots in Greenwich Village in 1969, psychological research focused mainly on the
1
This work was supported, in part, by grants from the National University of Ireland, Maynooth and The Irish Research Council for Science, Engineering and Technology (IRCSET). Correspondence concerning this chapter should be addressed to Claire Cullen or Professor Dermot Barnes-Holmes, Department of Psychology, National University of Ireland, Maynooth, County Kildare, Ireland. E-mail:
[email protected] or
[email protected].
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causes and cures for what was considered the homosexual ‘pathology’ (Foucault, 1967; Masters, Johnson, and Kolodny, 1995; Weeks, 1983).2 For example, by the 1930s, Nazi medical authorities had accumulated a wealth of literature chronicling the so-called ‘degeneracy’ of gay men and lesbian women (Proctor, 1995; Weeks, 1983). Until the 1950s, gay men and lesbian women were diagnosed as mentally disordered and, as such, were imprisoned, given shock and drug therapies and, in many cases, executed (Terry and Urla, 1995). During the 1960s, however, researchers switched their attention from diagnosis to the study of attitudes toward homosexuality. This new focus on attitudes was paved by Weinberg’s (1972) introduction of the term ‘homophobia,’ which he defined as “the dread of being in close quarters with homosexuals – and in the case of homosexuals themselves, selfloathing” (p. 4; emphasis added). Recently, Herek (2000) proposed that the term homophobia be replaced by the less emotionally loaded term ‘sexual prejudice’ (i.e., negative attitudes toward an individual because of his or her actual or perceived sexual orientation). Herek (2000) suggested that anti-gay attitudes are more akin to prejudice than phobia. Yet another word in the anti-gay-attitude vernacular is the term ‘homonegativity,’ which has been defined by Morrison and Morrison (2002) as derogatory attitudes toward gay men and lesbian women. Although these terms are based upon slightly different theoretical conceptualizations, they each refer to anti-gay beliefs. The present chapter begins with an overview of results (spanning the last two decades) from a range of large and representative national surveys undertaken in the USA to assess attitudes toward gay men and lesbian women. This is followed by a discussion of the Modern Homonegativity Scale (MHS; Morrison and Morrison, 2002) which was developed to capture subtle forms of explicit prejudice toward gay men and lesbian women. The problems associated with self-report measures lead us to a discussion of the most popular and most researched measure of implicit attitudes, namely, the Implicit Association Test (IAT; Greenwald, McGhee, and Schwartz, 1998). This discussion is followed by a review of the range of studies that have used the IAT for the assessment of implicit homonegativity. Particular emphasis will be placed upon the roles of a variety of procedural, demographic and psychological variables, focusing on the correspondence between implicit and explicit attitudes. Finally, a range of implicit measures that offer an alternative to the IAT as a measure of implicit homonegativity will be considered.
SELF-REPORT MEASURES OF HOMONEGATIVITY Traditionally, psychologists have relied upon direct self-report methods, such as questionnaires to measure anti-gay attitudes (De Houwer, 2006). One of the earliest American opinion surveys of attitudes toward homosexuality was a 1965 Harris Poll which found that 70% of respondents reported that gay men and lesbian women were harmful to American life (Herek, 2002). In 1970, more than 70% of a representative household nationwide probability sample of 30,018 American adults reported that sexual acts between two persons of the same 2
The American Psychological Association (APA) has recommended the following terms when referring to specific persons or groups. The adjective terms ‘lesbian’ and ‘gay male’ are preferred to ‘homosexual;’ and the noun terms “lesbians” and ‘gay men’ are preferred to ‘homosexuals’ (Herek, Kimmel, Amaro, and Melton, 1991). We follow the recommendations of APA, except when referring to studies (and quoting scale-items) that have employed ambiguous and conceptually unclear terms such as ‘homosexual(s)’ and ‘homosexuality.’
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sex are “always wrong” (Levitt and Klassen, 1974, p. 31). This survey also revealed that more than 80% reported they would not associate with “these people” if they could avoid it (p. 42). In addition, 65.2% reported that sexual activity or love between persons of the same sex is very much “obscene and vulgar” (p. 34). Furthermore, fear and distrust toward gay men and lesbian women emerged in the survey results. Specifically, 73.5% agreed that gay men and lesbian women are “dangerous as teachers or youth leaders because they try to get sexually involved with children”. In addition, 43.1% strongly agreed that gay men and lesbian women are “a high security risk for government jobs” (p. 34). Analyses of the polls spanning the last twenty years reveal that, in the West, self-reported negative attitudes toward gay men and lesbian women are fading (see Herek, 2000; Hicks and Lee, 2006; Steffens and Wagner, 2004; Yang, 1997, for reviews). However, the findings are not as clear-cut as one might assume (see Yang, 1997). For example, Loftus’ (2001) analysis of the 1973 to 1998 General Social Survey data (GSS; which employed a large national area probability sample of non-institutionalized adults) revealed that in the USA between the years of 1973 and 1976, attitudes regarding the morality of homosexuality became quite liberal. This liberal trend was interrupted by the expression of more conservative attitudes between 1976 and 1990, after which time a liberal trend resumed. Altemeyer’s (2001) investigation of the 1984 to 1998 GSS data similarly showed an increase in liberal attitudes toward homosexuality in the U.S., although beginning at an earlier date than that suggested by Loftus. In another analysis of the GSS data, Treas (2002) showed a decrease in liberal attitudes toward same-sex relations over a fifteen year period. Specifically, in 1973, more than 74.3% of respondents reported that sexual relations between two adults of the same sex are ‘always wrong’. This figure increased to 76.8% in 1988, but by 1998 had dropped to 58%. Logistic regression analyses revealed that age, education, frequency of attendance at religious services and survey year were significant sources of the latter decrease (Treas, 2002). Between 1988 and 1998, those who were younger, less educated, and less religious showed the largest reduction in anti-gay attitudes. Age, however, produced the strongest effects; that is, individuals aged between eighteen and twenty-eight years were 95% less likely than older individuals to express anti-gay attitudes. A recent joint analysis of the 1970s to 2003 Gallup Polls and the 2000 National Election Study (NES) data, conducted by Hicks and Lee (2006), suggested that U.S. attitudes toward same-sex relations have become more positive. Again, however, the findings were equivocal. In 1977, for example, 43% of respondents said that sexual activity between two persons of the same sex should be legalized. In 2001, 54% agreed with this view and in May 2003 this rose to 60%, but fell to 50% just two months later. While the trends summarized herein relied upon large random samples, there are limitations to drawing conclusions from such data. In particular, the wording and ordering of questions may have affected the observed trends. In addition, the majority of studies outlined (e.g., Hicks and Lee, 2006; Levitt and Klassen, 1974; Loftus, 2001; Treas, 2002; Yang, 1997) asked questions about sex-unspecified same-sex relations. Previous research (e.g., Kite and Whitley, 1996) has shown that using the generic term ‘homosexual’ in place of gay men and lesbian women in survey questions often produces an assumption that the target is male. The study of self-reported attitudes toward gay men and lesbian women has conventionally relied upon measures that assess ‘traditional’ or ‘old-fashioned’ homonegativity, which focuses on religious or moral objections (Morrison, Kenny, and Harrington, 2005). Examples of traditional forms of homonegativity include statements such
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as “gay men and lesbian women should not be allowed to be members of churches or synagogues”, and “homosexuality is a social corruption that can cause the downfall of a civilisation.” Over the last two to three decades, a non-monotonic liberalization in attitudes toward gay men and lesbian women has been revealed on survey measures that have assessed old-fashioned homonegativity. Recently, however, it has been suggested that the assessment of ‘modern homonegativity’ may reveal a more subtle kind of prejudice toward gay men and lesbian women than that revealed on measures of old-fashioned homonegativity (Morrison et al., 2005). Modern homonegativity is contingent upon the espousal of at least one or more of the following beliefs: … (a) Gay men and lesbian women are making unnecessary demands for social change (e.g., the right to marry); (b) prejudice and discrimination against gay men and lesbian women have become a thing of the past; and (c) gay men and lesbian women place too much emphasis on their sexuality and, in so doing, are culpable for their own marginalization (Morrison et al., 2005, pp. 220-221).
The Modern Homonegativity Scale (MHS; Morrison and Morrison, 2002) was developed to measure the construct of “modern homonegativity”. Attitudinal (Morrison et al., 2005) and behavioural (Morrison and Morrison, 2002) evidence in support of the reliability and validity of the measure has been provided. Specifically, a study conducted in the West of Ireland showed that 46% of male respondents endorsed the following statement from the MHS: “Gay men should stop shoving their lifestyle down other people’s throats” and 29% agreed with the statement “Lesbian women should stop shoving their lifestyle down other people’s throats” (Morrison et al., 2005, p. 243). In a Canadian study, Morrison and Morrison (2002) revealed that participants high in modern homonegativity (as measured by the MHS), avoided sitting beside a confederate wearing a T-shirt with a pro-gay or pro-lesbian slogan in a context in which doing so could be perceived as non-prejudicial. In summary, while the data from the polls over the last twenty years suggest that attitudes toward gay men and lesbian women are becoming more liberal, it appears that subtle forms of homonegativity may have replaced more traditional forms. Further, it should be noted that old-fashioned homonegativity has not evidenced a monotonic decline since the 1970s; rather, it appears to ebb and flow.
PROBLEMS WITH SELF-REPORT MEASURES In recent times, confounds inherent in self-report methods have been generally noted (e.g., de Jong, 2002; Gemar, Segal, Sagrati, and Kennedy, 2001; Raja and Stokes, 1998; Teachman, Gregg, and Woody, 2001). For example, individuals may be aware that their attitudes are socially undesirable and, therefore, employ strategies to conceal them from researchers (Paulhus, 1984; Rust and Golombok, 1999). Alternatively, individuals may not be aware that they hold a particular attitude and, thus, fail to report it (Dambrun and Guimond, 2004). These problems are further compounded by the fact that the way in which questions are presented or phrased in self-report instruments may influence an individual’s response (Rasinski, 1989). Furthermore, even if a self-report measure of subtle prejudice is used, such
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as the MHS, it is still relatively easy to self-present an egalitarian view (cf. Fazio, 1995), once a participant is aware of what constitutes subtle prejudice.
IMPLICIT ATTITUDES In order to circumvent these problems, researchers have devoted increasing attention to studying implicit attitudes. As defined by Greenwald and Banaji (1995), implicit attitudes are “introspectively unidentified or inaccurately identified traces of past experience that mediate favorable or unfavorable feeling, thought, or action toward social objects” (p. 8; see also Wilson, Lindsey, and Schooler, 2000). Although debate continues over the adequacy of this definition (see De Houwer, 2006), the core argument is that implicit attitudes are often unconscious and, thus, their influence on subsequent behaviors may go unnoticed. Insofar as implicit attitudes are often unconscious, traditional explicit measures such as questionnaires and open-ended interviews will likely fail to capture these psychological variables. As a result, researchers have attempted to develop reaction-time based methodologies in which implicit attitudes are inferred based on response speed and accuracy (see De Houwer, 2006). The Implicit Association Test (IAT; Greenwald et al., 1998) is currently the most popular reaction-time based measure of implicit cognition and its basic effect has been replicated many times (Greenwald, Nosek, Banaji, and Klauer, 2005). For example, the IAT has been used to assess implicit cognitions in domains such as sexism (e.g., Rudman and Glick, 2001), racism (e.g., Greenwald et al., 1998), religious stereotyping (e.g., Rudman, Greenwald, Mellott, and Schwartz, 1999) and ageism (Dasgupta and Greenwald, 2001), as well as a variety of political issues (see Nosek, Banaji, and Greenwald, 2002) and self-esteem (e.g., Bosson, Swann, and Pennebaker, 2000). As an indirect measure of implicit attitudes, the IAT rests on the assumption that participants should categorize concepts together that are strongly associated in memory more rapidly than concepts that are weakly associated (Greenwald et al., 1998). In a seminal study, Greenwald et al. (Experiment 1) used the IAT to test responses to four categories of items (e.g., flowers, insects, pleasant words, and unpleasant words). The researchers assumed that the concept flower and the attribute pleasant are associated in memory as are the concept insect and the attribute unpleasant. Based on this assumption, Greenwald et al. reasoned that responses should be faster when response key assignment was congruent (e.g., key 1 = flower and pleasant versus key 2 = insect and unpleasant) rather than incongruent (e.g., key 1 = flower and unpleasant versus key 2 = “insect” and pleasant). As predicted, mean response latencies were shorter for congruent relative to incongruent tasks. In a subsequent investigation, Greenwald et al. (1998; Experiment 3) employed the IAT to determine White college students’ implicit attitudes toward Black people The IAT presented traditional Black names (e.g., Jamel) and White names (e.g., Hank) together with positive words (e.g., friend) and negative words (e.g., murder). Greenwald et al. predicted that responses should be faster when response key assignment was congruent (e.g., key 1 = “White names” and “pleasant” versus key 2 = “Black names” and “unpleasant”) rather than incongruent (i.e., White-unpleasant versus Black-pleasant). Results were congruent with their prediction and, thus, a pro-White/anti-Black implicit bias was inferred from participants’ IAT
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performance. Critically, results for explicit measures diverged from those obtained on the IAT. In addition to the IAT, a range of so-called implicit measures, such as the Go/No-go Association Task (GNAT; Nosek and Banaji, 2001), Evaluative Priming (Fazio, Sanbonmatsu, Powell, and Kardes, 1986), the Emotional Stroop (Pratto and John, 1991) and the Extrinsic Affective Simon Task (EAST; De Houwer, 2003) have been offered. With the exception of the EAST, these alternative measures will not be discussed. To our knowledge, the EAST is the only established reaction time implicit measure apart from the IAT that has been used to assess implicit homonegativity.
THE IMPLICIT MEASUREMENT OF HOMONEGATIVITY Initial IAT studies. To date, the Implicit Association Test (IAT) has been the main methodology used for the assessment of implicit homonegativity. The first such study was reported by Banse, Seise, and Zerbes (2001), who conducted two experiments that examined the psychometric properties (Experiment 1) and fakeability (Experiment 2) of their Homosexuality-IAT. All participants were naïve with regard to the functioning of the IAT. In the first experiment, heterosexual males and females and gay men and lesbian women were used (i.e., a known-groups approach was adopted). Exclusively male heterosexuals were recruited for the second experiment. In addition to the Homosexuality-IAT (outlined subsequently), explicit affective and cognitive attitudes (Experiments 1 and 2) and the motivation to control prejudice (Experiment 2) were assessed. The Homosexuality-IAT assessed implicit attitudes toward both gay and lesbian sexual orientations by testing responses to the following four categories of items: heterosexual (e.g., photographs of opposite-sex couples), gay men and lesbian women (e.g., photographs of same sex couples; specifically, half of the photographs depicted male couples, and half depicted female couples), pleasant words and unpleasant words. Banse et al. assumed that for heterosexual participants, the concepts heterosexual + pleasant are likely associated in memory as are gay men/lesbian women + unpleasant. The reverse was assumed for the gay and lesbian participants. It was posited that speed and accuracy of responding on the IAT would reflect these associations. In Experiment 2, four conditions were employed to assess the extent to which the Homosexuality-IAT was resistant to manipulation in comparison to explicit measures (Fazio, 1995). Specifically, participants in a control condition were advised that the aim of the study was “to develop new measures of attitudes toward homosexuality.” In the ‘demand condition’ participants were told that “Even today people are discriminated against because of their sexual orientation; therefore, attitudes toward homosexuality are an important research topic” (Banse et al., 2001, p. 155). In the ‘persuasion condition,’ this line was supplemented with the following anti-homonegative information: (a) three texts; (b) a film clip; and (c) details regarding the struggle of various gay organizations. The ‘manipulation condition’ assessed if participants could fake an extremely positive attitude to homosexuality when asked to do so.
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Results showed that, in general, attitudes toward homosexuality were relatively positive. In Experiment 1, however, implicit and explicit attitudes converged to reveal in-group biases for both groups (i.e., heterosexually- and homosexually-identified participants). Specifically, the IAT correlated moderately with explicit cognitive attitudes toward homosexuality (e.g., “Male homosexuality is a sickness” or “Lesbian women should not work with children or adolescents”) but strongly with the affective attitudes (e.g., I would feel very uncomfortable if “I learn that a teacher of my son is gay” or “Nearby two lesbians are kissing each other”). A significant main effect for gender suggested that compared to females, males were more homonegative on each type of measure. A main effect for sexual orientation suggested that compared to gay men and lesbian women, heterosexuals were more explicitly and implicitly homonegative. These main effects, however, were not qualified by a gender x sexual orientation interaction effect. In the second experiment, participants were able to fake a more positive explicit but not implicit attitude toward gay men and lesbian women. Neither implicit nor explicit attitudes were influenced by persuasive information. Individuals with a weak motivation to control prejudice showed more homonegativity on both the IAT and the cognitive (but not affective) explicit measure than those who were strongly motivated. In 2003, German researchers Steffens and Buchner published results from two experiments designed to explore the transituational stability (i.e., test-retest reliability) of the IAT using structural equation modeling. In contrast to Banse et al. the IAT used by Steffens et al. assessed implicit attitudes toward male homosexuality and male-female heterosexuality. IAT responses to the following four categories of items were assessed: heterosexual men and women (e.g., couple names: Michael + Sarah), gay men (e.g., couple names: Thomas + Philip), pleasant words and unpleasant words. Given their sample (i.e., heterosexual and homosexual men and women), it was assumed that responses would reflect pro-straight/antigay attitudes. In addition to the IAT, explicit measures were administered to participants in both experiments. In the first experiment, the IAT was repeated after one week whereas in the second experiment, it was repeated after only 10 minutes. In the latter case, the IAT also was modified to improve test-retest reliability (i.e., more items were presented to participants and the stimuli were altered), but the changes proved to have no effect. In both experiments, explicit attitudes toward gay men were positive and stable across situations. In contrast, implicit attitudes were negative and unstable. This was confirmed by the test-retest correlation for the explicit attitudes which was significantly higher than the correlation obtained for the implicit attitudes. Correlations between implicit and explicit attitudes were moderate. Specifically, in the first study, implicit attitudes assessed on both the first and second measurement occasions were related to explicit attitudes assessed on both occasions. The correlations between implicit and explicit attitudes slightly improved when both were assessed on the second measurement occasion. Despite a change of explicit measure, the same pattern of correlations was observed in the second study. Excluding the non-heterosexual participants did not change the results of the statistical tests. In summary, these findings were taken to indicate that IAT effects measured at a given point in time should not be interpreted as reflecting stable trait-like cognitions. The review of IAT studies examining implicit homonegativity reveals that in-group biases were repeatedly evidenced by heterosexuals but not by non-heterosexuals. Thus, in general, evidence for the known-groups validity of the homosexuality-IAT was provided. In addition, the IAT was shown to be impervious to persuasion and faking, but repeated
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administrations revealed that the measure is relatively unstable and, thus, cannot be used to assess individual traits.
THE IAT AND MODERATING VARIABLES In the first American-based study, Jellison, McConnell, and Gabriel (2004) reported two experiments germane to the work reported by Banse et al. (2001), with the exception that only male participants were used because previous research has shown that homonegativity is more common among men than among women (e.g., Adams, Wright, and Lohr, 1996; Banse et al., 2001). In their first experiment, using a known-groups approach, Jellison et al. (2004) assessed whether implicit and explicit attitudes would: (a) be related; (b) differ as a function of participants’ sexual orientation; and (c) predict behaviors relevant to sexual orientation among gay men. The second experiment which employed only heterosexual participants replicated and extended the first experiment by investigating the moderating influence of motivation to control prejudice and traditional gender and identity role norms on the relationship between implicit and explicit homonegativity. The Homosexuality-IAT3 assessed implicit attitudes toward male homosexuality, using a combination of images and verbal stimuli. A modified version of the Homosexuality-IAT was used in their second experiment. In addition to the IAT, explicit attitudes toward male homosexuality were assessed via a range of self-report questionnaires. The gay male participants in Experiment 1, however, completed various behavioral questionnaires constructed to assess immersion in gay culture and self-presentational strategies such as counterfeiting a heterosexual identity or avoiding disclosure of sexual orientation. Consistent with previous research (e.g., Banse et al., 2001; Steffens and Buchner, 2003), implicit and explicit sexual orientation attitudes were related and differed as a function of participants’ sexual orientation. Specifically, significant in-group and relatively strong outgroup implicit and explicit biases were produced by both heterosexual and gay male participants. That is, on all of the measures, participants produced positive attitudes towards their own sexual orientation in-group and negative attitudes toward their sexual orientation out-group. Interestingly, compared to the gay male participants, the implicit in-group biases were stronger for the heterosexual participants. The measures also predicted separate gayrelated behaviors. In particular, implicit attitudes predicted involvement and immersion in gay culture, while explicit attitudes predicted self-disclosure behaviors for gay men. In the second experiment, the pro-straight implicit and explicit in-group bias was related to endorsements of heterosexual identity and traditional masculine gender roles (Herek, 2002). Contrary to Banse et al. (2001), implicit attitudes were not related to motivation to control prejudice. In the same year, Jost, Banaji and Nosek (2004) analysed the data from heterosexual and gay respondents obtained between March and October 2002, from the Gay-Straight IAT
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Jellison et al. (2004) actually refer to their IAT as the Sexual Orientation-IAT. However, that IAT was a conceptual replication of the IAT offered by Banse et al. (2001) and, thus, for consistency we refer to it as the Homosexuality-IAT.
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tasks4 available at http://tolerance.org. Their study was undertaken to explore the moderating influence of self-reported conservatism on implicit and explicit homonegativity. The IAT employed a mixture of symbols and words as stimuli. Results showed that both gay and heterosexual groups produced strong explicit in-group biases but only the heterosexuals produced strong implicit in-group biases. Gay respondents exhibited only a slight implicit in-group bias. In fact, contrary to previous research (e.g., Banse et al., 2001; Jellison et al., 2004), findings indicated that more than a third (37.5%) of gay participants showed an implicit out-group bias. Political conservatism was strongly predictive of implicit and explicit in-group biases for heterosexual participants. In contrast, political conservatism predicted out-group implicit and explicit biases for the gay participants. One year later, as part of a larger study measuring implicit attitudes to a diverse range of social targets, Nosek, Greenwald and Banaji (2005) analyzed the data from two Gay-Straight IAT tasks available at the same demonstration website (i.e., http://tolerance.org). The study sought to assess if subtle shifts in semantic meaning of the exemplars representing the concept category ‘Gay’ could influence IAT effects. No details pertaining to participant sexual orientation were provided by the researchers. The two IATs, which employed a total of 24 picture and verbal stimulus items, were almost identical with the exception that the emphasis of two items representing the category ‘Gay’ were shifted to emphasize gender (i.e., lesbian women or gay men). All remaining stimuli were held constant across the tasks. Stimulus modality (i.e., pictures or words) was not shown to influence IAT effects. As a result of changing the salience of only two of the exemplars, differences in implicit attitudes toward homosexuality emerged between the two IAT tasks. That is, consistent with previous explicit attitude research (e.g., Herek, 1984), implicit homonegativity was stronger when gay men as opposed to lesbian women were emphasized. Using male and female heterosexual and homosexual students, Steffens (2005) conducted three experiments in Germany to explore implicit and explicit attitudes toward both lesbian women and gay men on separate IAT tasks. In the first experiment, half of the participants started with the Lesbian Women-IAT first and half started with the Gay Men-IAT first. In the second study, implicit gender-related attitudes were first assessed via a Gender-Self-Concept IAT. Directly afterwards, males responded to the Gay Men-IAT and females responded to the Lesbian Women-IAT. In the final study, the order of Lesbian and Gay-IATs and GenderRole-IATs were counterbalanced. In all three studies, implicit attitudes were assessed prior to explicit attitudes. The experiments assessed if implicit and explicit attitudes would: (a) be related; (b) differ as a function of the target (e.g., lesbian women and gay men) and participant sexual orientation; and (c) differ as a function of gender related beliefs (Study 2 and 3). Contrary to Nosek et al., the IAT tasks employed verbal stimuli only. Although attitudes were not extremely negative, heterosexual males repeatedly expressed implicit and explicit in-group biases across the studies (Banse et al., 2001) while females did not. In the first study, both implicit and explicit attitudes toward gay men and lesbian women were related. The correlations, however, were subject to order effects. Specifically, beginning with the Gay Men-IAT resulted in a strong relationship between implicit and explicit attitudes, but this relationship disappeared for participants who completed the Lesbian 4
The term ‘straight’ is used here (instead of heterosexual) to maintain consistency with the terminology employed by Jost et al. (2004).
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Women-IAT first. Furthermore, sexual orientation was related to implicit attitudes toward gay men but only for participants who had undertaken the Gay Men-IAT first. Finally, a small correlation was observed between sexual orientation (sex was controlled for) and explicit attitudes towards gay men and lesbian women. In the second study, there were no correlations among the implicit attitudes toward gay men and lesbian woman and implicit gender-related attitudes. Females’ implicit attitudes toward lesbian women and explicit gender-related attitudes were related. Sexual orientation was correlated with implicit gender-related attitudes but only for males. That is, males screened as heterosexual more strongly associated self + male on the Gender Self-ConceptIAT. In the final study, again, no relationships were observed among implicit attitudes toward gay men and lesbian woman and implicit gender-related attitudes. There were, however, correlations between the explicit measures. Specifically, for both genders, explicit attitudes toward gay men and lesbian women were strongly related. In addition, males’ explicit attitudes toward working women were related to attitudes toward lesbian women and gay men (the latter correlation was stronger). For females, modern sexism was related to explicit attitudes toward lesbian women and gay men (again, the latter correlation was the stronger of the two). The Lesbian-IAT was moderately related to explicit attitudes towards lesbian women, explicit modern sexism, and explicit gender-related attitudes. The Gay Men-IAT was moderately related to explicit attitudes toward working women. Unlike the first two studies, sexual orientation was unrelated to implicit and explicit attitudes. A combined analysis of the data from all three experiments (controlling for sex) revealed in-group implicit biases for the small number of lesbian and gay participants but interestingly not for bisexual participants. In another American-based study, the IAT was used to determine to what extent implicit homonegativity is moderated by religious dimensions of personality (Rowatt et al., 2006). The IAT assessed participants’ implicit attitudes toward male homosexuality and employed a mixture of images and words as stimuli. In addition, self-reported religious orientation, impression management and attitudes toward homosexuality were assessed. Unfortunately, no details pertaining to participant sexual orientation were provided. As a group, participants produced a pro-straight/anti-gay bias on both the IAT and the explicit attitudinal measures. Contrary to previous research (e.g., Banse et al., 2001), no sex differences in IAT performance were observed. After controlling for impression management, explicit and implicit attitudes toward homosexuality were weakly correlated. Religious fundamentalism, Christian orthodoxy, right-wing authoritarianism, and impression management predicted both implicit and explicit homonegativity with religious fundamentalism being the strongest predictor. The following year, the data obtained between 2000 and 2006 from the Gay-Straight IAT tasks available on http://implicit.harvard.edu.were analyzed as part of a larger demonstration website data analysis of 17 different social targets (Nosek et al., 2007). The research was undertaken to assess if implicit and explicit homonegativity are (a) pervasive across demographic groups; (b) moderated and predicted by inter-individual difference variables (demographic as opposed to psychological); and (c) related constructs. The sexual orientation of the participants was not reported. The IAT and explicit measures were exactly the same as those employed in the Jost et al. (2004) study. The results showed that, in general, implicit and explicit homonegativity are relatively pervasive across demographic groups. Replicating previous studies, the majority (i.e., 68%) of participants showed a pro-straight implicit bias
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but only 15% produced a pro-gay implicit bias. Implicit and explicit attitudes to sexual orientation were moderately related. In fact, this was the strongest relationship evidenced across all 17 social group attitudes assessed. In addition, there was considerable interindividual variability. Consistent with previous research (for reviews see Herek, 1984; Kelley, 2001; Kite and Whitley, 1996; Weishut, 2000), implicit and explicit attitude relationships were moderated by gender, ethnicity, nationality, political orientation, and age. Specifically, compared with females, males were more implicitly and explicitly homonegative. With regard to ethnicity, white individuals were less homonegative than black individuals. Participants from the U.S. and Asia showed stronger implicit and explicit pro-straight biases than those from Australia, Canada, Europe and the U.K. Politically liberal individuals produced a moderate pro-straight implicit bias but no explicit bias. In contrast, conservatives produced a strong pro-straight bias on both implicit and explicit measures. Interestingly, for liberals, implicit attitude effect magnitudes were stronger than those for explicit attitudes, but the reverse was the case for conservatives. Age moderated the relationship between implicit and explicit attitudes toward homosexuality but not in the usual way (see, for example, Herek, 1984; Hudson and Ricketts, 1980). A curvilinear pattern on both the IAT and the explicit measures showed that older and younger participants produced stronger pro-straight biases than their middle-aged counterparts. In summary, consistent with previous research using self-reported attitudes toward homosexuality (e.g., Herek, 1984), research has shown that implicit homonegativity is moderated by a range of inter-individual differences (both demographic and psychological). The type of exemplars employed by the IAT also was observed to influence IAT effects. Critically, the IAT was shown to predict gay-related behavior.
FOCUSING ON THE MODERATING EFFECTS OF MOTIVATION Given the somewhat inconsistent findings observed in previous research regarding the influence of motivation to control implicit homonegativity, the following five studies targeted this issue in particular. The first of these studies (Rohner and Björklund, 2006) assessed implicit and explicit attitudes toward both male and female homosexuality with a sample of predominantly heterosexual participants. Motivation to control homonegativity was directly as opposed to self-reportedly manipulated using two experimental conditions (i.e., attend to homosexuality – socially sensitive; and attend to age – less socially sensitive). Specifically, a computerised picture rating measure (PRM) presented images of same and opposite-sex couples to participants who were instructed to rate each picture in terms of its positive and negative valence. Instructions were manipulated, such that participants assigned to the ‘attend to homosexuality condition were informed that attitudes toward gay and lesbian couples were being assessed. In the ‘attend to age’ condition, participants were told that attitudes towards young and old couples were being investigated. In their second experiment, a known-groups approach was employed to investigate if implicit attitudes, as measured by the IAT from Experiment 1, differed as a function of sexual orientation. The results of Experiment 1 showed that consistent with previous research, in general an implicit pro-straight/anti-gay bias was produced on the IAT and the computerised PRM. On
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the PRM, attending to homosexuality as opposed to age resulted in a larger number of participants giving negative ratings to same-sex pictures. Picture ratings and explicit attitudes toward homosexuality were strongly related, but the IAT was only weakly correlated with both of these measures. Contradicting the findings of Banse et al. (2001), neither implicit nor explicit attitudes were influenced by motivational intent. The results of Experiment 2 showed that implicit attitudes differed as a function of participant sexual orientation, with heterosexual participants evidencing an in-group bias on the IAT. In contrast, gay men and lesbian women produced relatively neutral attitudes. Consistent with Rowatt et al. (2006), no sex differences in implicit or explicit attitudes were observed in either of the two experiments. American researchers, Boysen, Vogel, and Madon (2006), conducted two experiments to explore the moderating influences of situational and motivational variables on heterosexual participants’ implicit and explicit attitudes toward homosexuality. A modified version of the Banse et al. (2001) IAT was employed to assess implicit attitudes toward both lesbian women and gay men. Participants assigned to the ‘public assessment condition’ were told that the experimenter would be privy to their IAT and explicit scores. In the ‘private assessment condition’ all measures were completed in private and participants were informed that their attitudes toward homosexuality would remain private. Consistent with earlier research, participants generally produced pro-straight in-group biases on the IAT. The bias was reduced by more than half when assessed in the public assessment situation. A similar pattern emerged for the explicit attitudes. That is, in general intolerant attitudes were produced on the Index of Homophobia (Hudson and Ricketts, 1980) and on the Heterosexism Scale (Park and Bieschke, 2002). Participants expressed less hostility toward gay men and lesbian women on these explicit measures in the public assessment situation compared to the private assessment situation (the difference was significant for the Heterosexism Scale only). Implicit and explicit attitudes toward gay men and lesbian women were unrelated in the public setting. In the private setting, however, attitudes expressed on the IAT and on the Heterosexism Scale were weakly correlated, but this measure specific effect is not discussed by the authors. In the second experiment, the participants completed the IAT used in Experiment 1, in a public assessment situation under either a ‘bogus pipeline’ or ‘no-bogus pipeline’ condition. All participants believed that skin conductance and heart rate would be monitored following completion of the IAT (although none were actually monitored). Participants in the no-bogus pipeline condition believed that this was part of a separate study but those in the bogus pipeline condition believed that the experimenter would have access to their ‘true’ attitudes toward homosexuality. A manipulation check revealed that participants in the latter condition were significantly more nervous than their no-bogus pipeline counterparts. The basic assumption was that participants in the bogus-pipeline condition would not be motivated to manipulate their IAT performance because the ‘truth’ would be revealed by the skin conductance measure; in contrast, participants in the no-bogus pipeline condition would be motivated to the same level as participants in the public condition in Experiment 1. Interestingly, implicit homonegativity was unaffected by the bogus pipeline manipulation. The authors, thus, concluded that the impact of the public setting on the IAT performance occurred via a process that remains outside participants’ awareness or voluntary control. Previous researchers had not distinguished between both internal and external sources of motivation to control prejudice when assessing its influence on implicit homonegativity. Furthermore, the influence of inter-group contact on implicit homonegativity had been a relatively under-studied phenomenon up to this point, with Jellison et al. (2004) reporting an
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attenuating effect for heterosexual males but with no data on females. Lemm (2006) was the first to assess the dual roles of internal and external sources of motivation and inter-group contact on implicit and explicit homonegativity. Implicit and explicit attitudes toward gay males were assessed. Prior to assessing explicit attitudes toward gay men, heterosexual participants’ implicit attitudes were assessed via separate counterbalanced IAT tasks. One IAT employed verbal stimuli and another employed picture stimuli. Replicating the pattern observed in earlier research, generally a strong pro-straight ingroup implicit bias was produced on the IAT but not on the explicit measures. Implicit and explicit attitudes were moderately correlated, and the two IATs were strongly correlated. As observed by previous researchers, implicit and explicit attitudes toward homosexuality did not differ significantly between the sexes. Positive implicit and explicit attitudes toward gay men were related to the amount and nature of contact with gay, lesbian, and bisexual individuals. In addition, participants who received direct disclosure of sexual orientation from their closest contacts reported less anti-gay attitudes than those who had not. Explicit and implicit attitudes toward gay men were moderated by self-reported internal but not external motivation to control prejudiced reactions. Participants who had self-reported high internal motivations were significantly less homonegative than those reporting low internal motivations. Amount of contact was weakly related to internal motivation. Motivation (both internal and external), however, was a stronger predictor of implicit and explicit homonegativity than contact. Dasgupta and Rivera (2006) conducted two experiments to investigate the extent to which the relationship between implicit homonegativity and negative behavior is jointly moderated by: (a) conscious motivation to have egalitarian gender-related attitudes; and (b) conscious control over subtle behaviors. The IAT employed a mixture of pictures and words to assess heterosexuals’ implicit attitudes toward gay men. In addition, self-reported attitudes about gender roles and gender identity, and self-reported behavioral control were assessed. Contrary to previous research, explicit attitudes toward homosexuality were not measured. Finally, six items (adopted from McConnell and Leibold, 2001) were used to code behaviors as positive or negative reactions toward either a gay male or heterosexual male confederate. In particular, three items (i.e., amount of eye contact, number of smiles, and body posture) focused on specific behaviors observed to occur between the participant and confederate. A further three (i.e., the participant’s overall friendliness, apparent comfort, and apparent interest in the interaction with the confederate) focused on global behaviors. The second experiment replicated the first, but used a more diverse sample. Across the experiments, participants evidenced the in-group implicit biases typically found in implicit homonegativity research. The anti-gay implicit bias worsened, however, in the second experiment. Additionally, self-reported gender-related beliefs were more traditional among males than among females. IAT and gender-related effects were more pronounced both for males and overall in Experiment 2. In the first experiment, both sexes reacted positively toward the confederate irrespective of his perceived sexual orientation. In the second experiment, compared to females, male behavioral reactions toward the gay confederate were more negative. Implicit homonegativity was related to discriminatory behavior among participants who were both weakly motivated to be egalitarian and unable to control their behavior. A final IAT study, based in Switzerland, investigated the joint moderating effects of situational and person variables on the relationship between implicit attitudes toward gay men and lesbian women and deliberate helping behaviour (Gabriel, Banse, and Hug, 2007). The
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IAT, which had been used by Banse et al. (2001), was employed to assess heterosexual men’s implicit attitudes toward both lesbian women and gay men. Explicit attitudes toward homosexuality also were measured. Helping behaviour was examined by providing participants with an opportunity to donate money to a local gay organisation and sign a petition. Internal motivation to control homonegativity was assessed both explicitly and experimentally by the absence or presence of an experimenter who sought support for a local gay organisation. Relationships between implicit and explicit attitudes were weak. The relationship between implicit attitudes toward homosexuality and deliberate helping behaviour was moderated by situational and person variables. More helping behaviour was shown in the public rather than private situation. Individuals who were less internally motivated to control homonegativity showed corresponding implicit and explicit attitudes, while a divergence was shown for highly motivated individuals. Helping behaviour in the public setting only was predicted by implicit attitudes and motivation to control homonegativity. Surprisingly, in the public setting, participants who had more positive implicit attitudes and a strong motivation to control homonegativity showed the least helping behaviour for a gay organisation. The authors explained this result by suggesting that individuals who are both highly motivated to control prejudice and hold pro-gay implicit attitudes may fear appearing pro-gay and, thus, correct their behaviour to appear less so. In contrast, individuals with weak motivations to control prejudiced reactions did not have to correct for perceived bias and thus acted in accordance with their implicit attitudes (cf. the flexible correction model; Wegener and Petty, 1997). The authors recognized, however, that this explanation was post-hoc and that more research was needed to explore further the moderating influence of cognitive variables on the homonegative attitude-behaviour link. In summary, consistent with previous studies using Homosexuality-IATs, in-group implicit biases were repeatedly produced by heterosexual participants but not by gay and lesbian participants. In addition, results pertaining to the relationship between homonegativity and motivation to be egalitarian were mixed. To illustrate, Rohner and Björklund (2006) and Boysen et al. (2006) reported no relationship between implicit anti-gay attitudes and the motivation to control homonegativity. In contrast, research that distinguished between levels and sources of motivation did show a relationship (e.g., Lemm, 2006). Specifically, a high level of internal motivation to control homonegativity predicted less implicit anti-gay attitudes. Combinations of implicit homonegativity and conscious processes (e.g., behavioural control and weak motivation) also predicted discriminatory behaviour. Overall, therefore, the relationship between implicit homonegativity and helping behaviour were moderated by both motivational (i.e., internal) and situational variables.
SOME INCONSISTENCIES IN THE RESEARCH A number of inconsistencies were evident across the IAT studies and these will be discussed in turn. The first issue relates to stimulus modality. Specifically, there was wide variability across the studies with regard to the stimuli employed. Some studies used only verbal stimuli, others employed only picture stimuli, and some used a combination of the two. Evidence to suggest that stimulus modality has no effect on implicit attitudes was provided by
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two of the studies that examined implicit homonegativity using the IAT (Nosek et al., 2005; Lemm, 2006). In contrast, researchers’ investigating other constructs (such as fear of spiders) – but with the EAST – have provided evidence to suggest that picture stimuli activate attitudes more directly than verbal stimuli (e.g., Huijding and de Jong, 2005, 2006). Furthermore, some studies did not make clear that exemplars representing the category ‘gay’ were related to homosexuality. For example, some participants may have perceived the task to be an assessment of same and opposite-sex friendships and not attitudes toward gay and straight people, thus reducing the size of the anti-gay effect. A second issue pertains to the target categories. Many of the studies assessed attitudes towards both lesbian women and gay men, while others focussed on attitudes toward gay men or lesbian women only. This makes cross-study comparisons difficult. In addition, explicit measures that were compared to implicit measures varied with regard to their specificity. Some explicit measures required participants to rate “Gay” relative to “Straight,” while others required participants to rate “Gay” alone (i.e., not relative to “Straight”). Furthermore, when semantic differentials were used they did not always use the terms employed with the implicit measures. Finally, it appears that many, if not all, of the studies summarized thus far utilized relatively crude measures of sexual orientation. Given that implicit measures are sensitive to group differences it would be important for future studies to use more sensitive multidimensional screens. (Further details on this issue will be provided in a later section of the chapter.)
POSSIBLE ALTERNATIVES TO THE IAT Evidence in support of the reliability and validity of the IAT as a measure of implicit cognition has been reported across a wide variety of domains (e.g., Fazio and Olson, 2003; Nosek et al., 2002). A number of limitations inherent in the measure, however, have been identified (see Arkes and Tetlock, 2004; Blanton and Jaccard, 2006; Blanton, Jaccard, Gonzales, and Christie, 2006; Cunningham, Preacher, and Banaji, 2001; De Houwer, 2002; Fiedler, Messner, and Bluemke, 2006; Nosek and Sriram, 2007). Two limitations, in particular, will be discussed. The first is that the IAT provides a measure of relative associative strength and, thus, cannot be used to measure the valence of individual concepts (De Houwer, 2002; Nosek et al., 2005). The second limitation concerns the fact that the IAT provides a relatively indirect measure of implicit attitudes. The IAT provides a relativistic measure because each trial involves presenting both of the relevant categories, such as Gay and Straight. Thus, the IAT effect is based on responses that occur in the context of both categories, rather than each independently. As a result, a prostraight/anti-gay IAT effect could indicate that a participant has a positive attitude to “Straight” and a neutral attitude to “Gay”, or it could indicate a neutral attitude to “Straight” and a negative attitude to “Gay”. The IAT can indicate that x is preferred to y, but it cannot reveal to what extent x and y are liked or disliked, per se. The three studies outlined subsequently offer alternatives to the IAT as a methodology for the assessment of implicit homonegativity. The EAST. In order to circumvent the relativistic nature of the IAT, the EAST (De Houwer, 2003) was developed to assess implicit attitudes toward individual concepts. Unlike the IAT, the EAST is based on a comparison of performance on trials within a single task
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rather than on a comparison of performances on different tasks. On some trials, white words are presented while on other trials the words are coloured green or blue. Participants are required to press a key in response to the meaning of white words (e.g., left = positive, right = negative) and the colour of the green and blue words (e.g., left = green, right = blue). The premise is that responses become extrinsically associated with positive or negative valence. Thus, responses should be faster when a positive word is presented in green (the positive colour) rather than blue (the negative colour). Similarly, responses should be faster when a negative word is presented in blue rather than green. In other words, performance should be superior on trials in which participants are required to categorize colored positive words positively and colored negative words negatively. Recently, a Belgian study employed a known-groups approach to: (a) test the validity of the EAST and the IAT; and (b) determine if implicit homonegativity as measured by the EAST and IAT differed as a function of participant sexual orientation (De Houwer and De Bruyckner, 2007b; Experiment 3). The IAT used was a conceptual replication of the IAT developed by Banse et al. (2001), with the exception that photographs were replaced by word stimuli. Thus, implicit attitudes toward both male and female homosexuality were assessed. The terms that had been employed in the IAT were retained for use in the EAST, with the exception that the targets ‘homosexual’ and ‘heterosexual’ were replaced by the terms ‘hetero,’ ‘gay,’ ‘lesbian,’ and the neutral stimulus, ‘######.’ Explicit cognitive and affective attitudes toward homosexuality also were assessed. Implicit attitudes as measured by the IAT, but not the EAST, differed as a function of participant sexual orientation. Specifically, both groups produced in-group implicit biases on the IAT. Furthermore, on the explicit measures, gay men and lesbian women reported more positive attitudes toward homosexuality than did heterosexual participants. Consistent with Banse et al. (2001), the IAT correlated weakly with explicit cognitive attitudes toward homosexuality but strongly with affective attitudes, suggesting that the IAT captures spontaneous or evaluative ‘gut reactions.’ These results provided support for the validity of the IAT, while the EAST failed its challenge to offer an alternative measure of implicit homonegativity. (However, it should be noted that recent research suggests a modified EAST procedure may prove to be more sensitive; De Houwer and De Bruycker, 2007a). Sequential priming. Another alternative to the IAT, which has been offered recently, is the Sequential Priming Procedure. Similar to the EAST, it does not share the IAT’s limitation of being a relativistic measure because evaluations of target stimuli are based upon associations between the target stimulus and its preceding prime alone. Only one published study has employed sequential priming as a measure of implicit attitudes to homosexuality (Meir, Robinson, Gaither, and Heinert, 2006). These authors developed the procedure to assess: (a) the moderating influence of self-deception on heterosexual males’ implicit attitudes toward gay men; and (b) implicit cognitive reactivity to images of gay sexual activity. In the Sequential Priming Procedure, heterosexual males were presented with a prime stimulus followed by a reaction-time measurement of their target stimulus evaluations. There were two categories of primes (i.e., A = images of clothed or semi-clothed gay couples in sexual poses and B = images of neutral objects such as a chair or a lamp). A single prime was presented on each trial. Participants were invited to categorize the primes vocally as either ‘Gay’ or ‘Neutral’ with both speed and accuracy. Immediately following the prime categorizations, a positive (e.g., great, good) or negative (e.g., awful, bad) target word
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appeared on the screen. Participants were instructed to categorize the words as ‘positive’ or ‘negative,’ again with speed and accuracy, by pressing the appropriate response key. Reaction times were assessed on the basis of four conditions: gay/positive, gay/negative, neutral/positive, and neutral/negative. If presentation of the gay prime resulted in faster categorizations of positive as opposed to negative target words, this was assumed to indicate that the participant had a positive bias toward the gay prime. In contrast, if the gay prime resulted in faster categorizations of negative rather than positive targets, this was assumed to be evidence of a negative bias toward the gay prime. Participants also were exposed to a picture viewing-time task that measured time spent viewing images of gay and heterosexual sex. Self-deception and attitudes toward homosexuality were assessed via self-report questionnaires. Consistent with research using the IAT for the assessment of implicit homonegativity, participants generally produced implicit and explicit in-group biases. Additionally, implicit and explicit anti-gay biases were evident in participants who were high (as opposed to low) in self-deception. Participants who were both high in self-deception and explicitly anti-gay spent less time viewing images of gay sex in the viewing-time task in comparison to those reporting low levels of self-deception. The findings suggest that anti-gay individuals with high levels of self-deception react to images of gay sex in a homophobic aversive and avoidant manner. In contrast, anti-gay individuals with low levels of self-deception react to such images in a sexually prejudiced manner (c.f. Herek, 2000) that manifests as a general discomfort and condemnation of gay sex as opposed to extreme phobic aversion and avoidance. The Implicit Relational Assessment Procedure. As noted previously, a second possible limitation to the IAT (and, indeed, the EAST and Sequential Priming), is that it provides a relatively indirect measure of implicit attitudes. In noting the indirect nature of the IAT, for example, De Houwer (2002) argued that:
. . . [it] does not provide a measure of beliefs, nor was it designed to do so. It can only provide an index of associations that are assumed to be involved in certain beliefs and thus indirect evidence for the presence of certain beliefs (pp. 117-118). Thus, if a methodology such as the IAT indicates that ‘Gay’ and negative words are strongly associated, it then is inferred that such implicit associations underlie negative attitudes about gay people. Although such an inference seems reasonable, it is prudent to develop additional methodologies that aim to provide relatively direct measures of implicit cognition. One such methodology has recently been offered: the Implicit Relational Assessment Procedure (IRAP; Barnes-Holmes, Barnes-Holmes, Power, Hayden, Milne, and Stewart, 2006, Barnes-Holmes, Hayden, Barnes-Holmes, and Stewart, in press; McKenna, Barnes-Holmes, Barnes-Holmes, and Stewart, 2007). It is theorized that the IRAP’s structure may permit a more fine-grained assessment of implicit homonegativity than that afforded by the IAT. The IRAP was developed from a modern behavioral theory of human language and cognition known as Relational Frame Theory (RFT; Hayes, Barnes-Holmes and Roche, 2001). According to RFT, the core elements of human cognition are relational acts. Unlike the IAT (and EAST and Sequential Priming), each trial of the IRAP asks participants to confirm or deny a specific attitude or belief by responding to a previously established verbal
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relation between a sample stimulus and a target term (e.g., Gay – Normal = Similar or Opposite?). In brief, the IRAP requires participants to respond quickly and accurately in ways that are either consistent or inconsistent with their putative attitudes. Theoretically, it is assumed that overt relational responses defined as consistent on the IRAP will be preceded by incipient or private responses that occur at a higher probability than those responses defined as inconsistent; the probability of such responses is assumed to be determined by historical and current contextual variables. Its basic rationale is that participants should respond more quickly on tasks that reflect their attitudes (i.e., pro-straight or pro-gay attitudes) than on tasks that do not because incipient relational responding will coordinate more frequently with consistent overt responding. In other words, during inconsistent trials participants’ responding is expected to be slower, as they respond against their more probable incipient relational responses. The extent of the observed difference between pro-straight and pro-gay trials is assumed to provide a direct index of the strength of the specific attitude being assessed. An important feature of the IRAP, in the context of providing an alternative measure of implicit homonegativity to that offered by the IAT, is the fact that it consists of four trialtypes (see below), and this structure may permit the assessment of specific, rather than relative implicit responses. In a very recent and currently unpublished IRAP study, a knowngroups approach was employed to determine if explicit and implicit attitudes toward homosexuality would: (a) be related; and (b) differ as a function of participants’ sexual orientation (Cullen, Barnes-Holmes, Barnes-Holmes, and Stewart, 2007). The IRAP presented one of two sample stimuli (e.g., ‘Straight’ or ‘Gay’). Additionally, two sets of target stimuli were presented; one comprised negative stereotypical terms for gay people (e.g., ‘abnormal,’ or ‘dangerous’) and the other set comprised positive stereotypical terms for straight people (e.g., ‘normal,’ or ‘safe’). Each set of target terms was presented with each sample. Thus, four different trial-types were created (see Figure 1). The fact that the two categories (‘Gay’ and ‘Straight’) were presented on separate trials with just one target permits a less relativistic measure of implicit responses to those categories than that provided by the IAT (which presents both categories on each trial during the critical test blocks). Participants were required to respond as quickly and accurately as possible to the relation between the sample and target by pressing the appropriate response key in order to choose one of the two relational terms (e.g., ‘Similar’ or ‘Opposite’). In addition to the IRAP, the Modern Homonegativity Scale (MHS: Morrison and Morrison, 2002), assessed self-reported attitudes toward lesbian women and gay men. Consistent with the theoretical positions of both Klein, Sepekoff, and Wolf (1985) and Alderson and Orzeck (2006), sexual orientation was conceptualized as multi-variate and dynamic, and was assessed using two multi-dimensional measures.5 The raw latency data were transformed using an adaptation of the D-algorithm developed by Greenwald, Nosek, and Banaji (2003) to control for individual variations in speed of
5
We do not believe that our statistical analysis (i.e., collapsing scores into a dichotomy of heterosexual and nonheterosexual) alters our conceptualization of sexual orientation. Using two different samples, Weinrich et al. (1993) found that all 21 items of the KSOG loaded onto the first orthogonal factor with the implication that little injury results from reducing the grid to a single number called sexual orientation.
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responding that may act as a possible confound when analyzing between-group differences. Specifically, (1) only response latency data from test-blocks were used; (2) latencies above
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Figure 1. Examples of the four IRAP trial-types. The sample (Straight or Gay), target word (safe, offensive, etc.) and response options (Similar and Opposite) appeared simultaneously on each trial. Arrows with superimposed text boxes indicate which responses were deemed pro-straight or pro-gay (boxes and arrows did not appear on screen). Selecting the pro-straight response option during a prostraight block, or the pro-gay option during a pro-gay block, cleared the screen for 400 ms before the next trial was presented; if the pro-gay option was chosen during a pro-straight block, or the prostraight option during a pro-gay block, a red X appeared on screen until the participant emitted the alternative response.
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10,000 ms were eliminated from the dataset; (3) the data for participants for whom more than 10% of test-block trials had latencies less than 300 ms were eliminated; (4) twelve standard deviations for the four trial-types (i.e., four for the response latencies from test blocks 1 and 2, test blocks 3 and 4, and test blocks 5 and 6) were computed; (5) twenty-four mean latencies for the four trial-types in each test-block were computed; (6) difference scores for each of the four trial-types, for each pair of test-blocks were computed by subtracting the mean latency of the consistent test-block from the mean latency of the corresponding inconsistent test-block; (7) each difference score was divided by its corresponding standard deviation (from step 4), yielding 12 D-IRAP scores, one score for each trial-type for each pair of test-blocks; (8) four overall trial-type D-IRAP scores were calculated by averaging the three scores for each trialtype across the three pairs of test blocks. Initial results for each of the four IRAP trial-types are presented in Figure 2.6 Specifically, on the IRAP, both groups responded more quickly when confirming rather than denying ‘Straight-Positive’ and ‘Gay-Positive’ belief-statements. Furthermore, both groups responded more quickly when denying rather than confirming ‘Straight-Negative’ statements. Critically, however, the groups diverged when responding to ‘Gay-Negative’ trial-types. Specifically, the heterosexual group confirmed the statements more quickly (positive Dscore) than the non-heterosexual group who denied them more quickly (negative D-score). Although the data set are not yet complete, it is worth noting that only this final Gay-Negative trial type produces a group difference that approaches significance (p = .07). The IRAP data are broadly consistent with the results of other studies (e.g., Jost et al., 2004; Rohner and Björklund, 2006), in that the only evidence of implicit out-group prejudice was observed for the heterosexuals (but only on one trial-type). The fact that this effect only emerged for the Gay-Negative trial-type could be seen as consistent with recent evidence that suggests the influence of a negativity bias in attitude formation (cf. Kunda, 1999). That is, when negatively valenced stimuli are presented with ‘Gay,’ this serves to activate an implicit anti-gay bias, which is not observed when positively valenced stimuli are presented. This result could have some interesting implications to which we will return subsequently. On the Modern Homonegativity Scale, self-reported attitudes toward gay men and lesbian women were not positive. In addition, significant between-group differences emerged. Specifically, heterosexual participants reported more homonegative attitudes toward both gay men and lesbian women compared to the attitudes reported by non-heterosexuals. Both groups’ self-reported attitudes toward gay men were more negative than attitudes toward lesbian women. Consistent with previous research (e.g., Rohner and Björklund, 2006), there were no significant correlations between the implicit and explicit measures. In summary, heterosexual in-group implicit biases were produced on the Sequential Priming Procedure, the IRAP and the IAT but not on the EAST. Critically, the IRAP replicated the implicit effects reported in previous studies even though participants were required to respond directly to relatively blunt belief-statements about human sexuality (e.g., Gay – Dangerous – Similar). Before concluding, two general issues arising from the current review seem important. Failures to conceptually and operationally define sexual orientation. Despite attempts to investigate known-group validity, many researchers failed to operationally and conceptually
6
At the time of writing, data collection was incomplete and thus the analyses are preliminary.
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.4
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Figure 2. Overall mean adjusted D-IRAP scores for the Heterosexual and Non-Heterosexual groups with respect to the four IRAP trial-types. On the graph positive D-IRAP scores reflect a pro-straight implicit bias and negative D-IRAP scores reflect a pro-gay bias. The zero-point reflects no bias. Both heterosexual and non-heterosexual groups confirmed ‘Straight-Positive’ belief statements (e.g., Straight – Safe = True) more quickly than they denied them (Straight – Safe = False). The heterosexual group confirmed them faster than the non-heterosexual group. Both groups denied ‘Straight-Negative’ belief statements (e.g., Straight – Dangerous = False) faster than they confirmed them (e.g., responding ‘True’), but this time the non-heterosexual group denied the statements more quickly than the heterosexual group. The two groups confirmed ‘Gay-Positive’ statements (e.g., Gay – Safe = True) faster than they denied them (e.g., responding ‘False’). The heterosexual group did so faster than the non-heterosexual group. The groups diverged when responding to ‘Gay-Negative’ IRAP statements (e.g., Gay – Dangerous = True). Specifically, the heterosexual group confirmed the statements (by responding ‘True’ faster than responding ‘False’) but the non-heterosexual group denied them (by responding ‘False’ faster than ‘True’).
define participant sexual orientation. In order to better test this form of validation, future researchers should include such definitions. Some of the studies reviewed here did employ a single-dimension self-identification assessment of sexual orientation (e.g., on a Kinsey-type bipolar scale). However, this method has been criticized as an over-simplification, with many researchers (e.g., Chung and Katayama, 1996; Coleman, 1987; Klein et al., 1985; Storms, 1980) arguing that self-identification fails to consider other relevant dimensions. Given the lack of consensus in the literature (cf. Berkey, Perelman-Hall, and Kurdek, 1990), we cannot make a ‘definitive’ recommendation regarding the ‘best’ measure for the assessment of sexual orientation. Nevertheless, it appears that multi-dimensional measures offer more conceptual complexity than self-identification measures. Relationship between implicit and explicit attitudes. Within the domain of prejudice, a divergence between performance on implicit and explicit attitude measures has been viewed as evidence to support the theoretical distinctiveness of implicit and explicit cognitions (e.g., Greenwald and Banaji, 1995; Greenwald et al., 1998). A majority of the studies reviewed here revealed diverging and weak relationships between implicit and explicit attitude measures. Interestingly, however, a number of medium to strong relationships also were observed.
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Although the findings appear contradictory, two types of variables (i.e., individual difference variables and procedural variables) may help to explain the conditions under which implicit and explicit attitudes are related. First, attention was focussed, across studies, on the role of one individual difference variable in particular (i.e., motivation). When participants were internally motivated to control their prejudice (e.g., Lemm, 2006) at a low level (e.g., Banse et al., 2001), implicit and explicit attitudes were shown to correlate. Conversely, when participants were internally motivated but at a high level, implicit and explicit attitudes diverged (e.g., Gabriel et al., 2007). Second, the procedural variable that may account for the presence or absence of a relationship between implicit and explicit attitudes is the type of explicit or implicit measure employed. Consistent with the view that implicit measures tap affective or evaluative cognitions (e.g., Wilson et al., 2000), strong relationships between explicit affective and implicit attitudes were observed (e.g., Banse et al., 2001). Relationships between implicit and explicit attitudes were shown only in studies that employed the IAT as a measure of implicit homonegativity, whereas studies that employed the EAST, the Sequential Priming Procedure and the IRAP showed weak and diverging relationships.
DISCUSSION In general, implicit attitudes as measured by the IAT, the Sequential Priming Procedure and the IRAP (but not the EAST) differed as a function of group status. Heterosexual ingroup implicit biases were repeatedly shown. Non-heterosexuals repeatedly produced responses on implicit measures that failed to indicate a strong in- or out-group bias. In contrast, both groups produced in-group biases on the explicit measures. Implicit and explicit attitudes toward homosexuality were moderated by a range of interpersonal, situational and procedural variables. Support for the theoretical distinctiveness of implicit and explicit attitudes was provided, such that the majority of studies showed weak and diverging implicitexplicit attitude relationships. Moreover, implicit attitudes predicted commonly practiced behaviors relevant to sexual orientation among gay men (e.g., immersion in gay culture) whereas explicit attitudes predicted behaviours that require deliberation such as the decision to disclose one’s sexual orientation and the nature of that disclosure (e.g., Jellison et al., 2004). The IAT was shown to be impervious to faking, but test-retest correlations were low. Additional analyses of the IRAP, EAST and Sequential Priming Procedure’s reliability and validity are needed. Furthermore, additional analyses will be needed to test the controllability of these measures and their vulnerability to motivational influences (but see McKenna et al. [2007] for evidence that the IRAP is resistant to faking). Despite trends in the polls suggesting that attitudes towards homosexuality have become more liberal in recent times, heterosexual in-group implicit biases (though not extremely antigay) paint a rather different picture. It may not be ‘politically correct’ to outwardly express negativity toward gay men and lesbian women; however, implicit homonegative attitudes may manifest themselves in situations where relative judgements are required (e.g., considering a gay versus straight candidate for a job promotion). Indeed, the ‘negativity bias’ observed with the IRAP suggests that vigilance in this area is particularly important. In the job promotion scenario, for example, if a gay man or lesbian woman (but not a heterosexual
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man or woman) exhibits even a single behaviour perceived to be negative, then he or she may become a casualty of both an out-group prejudice (assuming that the interviewer is heterosexual) and a negativity bias. Interventionists would do well to encourage people to be aware that, despite self reported positive feelings toward gay men and lesbian women, they may be more sensitive to negative characteristics present in a gay rather than straight individual. In any case, there is clear evidence for in-group heterosexual pride and out-group prejudice using both implicit and explicit attitude measures, and thus any perceived liberalisation of views within this area should be treated with caution.
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McKenna, I. M., Barnes-Holmes, D., Barnes-Holmes, Y., and Stewart, I. (2007). Testing the fake-ability of the Implicit Relational Assessment Procedure (IRAP): The first study. International Journal of Psychology and Psychological Therapy, 7, 123-138. Meir, B. P., Robinson, M. D., Gaither, G. A., and Heinert, N.J. (2006). A secret attraction or defense loathing? Homophobia, defense, and implicit cognition. Journal of Research in Personality, 40, 377-394. Morrison, M. A., and Morrison, T. G. (2002). Development and validation of a scale measuring modern prejudice toward gay men and lesbian women. Journal of Homosexuality, 43, 15-37. Morrison, T. G., Kenny, P., and Harrington, A. (2005). Modern prejudice toward gay men and lesbian women: Assessing the viability of a measure of modern homonegative attitudes within an Irish context. Genetic, Social, and General Psychology Monographs, 131, 219-250. Nosek, B. A., and Banaji, M. R. (2001). The go/no-go association task. Social Cognition, 19, 625-666. Nosek, B. A., Banaji, M., and Greenwald, A. G. (2002). Harvesting implicit group attitudes and beliefs from a demonstration web site. Group Dynamics, 6, 101-115. Nosek, B. A., Greenwald, A. G., and Banaji, M. R. (2005). Understanding and using the Implicit Association Test: II. Method variables and construct validity. Personality and Social Psychology Bulletin, 31, 166-180. Nosek, B. A., Smyth, F. L., Hansen, J. J., Devos, T., Lindner, N. M., Ranganath, K. A., Tucker Smith, C., Olson, K. R., Chugh, D., Greenwald, A. G., and Banaji, M. R. (2007). Pervasiveness and correlates of implicit attitudes and stereotypes. European Review of Social Psychology, 18, 36-88. Nosek, B. A., and Sriram, N. (2007). Faulty assumptions: A comment on Blanton, Jaccard, Gonzales, and Christie (2006). Journal of Experimental Social Psychology, 43, 393-398. Nungesser, L. G. (1983). Homosexual acts, actors and identities. New York: Praeger. Park, J., and Bieschke, K. L. (2002, August). Development of the Heterosexism Scale. Poster session presented at the Annual Convention of the American Psychological Association, Chicago, IL. Paulhus, D. L. (1984). Two-component model of socially desirable responding. Journal of Personality and Social Psychology, 46, 598-609. Paulhus, D. L. (1991). Measurement and control of response bias. In J. P. Robinson, P. R. Shaver, and L. S. Wrightsman (Eds.), Measures of personality and social psychological attitudes (pp. 17-59). New York: Academic Press. Paulhus, D. L., and Reid, D. B. (1991). Enhancement and denial in socially desirable responding. Journal of Personality and Social Psychology, 60, 301-317. Plant, E. A., and Devine, P. G. (1998). Internal and external motivation to respond without prejudice. Journal of Personality and Social Psychology, 75, 811-832. Pratto, F., and John, O. P. (1991). Automatic vigilance: The attention grabbing power of negative social information. Journal of Personality and Social Psychology, 61, 380-391. Proctor, R. N. (1995).The destruction of ‘Lives Not Worth Living.’ In J. Terry and J. Ursla (Eds.), Deviant bodies (pp. 179-196). Bloomington and Indianapolis, Indiana: Indiana University Press. Raja, S., and Stokes, J. P. (1998). Assessing attitudes toward lesbians and gay men: The Modern Homophobia Scale. Journal of Gay, Lesbian, and Bisexual Identity, 3, 113-134.
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In: The Psychology of Modern Prejudice Editors: Melanie A. Morrison and Todd G. Morrison
ISBN 978-1-60456-788-5 © 2008 Nova Science Publishers, Inc.
Chapter 10
MODERN HETEROSEXISM AND SOCIAL DOMINANCE ORIENTATION: DO SUBDOMAINS OF HETEROSEXISM FUNCTION AS HIERARCHY-ENHANCING LEGITIMIZING MYTHS? N. Eugene Walls University of Denver
ABSTRACT Subdomains of modern heterosexism are examined to determine if they function as hierarchy-enhancing legitimizing myths as social dominance theory predicts. Using an undergraduate sample of 456 female and 195 male students (N=651) from 6 colleges and universities, the study finds that three of the subdomains (aversive heterosexism, amnestic heterosexism, and paternalistic heterosexism), along with hostile heterosexism, function as predicted. However, positive stereotypic heterosexism (i.e., endorsement of positive stereotypes) appears to function somewhat differently. The findings support existing literature that suggests that modern forms of prejudice function as hierarchyenhancing legitimizing myths, while raising questions about how the endorsement of positive stereotypes might function to support social stratification.
INTRODUCTION Group inequalities in social, political, and economic outcomes have existed in virtually all post-hunter and gatherer societies (Davis and Moore, 1945; Kerbo, 2003). However, societies have varied significantly in the manner and extent of inequalities, by which characteristics are salient markers of status among social groups, and by who is included and excluded within these groups (Hofstede, 1984; Sidanius, 1993). In terms of these inequalities, societies can be conceptualized as systems of group-based social hierarchies where dominant groups receive a disproportionately large share of positive social values (e.g., political power, high social status, wealth, and material resources) and subordinate groups receive a
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disproportionately large share of negative social values (e.g., low social status, poverty, societal sanctions, and stigmatization; Sidanius and Pratto, 1999). These inequalities in the social structure and its institutions are maintained, at least in part, by attitudes, beliefs, and ideologies that justify the stratification (Eyerman and Jamison, 1991; Jost, 1995). Given the long-standing and almost universal nature of these systems of inequality and the prejudice, stereotypes, violence, and coercion that accompany them, these issues have been topics of a considerable amount of research within the social sciences (Fiske, 1998). The current study extends this scholarship by examining whether modern forms of prejudice function as hierarchy-enhancing legitimizing myths within the context of the social dominance theoretical framework. The relationships between various subdomains of modern homonegativity (Morrison and Morrison, 2002) or modern heterosexism (Walls, in press-a), social dominance orientation (Sidanius and Pratto, 1999), and support for lesbian and gay rights are investigated as a way to explore the relationship between modern prejudice and public policies that challenge existing social inequities. A review of the literature will outline, first, the points of social dominance theory that are salient to this study, as well as a brief discussion of modern heterosexism and a description of the domains of modern heterosexism. Following that will be an examination of what is currently known about the relationship between social dominance orientation and both hostile and modern forms of heterosexism. Finally, findings relating social dominance orientation and public policies regarding lesbian women and gay men will be reviewed.
SOCIAL DOMINANCE THEORY Social dominance theory (Sidanius and Pratto, 1999) was developed as an attempt to synthesize many of the theoretical approaches to understanding prejudice and discrimination. The theory argues that every complex society is organized by systems of social group-based hierarchies in which at least one social group has dominance over others, and at least one group occupies a subordinate position. The approach contends that there is a set of fundamental and general processes that undergird the emergence and maintenance of groupbased stratification within societies even though there is variation in the degree to which societies are hierarchically organized and around which groups are granted status. Two components of social dominance theory that are salient for this study are social dominance orientation and legitimizing myths. Social dominance orientation is defined as “..the extent to which one desires that one’s in-group dominate and be superior to outgroups” (Pratto, Sidanius, Stallworth, and Malle, 1994, p. 742), and is captured by the Social Dominance Orientation scale (SDO; Sidanius and Pratto, 1999). Those who are high in social dominance orientation are more likely to justify stratification and the existing system of privileges and discrimination, while those who are low in social dominance orientation are more likely to support ideologies and values that seek to dismantle social stratification (Sidanius and Pratto, 1999). Empirical research has supported social dominance theory’s hypothesized relationship between social dominance orientation and various forms of prejudice toward a variety of social groups, and across a variety of cultures (Pratto et al., 1994). Social dominance orientation has been shown to be predictive of racism/ethnic prejudice (Pratto et al., 1994; van
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Hiel and Mervielde, 2005), nationalism (Sidanius, Feshbach, Levin, and Pratto, 1997), the Protestant work ethic (Christopher and Mull, 2006), and political conservatism (Sidanius, Pratto, and Bobo, 1996; van Hiel, Pandelaere, and Duriez, 2004) among other constructs. Likewise it is predictive of support for lesbian and gay rights (Cerecedes, 2003; Pratto et al., 1994), women’s rights (Heaven, 1999; Pratto et al., 1994), social welfare programs (Pratto et al., 1994), and affirmative action (Federico and Sidanius, 2002; Haley and Sidanius, 2006; Jost and Thompson, 2000). In order to minimize intergroup conflict, the group-based inequalities in a society are legitimized through ideologies which justify discrimination and the existing stratification (Jost and Banaji, 1994, Jost and Major, 2001; Sidanius, 1993). Within the context of social dominance theory, the term legitimizing myths is used to capture the concept of these systemjustifying ideologies. Formally defined as “…values, attitudes, beliefs, causal attributions, and ideologies that provide moral and intellectual justification for social practices that either increase, maintain or decrease levels of social inequality among social groups” (Sidanius and Pratto, 1999, p. 104), legitimizing myths are the cultural scripts that link individual belief to social practice. They may function to either enhance or attenuate stratification resulting in hierarchy-enhancing legitimizing myths and hierarchy-attenuating legitimizing myths. Legitimizing myths also may take a number of different forms. They may be ideologies such as the Protestant work ethic, the belief that the U.S. is a meritocratic society, or the endorsement of democratic egalitarian values. They may be cultural beliefs such as the belief that intelligence is a fixed capacity that can be accurately measured by intelligence tests. Or, they may be stereotypes and prejudices about a social group. One goal of social dominance theory has been to connect individual level differences with both cultural-level scripts and support or opposition to macro-level public policies. As such, the theory suggests that legitimizing myths mediate the relationship between individual level endorsement of social dominance orientation and support for (or opposition to) public policies that seek to attenuate stratification. In other words, part of the relationship between social dominance orientation and public policies is a result of the causal relationship between social dominance orientation and the various legitimizing myths. Social dominance orientation should, according to the theory, have both a direct relationship with public policy support, as well as an indirect relationship through legitimizing myths. In this way, legitimizing myths become the cultural scripts that connect the micro- to the macro-level. Individuals who have a high social dominance orientation embrace hierarchy-enhancing legitimizing myths and reject hierarchy-attenuating legitimizing myths. This endorsement of hierarchy-enhancing legitimizing myths should, likewise, be related to higher endorsement of hierarchy-enhancing public policies and rejection of hierarchy-attenuating public policies. The opposite of this pattern should hold true for individuals who have a low social dominance orientation. The formal model for this relationship is represented in Figure 1.
NOMENCLATURE Prior to the discussion of the literature on modern forms of prejudice toward lesbian women and gay men, a word on the choice of the term heterosexism is in order. Prejudice
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Figure 1. The effects of social dominance orientation on hierarchy-enhancing and hierarchy-attenuating social policies as partially mediated by hierarchy-enhancing and hierarchy-attenuating legitimizing myths. Note. Adapted from: Sidanius, J., and Pratto, F. (1999). Social dominance (p. 105). Cambridge, UK: Cambridge University Press. Copyright 1999 by the Cambridge University Press. [Adapted with permission.]
toward lesbian women and gay men has been called a number of terms, including homophobia (Blumfield, 1992; Smith, 1971; Weinberg, 1974), homoerotophobia (Churchill, 1967), homosexism (Hansen, 1982a, 1982b; Lehne, 1976), heterosexism (Morin and Garfinkle, 1978; Pharr, 1988), homonegativism (Hudson and Ricketts, 1980), homo-hatred (Appleby and Anastas, 1998), homoignorance (Appleby and Anastas, 1998), homonegativity (Morrison and Morrison, 2002) and sexual prejudice (Herek and Capitanio, 1996). Herein, the term heterosexism will be used, and is conceptualized as the system of attitudes, behaviors, policies, and norms toward lesbian women and gay men (both at individual and institutional levels) that support the subjugation of lesbian, gay, and bisexual individuals and communities, and the concomitant privileging of heterosexual identities. The term heterosexism has been chosen over the numerous other options for a number of reasons. First, it parallels the construction of other words used to denote systems of subjugation based on social location, position, and identity, such as racism, sexism, and classism. Second, it is one of the two most widely known ways of referring to anti-gay prejudice in the existing academic literature (Appleby and Anastas, 1998). Third, heterosexism was chosen over the term homophobia as homophobia has been criticized by numerous scholars as connoting an irrational psychological disorder – a phobia. Finally, while some scholars have championed the use of the term homophobia to represent individually-held prejudices and behaviors, and heterosexism to denote institutional-level processes including the privileging of heterosexuality, the use of the terms in such a manner obscures the integrated nature whereby individual attitudes and behaviors foster and justify institutional and systemic processes, which concomitantly reinforce and support individual attitudes and behaviors. The term hostile heterosexism is used within this paper to capture traditional anti-gay attitudes based on pathologizing lesbian women and gay men either psychologically, socially,
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or morally, regardless of which terminology or measure the original author used. Similarly the term modern heterosexism is used as an umbrella term capturing the various theorized domains of heterosexism based on the ideas of modern prejudice theory. The decision to use these two terms in this manner is not meant to deny nuanced differences in theoretical understandings of, or the measures capturing, the attitudes and beliefs within each type of heterosexism, but to underscore the differentiation between old-fashioned and modern heterosexism clusters.
MODERN HETEROSEXISM Modern prejudice theorists argue that the way in which prejudicial attitudes toward historically marginalized groups gets expressed has changed. The overt expression of racism, sexism, and heterosexism that was much more prevalent and open in the recent past of the U.S. has decreased (Bachrach, Hindin, and Thomson, 2000; Balanko, 1998; Farley, 1997; Jones, 1999), and been replaced by forms of prejudice that are much more subtle and covert (McConahay, 1986; Morrison and Morrison, 2002; Swim, Aiken, Hall, and Hunter, 1995; Tougas, Brown, Beaton, and Joly, 1995; Walls, in press-a). Historically, old-fashioned heterosexism has been based on ideologies that pathologize homosexuality. These ideas have emanated from a number of sources including religion (homosexuality as immoral and sinful), cultural constructions of hegemonic masculinity (homosexuality as weak and submissive), and natural law (homosexuality as unnatural), to name a few. Modern heterosexism, on the other hand, is not based – at least rhetorically – on the pathologizing of homosexuality. Instead modern heterosexism embodies arguments that support the continued subjugation of same-sex oriented people and the privileging of heterosexuality through rhetoric that is grounded more in justifications within the sociopolitical realm rather than the character of the lesbian and gay person or community. Modern heterosexism is less overtly pathologizing and hostile. Examples of justifications that modern heterosexists might currently deploy, for example, include suggesting that lesbian women and gay men are militant, demanding too much, too quickly. They might suggest that discrimination and prejudice against the community is a thing of the past. They might claim that they have nothing against gay people, but – out of a sense of protection – that they would never want one of their children to be lesbian or gay. Finally, they may invoke supposedly positive stereotypes about lesbian women and gay men. Building on the theoretical foundation laid by modern racism and sexism researchers, Morrison and Morrison (2002) developed a scale – the Modern Homonegativity Scale (MHS) – to capture negative attitudes toward lesbian women and gay men that are not based on moral and religious objections (as they are in “old-fashioned” homonegativity). The scale performed well psychometrically in the four initial studies undertaken to test its reliability and validity, and factor analysis identified that the scale was unidimensional as theorized. Two additional studies have further supported the psychometric properties of the instrument (Morrison, Kenny, and Harrington, 2005). In both publications, the authors found that modern homonegativity emerged as a separate domain, distinct from old-fashioned homonegativity. Cowan, Heiple, Marquez, Khatchadourian, and McNevin (2005) examined modern heterosexism by using a modified version of the Modern Sexism Scale (Swim et al., 1995)
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where they replaced the term women with gays and lesbians. Their derived scale had acceptable reliability and functioned as predicted. A recent study by Morrison and Bearden (2007) examines the construction and validation of an instrument developed to capture the endorsement of positive stereotypes of gay men. The scale, the Homopositivity Scale, had adequate construct validity and internal consistency. While the authors raised numerous questions about the relationship of the scale to other forms of prejudicial attitudes and social psychological constructs, they did not, however, appear to conceptualize the endorsement of positive stereotypes specifically as a form of modern prejudice. A final study that sought to extend the ideas of modern prejudice into the area of heterosexism was completed by Walls (in press-a). Similar to Morrison and Morrison (2002), Walls developed and examined an instrument, the Modern Heterosexism Inventory (MHI), over a series of four studies. Walls, however, argued that modern prejudice theory suggested more than just one domain of modern heterosexism and theorized the existence of four specific subdomains: aversive heterosexism, amnestic heterosexism, paternalistic heterosexism, and positive stereotypic heterosexism. As the current study utilizes the MHI, a brief summary of the four subdomains is presented next and the scale is included in Appendix A. For full discussion of the different domains, see Walls (in press-a). In contrast to hostile heterosexism, which uses rhetoric relying on traditional negative stereotypes to pathologize lesbian women and gay men, aversive heterosexism is couched in less inflammatory language. Aversive heterosexist rhetoric might argue that the lesbian and gay movement is wanting too much, too fast, or that the movement is militant. The aversion here is not necessarily a cognitive and emotional aversion to lesbian and gay people per se (although it could be), but rather aversion to the political and cultural demands of the movement or the pace of those demands. While much of white opposition to integration of African Americans in the southern U.S.A. in the 1960s was based on old-fashioned racist notions, some resistance from more moderate segments of society was, at least rhetorically, grounded in concern about the tactics and pace of social change, as well as the implications of that change on stability and established interests. Famous examples of such rhetoric include the "Call for Unity" and "An Appeal for Law and Order and Common Sense" letters written by religious leaders in Birmingham, Alabama to which King responded with his famous "Letter from a Birmingham Jail." Kopkind (1971) also demonstrates a similar political process whereby the Kerner Commission Report (National Advisory Commission on Civil Disorders, 1968) was watered down by political moderates who believed the initial recommendations were too radical and threatened established interests. Due to use of the term aversive, it might be tempting to assume that aversive heterosexism is akin to Gaertner and Dovidio's (1986) conceptualization of aversive racism. However, it should be noted that Gaertner and Dovidio's (1986) construct is based on the idea of a conflict between the values of egalitarianism and anti-black sentiments held at an unconscious level by the same individual. While an individual's aversive heterosexist discourse may very well emerge from a similar intrapsychic conflict about lesbian and gay people, aversive heterosexism has not been conceptualized in terms of its psychological etiology, but rather in terms of the social manifestation of particular forms of rhetoric that justify continuation of social stratification based on sexual orientation. The second form of modern prejudice is amnestic heterosexism. Endorsement of amnestic heterosexism is a shift to a cluster of attitudes that appear less hostile than aversive heterosexism. The amnestic heterosexist might suggest that discrimination is a thing of the
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past, and that lesbian women and gay men are treated fairly in contemporary society. The amnestic heterosexist may be making these claims out of ignorance, out of refusal to acknowledge factual information, for political mobilization reasons, or even out of life experience where they see many successful lesbian women and gay men. The third form of modern heterosexism is paternalistic heterosexism. Individuals may express this set of cognitive and affective components toward lesbian women and gay men as a conceptual social group or as concern for specific lesbian or gay (or potentially lesbian or gay) individuals. The conceptualization of paternalistic heterosexism requires both an expression of concern combined with an indication of preference for heterosexuality. A paternalistic heterosexist may express, for example, that while she does not have anything against gay or lesbian people, she would rather her daughter not be a lesbian because it would make her daughter's life harder in some way. The last domain of modern heterosexism is positive stereotypic heterosexism.1 This domain represents the endorsement of positive stereotypes (e.g., gay men are creative, lesbian women are independent). Positive stereotypic heterosexism reinforces stereotypes, albeit with a focus on alleged or actual appreciation for the stereotypic characteristic(s). While long overlooked by researchers, an increasing number of scholars are beginning to question the role that positive stereotypes may play in maintaining systems of stratification (Czopp, 2004, 2008; Morrison and Bearden, 2007; Walls, in press-a).
SOCIAL DOMINANCE ORIENTATION AND HETEROSEXISM SDO and Hostile Heterosexism Across different types of negatively-valenced prejudice against various social groups, social dominance orientation has been found to be one of the strongest predictors (Altemeyer, 1
One might question why a domain pertaining to negative stereotypes was not included in the MHI. While not conclusive, the research on the relationship between negative stereotypes of lesbian women and gay men, and what has been termed hostile heterosexism in this paper suggests a fairly robust relationship (Gentry, 1987; Jackson and Sullivan, 1990; Sigelman, Howell, Cornell, Cutright, and Dewey, 1990; Simon, 1998). For example, the stereotype that gay men are sexually promiscuous is related to prejudicial attitudes that suggest gay men are immoral or perverse. Thinking about the relationship between positive stereotypes and prejudicial attitudes raises a number of interesting research questions, including whether or not endorsement of positive stereotypes should be included in a measure of modern heterosexism. The answer may, in part, depend on whether heterosexism is conceptualized as either beliefs or attitudes, and the relationship between the two. In line with much of the social psychological literature, I see stereotypes and prejudice as different, but related. The distinction that stereotypes are cognitive beliefs and prejudices are evaluative attitudes (Azjen, 1989; Fishbein and Ajzen, 1975) is somewhat problematic. For example, the negative stereotype that gay men are pedophiles, I would argue, has embedded within it a negative evaluation (unless we want to suggest that being called a pedophile is non-evaluative). I adhere more closely with the model suggested by Zanna and Rempel (1988) whereby prejudicial attitudes are evaluations of an object that emerge from a combination of cognitive beliefs (including stereotypes), affective information, and past experiences. In theorizing a domain of heterosexism that I call positive stereotypic heterosexism, I am suggesting that there is a cluster of stereotypes (beliefs about characteristics common to lesbian women and gay men that are, in general, seen as positive attributes) that form a prejudicial attitude (positive stereotypic heterosexism) that functions to support social stratification based on sexual orientation. For more on the complex relationship between stereotypes and prejudice regarding lesbian women and gay men, see Simon (1998).
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1998). Likewise, while limited, the studies that have been published on the relationship between social dominance orientation and hostile heterosexism suggest that social dominance orientation functions similarly. Using various measures of hostile heterosexism (e.g., Attitudes towards Lesbians and Gay men [Herek, 1988], Heterosexual Attitudes toward Homosexuals [Larson, Reed, and Hoffman, 1980]), a few studies have demonstrated that higher levels of social dominance orientation are associated with increased levels of traditional, anti-gay prejudice (Kilianski, 2003; Pratto, Sidanius, Stallworth, and Bertram, 2000; Whitley and Ægisdóttir, 2000; Whitley and Lee, 2000). Further, while anti-egalitarianism and social dominance orientation are not the same theoretical concept, they are closely related, with attitudes toward egalitarianism occasionally being used as a proxy for social dominance orientation (Sidanius and Pratto, 1999). In line with the findings on social dominance orientation and hostile heterosexism, researchers have found consistently that hostile heterosexism is associated with increased anti-egalitarian attitudes and values, or conversely that pro-gay attitudes are associated with egalitarian attitudes (Biernat, Vescio, Theno, and Crandall, 1996; Brewer, 2003; Wilcox and Wolpert, 1996, 2000). Hegarty, Pratto, and Lemieux (2004) have argued – much in line with the symbolic racism literature – that a tension exists between the norm of egalitarianism and anti-gay affect resulting in what they call heterosexist ambivalence. Likewise, Ellis (2002) found that undergraduate students expressed high levels of endorsement of egalitarianism until it clashed with their ideological beliefs regarding lesbian women and gay men at which time their anti-gay/anti-lesbian beliefs appeared to override their commitment to equality.
SDO and Modern Heterosexism While there is not extensive research on modern forms of prejudice within the social dominance theoretical framework, what has been done has focused primarily on symbolic racism (Miller, Smith, and Mackie, 2004; see relatedly, Arriola and Cole, 2001) or modern sexism (Sibley and Wilson, 2004). These studies have tended to indicate that modern prejudice functions as predicted by social dominance theory. One study that has been published that examines social dominance orientation and various forms of heterosexism was completed by Worthington, Dillon, and Becker-Schutte (2005). They examined five subdomains of heterosexuals’ attitudes toward lesbian women and gay men. Two of those subdomains – hate and religious conflict – mirror traditional forms of hostile heterosexism, and in line with previous findings using more established measures of hostile heterosexism, higher levels of social dominance orientation were significantly correlated with both subdomains. One subdomain, knowledge of LGB history, symbols, and community, captured respondents' awareness of lesbian and gay culture and was – as expected – negatively related to social dominance orientation. Likewise the two remaining subdomains also were negatively related to social dominance orientation. They captured support for lesbian and gay civil rights, and what the authors termed internalized affirmation – a five-item factor which reflects “…a personalized affirmativeness and a willingness to engage in proactive social activism” (p. 108). While Worthington et al. (2005) found relationships in the expected directions between subdomains of heterosexism and social dominance orientation, their study has a number of limitations. First, they did not examine the mediating effect of prejudice on the relationship
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between social dominance orientation and public policy support that the theory predicts. While this may be seen simply as an avenue for future research, social dominance theory predicts hierarchy-enhancing legitimizing myths function specifically as mediating variables between SDO and public policy support. As such, in order to examine whether various domains of attitudes toward lesbian women and gay men functioned as hierarchy-enhancing legitimizing myths, the test of mediation is vital. The second limitation is that Worthington and colleagues' (2005) conceptualization of heterosexism fails to examine subdomains of attitudes toward lesbian women and gay men that have been suggested as integral components of modern heterosexism by either Morrison and Morrison (2002) or Walls (in press-a), or by the modern prejudice literature in general. These include clusters of attitudes such as believing that the lesbian and gay rights movement is too militant, or that discrimination is a thing of the past. With regard to the actual psychometrics of the measurement used, Worthington et al. (2005) acknowledged a number of inconsistencies across their studies, and potential issues with inflation of validity measures, leading them to recommend further examination of the psychometrics of the scale. Finally, the Worthington et al. (2005) scale does not discriminate between attitudes toward lesbian women and attitudes toward gay men which have been shown to be an important difference (Herek, 1988, 2000; LaMar and Kite, 1998; Whitley and Kite, 1993).
SOCIAL DOMINANCE ORIENTATION AND LESBIAN AND GAY RIGHTS While in general, higher degrees of social dominance orientation predict support for discriminatory public policies and opposition to values of harmony, openness and equality (Heaven and Bucci, 2001; Heaven and Connors, 2001; Knight, 2004; Pratto, Stallworth, and Conway-Lanz, 1998; Sibley and Liu, 2004), the vast majority of this research has not examined policies seeking to ameliorate inequities based on sexual orientation. The small amount of research that has been undertaken suggests that respondents higher in social dominance orientation are – as predicted by the theory – less likely to support lesbian and gay rights (Pratto et al., 1994), same-sex marriage (Cerecedes, 2003), and same-sex civil unions (Saucier and Cawman, 2004).
HETEROSEXISM AND LESBIAN AND GAY RIGHTS Hostile Heterosexism and Lesbian/Gay Rights More, though still limited, scholarship exists on the relationship between attitudes regarding lesbian women and gay men, and attitudes toward lesbian and gay rights. Higher levels of hostile heterosexism, not surprisingly, have been found to be predictive of opposition to lesbian and gay rights (Wood and Bartkowski, 2004; Yang, 1997), civil unions (Saucier and Cawman, 2004), equalizing age of sexual consent laws for heterosexuals and lesbian women/gay men (Moran, 2001; Waites, 2000, 2001), restrictive policies regarding HIV and AIDS (Dunlap, 1989; Jelen and Wilcox, 1992; Price and Hsu, 1992), and opposition to civil rights for transgender men and women (Tee and Hegarty, 2006). Likewise, stronger
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endorsement of negative stereotypes of lesbian women and gay men also has been associated with decreased support for a composite measure of gay and lesbian rights which included attitudes about adoption, serving in the military, and filing joint taxes (Wood and Bartkowski, 2004). It should be noted that few studies have examined the impact of hostile heterosexist attitudes on actual civic engagement behaviors that seek to directly affect public policy. One study that moved beyond the link between hostile heterosexism and public policy attitudes to an examination of political behavior was done by Saucier and Cawman (2004). They linked higher levels of hostile heterosexism with voting patterns, active opposition to Howard Dean’s candidacy for governor of Vermont, and increased support for Take Back Vermont, an organization seeking to abolish same sex civil unions in that state. In their analysis of the arguments offered by those supporting discrimination against lesbian women and gay men, Saucier and Cawman found a consistent claim that the opposition to same sex civil unions was not based in anti-gay/anti-lesbian attitudes per se, but rather was attributed to other factors – a pattern parallel to the one found in the aversive racism literature (Gaertner and Dovidio, 1986). Likewise, in examinations of the rhetoric used against the repeal of Section 28 in Great Britain – a repeal that would have equalized age of consent for sex for both opposite sex and same sex partners – Waites (2001) suggests that the arguments for antilesbian/anti-gay discrimination had undergone “refinement” such as discussing the repeal of Section 28 as “lowering the age of consent” instead of “equalizing the age of consent”. Moran (2001) noted that opponents of the repeal spoke carefully to avoid condemnation of homosexuality – instead of talking of sin, they talked of the “lack of moral equivalence” between heterosexuality and homosexuality.
Modern Heterosexism and Lesbian/Gay Rights Like most of the scholarship on heterosexism, the empirical work on the relationship between attitudes regarding lesbian women and gay men and public policies has focused predominately on hostile heterosexism. In the one study identified that examined the relationship directly, Morrison et al. (2005) found that modern heterosexism (as measured by the Modern Homonegativity Scale) was negatively correlated with support for lesbian and gay rights using the Support for Lesbian and Gay Human Rights scale (Ellis, Kitzinger, and Wilkinson, 2002). They tested the relationship between modern heterosexism toward lesbians with support for lesbian rights, and the relationship between modern heterosexism toward gay men with support for the rights of gay men. In both cases, the predicted relationship held. While it is clear that rhetoric used to legitimize support for the continuance of discriminatory policies based on sexual orientation is shifting away from traditional hostile heterosexist justification, other than the one study cited above, little is known about the relationship between modern forms of heterosexism and lesbian- and gay-related public policies.
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HYPOTHESES Social Dominance Orientation and Heterosexism Based on the existing literature, it is anticipated that higher scores on the SDO scale will be associated with higher scores on the Attitudes toward Lesbians and Gay Men (short form, ATLG-S; Herek, 1988), a measure of hostile heterosexism. This relationship, if found, would mirror previous findings. Given the empirical evidence of the relationship between social dominance orientation and modern forms of racism, sexism, and heterosexism, it is anticipated that higher scores on the SDO scale also will be associated with higher scores on all four measures of modern heterosexism (MHI-Amnestic, MHI-Aversive, MHI-Paternalistic, and MHI-Positive Stereotypic).
Social Dominance Orientation and Lesbian and Gay Rights Social dominance orientation has consistently been negatively correlated with support for policies that seek to decrease levels of social stratification. Therefore, it is anticipated that higher scores on the SDO scale will be associated with lower scores on the measure of support for lesbian and gay rights.
Heterosexism and Lesbian and Gay Rights Hostile heterosexism has consistently been shown to predict opposition to lesbian and gay rights when measured by a number of different instruments capturing homophobic attitudes. ATLG-S scores, therefore, should be negatively related to the measure of support for lesbian and gay rights. Research examining the relationship between modern forms of heterosexism and support for lesbian and gay rights is limited. One study found – as hypothesized – that increases in modern heterosexism (as measured by the Modern Homonegativity Inventory [Morrison and Morrison, 2002]) were associated with decreased support for gay and lesbian civil rights (Morrison et al., 2005). While not specifically using a measure of lesbian and gay rights per se, one other study examined the relationship between modern heterosexism and perceptions of hate crimes against lesbian women and gay men. The authors found that increases in their measure of modern heterosexism were associated with increased levels of approval of hate crimes, and decreased levels of perception of hate crimes as harmful and offensive (Cowan et al., 2005). In addition to these two empirical studies, a number of studies have demonstrated that opposition to public policies promoting equity for lesbian women and gay men has frequently been justified through rhetoric that moves away from condemnation of homosexuality as immoral (as would be expected in hostile heterosexism) toward justifications that appear less hostile (Burridge, 2004; Waites, 2001). This type of shift in political rhetoric supports the argument from the modern prejudice literature that when expression of prejudicial attitudes becomes stigmatized, new rhetoric and ideologies evolve
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that justify the continuation of social stratification based on rationale that appear “less” prejudicial. It could reasonably be argued that three of the four forms of modern heterosexism examined in this study – aversive heterosexism, amnestic heterosexism, and paternalistic heterosexism – fall under this rubric. Therefore, it is anticipated that higher scores on the MHI that capture these three domains of heterosexism (MHI-Amnestic, MHI-Aversive, MHIPaternalistic) will be associated with decreased scores on the measure capturing support for lesbian and gay rights. Only one additional subtype of heterosexism remains: positive stereotypic heterosexism. As positive stereotypic heterosexism is subjectively experienced as favorable, it might seem reasonable to expect that many of the respondents who endorse positive stereotypes of lesbian women and gay men may consider themselves non-heterosexist. As such, these respondents may very well be supportive of lesbian and gay rights. This rationale would lead to the hypothesis that those with higher levels of positive stereotypic heterosexism should be more supportive of lesbian and gay rights. However, another argument – with increasing empirical support – suggests the opposite (or a least a more complex) relationship. Research on the model minority stereotype about Asians (e.g., Asians are good students, Asians are good in math) has demonstrated that priming for these positive stereotypes can negatively affect Asian Americans' emotional state and performance on tasks related to the stereotype content under certain conditions (Chng, Ding, and Perez, 1998; Crystal, Chen, Fuligni, and Stevenson, 1994; Shih, Ambaday, Richeson, Fujita, and Gray, 2002) similar to the effect of negative stereotypes in stereotype threat contexts (Steele and Aronson, 1995). In their study of the model minority stereotype, Lin, Kwan, Cheung, and Fiske (2005) found that the more non-Asian respondents in their study stereotyped Asians as being highly competent, the less willing they were to be roommates with Asian American students. Czopp and Monteith's (2006) work on endorsement of positive stereotypes of African Americans suggests that some whites may use complimentary stereotypes (e.g., African Americans are natural athletes, African Americans are musically talented) as a way to establish moral credentials (Monin and Miller, 2001) that they are not racist, which in turn gives them greater permission to voice their hostile attitudes about African Americans. From a more structural perspective, Czopp (2004) found that white males were more likely to encourage African American student athletes than white student athletes to pursue professional sports careers at the expense of their academic performance. This suggests that positive stereotypes may play a role in maintaining structural occupational segregation by encouraging pursuit of careers that have a lower likelihood of success. Walls (2007-b) has demonstrated that positive stereotypes are correlated with decreased support for ameliorative public policies – at least for those who score low on hostile forms of prejudice. Finally, Jost and Kay (2005) found evidence that positive stereotypes can function as cultural scripts that justify and legitimize social stratification. Given the increasing amount of evidence that endorsement of positive stereotypes plays a role in maintaining social stratification, it is hypothesized, in accordance with social dominance theory, that positive stereotypic heterosexism will function as a hierarchyenhancing legitimizing myth. Therefore, higher scores on the MHI-Positive Stereotypic scale should be associated with lower scores on the measure capturing support for lesbian and gay rights.
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MEDIATING ROLE OF HETEROSEXISM The final hypotheses regard the central relationships predicted by social dominance theory. Figure 1 outlines the theoretical relationship whereby social dominance is directly associated with support for public policies that promote or challenge stratification, and social dominance is indirectly associated with support for those public policies through hierarchyenhancing and hierarchy-attenuating legitimizing myths such as prejudicial attitudes. In line with this theoretical understanding of the manner in which legitimizing myths function, it is predicted that the variables capturing all five subdomains of heterosexism (ATLG-S, MHIAmnestic, MHI-Aversive, MHI-Paternalistic, and MHI-Positive Stereotypic) will partially mediate the relationship between the SDO scale and the measure capturing support for lesbian and gay rights. If supported, these results will suggest that social dominance is associated directly with opposition to gay and lesbian rights, and indirectly through modern subdomains of heterosexism, acting as hierarchy-enhancing legitimizing myths.
METHOD Participants Participants in the study were undergraduates taking introductory social science courses at six U.S. colleges and universities. As one option to complete a course component on social science research, students could participate in the web-based study. Five of the research sites were private universities, consisting of two Catholic-affiliated schools, one Mennoniteaffiliated college, one Baptist-affiliated university, and one university not affiliated with a religious denomination. The sixth school was a medium-sized public university in the Midwest. The overall sample consisted of 651 undergraduates taking introductory social science courses, a sample size larger than the number needed to be adequate for testing of small to medium structural equation models which is approximately 400 (Boomsma, 1983). Of the 651 respondents, 70.1% were female and 29.9% were males. Caucasians made up the majority of the sample (81.1%), followed by Hispanics (6.7%), African Americans (5.4%), Asian/Asian Americans (3.9%), biracial (2.3%), and less than 1% each of individuals who identified as Native Americans, or other. The majority of respondents were first year students (54.2%), 25.5% were sophomores, 12.9% were juniors and the remaining 7.4% were seniors. Ages ranged from 18 to 56, with a mean of 20.4 years (SD = 4.5). Approximately 3% of the students identified themselves as lower class, followed by 19% as working class, 66% as middle class, and 12% as upper class. With regard to religion, respondents were asked a series of questions. First, they were asked, "What religion do you consider yourself?" with a response set of Buddhist, Christian, Hindu, Islamic, Jewish, No religious belief/agnostic/atheist, and Other, please specify. They were then asked, "If you are a Christian, which of the following categories best describes you?". The response set for this question was based on the religious tradition schema developed by Steensland et al. (2000) and included Catholic, Conservative non-traditional (Jehovah's Witness, Mormon, Christian Science, etc.), Evangelical Protestant (Baptist, AME,
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Church of God in Christ, Pentecostal, Assembly of God, etc.), Liberal non-traditional (Unitarian, Unity, Humanistic, Spiritualists, New Age, etc.), Mainline Protestant (Methodist, Presbyterian, Episcopal, United Churches of Christ, Disciples of Christ, etc.), and Nondenominational. Finally, as a check on respondents’ self-classification, they were asked the open-ended question, "What is the actual name of the church you attend or consider yourself to be part of (this information is for denominational classification purposes only)?" Combining the answers to these three questions to obtain a classification of religious tradition, it was found that 38.1% of the sample reported religious affiliations as Catholic, 34.1% with churches in denominations classified as conservative Protestant, 14.4% reported no religious affiliation, 11.6% as mainline or liberal Protestant, and the remaining 1.7% as other non-Christian religious affiliations. To determine political affiliation, respondents were asked, "On a scale of political ideology, individuals can be arranged from strongly liberal to strongly conservative. Which of the following best describes your views?" with a response set from Strongly liberal to Strongly conservative. Combining the categories of strongly liberal, somewhat liberal, and slightly liberal into one category, and the three corresponding categories at the conservative end of the continuum, almost 35% of the respondents consider themselves politically liberal, 24% moderate, and the remaining 41% conservative. The online survey was programmed in such a way as to decrease the likelihood of missed items or failure to complete the survey. For all missed items on the survey, the online program would prompt respondents to insure that they had intended to skip the question. Therefore, the range of missing data on items went from no missing values on the first four items of the survey to a maximum of eleven missing values (1.69%) on the income question. The vast majority of items had between three missing cases (0.5%) and seven missing cases (1.1%). Maximum likelihood multiple imputation was utilized using the LISREL 8.71 program (Jöreskog and Sörbom, 2002) to address issues of missing values.
Measures and Instruments The measures selected were drawn from published studies examining social dominance, prejudicial attitudes, and/or public opinions. All scales used have demonstrated adequate psychometric qualities. Hostile heterosexism. Negatively-valenced prejudicial attitudes toward lesbian women and gay men were captured using the short form of Herek’s (1988) Attitudes Towards Lesbians and Gay Men Scale (ATLG-S) . This scale and its long form version are among the most widely used scales to measure attitudes about lesbian women and gay men in the last twenty years (for recent examples, see Ellis et al., 2002; Span and Vidal, 2003; van de Meerendonk, Eisinga and Felling, 2003). The scale consists of ten items, five capturing attitudes toward lesbian women, and five capturing attitudes toward gay men. The scale contains items such as, "Female homosexuality is a sin," and "I think male homosexuals are disgusting." The response set used was a seven point Likert scale yielding a range of scores from 10 to 70. Higher scores indicate higher levels of hostile heterosexism. The scale and its longer version have undergone extensive testing for factor structure, item analysis, construct validity and reliability (Herek, 1984, 1987, 1988; Stoever and Morera, 2007; for a review of the empirical evidence of the validity of the short form of the scale, see Herek, 1994.)
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Modern heterosexism. The Multidimensional Heterosexism Inventory (MHI; Walls, in press-b; see Walls and Rodriguez, 2002 for earlier versions) captures four subdomains of modern heterosexism – aversive heterosexism, amnestic heterosexism, paternalistic heterosexism and positive stereotypic heterosexism. The reliability of the overall scale is reported at .82, while the reliabilities of the subdomain scales were reported at .84, .64, .89 and .90, respectively. The instrument consists of 23 questions with six items capturing aversive heterosexism, four capturing amnestic heterosexism, seven capturing paternalistic heterosexism, and six capturing positive stereotypic heterosexism (see Appendix A). The response set for the paternalistic heterosexism scale includes a seven point Likert scale with an additional response for those who do not have preference for a heterosexual child over a gay or lesbian child to indicate such. The response set for the remaining three scales are seven point Likert scales. Scores for each scale are standardized to a seven point range where higher numbers represent greater endorsement of that domain of heterosexism. The scales have performed as hypothesized with constructs such as authoritarianism, hostile heterosexism, interpersonal contacts, political ideology, gender role discrepancy, and religiosity. Social Dominance Orientation (SDO; Sidanius and Pratto, 1999). The Social Dominance Orientation (SDO) scale is a 16-item measure resulting from the testing of items on 18,741 respondents in 45 samples from eleven different countries. Some of the samples used for psychometric testing were probability samples, while others were convenience samples. Respondents have included secondary students, undergraduates and more than 4,500 nonstudent adults. (See Sidanius and Pratto [1999] for full details on samples.) The measure captures general preference for inequality among social groups and support for hierarchy. Questions include statements such as "Inferior groups should stay in their place" and "Some groups of people are simply inferior to other groups." The response set used was a seven point Likert scale yielding a possible range of scores from 16 to 112. Higher scores on the SDO scale indicate higher levels of social dominance orientation. SDO has demonstrated strong reliability including one study using a one-month time interval between administrations of the scale (r =.86, p<.01; Sidanius and Pratto, 1993). Sidanius and Pratto (1999) have demonstrated that the scale captures a construct that is distinct from political conservatism, authoritarianism, and a number of personality constructs including propensity for cruelty (Altemeyer, 1998), neuroticism, conscientiousness, agreeableness, openness to experience, and extroversion (Pratto et al., 1994). Support for lesbian/gay rights. Six questions were asked to determine respondents' level of support for lesbian and gay rights. Questions were based on recent political issues that have been in the media regarding public policies directly affecting lesbian women and gay men because of their sexual orientation. These questions include: (1) “Lesbian women and gay men should NOT be allowed to serve in the U.S. Armed Forces”; (2) “I favor laws to protect lesbian women and gay men against job discrimination” (Rosenstone, Kinder, Miller, and National Election Studies, 1996); (3) “Same-sex couples should have the right to marry one another” (Davis, Smith, and Marsden, 1998); (4) “Private same-sex sexual behavior between consenting adults should be illegal in the U.S.”; (5) “Lesbian women and gay men should NOT be allowed to adopt children even if they meet all the other criteria required of adoptive parents”; (6) “It is necessary to pass laws to make sure that lesbian women and gay men have equal rights” (CBS News/The New York Times, 1993). Responses to questions 1, 4, and 5 were reverse-coded. The response set was a seven point Likert scale resulting in a possible range of scores from 6 to 42. Higher scores indicate greater support for lesbian and gay rights.
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RESULTS In addition to the tests to determine whether the five subdomains of heterosexism function as hierarchy-enhancing legitimizing myths as predicted by social dominance theory, differences in the school subsamples were tested and are briefly discussed. Following that is the examination of the various scales reliabilities in the sample, broken down by gender, and this section ends with the tests of mediation. Analyses other than structural equation modeling were completed using Stata 9.2 (StataCorp, 2005), ScoreRel CI (Barnette, 2005), and MedGraph-I (Jose, 2003). LISREL was used for the structural equation modeling. Bonferroni adjustments were used to decrease likelihood of a Type I error. Mediation testing was conducted using a process similar to the four steps outlined by Baron and Kenny (1986). First, the path coefficient between SDO and the measure capturing support for lesbian and gay rights was examined for significance. Then, the coefficient between SDO and the measure capturing the specific domain of heterosexism was similarly examined. In the third step, the relationship between the measure capturing the specific domain of heterosexism and the measure capturing support for lesbian and gay rights was examined for significance, controlling for SDO. Finally, the difference in the path coefficient between SDO and the measure capturing support for lesbian and gay rights with and without the mediator variable was examined for significance using Sobel's (1982) test. Additionally two other measures are reported which represent slightly modified tests similar to Sobel's (Aroian, 1947; Goodman, 1960). For detailed information on the differences between the tests, see MacKinnon, Lockwood, Hoffman, West, and Sheets (2002).
Subsample Differences Data were collected at six different universities and colleges as a way to increase variability within the sample. The universities were chosen such that there was institutional variability in terms of characteristics such as religious affiliation (Catholic, Mennonite, Baptist, and secular), gender composition (coed and all female), social class (public and private), and political orientation (conservative, moderate, and liberal). As such, some of the variability on the dependent variable or on the mediating variables could be a result of such differences. To determine if differences existed, the dependent variable and the mediating variables were examined in two ways. First, the bivariate relationships were examined to determine if school differences emerged. Then, for variables in which school differences emerged, multivariate relationships were examined controlling for the above-mentioned characteristics that varied between the schools and on which purposive sampling of schools was based. In the bivariate examination, no differences emerged on the primary dependent variable, the measure of support for lesbian and gay rights, nor on the mediating variables, MHIAmnestic and MHI-Paternalistic (analyses not shown). Differences did, however, emerge on the mediating variables, ATLG-S, MHI-Aversive, and MHI-Positive Stereotypic whereby one or two schools differed significantly from the others. All significant differences, however, disappeared once religious affiliation, social class, gender, and political orientation were added to the analyses.
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Descriptive Statistics and Scale Score Reliabilities Table 1 shows the reliability coefficients with 95% confidence intervals, means and standard deviations for the SDO, the support for lesbian and gay rights scale, the ATLG-S, and the four scales of the MHI. Additionally, information is included on the percentage of the sample that scored above the midpoint on each of the separate scales. Inspection of the mean scale scores indicates that, on average, males score higher on SDO, ATLG-S, and all four scales of the MHI, and females score higher on support for lesbian and gay rights (analyses not shown). Gender differences were examined using t-tests, with results indicating that male and female participants differed significantly (p<.05) on all scales with the exception of the paternalistic heterosexism. Table 2 lists the correlations for all scales.
Mediation Results Hostile heterosexism Hostile heterosexism functions as a hierarchy-enhancing legitimizing myth as predicted by social dominance theory. Figure 2 illustrates the structural relationship between social dominance orientation, hostile heterosexism, and support for lesbian and gay rights. Increased levels of social dominance orientation positively related to increased levels of hostile heterosexism (p<.001) and negatively related to support for lesbian and gay rights (p<.001). Likewise, hostile heterosexism is negatively related to support for lesbian and gay rights (p<.001). Hostile heterosexism partially mediates the relationship between social dominance orientation and support for lesbian and gay rights, reducing social dominance orientation’s relationship with support for lesbian and gay rights from a t-value of -8.43 in the bivariate relationship (not shown) to a t-value of -3.35. A Sobel's test value of 6.06 (Aroian value = 6.06, Goodman value = 6.07) indicates significance. Table 1. Descriptive Statistics and Alpha Coefficients for All Scales Group
M
SD
% above scale midpoint
α (95% CI)
Hostile Heterosexism (ATLG-S)
Men
41.46
15.97
53.89%
.92 (.91-.94)
Women
35.56
17.94
39.33%
.95 (.94-.95)
Modern Heterosexism (MHI-Amnestic)
Men
2.89
1.17
11.92%
.79 (.74-.83)
Women
2.34
1.03
3.74%
.78 (.74-.81)
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Group
M
SD
% above scale midpoint
α (95% CI)
Modern Heterosexism (MHI-Aversive)
Men
4.42
1.29
60.94%
.87 (.84-.90)
Women
3.91
1.49
46.37%
.92 (.90-.93)
Modern Heterosexism (MHI-Paternalistic)
Men
3.83
2.18
63.73%
.95 (.93-.96)
Women
3.64
2.28
61.06%
.95 (.95-.96)
Modern Heterosexism (MHI-Positive Stereotypic)
Men
3.38
1.32
30.05%
.88 (.85-.90)
Women
3.03
1.24
19.11%
.87 (.85-.89)
Social Dominance Orientation (SDO)
Men
44.16
17.83
14.51%
.89 (.86-.91)
Women
37.62
15.72
6.43%
.89 (.88-.91)
Support for Lesbian and Gay Rights
Men
25.31
9.86
52.33%
.87 (.83-.89)
Women
31.00
9.24
74.17%
.86 (.84-.88)
Table 2. Intercorrelations among Scales
Variable
1
2
3
4
1. ATLG-S 2. MHI - Amnestic 3. MHI - Aversive 4. MHI – Paternalistic 5. MHI - Positive stereotypic 6. SDO 7. Lesbian/Gay rights
-.34*** .74*** .23***
-.38*** .09**
-.27***
--
.07*
.30***
.18***
.14***
--
.29*** -.83***
.28*** -.39***
.36*** -.70***
.18*** -.21***
.19*** -.07*
Note. ***p<.001, **p<.01, *p<.05.
5
6
7
--.35***
--
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Figure 2. Hostile heterosexism as a partially mediating factor in the relationship between social dominance orientation and support for lesbian and gay rights. Note. ***p<.001, Bonferroni adjusted. Standard errors in parentheses. Measurement model omitted from diagram.
Aversive heterosexism. Aversive heterosexism also appears to work in the manner predicted by social dominance theory. Figure 3 illustrates the relationship. In the model, higher levels of social dominance orientation are associated with higher levels of aversive heterosexism (p<.001), and lower levels of support for lesbian and gay rights (p<.001). Aversive heterosexism is negatively related to support for lesbian and gay rights (p<.001) and partially mediates the relationship between social dominance orientation and support for lesbian and gay rights (i.e., a t-value of -8.43 in the bivariate relationship between social dominance orientation and support for lesbian and gay rights is reduced to that of a t-value of -4.55). The mediation effect is significant as indicated by a Sobel's test value of 6.03 (Aroian value = 6.01, Goodman value = 6.04). Amnestic heterosexism. Social dominance orientation is positively related to amnestic heterosexism (p<.001), and negatively related to support for lesbian and gay rights (p<.001). Amnestic heterosexism is negatively related to support for lesbian and gay rights (p<.001). The addition of amnestic heterosexism to the model reduces the t-value of -8.43 for the bivariate relationship between social dominance orientation and support for lesbian and gay rights to a t-value of -5.26. Amnestic heterosexism partially mediates the relationship resulting in a Sobel's test value of 4.65 (Aroian value = 4.63, Goodman value = 4.68). This model is illustrated in Figure 4. Paternalistic heterosexism. Paternalistic heterosexism functions as predicted. Figure 5 shows the results of the model. Social dominance orientation is significantly correlated with paternalistic heterosexism (p<.001), and support for lesbian and gay rights (p<.05), while paternalistic heterosexism is negatively correlated with support for lesbian and gay rights (p<.001). The relationship between social dominance orientation and support for lesbian and gay rights is partially mediated by the addition of paternalistic heterosexism to the model
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represented by a drop in t-value from -8.43 in the bivariate relationship to -3.34. A Sobel's test value of 2.60 (Aroian value = 2.51, Goodman value = 2.55) indicates significance. Positive stereotypic heterosexism. The last subdomain of heterosexism to be examined is positive stereotypic heterosexism. The hypotheses that increased levels of social dominance orientation are associated with increased levels of positive stereotypic heterosexism (p<.001), and with decreased support for lesbian and gay rights (p<.001) are supported (see Figure 6). Contrary to what was predicted, however, positive stereotypic heterosexism moves from a significant negative relationship with support for lesbian and gay rights in the bivariate relationship (t = -2.64, not shown) to a level of non-significance (t = -0.52) in the full model. This suggests that the endorsement of positive stereotypes may either function entirely differently than predicted by social dominance theory or have a more complex role in the maintenance of social stratification than do negatively-valenced forms of prejudice, be they hostile or modern.
CONCLUSION In this paper, the functioning of hostile and modern forms of heterosexism has been examined within a social dominance theoretical framework. In line with prior research, higher levels of social dominance orientation were positively associated with higher levels of all of the domains of heterosexism, and negatively associated with support for lesbian and gay rights. Similarly greater levels of all domains of heterosexism were negatively associated with support for lesbian and gay rights. This suggests that one way to decrease prejudicial attitudes toward lesbian women and gay men might be to attempt to decrease levels of social dominance orientation; that is, to challenge ideas that some groups in society deserve more than other groups. It also suggests that work toward decreasing levels of social dominance orientation, as well as directly challenging attitudes toward lesbian women and gay men could have a positive impact on increasing support for lesbian and gay rights. Shifting our attention to the various tests of mediation, the findings suggest that the more negatively-valenced forms of modern heterosexism (aversive, amnestic, and paternalistic) function very well as hierarchy-enhancing legitimizing myths similar to the functioning of hostile heterosexism. However, because all tests of mediation indicated partial, rather than full mediation, a relationship continued to exist between social dominance orientation and support for lesbian and gay rights in the models. Would this remaining relationship between social dominance orientation and support for lesbian and gay rights continue to exist if tests of multiple mediations in the same model had been conducted, or are there other hierarchyenhancing legitimizing myths (e.g., endorsement of traditional gender roles) that explain the remaining relationship between the two? Given the linkages between heterosexism and sexism, it seems that it is reasonable to assume that factors other than just prejudice toward lesbian women and gay men (in all of its various forms) might be functioning as mediators between social dominance orientation and support for lesbian and gay rights.
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Figure 3. Aversive heterosexism as a partially mediating factor in the relationship between social dominance orientation and support for lesbian and gay rights. Note. ***p<.001, Bonferroni adjusted. Standard errors in parentheses. Measurement model omitted from diagram.
Figure 4. Amnestic heterosexism as a partially mediating factor in the relationship between social dominance orientation and support for lesbian and gay rights. Note. ***p<.001, Bonferroni adjusted. Standard errors in parentheses. Measurement model omitted from diagram.
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Figure 5. Paternalistic heterosexism as a partially mediating factor in the relationship between social dominance orientation and support for lesbian and gay rights. Note. ***p<.001 *p<.05, Bonferroni adjusted. Standard errors in parentheses. Measurement model omitted from diagram.
Figure 6. Positive stereotypic heterosexism as a (non-significant) mediating factor in the relationship between social dominance orientation and support for lesbian and gay rights. Note. ***p<.001, Bonferroni adjusted. Standard errors in parentheses. Measurement model omitted from diagram. Path between positive stereotypic heterosexism and support for lesbian and gay rights is non-significant.
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The final domain of modern heterosexism which captures the endorsement of positive stereotypes, however, appears to function somewhat differently than is predicted by social dominance theory. Given Walls’ (2007-b) findings that the endorsement of positive stereotypes operate differently depending on the level of hostile prejudice, this finding is not surprising, and suggests that more research needs to be conducted to better understand the role of positive stereotypes in supporting social stratification. It is possible that positive stereotypic heterosexism has a moderated mediation effect on the relationship between social dominance orientation and support for lesbian and gay rights, such that the relationship is different for those who are high on hostile heterosexism than for those who are low on hostile heterosexism. Or the moderating variable may be the subject's own sexual orientation. It could be that a mediating relationship exists, but only for heterosexuals. The other primary implication of these findings is that – as other scholars have suggested – prejudicial attitudes toward lesbian women and gay men are multidimensional (i.e., rather than there being a single form of heterosexism, these attitudes are better conceptualized as a system of heterosexisms). The empirical and anecdotal evidence consistently indicates that the face of prejudice against lesbian women and gay men has changed – and is continuing to change. The shift from the more traditional hostile attitudes to an ideology that may appear to be less harsh and prejudicial is embedded within a context where the open, direct expression of prejudice is increasingly stigmatized. This shifting decrease in the expression of hostile prejudice may be an attempt to avoid stigmatization, a protection of self- or group-esteem, a protection of a non-prejudiced self-identity, a desire to justify an inequitable social structure, or some combination thereof. What is evident, however, is that it is no longer adequate to talk of heterosexism to indicate only hostile forms of prejudice. Doing so will likely exclude a large part of the landscape of prejudice as it is experienced and expressed today. The changing nature of prejudice also implies another caveat. The instruments used here to capture modern prejudice against lesbian women and gay men will – at some point in the future – be outdated and in need of revision. Using these instruments in the current context however will help create a public record of the shifts in prejudice so that we – as scholars – can not only understand what prejudice looks like in a certain sociohistorical context with a certain population, but we also can begin to study the factors that foster shifts in the specific manifestations of prejudice. Finally, the effects, dynamics, processes and content of positive stereotypes are an area of research within which little has been undertaken. Pioneers in this area like Jackman (1994) have convincingly argued that positively-valenced attitudes may be more functional in the long run at maintaining the oppression of certain groups than attitudes that are outright hostile. Similarly, researchers such as Czopp (2008, see also Czopp and Monteith, 2006) have demonstrated empirical support for the need to look more closely at the endorsement of positive stereotypes. As we grapple with the increasing multicultural nature of our world, we must not categorically dismiss positive stereotypes, nor underestimate the role they may play in reinforcing social stratification. There are several limitations to the study that warrant mention. The most obvious limitation of the study is its reliance on an undergraduate, convenience sample which has been one of the major criticisms of much social psychological research (Myers, 1983; Wintre, North and Sugar, 2001). Since all studies depart from the ideal research design in some ways with various trade-offs having to be negotiated by the researcher, the important question is, then, in what ways might this study’s departure from the ideal influence its findings and the
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ability to infer from the results? An examination of the empirical literature regarding the relationships between prejudicial attitudes (Glick and Fiske, 1996; McFarland and Adelson, 1996; Whitley and Lee, 2000), social dominance orientation (Sidanius, Pratto, and Bobo, 1994; see also Altemeyer, 1998; Pratto, Sidanius, and Stallworth, 1993; Pratto et al., 1994; Sidanius, Levin, Liu and Pratto, 2000; Sidanius and Pratto, 1993; Whitley and Lee, 2000), and public policies (Alwin and Krosnick, 1991) suggest that differences between undergraduate samples and non-student adult samples are minimal. The empirical findings of the above studies suggest, first, that the idea that young adults have substantially less stability in sociopolitical attitudes than other age groups is weakly supported. Second, they suggest that the relationships between the attitudinal constructs used in this project and attitudes regarding homosexuality are likely to be stronger in the U.S. adult population than among college undergraduates in the U.S. Therefore, findings with college undergraduates provide a conservative estimate of the relationships between constructs found in the adult population. Another limitation for the study concerns the role of gender and sexual orientation in the results. Research has clearly shown that both the gender of the subject as well as the gender of the target of the attitudes has an impact on the results of studies examining attitudes toward lesbian women and gay men (Herek, 1988, 2000; LaMar and Kite, 1998; Whitley and Kite, 1993). It is possible that gender is a moderating variable in the results found here and future research should examine whether gender influences the relationships. Similarly, the survey did not ask about participants’ sexual orientation. It is reasonable to assume that the relationships between the variables of interest in this study may vary depending on the sexual orientation of the participant. For example, in his study of positive stereotypes of women, Walls (2007-b) found an interaction effect between endorsement of positive stereotypes and levels of hostile sexism on the support for women's rights among males in his sample, but not among females. The findings and limitations of the study suggest potential avenues for future study. Replication of the study with a non-undergraduate sample could address some of the issues of generalizability and further support (or challenge) the notion that relationships such as the ones that emerged in this study are conservative tests of the same relationships in the general population. Additional work on the possibility of a moderated mediation effect based on either levels of hostile heterosexism, gender, or sexual orientation may provide more clues as to the way in which positive stereotypic heterosexism functions in the maintenance of social stratification based on sexual orientation. More complex models, such as combining all of the tested mediation effects into a single model, might also offer additional insight into the ways in which a system of heterosexisms functions as hierarchy-enhancing legitimizing myths. Finally, other potential mediating variables – particularly those around issues of gender – could be examined to determine whether other factors influence the relationship between social dominance orientation and support for lesbian and gay rights.
APPENDIX A Multidimensional Heterosexism Inventory For this first group of questions, please check the answer that best matches your agreement or disagreement with the statement
Strongly Disagree 1. Lesbianism is given too much attention in today's society. 2. Gay men are treated as fairly as everyone else in today's society. 3. Lesbians are better than heterosexual women at physically defending themselves. 4. Lesbians make too much noise about their sexuality. 5. Gay men take better care of their bodies than do heterosexual men. 6. Most people treat lesbians as fair as they treat everyone else. 7. Gay men should stop shoving their lifestyle down everyone else's throat. 8. Lesbians are more independent than heterosexual women. 9. Things would be better if lesbians would quit trying to force their lifestyle on everyone else. 10. Gay men no longer face discrimination in the U.S. 11. Lesbians have become too radical in their demands. 12. Gay men are more compassionate than heterosexual men. 13. Lesbians excel at outdoor activities more than heterosexual women. 14. There is too much attention given to gay men on television and in the media. 15. Discrimination against lesbians is virtually non-existent in today's society. 16. Lesbians are better than heterosexual women at auto maintenance and repair.
Somewhat disagree
Slightly Disagree
Neither Agree nor Disagree
Slightly Agree
Somewhat Agree
Strongly Agree
Appendix A (Continued) For this second group of questions, we ASSUME that you have a son/daughter or we ask you to IMAGINE that you have a child if you do not have one. Please check the answer that most closely matches your agreement or disagreement with each statement. Also note, that sometimes the question refers to having a daughter and sometimes to having a son. If you agree with ALL parts of the statement then your answer should be on the agree side of the scale. If you disagree with ANY part of the statement then your answer should be on the disagree side of the scale. If you are just as happy having a gay/lesbian kid as a heterosexual kid, then you can check the OK with Gay Kid answer.
Okay with gay kid 17. I would prefer my daughter NOT be homosexual because she would unfairly be stopped from adopting children. 18. I would prefer my son NOT be homosexual because most churches would unfairly reject him. 19. I would prefer my daughter NOT be homosexual because she would face unfair discrimination. 20. I would prefer my son NOT be homosexual because he would unfairly be denied the right to marry the man he loved. 21. I would prefer my daughter NOT be homosexual because religious institutions unfairly reject lesbians. 22. I would prefer my son NOT be homosexual because it would unfairly be harder for him to have or adopt children. 23. I would prefer my son NOT be homosexual because he would unfairly be discriminated against.
Strongly Disagree
Somewhat disagree
Slightly Disagree
Neither Agree nor Disagree
Slightly Agree
Somewhat Agree
Strongly Agree
Scoring Questions 3, 5, 8, 12, 13, and 16 capture positive stereotypic heterosexism. Questions 2, 6, 10, and 15 capture amnestic heterosexism. Questions 1, 4, 7, 9, 11, and 14 capture aversive heterosexism. Questions 17, 18, 19, 20, 21, 22, and 23 capture paternalistic heterosexism. To score the positive stereotypic heterosexism, amnestic heterosexism, and aversive heterosexism scales, total items substituting 1 to 7 for strongly disagree, somewhat disagree, slightly disagree, neither agree nor disagree, slightly agree, somewhat agree, and strongly agree, respectively. Divide by the number of items in the scale to get a standardized score where higher numbers represent greater agreement. To score the paternalistic heterosexism scale, total items substituting 1 to 8 for okay with gay kid, strongly disagree, somewhat disagree, slightly disagree, neither agree nor disagree, slightly agree, somewhat agree, and strongly agree, respectively. Divide total by eight to get an average score. To standardize score so that it is on a metric comparable to the other three scales, multiply the average score by seven, then divide by eight.
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Sigelman, C. K., Howell, J. L., Cornell, D. P., Cutright, J. D., and Dewey, J. C. (1990). Courtesy stigma: The social implications of associating with a gay person. Journal of Social Psychology, 13, 45-56. Simon, A. (1998). The relationship between stereotypes of and attitudes toward lesbians and gays. In G. M. Herek (Ed.), Stigma and sexual orientation: Understanding prejudice against lesbians, gay men, and bisexuals (pp. 62-81). Thousand Oaks, CA: Sage. Smith, K. T. (1971). Homophobia: A tentative personality profile. Psychological Reports, 29, 1091-1094. Sobel, M. E. (1982). Asymptotic intervals for indirect effects in structural equation models. In S. Leinhart (Ed.), Sociological methodology 1982 (pp. 290-312). San Francisco: JosseyBass. Span, S. A., and Vidal, L. A. (2003). Cross-cultural differences in female university students’ attitudes toward homosexuals: A preliminary study. Psychological Reports, 92, 565-572. StataCorp. (2005). Stata Statistical Software: Release 9.2. College Station, TX: StataCorp LP. Steele, C., and Aronson, J. (1995). Stereotype threat and the intellectual test performance of African Americans. Journal of Personality and Social Psychology, 69, 797-811. Steensland, B., Park, J. Z., Regnerus, M. D., Robinson, L. D., Wilcox, W. B., and Woodberry, R. D. (2000). The measure of American religion: Toward improving the state of the art. Social Forces, 79, 291-318. Stoever, C. J., and Morera, O. F. (2007). A confirmatory factor analysis of the Attitudes toward Lesbians and Gay Men (ATLG) measure. Journal of Homosexuality, 52, 189-209. Swim, J. K., Aiken, K. J., Hall, W. S., and Hunter, B. A. (1995). Sexism and racism: Oldfashioned and modern prejudices. Journal of Personality and Social Psychology, 68, 199214. Tee, N., and Hegarty, P. (2006). Predicting opposition to the civil rights of trans persons in the United Kingdom. Journal of Community and Applied Social Psychology, 16, 70-80. Tougas, F., Brown, R., Beaton, A. M., and Joly, S. (1995). Neosexism: Plus ça change, plus c'est pareil. [The more things change, the more they are the same]. Personality and Social Psychology Bulletin, 21, 842-849. van de Meerendonk, B., Eisinga, R., and Felling, A. (2003). Application of Herek’s Attitudes toward Lesbians and Gay Men (ATLG) scale in the Netherlands. Psychological Reports, 93, 265-275. van Hiel, A., and Mervielde, I. (2005). Authoritarianism and social dominance orientation: Relationships with various forms of racism. Journal of Applied Social Psychology, 35, 2323-2344. van Hiel, A., Pandelaere, M., and Duriez, B. (2004). The impact of need for closure on conservative beliefs and racism: Differential mediation by authoritarian submission and authoritarian dominance. Personality and Social Psychology Bulletin, 30, 824-837. Waites, M. (2000). Homosexuality and the New Right: The legacy of the 1980s for new delineations of homophobia. Sociological Research Online, 5. Retrieved January 18, 2007, from http://www.socresonline.org.uk/5/1/waites.html Waites, M. (2001). Regulation of sexuality: Age of consent, Section 28, and sex education. Parliamentary Affairs, 54, 495-508. Walls, N. E. (in press-a). Toward a multidimensional understanding of heterosexism: The changing nature of prejudicial attitudes. Journal of Homosexuality.
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Walls, N.E. (2007-b). Grappling with the relationship between endorsement of positive stereotypes and support for equal rights. Advances in Gender Research. Walls, N. E., and Rodriguez, R. R. (2002, November). Construction of the Tetradic Heterosexism Index: Understanding the complexities of attitudes toward lesbian women and gay men. Paper presented at the meeting of the Society for the Scientific Study of Sexuality, Montreal, Canada. Weinberg, G. (1974). Society and the healthy homosexual. New York: Doubleday. Whitley, B. E., Jr., and Ægisdóttir, S. (2000). The gender belief system, authoritarianism, social dominance, and heterosexuals’ attitudes toward lesbians and gay men. Sex Roles, 42, 947-967. Whitley, B. E., Jr., and Kite, M. E. (1993). Sex differences in attitudes toward homosexuality: A comment on Oliver and Hyde. Psychological Bulletin, 117, 147-154. Whitley, B. E., Jr., and Lee, S. E. (2000). The relationship of authoritarianism and related constructs to attitudes toward homosexuality. Journal of Applied Social Psychology, 30, 144-170. Wilcox, C., and Wolpert, R. M. (1996). President Clinton, public opinion, and gays in the military. In C. A. Zimmerman (Ed.), Gay rights, military wrongs: Political perspectives on lesbians and gays in the military (pp. 127-145). New York: Garland Publishing. Wilcox, C., and Wolpert, R. M. (2000). Gay rights in the public sphere: Public opinion on gay and lesbian equality. In C. A. Zimmerman, K. D. Wald, and C. Wilcox (Eds.), The politics of gay rights (pp. 409-432). Chicago, IL: University of Chicago Press. Wintre, M. G., North, C., and Sugar, L. A., (2001). Psychologists’ response to criticisms about research based on undergraduate participants: A developmental perspective. Canadian Psychology, 42, 216-225. Wood, P. B., and Bartkowski, J. P. (2004). Attribution style and public policy attitudes toward gay rights. Social Science Quarterly, 85, 58-74. Worthington, R. L., Dillon, F. R., and Becker-Schutte, A. M. (2005). Development, reliability, and validity of the Lesbian, Gay, and Bisexual Knowledge and Attitudes Scale for Heterosexuals (LGB-KASH). Journal of Counseling Psychology, 52, 104-118. Yang, A. S. (1997). The polls-trends: Attitudes toward homosexuality. Public Opinion Quarterly, 61, 477-507. Zanna, M. P., and Rempel, J. K. (1988). Attitudes: A new look at an old concept. In D. BarTal and A. W. Kruglanski (Eds.), The social psychology of knowledge (pp. 315-334). Cambridge, MA: Cambridge University Press.
In: The Psychology of Modern Prejudice Editor: Melanie A. Morrison and Todd G. Morrison
ISBN 978-1-60456-788-5 © 2008 Nova Science Publishers, Inc.
Chapter 11
MODERN RAPE MYTHS: THE ACCEPTANCE OF MODERN MYTHS ABOUT SEXUAL AGGRESSION (AMMSA) SCALE Friederike Eyssel and Gerd Bohner Universität Bielefeld, Germany
ABSTRACT Rape myths are attitudes about sexual violence that blame the victim while exonerating the perpetrator of a rape (Bohner, 1998). In the past, such myths have been assessed with “traditional” measures, which are marked by rather blatant item wording. To overcome the problems of classic measures of rape myth acceptance (RMA), the “Acceptance of Modern Myths about Sexual Aggression” (AMMSA; Gerger, Kley, Bohner, and Siebler, 2007) scale was developed. Following the approach taken in research on modern forms of racism and sexism (see Swim, Aikin, Hall, and Hunter, 1995), this scale assesses both less obvious myths about rape and myths about less severe forms of sexual aggression. A series of studies tested the reliability and validity of the newly developed measure. The chapter will review these findings along with more recent research on the AMMSA scale.
INTRODUCTION In his landmark monograph, “The Nature of Prejudice,” Allport (1958/1954) defined prejudice as “an aversive or hostile attitude toward a person who belongs to a group, simply because he belongs to that group, and is therefore presumed to have the objectionable qualities ascribed to the group” (p. 8). Such negative attitudes based on faulty overgeneralizations have been studied extensively in research on intergroup relations, with ethnic prejudice and sexism being two highly prominent domains of study. The importance of this research derives from the fact that racial and gender prejudices are among the main factors underlying discriminatory behavior (Plous, 2003). Recognizing and understanding the psychological mechanisms underlying prejudice can ultimately help in devising ways of
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eliminating, or at least counteracting, discrimination on the basis of race or gender (see Crosby, Iyer, and Sincharoen, 2006). In this chapter we focus on a set of prejudiced beliefs that have come to be known as “rape myths”. These may formally be defined as “descriptive or prescriptive beliefs about rape (i.e., about its causes, context, consequences, perpetrators, victims, and their interaction) that serve to deny, downplay or justify sexual violence that men commit against women” (Bohner, 1998, p. 14)1. At first glance, this definition does not easily fit Allport’s definition of prejudice, because the scope of rape myths seems to be wider than that of “attitudes toward persons”. However, there are many similarities between these concepts. Across scientific disciplines, the term "myth" commonly denotes false or biased beliefs which are widely shared and serve to explain and justify existing "cultural arrangements" (Lonsway and Fitzgerald, 1994). Thus, like prejudice in general, rape myths have been shown to be widely held in society (e.g., Amnesty International UK, 2005; Feild, 1978; Ward, 1995; Weis, 1982) and serve to rationalize and maintain a status quo of injustice or inequality (see Allport, 1958; Bohner, 1998). Aspects of intergroup relations also are core ingredients of rape myths: First because perpetrator and victim status in sexual violence covary strongly with gender, and secondly because women who endorse rape myths tend to construe rape victims as a stigmatized out-group (for a review, see Bohner, 1998).
MODERN FORMS OF PREJUDICE A further important parallel between rape myths and other prejudiced beliefs is the fact that their content and expression seem to have changed over the last three decades. In the course of societal and socio-political developments, it has become a cultural norm to endorse egalitarian, anti-racist and anti-sexist values and beliefs, and to take seriously the plight of victims of sexual violence. Or at least, it has become increasingly unacceptable to openly express negative affect or beliefs about racial out-groups, women, or victims of sexual violence. In the domain of racism research, it has been found that the expression of racism “is more subtle in modern society than in the past” (Swim, Aikin, Hall, and Hunter, 1995, p. 199). As people refrain from displaying their racist attitudes and beliefs, their negative resentments remain under the surface; yet, they are still present and may continue to cause discriminatory behavior. In the literature, these developments have been captured with labels such as symbolic racism (Sears, 1988), aversive racism (Dovidio, Mann, and Gaertner, 1989; Gaertner and Dovidio, 1986), racial ambivalence (Katz, Wackenhut, and Hass, 1986), or modern racism (McConahay, 1986; Pettigrew, 1989). According to Sears (1988), the beliefs underlying modern racism are threefold: (1) the denial of continuing discrimination, (2) antagonism to Black people’s demands, and (3) resentment about special favors for Black people (see also McConahay, 1986). Swim and her colleagues (1995) drew parallels between modern racism and modern sexism and applied a similar theoretical framework to the field of gender-related prejudice. 1
Rape myths also can pertain to men and men also can fall victim to the crime of rape (King, 1992; Scarce, 1997). However, because the vast majority of rape victims are female and the majority of rape perpetrators male, we focus on this particular perpetrator-victim constellation.
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They compare the situation of Black people and women because nowadays the expression of prejudicial or stereotypical views is not socially sanctioned, independent of whether the target is a Black person or a woman. Women, too, have been striving for equal rights and advancement in the workplace, which has resulted in the establishment of a range of policies and measures to counter gender inequality. Whereas a modern sexist may express a positive attitude toward women as a group, he or she still holds the view that such initiatives grant women rights and advantages which threaten the presumed equality of men and women. They not only “resent complaints about discrimination” (Swim and Cohen, 1997, p. 105) – modern sexists even deny the existence of discrimination against women and, thus, are convinced that any effort against discrimination is in fact unnecessary. Summing up, “beliefs are defined as modern sexist if they support the maintenance of the status quo of gender inequality” (Swim and Campbell, 2001, p. 221; for a similar approach, see Tougas, Brown, Beaton, and Joly, 1995). In racism and sexism research, self-report measures have been devised to assess modern forms of prejudice (for a review, see Swim et al., 1995). They are characterized by more subtle, indirect item content, which capture the three themes of modern prejudice identified by Sears (1988). Research on these measures has established the validity of the modern racism and modern sexism constructs and shown them to be distinct from “old-fashioned” forms of prejudice (e.g., Swim et al., 1995). In what follows, we turn to parallel developments in the domain of rape myths.
MODERN RAPE MYTHS: CONTENT AND MEASUREMENT As with racism and sexism, societal changes are likely to have had an impact on both the content of, and the willingness to report, beliefs related to sexual violence. If this is true, then it would be useful to develop a new instrument for assessing these beliefs. Like modern racism and sexism scales, such a new instrument should capture the content of current beliefs, and should address them in a subtle manner in order to avoid socially desirable response tendencies. Prominent and widely used scales designed to assess “old-fashioned” rape myth acceptance (RMA) have been proposed by Feild (1978), Burt (1980), Costin (1985), and, most recently, by Payne, Lonsway, and Fitzgerald (1999). As far as the content of rape myth items is concerned, it varies widely across the different scales (for reviews, see Bohner, 1998; Lonsway and Fitzgerald, 1994). However, most of the common myths tend to blame the victim (e.g., “Women often provoke rape through their appearance or behavior”), exonerate the perpetrator (e.g., “Men often can't control their sexual urges”), and deny or belittle the violence inherent in rape (e.g., “Women often make up rape accusations as a way of getting back at men”; “When a woman starts a relationship with a man, she must be aware that the man will assert his right to have sex ”; see Burt, 1991). As these examples show, the wording used is rather blatant. We believe this is a major problem with the established RMA scales. Specifically, in recent studies, participants’ responses have often been close to the low endpoint of the response scale which has resulted in severely positively skewed RMA distributions. Findings reported by Payne and her colleagues (1999, p. 52) represent a good example of this tendency: In their study, using a 1
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to 7 Likert scale, the average RMA scores of female and male participants were 2.1 and 2.7, respectively. In a recent study using a German version of Costin’s (1985) Rape Scale (Bohner, Siebler and Schmelcher, 2006), male participants’ mean scores were 2.6 (Exp. 1) and 2.7 (Exp. 2) on a scale ranging from 1 (do not agree at all) to 7 (agree very much). The distribution of this RMA measure was considerably positively skewed. With female students, even lower means (ranging from 2.0 to 2.2) and more skewed RMA distributions were obtained (Bohner, 1998; Bohner, Siebler, and Raaijmakers, 1999). These findings clearly support our suspicion that both the content of rape myths may have changed and the willingness to express acceptance of such blatant myths may have declined. From a methodological point of view, severely skewed distributions pose a problem because the most common statistical tests require that scores or error terms are normally distributed. Furthermore, skewed RMA distributions may hamper the effectiveness of applied research featuring interventions that are designed to reduce sexual violence or rape accepting attitudes. In this context, it appears to be difficult to demonstrate any beneficial effect of an intervention if the means of the target variable at base-line are already close to the bottom of the scale. To illustrate, in our own research (Bohner et al., 2006) it appeared more difficult to reduce male participants’ RMA by providing feedback information about other men’s alleged low RMA, whereas providing feedback about other men’s high RMA was effective in increasing participants’ own RMA (Exp. 1). In a second experiment, we (Bohner et al., 2006) aimed at testing whether participants’ rape proclivity (RP) was affected by a wider range of levels of RMA norm feedback. However, it turned out impossible to create a symmetrical design with very low (- 2 SDs) to very high (+ 2 SDs) levels of norm feedback relative to participants’ own RMA scores, because the very low RMA feedback would have fallen outside the scale range. To address these problems with old-fashioned scales of rape myth acceptance, a development parallel to research on modern racism and modern sexism was recently proposed by Gerger, Kley, Bohner, and Siebler (2007). These authors set out to measure myths about sexual aggression in a more subtle manner, with emphases on both different item content and less blatant item wording. They developed a new self-report measure which they called the Acceptance of Modern Myths about Sexual Aggression (AMMSA) scale. Following the approach taken in research on modern forms of racism and sexism (see Swim et al., 1995), such a scale should assess both less obvious myths about rape and myths about less severe forms of sexual aggression. Gerger and her colleagues expected this to result in greater endorsement relative to the more blatant item content of traditional RMA scales, and accordingly higher means and more symmetrical distributions.
The AMMSA Scale2 Initially, the authors generated a pool of 60 items that could roughly be described as reflecting the following content categories: (1) denial of the scope of the problem (e.g., "Many women tend to misinterpret a well-meant gesture as a 'sexual assault'"); (2) 2
The German and the English AMMSA can be retrieved online: http://www.uni- bielefeld.de/psychologie/ae/AE05/AMMSA/index.html
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antagonism toward the demands made by victims of sexual violence (e.g., "Instead of worrying about alleged victims of sexual violence society should rather attend to more urgent problems, such as environmental destruction"); (3) lack of support for policies designed to help alleviate the effects of sexual violence (e.g., "Nowadays, the victims of sexual violence receive sufficient help in the form of women's shelters, therapy offers and support groups"); (4) beliefs that male coercion forms a natural part of sexual relationships (e.g., "When a woman starts a relationship with a man, she must be aware that the man will assert his right to have sex"); and (5) beliefs that exonerate male perpetrators by blaming the victim or the circumstances (e.g., "Alcohol is often the culprit when a man rapes a woman"). The five content categories were chosen so as to closely follow the scale development process described by Swim and colleagues (1995). The latter two content categories were added, however, to suit the context of male sexual violence. In group discussions among the authors, the items were examined with regard to their accordance with the conceptualization of rape myths. Redundant items and items with unsuitable content were consensually deleted from the item-pool resulting in a set of 43 items. This set was further reduced to 30 items based on item-total correlations and item means through an initial study. This German-language AMMSA scale then was carefully translated to English to obtain a measure for Englishspeaking participants. (Item wordings of the English version of the AMMSA scale can be found in the Appendix.) The translation process closely followed Brislin’s (1970) guidelines: First, one bilingual person translated the questionnaire from German to English, and a second bilingual person translated it back to German. Finally, differences in the original and backtranslated versions were discussed and resolved by joint agreement of the authors and translators. In total, 1,279 (716 German-speaking and 563 English-speaking) participants took part in a series of four validation studies to assess the convergent and discriminant validity of the AMMSA scale (for a detailed report, see Gerger et al., 2007). These studies differed in sites of recruitment (laboratory setting, field setting, and the Internet) thereby making it possible to study participants of different ages, professions, socio-economic statuses and countries of origin. Finally, to obtain data for the English and German versions of the AMMSA, Germanand English-speaking participants were recruited.
AMMSA SCALE VALIDATION Gerger et al. (2007) investigated the psychometric quality of the newly developed 30item AMMSA scale across four studies. To test whether AMMSA scores are conceptually distinct from a more traditional measure of RMA, we conducted an additional factor analysis using the dataset from Gerger and colleagues’ Study 4. When the 30 AMMSA items and the 17 items of the short-form Illinois Rape Myth Acceptance (IRMA) scale (Payne et al., 1999) were factor analyzed (using maximum likelihood extraction and promax oblique rotation) with the number of factors to be extracted set at two, 25 of the 30 AMMSA items loaded on the first factor, whereas the majority of the IRMA items loaded on the second factor. The scree plot and goodness of fit indices, χ² (988) = 4199.34, p < .001, however, suggested a one-factor solution. Thus, while the AMMSA and IRMA measures can be separated factorially, they measure highly similar constructs.
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Reliability analyses of the AMMSA scale conducted by Gerger et al. (2007) yielded very high scale score reliabilities, with Cronbach’s α ranging from .90 to .95. In three studies, the test-retest reliability of AMMSA was assessed; these coefficients were also satisfactory, with rtt ranging from .67 to .88 over a delay of 3 to 13 weeks. Specifically, in an Internet study that tested the German and English versions in parallel, rtt was .81 and .84, respectively. Thus, considering that the AMMSA scale was designed to assess attitudes that are assumed to be less stable than personality traits, it showed highly satisfactory levels of test-retest reliability. Generally, item-total correlations ranged from .21 to .82 across the four studies. The mean across the 30 AMMSA items was defined as a participant’s AMMSA score. Table 1 shows AMMSA scale means in comparison to means on the short form of the IRMA scale (IRMA-SF; Payne et al., 1999). The IRMA-SF scale was used as a standard of comparison since it is the most recent, well established, and broadly validated instrument designed to assess traditional RMA. Table 1. Comparison of AMMSA and IRMA-SF scale means for male and female respondents and percentage of respondents who scored above the scale mean (=4) across 4 studies (Studies 1 & 2 with students, Study 3 with passengers of commuter trains, Study 4 via the Internet) Study 1 Male respondents AMMSA M SD % scored > 4 IRMA M SD % scored > 4 N Paired samples t-test for difference AMMSA – IRMA Female respondents AMMSA M SD % scored > 4 IRMA M SD % scored > 4 N Paired samples t-test for difference AMMSA – IRMA
2
3
3.45 0.91 50
3.21 1.13 39
3.33 0.93 42
3.15* 0.93 36
3.60* 0.98 55
2.53 0.90 17 93
2.17 0.94 10 40
2.37 0.94 11 87
2.11 0.77 5 83
2.52 1.07 17 148
15.41*** d = 1.02
11.92*** d = 1.00
19.57*** d = 1.03
18.83*** d = 1.22
20.95*** d = 1.05
3.30 0.70 35
na
3.11 0.85 36
2.72* 0.81 18
3.18* 0.89 35
2.21 0.64 5 106
na
2.10 0.71 4 101
1.78 0.69 2 197
2.04 0.92 7 403
22.92*** d = 1.29
27.37*** d = 1.25
38.18*** d = 1.26
24.81*** d = 1.63
4 (German)
4 English)
Note. AMMSA = Acceptance of Modern Myths about Sexual Aggression; IRMA = Illinois Rape Myth Acceptance Scale (short form). Values could range from 1 to 7, with higher values indicating higher RMA. * The gender difference is significant; German sample: t(278) = 3.85, p < .001, d = 0.49; English sample: t(549) = 4.73, p < .001, d = 0.45; for all other sex differences in AMMSA, p > .05. *** p < .001. na = not assessed.
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As can be seen in Table 1, the AMMSA scale means were significantly higher than the IRMA scale means across all four studies. This speaks to the more subtle nature of the beliefs assessed by the AMMSA scale. However, the average endorsement rate of rape myths assessed with the AMMSA is generally below the scale midpoint. This might be due to the fact that rape-related attitudes are not strongly endorsed in contemporary society, particularly among student samples. Furthermore, male respondents tended to report higher AMMSA scale scores than did female respondents. This is similar to findings with old-fashioned RMA scales, where large sex differences are often observed (see Bohner, 1998). However, it should be noted that the sex difference appears to be smaller with the AMMSA scale (i.e., men and women’s scores differed significantly in only one of the four studies reported by Gerger et al. [2007, Study 4]). As discussed before, the positive skewness commonly found with distributions of classic RMA measures has posed a problem in recent research. Consequently, one aim in constructing the AMMSA scale was to obtain less skewed distributions of RMA means. As expected, a symmetrical, approximately normal distribution of AMMSA scores was a stable characteristic of the scale across the four studies reported by Gerger and colleagues (2007), whereas IRMA-SF scores showed severely skewed distributions. To illustrate, Figure 1 displays sample distributions of the new AMMSA scale and the traditional IRMA-SF measure (Payne et al., 1999) based on an Internet study with 879 participants from 35 countries (Gerger et al., 2007, Study 4). Gerger et al. (2007) also provided evidence for the convergent and discriminant validity of the AMMSA scale by examining its pattern of correlations with other constructs. Specifically, the authors obtained high correlations (ranging from .76 to .80 across the studies) with constructs that express hostility toward women and masculine ideology, such as hostile sexism (Glick and Fiske, 1996) and a range of rape-supportive beliefs (Burt, 1980). For instance, in Study 2 with male participants only, scores on the AMMSA correlated highly with adversarial sexual beliefs (Burt, 1980), r = .76; acceptance of interpersonal violence (Burt, 1980), r = .77; and the likelihood to sexually harass (Pryor, 1987), r = .60. These findings reflect the convergent validity of the AMMSA. In these respects, the AMMSA scale seems to function in a similar way as was shown for traditional rape myth scales (see Murnen, Wright, and Kaluzny, 2002). Additionally, as expected, positive but somewhat lower correlations were found between scores on the AMMSA and constructs involving general outgroup derogation, including right-wing authoritarianism (RWA) and social dominance orientation (SDO; see Kreindler, 2005), as well as between the AMMSA and a general measure of the belief in a just world (JWB; Lerner, 1980). The correlations between AMMSA and RWA range from .44 (in the English sample of Study 4 reported in Gerger et al., 2007) to .75 (Study 3, Gerger et al. [2007]). SDO correlates with AMMSA between .48 and .58 (Studies 3 and 4, Gerger et al. [2007]). JWB is a broader concept than RMA, but similar with respect to the fact that rape myths also encompass the belief that victims of sexual violence and rape actually “get what they deserve,” since women even “ask for it.” AMMSA and JWB correlate between .17 and .39 across three studies (see Gerger et al., 2007). Finally, AMMSA scores were unrelated to impression management (Musch, Brockhaus, and Bröder, 2002; Paulhus, 1998), as indicated by correlation coefficients ranging from -.06 to .03 in three independent samples (see Gerger et al., 2007).
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Figure 1. Distributions of the English and German versions of the Illinois Rape Myth Acceptance (IRMA) Scale (short form) and the Acceptance of Modern Myths About Sexual Aggression (AMMSA) scale. Adapted from Gerger et al. (2007).
Compared to the IRMA and other available rape myth scales (e.g., Costin, 1985), the AMMSA scale is more likely to meet the criteria required for the computation of various inferential statistics, especially if sample sizes are small.
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Eyssel and Bohner (2008) recently replicated the results regarding SDO and JWB. Moreover, for the 105 male participants in their study, AMMSA was positively correlated with several measures of different forms of sexism. Most pronounced were the correlations between AMMSA and hostile sexism, r = .86, and between AMMSA and normative gender role orientation (Athenstaedt, 2002), r = .65. Despite the high intercorrelation of the AMMSA scale with hostile sexism, the AMMSA does assess stereotypic beliefs about rape, which are naturally marked by hostility toward women. However, with an emphasis on sexual violence, RMA is clearly conceptually distinct from hostile sexism. With regard to discriminant validity, the statistical relation was slightly less pronounced but still highly significant between AMMSA and benevolent sexism, r = .57, as well as AMMSA and modern sexism, r = .52. For female participants in this study, a similar correlation pattern emerged; however, the correlations obtained were generally lower. Also, for females, no significant correlation was found between AMMSA and JWB, r = .11, p = .26, whereas AMMSA and SDO were significantly statistically related, r = .23. Thus, there is clear evidence for the discriminant validity and mixed evidence for the convergent validity of the AMMSA scale in this sample of female students. More recent data (Eyssel and Bohner, 2007) for male participants also replicated the correlation patterns described above. In addition, we found that AMMSA was significantly correlated with a preference for sexist humor, r = .38, a relatively indirect measure of sexist beliefs. Here, the preference for sexist humor was assessed by presenting participants with jokes of sexist and nonsexist content, asking them to rate these according to their funniness. Further analyses based on the datasets from Gerger and colleagues’ (2007) Study 4 (Heitland and Bohner, 2008) showed that whereas age was uncorrelated to RMA overall, independent of type of RMA scale used (IRMA or AMMSA), a curvilinear trend for the endorsement of rape myths across 5 different age groups could be found: That is, adolescents (ages 14 to 20) as well as senior people (ages 45 to 71) seem to report higher RMA than the age cohorts in between. This may be interpreted in terms of a cohort effect, indicating that those born and raised between the 1970s and 1980s are more liberal in attitudes relative to those younger or older. An analogous finding with regard to RWA supports this notion.
Functions of Rape Myths: Classic Findings and Initial Evidence with the AMMSA Scale In the following, we first review research on the gender-specific functions of rape myth acceptance using old-fashioned measures, and then present initial evidence for related findings obtained with the AMMSA scale. Early studies on the RMA construct were focused on responsibility attributions in relation to rape scenarios (e.g., Jones and Aronson, 1973; for reviews, see Krahé, 1991; Pollard, 1992). One of the main findings was that perceivers' level of rape myth acceptance was positively related to their attribution of responsibility to the victim, and negatively related to their attribution of responsibility to the perpetrator. Thus, RMA was understood as a general cognitive schema that guides the interpretation of specific case information. Another line of research used RMA measures in the context of predicting men's rape proclivity (RP). These correlational studies generally showed that higher RMA was related to greater RP (e.g., Malamuth, 1981; Malamuth and Check, 1985; Quackenbush, 1989; for reviews, see Bohner,
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1998; Murnen et al., 2002). For example, Malamuth (1981) asked males to report the likelihood "that they personally would rape if they could be assured of not being caught and punished" (p. 140) along a five-point scale, and assessed these men's RMA using a scale developed by Burt (1980). Results showed a correlation between the likelihood of raping (LR) and RMA that was as high as r = .60 (Malamuth, 1981, p. 144). In a recent metaanalysis, the mean correlation between Burt's RMA scale and Malamuth's LR measure was found to be .26 across 11 studies (Murnen et al., 2002). Other research has addressed the assessment of RMA in relation to demographics, education levels, as well as various attitude and individual-difference measures (for a review, see Lonsway and Fitzgerald, 1994). Furthermore, RMA has been studied in relation to linguistic aspects of writing and reading about rape (Bohner, 2001; Henley, Miller, and Beazley, 1995), and some researchers have examined the impact of RMA on information processing styles in risk perception and judgments of one’s own vulnerability (Bohner, Danner, Siebler, and Samson, 2002; Grayson and Schwarz, 1999). Bohner and his research group (Bohner and Lampridis, 2004; Bohner et al., 1999; Bohner, Weisbrod, Raymond, Barzvi, and Schwarz, 1993) have placed particular emphasis on the gender-specific functions of RMA. Their research indicated that the acceptance of rape myths may serve as an anxiety buffer that allows women to reduce their subjective vulnerability to sexual assault and protect their self-esteem. Apparently, women who endorse rape myths believe that rape happens only to a certain type of woman (e.g., one who behaves "inappropriately"), whom they perceive as dissimilar from themselves. On the other hand, Bohner and colleagues (Bohner and Lampridis, 2004; Bohner et al., 1999; Bohner et al., 1993) found that women who reject rape myths construe rape as a potential threat to all women, including themselves. Across several studies, they found that women low in RMA who were exposed to situations in which rape was salient subsequently reported lower selfesteem and more negative affect, whereas women high in RMA who were exposed to the same situations remained largely unaffected (Bohner and Lampridis, 2004; Bohner et al., 1999; Bohner et al., 1993). For men, rape myth acceptance might be used to rationalize and justify men’s own tendencies to engage in sexual aggression (see also Burt, 1980). Bohner and colleagues (Bohner, Jarvis, Eyssel, and Siebler, 2005; Bohner et al., 1998) demonstrated that men whose own level of RMA had been made accessible by the initial completion of an RMA scale showed a higher correlation between RMA and RP compared to men who completed the RMA scale only after the RP measure. This finding is due to the fact that through completion of the AMMSA scale, rape-related beliefs become more salient, which subsequently affects self-reported RP Furthermore, male students who had received experimentally manipulated feedback stating that other students’ level of RMA was high (versus low) later reported that they would be more (versus less) likely to commit sexual violence (Bohner et al., 2006). In a related experiment, Eyssel, Bohner, and Siebler (2006) used the AMMSA scale to study the effects of information about others’ AMMSA on men’s RP. The results replicated and extended previous findings: Participants reported lower RP if they were led to believe that others’ AMMSA scores were low (versus high). Similar effects of low versus high AMMSA scores on RP were found if these scores were presented as judgmental anchors and participants were only instructed to consider their appropriateness (e.g., “Do you think the mean response of male students to this item is higher or lower than X?” – presented along with an AMMSA item; X being a high or low score). These results also provide strong
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evidence for the proposed function of AMMSA of justifying and rationalizing men’s behavioral tendencies toward sexual aggression. In addition, recent research revealed that RMA predicts judgments of both victim blame and RP within the same sample of men, suggesting that the justification of sexual violence may go hand in hand with a certain readiness to commit such violence (Abrams, Viki, Masser, and Bohner, 2003; Michaelis and Bohner, 2005). In a similar vein, Temkin and Krahé (2008, Study 3) conducted research in the area of judicial decisions, specifically concerning judgments of victim blame and perpetrator responsibility in rape cases. They demonstrated that rape myth acceptance as measured with a 16- item short version of the AMMSA scale was related to the minimization of defendant liability and attribution of complainant blame in rape cases. That is, the more participants endorsed modern rape myths, the shorter the sentences they recommended in the event that the defendant was found guilty and the more they blamed the victim in the rape case. Temkin and Krahé’s research also supports the notion that the AMMSA scale provides a “modern” (i.e., more subtle and less blatant) instrument to assess rape-supportive beliefs. In their study, roughly 44% of their participants obtained scores above the scale midpoint (59% of the male and 34% of the female participants), using a 7-point response scale. (The average AMMSA score in this study was 3.90.) These results, as well as our own findings comparing the AMMSA with the IRMA-SF make it clear that, given more subtle item wording, a higher proportion of participants appear to endorse rape myths.
CONCLUSION In sum, the research reviewed in this chapter attests to the good psychometric properties of the AMMSA scale, our newly developed measure of modern rape myths. Nevertheless, the scale should be validated further using experimental designs. The initial results we reported here show that the AMMSA scale can well be characterized as a modern measure of attitudes about rape, in line with other prominent scales assessing modern forms of racial prejudice and sexism (Sears, 1988; Swim et al., 1995). As it is negatively sanctioned to hold or voice prejudiced attitudes nowadays, whether they are related to race, gender or sexual violence, these societal changes clearly have an impact on both the content of, and people’s willingness to express, blatantly stereotypic beliefs in self-reports. Consequently, researchers’ quest for assessing modern prejudiced beliefs has resulted in the development of more subtle and less obvious items to assess the concepts of interest (e.g., attitudes related to gender, race, or sexual aggression). With respect to the latter, research has only just started, and we hope that further studies will expand our knowledge regarding modern myths about sexual aggression and their specific psychological functions.
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APPENDIX English version of the Acceptance of Modern Myths About Sexual Aggression (AMMSA) Scale Item When it comes to sexual contacts, women expect men to take the lead. Once a man and a woman have started "making out," a woman's misgivings against sex will automatically disappear. A lot of women strongly complain about sexual infringements for no real reason, just to appear emancipated. To get custody of their children, women often falsely accuse their ex-husband of a tendency towards sexual violence. Interpreting harmless gestures as "sexual harassment" is a popular weapon in the battle of the sexes. It is a biological necessity for men to release sexual pressure from time to time. After a rape, women nowadays receive ample support. Nowadays, a large proportion of rapes is partly caused by the depiction of sexuality in the media as this raises the sex drive of potential perpetrators. If a woman invites a man to her home for a cup of coffee after a night out this means that she wants to have sex. As long as they don’t go too far, suggestive remarks and allusions simply tell a woman that she is attractive. Any woman who is careless enough to walk through “dark alleys” at night is partly to be blamed if she is raped. When a woman starts a relationship with a man, she must be aware that the man will assert his right to have sex. Most women prefer to be praised for their looks rather than their intelligence. Because the fascination caused by sex is disproportionately large, our society’s sensitivity to crimes in this area is disproportionate as well. Women like to play coy. This does not mean that they do not want sex. Many women tend to exaggerate the problem of male violence. When a man urges his female partner to have sex, this cannot be called rape. When a single woman invites a single man to her flat she signals that she’s not averse to having sex. When politicians deal with the topic of rape, they do so mainly because this topic is likely to attract the attention of the media.
rtt .41
M 4.13
.55
1.96
.66
2.67
.66
3.32
.59
3.72
.55
3.82
.52
3.29
.43
3.39
.44
2.38
.50
3.53
.51
2.13
.63
2.74
.49
3.61
.41
3.74
.51
3.49
.69 .31
2.77 3.72
.42
2.93
.37
4.32
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APPENDIX (CONTINUED) Item When defining "marital rape," there is no clear-cut distinction between normal conjugal intercourse and rape. A man’s sexuality functions like a steam boiler – when the pressure gets too high, he has to "let off steam." Women often accuse their husbands of marital rape just to retaliate for a failed relationship. The discussion about sexual harassment on the job has mainly resulted in many a harmless behavior being misinterpreted as harassment. In dating situations the general expectation is that the woman "hits the brakes" and the man "pushes ahead." Although the victims of armed robbery have to fear for their lives, they receive far less psychological support than do rape victims. Alcohol is often the culprit when a man rapes a woman. Many women tend to misinterpret a well-meant gesture as a "sexual assault." Nowadays, the victims of sexual violence receive sufficient help in the form of women’s shelters, therapy offers, and support groups. Instead of worrying about alleged victims of sexual violence society should rather attend to more urgent problems, such as environmental destruction. Nowadays, men who really sexually assault women are punished justly.
rtt .50
M 2.46
.65
3.27
.66
2.60
.60
3.66
.40
3.80
.38
4.35
.43 .68
3.62 3.16
.53
3.59
.49
2.59
.31
2.91
Note. rtt = item-to-total correlation; M = means; Data are based on N = 505 (Gerger et al., in press: Study 4). Values could range from 1 (totally disagree) to 7 (totally agree).
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In: The Psychology of Modern Prejudice Editor: Melanie A. Morrison and Todd G. Morrison
ISBN 978-1-60456-788-5 © 2008 Nova Science Publishers, Inc.
Chapter 12
OLD-FASHIONED AND MODERN PREJUDICE TOWARD ABORIGINALS IN CANADA Melanie A. Morrison11, Todd. G. Morrison2, Rebecca L. Harriman3 and Lisa M. Jewell3 1
2
University of Saskatchewan, Canada National University of Ireland, Galway 3 University of Saskatchewan, Canada
ABSTRACT This chapter provides a brief review of the systemic prejudice and discrimination directed against Aboriginal people in Canada. The extent to which social psychologists examining stereotyping, prejudice, and discrimination have included Aboriginal men and women as a research focus is examined, and the current authors’ research, which adds to the small number of published studies in this area, is outlined. Directions for future inquiry, particularly as they pertain to measurement issues, also are reviewed.
INTRODUCTION European settlers first came in contact with North American Aboriginal people approximately 500 years ago. Since that time, the cultural way-of-life for Aboriginal people has been systematically destroyed and denigrated by the white majority (Shepard, O’Neill, and Guenette, 2006). As European settlers immigrated to Canada, a policy of colonialism was created that entitled the more powerful white pioneers to dominate the less powerful Aboriginal population, leaving them with few rights and no status, and little power to redress the inequities they faced (Trimble, 1988). Formal and informal colonial policies resulted in the erosion of Aboriginal populations, the destruction of Aboriginal culture, and the forced 1
Correspondence about the article should be addressed to: Dr. Melanie A. Morrison, Department of Psychology, 9 Campus Drive, University of Saskatchewan, Saskatoon, Saskatchewan, S7N 5A5; Email:
[email protected].
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relocation and isolation of historical and extant Aboriginal communities (Trimble, 1988; Waldram, 1997). For example, the Indian Act of Canada of 1876 prohibited Aboriginal people from participating in indigenous cultural practices, denied them the right to vote, dictated who was allowed to move from reserve settings, and determined where Aboriginal children should attend school (Shepard et al., 2006). Throughout their history of colonization, Aboriginal people also have experienced pressure to assimilate the cultural practices of the white majority and, in so doing, forsake their own spiritual understandings via conversion to Christianity (Shepard et al., 2006). One of the most damaging practices instituted to facilitate the assimilation of Aboriginal people was the residential schooling system (Barnes, Josefowitz, and Cole, 2006; Hanson and Hampton, 2000; Shepard et al., 2006). During the 1800s, the Government of Canada in conjunction with the Roman Catholic Church established residential schools that called for the removal of Aboriginal children from their families and communities, and forced placement in boarding-type schools (Hanson and Hampton, 2000; Shepard et al., 2006). During their tenure at these institutions, Aboriginal children were supposed to be educated, converted to Christianity, and socialized according to the mores of the white majority. While at the schools, however, Aboriginal children were segregated by sex, forbidden to speak in their native languages, and/or disallowed to engage in any of their own cultural or religious practices (Barnes et al., 2006; Hanson and Hampton, 2000). Moreover, many of the children sent to residential schools were required to spend up to half of their school day performing janitorial duties and kitchen- or field-related labour (Barnes et al., 2006). Given the amount of time that Aboriginal children spent engaged in activities that were not reflective of the educational curricula, they typically received a sub-standard education (Barnes et al., 2006). Former residential school attendees have indicated that their basic needs were often neglected: they were malnourished, had insufficient/inappropriate clothing to wear, and lived in poorly heated buildings (Barnes et al., 2006). Many Aboriginal adults also reported being physically, sexually, and/or emotionally abused while at the schools (Barnes et al., 2006; Hanson and Hampton, 2000). The deleterious consequences of such abuse likely were exacerbated by the fact that Aboriginal children were separated from nurturing adults or sympathetic others and were thus forced to cope with such traumatic experiences on their own (Barnes et al., 2006; Hanson and Hampton, 2000). According to Shepherd et al. (2006), the trauma that these children experienced has, and continues to be, unintentionally transmitted to future generations, resulting in “intergenerational trauma.” Overall, the residential schools were highly oppressive institutions that have had a prolonged detrimental influence on the Aboriginal people of Canada. In recent decades, the state of affairs for Aboriginal people has become less oppressive. The Canadian government has attempted to address the inequities experienced by Aboriginal people in the form of reparations including compensation, restitution, restoration, and the designation of supplemental rights (Barsh, 1994; Juriansz, 1993; Mainville, 2001; Waldram, Herring, and Young, 2006). For instance, the Aboriginal Healing Foundation (AHF) was established in 1998 by the federal government to address the effects of trauma among those who were physically and sexually abused within residential schools (AHF, 2008; Waldram et al., 2006). In addition, government funding is being directed toward community-based social and health-related programs designed to enhance Aboriginal people’s quality of life (Barsh, 1994; Spence, 2004; Waldram et al., 2006). Despite such efforts, Aboriginal people still
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encounter prejudice and discrimination at institutional and interpersonal levels, as will now be discussed.
INSTITUTIONAL DISCRIMINATION Institutional discrimination reflects structural biases that are entrenched in a particular society’s policies and institutions, each of which has a harmful effect on minority groups (Pincus, 1996). Social scientists have found that discrimination is directed toward Aboriginal people within the legal, education, and health care systems. Research pertaining to discrimination in each of these institutions is outlined briefly. Legal System. Furniss (2001) conducted a media analysis of a public inquiry carried out in 1992 investigating allegations of racial prejudice and unfair treatment of Aboriginal people by the Royal Canadian Mounted Police (RCMP) and the British Columbia provincial justice system. Furniss cited testimonies from Aboriginal men and women that RCMP officers used excessive force during arrests, forcibly entered the homes of Aboriginal people without search warrants, assaulted Aboriginal persons while in jail, and offered inadequate responses to calls for help placed by Aboriginal people. The testimonies also suggested that Aboriginal people were less likely to receive adequate representation from their lawyers (Furniss, 2001). One Aboriginal man, for example, stated that he was encouraged by his lawyer to plead guilty to a crime he did not commit so that he would not waste “the judge’s time, the jury’s time, or his lawyer’s time for contesting the charge” (Furniss, 2001, p. 25). Finally, Furniss (2001) and Roberts and Doob (1997) documented instances of Aboriginal people being held overnight in jail cells despite insufficient evidence of their participation in criminal activity. Other instances of institutional discrimination in the legal system have been documented. Aboriginal people are more likely to be sentenced to jail, oftentimes because they are unable to pay their fines or there are no suitable alternatives to sentencing in remote Canadian rural areas (Cawsey, 1991; Roberts and Doob, 1997). Moreover, Aboriginal Canadians are less likely to apply for parole (which has been theorized to be a result of their mistrust of the legal system) and are not as likely to receive full parole when they do apply (Cawsey, 1991; Welsh, 2000). In a social psychological study assessing discrimination among mock-jurors, Pfeiffer and Ogloff (2003) investigated the prevalence of guilty verdicts and length of sentencing accorded to three defendants: English Canadian, French Canadian, or Native Canadian, when their victims were English Canadian, French Canadian, or Native Canadian. Results indicated that when participants were free to formulate opinions about the defendants’ guilt in accordance with their personal beliefs (i.e., subjective guilt ratings), the Native Canadian defendant was found significantly more guilty than the English or French defendant when the victim was depicted as English or French Canadian. Further, English Canadian defendants were found significantly less guilty when the victim was depicted as Native Canadian rather than French or English Canadian. Intriguingly, when study participants were given standardized legal instructions to follow (i.e., legal standard guilt ratings), which effectively reduce or eliminate “room for interpretation,” statistically significant differences in guilty verdicts were not obtained. In relation to this phenomenon, a very telling quotation is provided by a male
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participant: “He [the defendant] is Indian, therefore I am 99% sure he is a liar and is guilty – but I can’t find him legally guilty according to the judge’s instructions” (p. 309). Education. Aboriginal people have a disproportionately high dropout rate from high school and generally attain lower levels of education than the white majority (Barsh, 1994; James, Chavez, Beauvais, Edwards, and Oetting, 1995). It is estimated that 48% of Aboriginal people aged 15 years or older have not completed their high school education compared to 31% of the overall Canadian population (Mendelson, 2006). The main reason Aboriginal male youth offered for dropping out of high school was boredom (25%), while the main reason provided by female youth was pregnancy or the need to look after children (25%) (Statistics Canada, 2005). A study comparing American Indian dropouts (n = 265), at-risk students (n = 259) and current students (n=248) to Anglo American dropouts (n = 336), at-risk students (n = 237) and current students (n = 262) enrolled in middle and high schools in the central and southwestern parts of the United States provides additional insight into the systemic discrimination experienced by non-whites in the education system (James et al., 1995). Misunderstandings between white teachers and Aboriginal children with regards to non-verbal communication have been found to lead to conflict, increased levels of negative feedback, lower levels of positive feedback, and additional stress, making the school experience for Aboriginal students more challenging and less enjoyable (James et al., 1995). Thus, James et al. (1995) contend that an unwelcoming school environment in conjunction with the extensive use of a language (i.e., English) that is not necessarily the students’ first language has resulted in inequitable access to education for Aboriginal children. Contributing to the barriers to formal school training among Aboriginal youth, James et al. (1995) state that “those families that maintained traditional language in the face of this treatment are likely to be distant from and sceptical about mainstream society and are likely to communicate and model this attitude to their children” (p. 184). Thus, the multidimensional nature of the problem becomes apparent. Results from the authors’ study indicate that American Indian students who reported relatively high levels of use of a native language during their childhood were found to be more likely to drop out of school. This effect was particularly evident among the male American Indian students in the sample. Findings also revealed that American Indian students tended to believe that teachers liked Anglo American students better, with those who endorsed this view being more likely to leave school. Finally, a qualitative study conducted by Samuel and Wane (2005) suggests that Native Studies programs may experience difficulties that do not occur in other disciplines at universities. Nine female minority faculty members from a predominately white Canadian university were interviewed and commented that students can be inattentive, rude, and indifferent to lectures on racism, as well as critical of the curricula content of Native Studies courses. The interviewees also reported being evaluated more unfairly by students about their teaching and marking abilities, and felt they struggled more with their careers than faculty not involved in this discipline. Health Care. According to Browne (2007) and Browne and Varcoe (2006), Canadian nurses and physicians often hold and maintain negative stereotypes about Aboriginal men, women, and children and, in turn, provide health care that is not “culturally sensitive.” For instance, nurses may ask more probing questions regarding domestic violence and make more referrals about suspected child abuse for Aboriginal clients than for white clients (Browne and Fiske, 2001). Studies with Aboriginal Canadian women also reveal that some participants
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feel their health concerns are trivialized, dismissed, or neglected due to the stereotypic beliefs of nurses and physicians (Baker and Daigle, 2000; Browne and Fiske, 2001). Further, some Aboriginal women have reported feeling like “outsiders” who are not entitled to health care services (Browne and Fiske, 2001). Such research indicates that Aboriginal people’s negative experiences with health care professionals have compromised the quality of care they receive, reinforced their perception that Aboriginal values are not respected by the Western medical establishment, and instilled feelings of mistrust toward health care providers.
INTERPERSONAL DISCRIMINATION Interpersonal discrimination consists of harmful behaviours (e.g., verbal harassment and physical assault) that individuals, either singly or collectively, engage in to hurt or disparage members of a minority group (Pincus, 1996). To date, surprisingly few studies have focused on interpersonal discrimination against Aboriginal people. One study investigated racism directed toward Aboriginal students attending a small, Midwestern university in the United States and found that, of the 22 students interviewed, 14 reported being verbally attacked, at least once, during their tenure at the university (Huffman, 1991). Each of the 14 students had experienced attacks against Aboriginal people in general, while 9 of the students incurred personal attacks where they had been called derogatory names, often related to negative stereotypes about their social group. With regards to the perpetrators, each of the 14 participants reported hearing negative comments made by students; 5 students heard racist remarks from campus staff; and 2 students heard professors make negative comments about Aboriginal people. Not surprisingly, 16 of the 22 students perceived the university campus to be a hostile environment (i.e., they felt they were “outsiders” unwelcomed by the general university community and believed they were treated discriminatorily when accessing campus services). Another study examined perceptions of group and personal discrimination among a sample of Inuit people (N=191) in Nunavik (Poore et al., 2002). Participants were individuals who had never left their Northern communities, as well as those who had lived elsewhere in Canada at some point in their lives. Results indicated that Inuit persons who had lived outside of their community perceived more group discrimination directed toward Inuit people than those who have lived in the North their entire lives. Similarly, Inuit individuals who worked outside of their homes reported more group discrimination than those who did not work outside of the home. The authors suggest that group-level relative deprivation (i.e., the resentment and sense of injustice that arises from perceiving that one’s group has less than is deserved) stemming from contact with, and unfavourable comparisons to, other social groups may account for these differences. Unfortunately, no specific questions were asked regarding the nature of the group and personal discrimination that were perceived to occur. Other notable studies exploring the victimization of Aboriginal people are currently lacking. The racism to which Aboriginal people have been, and continue to be, subjected contributes to a sense of cultural estrangement and loss of self-worth (Shepard et al. 2006; Waldram, 1997). It is possible that the experiences of social disruption and personal alienation have contributed to the disadvantaged conditions in which many Aboriginal people live in and have served to compromise their physical and mental health. For example,
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Aboriginal people have among the lowest average earnings of any social group in Canada, one of the highest unemployment rates, and are disproportionately likely to live in the poorest neighbourhoods in a given geographic location (Barsh, 1994; Darden and Kamel, 2002; Spence, 2004). Aboriginal people are at increased risk for being offenders or victims of domestic violence (Darden and Kamel, 2002; Longclaws, Barkwell, and Rosebush, 1994) and, in comparison to the “average” Canadian, are more likely to consume and abuse alcohol and other drugs, experience depression, and attempt suicide (Carstens, 2000; Waldram, 1997; Whitbeck, Chen, Hoyt, and Adams, 2004; Whitbeck, McMorris, Hoyt, Stubben, and LaFromboise, 2002). These symptoms of poor mental health may stem from a profound sense of hopelessness, despair about the future, and a loss of spirituality and culture (Carstens, 2000; Timpson et al., 1988; Whitbeck et al., 2002; Whitbeck et al., 2004). They also may be the sequelae of efforts to cope with chronically stressful environments caused, in part, by discrimination (Armstrong, 1993; Whitbeck et al., 2002). Finally, Aboriginal people are more likely to contract sexually transmitted diseases (including HIV/AIDS) and suffer from malnutrition, diabetes, hypertension, and heart disease (Barsh, 1994; Vernon, 2007).
COVERAGE OF ABORIGINAL ISSUES BY SOCIAL PSYCHOLOGISTS To date, research-based efforts to understand the social forces underlying contemporary stereotypes, prejudice and discrimination toward Aboriginal men and women have been limited. Within Canada, there is a dearth of research coming from the discipline of psychology. To the present authors’ knowledge, only a handful of studies (e.g., ClaxtonOldfield and Keefe, 1999; Haddock, Zanna, and Esses, 1994) have examined stereotypes of Aboriginal people, with even fewer assessing prejudice (see Donakowski and Esses, 1996 and Haddock et al., 1994). Key findings emerging from these studies will be outlined briefly. Based on a review of the research conducted since Mackie’s (1974) study on Albertan Canadians’ stereotypes of North American Indians, it appears that the majority of characteristics believed to represent Aboriginals continue to be negative. In Claxton-Oldfield and Keefe’s (1999) examination of undergraduate students’ (N = 78) stereotypes of the Innu of Davis Inlet in Labrador, a remote area of Canada, the ascriptions given to the Innu were exceedingly negative. Specifically, “uneducated,” “substance abusing,” “poor,” and “isolated” emerged as the top four characteristics reported. In a series of studies, Haddock et al. (1994) examined the content of stereotypes as did Vorauer, Main, and O’Connell (1998; Study 1). Across the studies conducted, results indicated similar findings to those of ClaxtonOldfield and Keefe with regard to the negative valence of beliefs about Aboriginal individuals. For instance, Haddock et al. (1994) indicate that the most frequently cited stereotypes were “alcoholics,” “lazy,” and “uneducated”. In Vorauer et al.’s (1998) Study 1, the authors documented additional descriptors such as “not obedient” and “defiant,” each of which were thought to reflect a newer theme from those traditionally reported: in this case, “rebelliousness.” Commenting on Vorauer et al.’s (1998) findings, Corenblum and Stephan (2001) suggest that the presence of this new theme reflects non-Aboriginals’ beliefs about Aboriginal persons’ efforts to challenge the status quo. All of the available stereotyping studies that we identified were conducted prior to or during the 1990s. As stereotypes have been known to change over time (Devine and Elliott,
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1995), it is possible that the ascriptions of Aboriginal persons have become less negative and/or may now include positive characteristics. This line of inquiry serves as the primary objective of Study 1. To further bolster the rationale for this study, we point to the fact that the research we identified is limited to certain geographic locations in Canada (Alberta – Mackie, 1974; Manitoba – Corenblum and Stephan, 20012; Newfoundland – Claxton-Oldfield and Keefe, 1999; and Ontario – Donakowski and Esses, 1996; Haddock et al., 1994). It was felt that geographic areas (e.g., Saskatchewan) with an expected growth in the number of Aboriginal persons should be included. As well, researchers have yet to investigate whether stereotypes about Aboriginal men and women differ from each other. This distinction seemed important given theoretical advances in the area of stereotyping. For instance, the Stereotype Content Model (e.g., Fiske, Cuddy, Glick, and Xu, 2002; Fiske, Xu, Cuddy, and Glick, 1999) emphasises that inclusion of sub-groups captures nuances that may be obscured if relying solely on the superordinate category (Clausell and Fiske, 2005). Finally, an important issue in attitudinal research is whether people’s endorsement of positively and negatively valenced stereotypes about a social group predicts their prejudiced attitudes toward that group (e.g., Devine and Elliott, 1995). To assess this, Haddock et al. (1994) examined stereotypes in relation to symbolic beliefs, affective reactions, and prejudiced attitudes toward Native peoples and, by doing so, expanded upon the available literature to date by examining their associations. Of specific interest to our research was the significant positive correlation found between stereotypes of Native peoples and a 1-item evaluation thermometer (where scores could range from 0 to 100, and 50 provides an indication of neutrality). Corenblum and Stephan (2001) also observed that stereotypic beliefs correlated positively with negative attitudes toward outgroups (e.g., Euro-Canadians’ attitudes toward Native Canadians and vice versa). A secondary purpose of Study 1 was to determine the association between stereotypes ascribed to Aboriginal men and women and their linkage to prejudiced attitudes toward Aboriginals (using a modified measure of prejudice toward gay men and lesbian women) and other social groups. In summary, the relative omission of Aboriginal people in social psychological research on stereotyping and prejudice is surprising given the historical and contemporary treatment of members of Aboriginal communities, and the current debate about topics that fall under the rubric of “Aboriginal” issues. Such topics in Canada include land claims; reparations for time spent in residential schools; development and operation of Aboriginal-run initiatives at national, provincial, and local levels; the growing Aboriginal population, particularly within certain provinces (e.g., Saskatchewan); and ever-present social issues such as the disparities in health, education, and employment of Aboriginal people across the lifespan compared to the non-Aboriginal majority.
2
The study conducted by Vorauer et al. (1998) was situated in Manitoba; yet, the central focus was on metastereotypes (i.e., Aboriginals beliefs about how they are perceived by Whites).
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PURPOSE In Study 1, university students’ contemporary stereotypes about Aboriginal men and women were investigated. By focusing on a geographic location characterized by a growing Aboriginal population, this study would complement other research that has been conducted in Alberta, Manitoba, Ontario, and Newfoundland. In addition, by having participants evaluate Aboriginal men or Aboriginal women as distinct targets, potential differences in stereotype content could be identified. The central purpose of Study 2 was to develop and provide preliminary validation for measures of old-fashioned and modern prejudice toward Aboriginal people. These scales will address an important gap in the literature because they were: 1) constructed in accordance with “best practice” criteria for scale development; and 2) designed to examine constructs that remain central to the social psychological study of prejudice; namely, the interrelated, yet conceptually distinct, components of modern and oldfashioned negativity toward marginalized groups.
STUDY 1 Method Participants Two-hundred and eighty-nine participants (67 males, 222 females) completed a questionnaire pertaining to either Aboriginal men (n = 145) or Aboriginal women (n = 144). Participants ranged in age from 17 to 42 (M = 19.28; SD = 3.05) years, and a majority (86.9%, n = 251) self-identified as Caucasian.3 Most participants (98%, n = 279) reported that they were heterosexual. In terms of political orientation, approximately 44% (n = 127) indicated that they were extremely conservative, conservative, or somewhat conservative; and 48% (n = 139) indicated they attended religious services frequently or sometimes. All participants were current enrolees in a first year course entitled General Psychology and, thus, received course credit for their participation. Stereotype Measures Cultural Stereotype Checklist (CSC). Beginning with Katz and Braly’s (1933) classic study in which the authors presented a fixed set of stereotype ascriptions to participants, researchers concerned about stereotype content, accuracy, and change have employed different techniques: fixed lists of adjectives (e.g., Katz and Braly, 1933), free-response options to capture descriptors that might have been overlooked by researchers (e.g., Haddock et al. 1994), and a combination of the two (e.g., Madon, 1997). In the current study, a prescribed adjective list was given in conjunction with space for free responses. To measure participants’ perceived cultural stereotypes, participants were asked to place a check mark beside each of 103 descriptors that represented “society’s beliefs about Aboriginal men [women].” In accordance with Madon’s (1997) recommendation vis-à-vis the multidimensional nature of stereotypes, descriptors focused on behaviours (7 items), physical 3
As the number of Aboriginal participants was relatively small, we elected to include them in our analyses.
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characteristics (12 items), and personality traits (84 items). It should be mentioned that the large number of traits used in the present study were derived from a review of the literature on stereotype measurement of stigmatised groups (e.g., Devine and Elliott, 1995; Madon, 1997; Madon et al., 2001). Personal Endorsement of Cultural Stereotypes (PECS). In their critique of much of the early stereotype research, Devine and Elliott (1995) stressed the need to examine participants’ personal endorsement of cultural stereotypes. These authors found no significant differences between participants high and low in modern prejudice in terms of their awareness of cultural stereotypes (in this case about African Americans) but statistically significant differences were noted in terms of personal endorsement. Thus, while most individuals are cognizant of the cultural stereotypes of African Americans, they may not personally endorse these beliefs. To assess personal endorsement, visual analogue scales (VASs), ranging from 0 (extremely uncharacteristic) to 11 (extremely characteristic), were used. Horizontal VASs, anchored by words or phrases representing the extreme of the phenomenon in question (e.g., I feel the worst I have ever felt; I feel the best I have ever felt), have been used in previous assessments of chronic pain (Ogon, Krismer, Sollner, Kantner-Rumplmai, and Lampe, 1996), depression (Lees and Lloyd-Williams, 1999), and premenstrual mood symptoms (Steiner et al., 1999), and possess acceptable reliability and validity (Ahearn, 1997). Valence of Stereotypes. To determine whether the characteristics ascribed to Aboriginal men and women were positively or negatively valenced, fifteen participants – separate from those participating in Study 1 – were asked to review the list of 103 characteristics and rate the valence of each one “through the lens of desirability/undesirability.” Here, participants were to provide their evaluations along a continuum that ranged from -4 (very negative) to +4 (very positive). Zero was “neither negative nor positive”; in essence, a neutral point.
Prejudiced Attitudes Measures Anti-Fat Attitudes Scale (AFAS; Morrison and O’Connor, 1999). The AFAS consists of 5 items (e.g., “It is disgusting when a fat person wears a bathing suit at the beach”) that assess anti-fat attitudes. The present study modified the AFAS so as to provide separate assessments of fat men and fat women. Thus, two versions were administered, with the male AFAS being distributed to those completing the survey on Aboriginal women and the female AFAS being distributed to those completing the survey on Aboriginal men. The AFAS uses a five-point Likert-type scale (1 = strongly disagree to 5 = strongly agree), with total scores ranging from 5 to 25. Higher scores indicate greater anti-fat prejudice. Morrison and O’Connor (1999) and Brochu and Morrison (2007) indicate that the AFAS is psychometrically sound. In the present study, Cronbach’s alpha for the AFAS-Men was .61 (95% CI =.49 - .70)4 and, for the AFASWomen, .72 (95% CI = .64 - .79). Modern Homonegativity Scale (MHS; Morrison and Morrison, 2002). The Modern Homonegativity Scale (MHS) was designed to assess contemporary negative attitudes towards gay men and lesbian women. Its two parallel versions (MHS-G, which focuses on gay men and MHS-L, which focuses on lesbian women) each contain 12 items (e.g., “Many gay men [lesbian women] use their sexual orientation so that they can obtain special 4
It should be noted that the alpha coefficient for the AFAS-Men version was quite low. It is possible that being asked to evaluate fat men, in comparison to fat women, was rather novel for participants and, as such, a lack of response consistency across the AFAS-Men items may have occurred.
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privileges”) and, in the present study, participants were asked to rate their agreement or disagreement using a five-point Likert-type scale (1 = strongly disagree; 5 = strongly agree). Scores for both versions range from 12 to 60, with higher scores signifying greater levels of modern homonegativity. In the present study, alpha coefficients for the MHS-G and MHS-L were .90 (95% CI = .87 - .92) and .84 (95% CI = .79 - .87), respectively. Prejudiced Attitudes toward Aboriginals Scale (PATAS).5 To assess prejudiced attitudes toward Aboriginals, a modified version of the Modern Homonegativity Scale (MHS; Morrison and Morrison, 2002) was used. Participants were asked to rate their agreement with each statement on a five-point Likert-type scale (1 = strongly disagree; 5 = strongly agree). One item from the MHS (“Gay men [Lesbian women] who are ‘out-of-the closet’ should be admired for their courage”) was not applicable to Aboriginals and was thus, omitted. Total scores on the PATAS can range from 11 to 55, with higher scores indicating stronger modern prejudice toward Aboriginal persons. In this study, scale score reliability was .90 (95% CI = .87 - .92) for participants who assessed stereotypes about Aboriginal women, and .87 (95% CI = .84 - .90) for those evaluating stereotypes about Aboriginal men.
PROCEDURE Participants received a stereotype checklist, and were asked to indicate those characteristics that fit society’s view of Aboriginal men or Aboriginal women. To give participants the opportunity to specify any cultural descriptors which they felt had been overlooked, space was provided following the checklist. Participants then were asked to review the list of characteristics and transfer – to the top of the next page – five that they considered to be most representative of society’s beliefs about Aboriginal men or Aboriginal women. To assess their personal beliefs, participants were instructed to rate, using visual analogue scales, the extent to which they believed Aboriginal men or Aboriginal women possessed each of the top five characteristics listed. Participants then answered the measures of prejudiced attitudes.6 Completion of the survey took approximately 45 minutes. Once participants finished their questionnaires, they walked to the front of the classroom, submitted their materials, keeping their consent forms separate, and were handed a debriefing sheet detailing the nature of the study. All participants were thanked for their involvement, and were told they could contact the researchers to obtain a summary of the findings.
5
6
Male and female versions of the PATAS were not created. Thus, Study 1 measures prejudice toward the superordinate category (i.e., Aboriginals). Stereotypes and prejudice toward Aboriginals were a central focus of the present study; however, we also incorporated space to assess the stereotypes of other social groups (e.g., gay men, lesbian women, fat men and fat women). It was felt that presenting participants with each of the six social groups being targeted (male/female Aboriginals; gay men/lesbian women; and male/female fat persons) would be too timeconsuming and, thus, participants were randomly assigned to three of the social groups. Related measures of prejudice also were completed, again, with three groups in total being evaluated.
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Preliminary Data Analysis Multiplicative Index (MI). A multiplicative index (MI) was used to measure the overall strength and valence of each characteristic. It was calculated by multiplying individuals’ personal endorsement of a characteristic (as denoted by their mark on the visual analogue scale ranging from 0 to 11) by the valence of the characteristic (-4 to +4), the latter coming from the 15 independent assessors. Thus, for each characteristic, the index could range from 44 (maximal endorsement of a negatively valenced item) to +44 (maximal endorsement of a positively valenced item).
RESULTS Stereotype Ascriptions The 10 most frequently cited cultural stereotypes of Aboriginal men and Aboriginal women are listed in Tables 1 through 4. When examining the cultural stereotypes (as indicated in the CSC columns), overlap in content between those characteristics ascribed to Aboriginal men and women was found. For example, the cultural stereotype of both groups, from the perspective of participants, is that they are welfare dependent, uneducated, physically dirty, poor, alcoholic, and bad parents (the exception to the latter is when Aboriginal men were evaluated by female participants). Differences in content also were noted. Specifically, part of the cultural stereotype of Aboriginal men is that they are aggressive, abusive, and dangerous whereas, for Aboriginal women, part of their cultural stereotype is being sexually easy (noted by male participants) and undisciplined and spiritual (noted by both female and male participants). As can be seen from the tables, the characteristic “spiritual” was the only descriptor selected whose valence was positive (i.e., a characteristic whose rating was above 0 by the independent assessors and thought to be a “desirable human characteristic”). Personal endorsement scores (PECS) were computed to determine whether various cultural stereotypes of Aboriginal men and women were endorsed personally by study participants. Results indicated that PECS scores hovered around the mid-point (i.e., 5.5) which suggests that, overall, participants were not overly inclined to endorse the series of negatively valenced characteristics. The exception, however, seems to be endorsements made by male participants: their personal endorsement of “violent” (for Aboriginal men), “bad parent” (for Aboriginal men), “aggressive” (for Aboriginal men), “undisciplined” (for Aboriginal men), and “spiritual” (for Aboriginal women) received endorsement scores in excess of 7 on the 11-point VAS.
Prejudiced Attitudes Descriptive statistics for total scale scores on all prejudice measures are reported in Table 5. As can be seen, participants’ mean scale scores were approximately at the midpoint for each measure, which signifies that the sample held somewhat neutral attitudes, on average,
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Melanie A. Morrison, Todd. G. Morrison, Rebecca L. Harriman et al. Table 1. Stereotypes Most Frequently Given to Aboriginal Men (Males; n = 35)
Descriptor
CSC
PECS
Valence
MI
Welfare Dependent
94 %
6.94
- 2.31
- 16.03
Criminal
91 %
6.40
- 3.16
- 20.22
Alcoholic
89 %
6.31
- 2.75
- 17.35
Poor
85 %
5.40
- 1.13
- 6.10
Uneducated
80 %
5.00
- 2.16
- 10.80
Bad Parent
68 %
7.92
- 3.31
- 26.22
Abusive
66 %
1.00
- 3.81
- 3.81
Physically Dirty
66 %
6.28
- 2.97
- 18.65
Violent
63 %
7.65
- 3.53
- 27.00
Aggressive
60 %
8.48
- 2.06
- 17.47
Dangerous
60 %
1.30
- 2.66
- 3.46
Lazy
60 %
6.11
- 2.63
- 16.07
5.73 (2.36)
- 2.71 (0.73)
- 15.27 (7.85)
MEAN (SD)
Note. CSC = Cultural Stereotype Checklist; PECS = Personal Endorsement of Cultural Stereotypes (possible range 0-11); Valence (possible range -4 to +4); MI = Multiplicative Index (possible range -44 to +44).
toward these social groups. To examine the relationship between stereotyping and prejudice, a series of Pearson correlation coefficients were computed (see Table 6). Results indicated that scores on the PATAS were negatively related to the MIs for Aboriginal men (r = -.38) and Aboriginal women (r = -.31). Thus, stronger endorsement of negatively valenced stereotypes was associated with greater levels of modern prejudice toward Aboriginal persons. Finally, in accordance with the view that prejudice is a generalised phenomenon (e.g., Haddock et al., 1994; Morrison and Morrison, 2002) similar associations were observed between scores on the MI and indices of homonegativity and anti-fat attitudes.
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Table 2. Stereotypes Most Frequently Given to Aboriginal Men (Female; n = 110)
Descriptor
CSC
PECS
Valence
MI
Alcoholic
92 %
5.47
- 2.75
- 15.04
Welfare Dependent
89 %
6.36
- 2.31
- 14.69
Criminal
87 %
5.49
- 3.16
- 17.34
Uneducated
82 %
5.07
- 2.16
- 10.95
Poor
78 %
6.62
- 1.13
- 7.48
Dangerous
71 %
4.93
- 2.66
- 13.11
Undisciplined
68 %
6.35
- 2.13
- 13.53
Physically Dirty
68 %
5.00
- 2.97
- 14.85
Abusive*
66 %
4.03
- 3.81
- 15.35
Aggressive*
66 %
6.09
- 2.06
- 12.55
Lazy*
66 %
5.51
- 2.63
- 14.49
5.54 (0.77)
-1.98 (1.78)
-13.58 (2.62)
MEAN (SD)
Note. CSC = Cultural Stereotype Checklist; PECS = Personal Endorsement of Cultural Stereotypes (possible range 0-11); Valence (possible range -4 to +4); MI = Multiplicative Index (possible range -44 to +44). *Reflects a tie.
DISCUSSION This study investigated the types of characteristics perceived to be descriptive of Aboriginal men and Aboriginal women by the culture at large, as well as the degree to which participants endorsed these cultural characteristics. Results indicated that the cultural stereotypes of both groups consisted of descriptors that were negatively valenced, with the exception of “spiritual,” which was attributed to Aboriginal women. Given the valence of these ascriptions, the cultural stereotypes of Aboriginals do not appear to have improved from those identified in earlier studies.
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Table 3. Stereotypes Most Frequently Given to Aboriginal Women (Males; n = 31)
Descriptor
CSC
PECS
Valence
MI
Welfare Dependent
74 %
5.73
- 2.31
- 13.23
Poor
68 %
6.41
- 1.13
- 7.24
Bad Parent
68 %
4.86
- 3.31
- 16.10
Uneducated
58 %
6.65
- 2.16
- 14.36
Spiritual
52 %
8.75
2.06
18.03
Criminal
48 %
4.80
- 3.16
- 15.17
Alcoholic
48 %
4.21
- 2.75
- 11.58
Sexually Easy*
45 %
6.80
- 2.13
- 14.48
Physically Dirty*
45 %
6.23
- 2.97
- 18.51
Undisciplined*
45 %
7.67
- 2.13
- 16.34
6.21 (1.38)
-2.00 (1.56)
-10.90 (10.61)
MEAN (SD)
Note. CSC = Cultural Stereotype Checklist; PECS = Personal Endorsement of Cultural Stereotypes (possible range 0-11); Valence (possible range -4 to +4); MI = Multiplicative Index (possible range -44 to +44). *Reflects a tie.
Participants’ personal endorsement of these stereotypes was not as markedly negative. However, 56% of participants scored above the midpoint on the VAS denoting personal agreement with the cultural stereotypes of Aboriginal men and women. When Aboriginal men were the evaluative targets, approximately 67% of the male participants scored above the midpoint as did 45% of the women. When Aboriginal women were the targets, 70% of the male participants and 40% of the female participants scored above the midpoint. Consequently, it appears that a strong disjunction between cultural and personal stereotypes of Aboriginal men and women was not observed.
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Table 4. Stereotypes Most Frequently Given to Aboriginal Women (Females; n = 112)
Descriptor
CSC
PECS
Valence
MI
Welfare Dependent
90 %
6.65
- 2.31
- 15.36
Uneducated
86 %
5.23
- 2.16
- 11.30
Poor
82 %
5.88
- 1.13
- 6.64
Alcoholic
76 %
5.14
- 2.75
- 14.14
Bad Parent
73 %
4.52
- 3.31
- 14.97
Physically Dirty
70 %
4.05
- 2.97
- 12.03
Spiritual
69 %
8.47
2.06
17.45
Lazy
63 %
4.71
- 2.63
- 12.40
Undisciplined
62 %
6.11
- 2.13
- 13.01
Unreliable
56 %
5.48
- 3.06
- 16.77
5.62 (1.26)
- 2.04 (1.57)
- 9.92 (10.01)
MEAN (SD)
Note. CSC = Cultural Stereotype Checklist; PECS = Personal Endorsement of Cultural Stereotypes (possible range 0-11); Valence (possible range -4 to +4); MI = Multiplicative Index (possible range -44 to +44).
To date, scant attention has been paid to measuring prejudiced attitudes toward Aboriginal men and women. Of the few empirical studies that are available, authors have relied on: 1) single-item measures that assess overall evaluations of Aboriginals (e.g., Donakowski and Esses, 1996; Haddock et al., 1994); 2) scales modified to evaluate social and interpersonal contact situations with American Indians (e.g., Ancis, Choney, and Sedlacek, 1996); and 3) affective measures used with disparate social groups including Native people in Canada (e.g., Corenblum and Stephan, 2001).
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Melanie A. Morrison, Todd. G. Morrison, Rebecca L. Harriman et al. Table 5. Descriptive Statistics for All Prejudice Measures
Aboriginal Men
M
SD
Possible Range
Actual Range
PATAS
33.68
8.09
11-55
16-50
MHS-L
35.60
7.78
12-60
15-57
AFAS (female target)
14.36
3.81
5-25
5-25
PATAS
32.56
8.88
11-55
11-53
MHS-G
32.18
9.08
12-60
13-60
AFAS (male target)
15.27
3.22
5-25
5-25
Aboriginal Women
Note. PATAS = Prejudiced Attitudes toward Aboriginals Scale (midpoint = 33); MHS-L = Modern Homonegativity Scale – Lesbian Version (midpoint = 36); AFAS = Anti-fat Attitudes Scale (midpoint = 15); MHS-G = Modern Homonegativity Scale – Gay Version (midpoint = 36).
Table 6. Correlations between MI and Prejudice Measures
MI MI
Aboriginal Men Trait Ratings (n = 145) PATAS MHS-L -.38**
PATAS
AFAS-W
-.38**
-.29**
.46**
.44**
MHS-L
.41**
AFAS-W MI MI PATAS MHS-G
Aboriginal Women Trait Ratings (n = 144) PATAS MHS-G -.31**
AFAS-M
-.10**
-.17**
.44**
.29** .27**
AFAS-M Note. Participants did not receive all measures. MI = Multiplicative Index, a measure of the strength of the personally endorsed culturally stereotypic trait [PECS] X the valence of that trait)/5 traits in total. MHS-G; MHS-L; PATAS; AFAS-M (Anti-fat Attitudes Scale [Men]); AFAS-W (Anti-fat Attitude Scale [Women]). **p < .001.
Our first study investigated prejudice toward Aboriginal men and women using a scale that was originally designed to assess homonegativity (i.e., the MHS). The potential inappropriateness of MHS items, when applied to an Aboriginal target, may account for the finding that mean scores on the PATAS hovered around the midpoint; in other words,
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participants neither agreed nor disagreed with scale items but, rather, selected “don’t know” as their response choice. The purpose of Study 2 was to address this limitation by creating two measures of Aboriginal prejudice (old-fashioned and modern) that were psychometrically sound.
STUDY 2 As is recommended practice when developing a scale (e.g., Springer, Abell, and Hudson, 2002), a large pool of items was generated in a deliberate effort to oversample content domain. Fifteen individuals from both Aboriginal and non-Aboriginal backgrounds were invited to participate in either informal one-to-one interviews or informal small group discussions. For those participants who were non-Aboriginal, information about the prejudices to which they had been exposed while in contact with other non-Aboriginals was obtained as were the types of objections they personally held toward Aboriginal men and women. When interviewing Aboriginal participants, emphasis was placed on recording their direct experiences with prejudice, as well as their perceptions of non-Aboriginals’ objections toward those who identify as Aboriginal. Analysis of the interview data resulted in the creation of 144 scale items. In accordance with the theory of old-fashioned prejudice, items that reflected this content domain were based on the perceived inferiority of Aboriginal men and women. Sample items generated were: “Most Aboriginals sound intoxicated (drunk)”, “Most Aboriginals need classes on how to be better parents”, and “High standards of hygiene are NOT valued by Aboriginals”. Items reflecting modern prejudice were based on the assumptions that: 1) Aboriginal men and women place too much emphasis on their cultural backgrounds (e.g., Aboriginal cultural considerations must be made in many domains such as work and school); 2) Aboriginal men and women use their cultural differences to push for changes in the status quo, many of which are viewed as unnecessary (e.g., wanting the right to practice traditional ceremonies while incarcerated); 3) Aboriginal men and women exploit their “status” as Aboriginals to receive a host of special favours and handouts from various institutions; and 4) because they are the recipients of “special” opportunities and protections, discrimination toward Aboriginal persons is no longer a pressing social issue in Canada. Sample items denoting modern prejudice were: “Aboriginals seem to use their cultural traditions to secure special rights denied to non-Aboriginal Canadians,” “Many of the requests made by Aboriginals to the Canadian government are excessive,” and “Aboriginals should stop complaining about the way they are treated and simply get on with their lives.” These items then were administered in conjunction with other psychometrically sound scales designed to test convergent and divergent validity. It was hypothesised that the correlation between modern forms of prejudice (i.e., the Modern Prejudiced Attitudes toward Aboriginals Scale [M-PATAS] and the Modern Homonegativity Scale) would be stronger than the correlations evidenced between incongruent forms (e.g., the Modern Prejudiced Attitudes toward Aboriginals Scale and an old-fashioned measure of homonegativity, the Attitudes toward Gay Men Scale). Further, to test known-groups validity, it was hypothesised that men would evidence higher levels of prejudice toward Aboriginals. This hypothesis is in keeping with research (e.g.,
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Morrison and Morrison, 2002) indicating that men (typically) obtain higher scores on measures of prejudice than do women. Finally, the relationship between social desirability bias and Aboriginal prejudice, in both its old-fashioned and modern forms, was examined.
METHOD Participants Four hundred ninety-one undergraduate students attending a university in Western Canada completed the questionnaire package. Of these participants, a majority identified as Caucasian (88%, n = 432). (Seventeen self-identified as Aboriginal and were omitted from further analyses.) The numbers of male and female participants were 147 and 326, respectively. (One participant did not provide a response.) Participants’ ages ranged from 17 to 57 (M = 19.32; SD = 3.01).
Measures Attitudes toward Gay Men Scale (ATG; Herek, 1988, 1993). The reliable and valid shortform version of the ATG measures blatant objections to gay men (“Male homosexuality is a perversion”). This scale contains 5 items and, in the current study, employed a 7-point Likerttype response format (1 = strongly disagree; 7 = strongly agree). Participants scoring higher on the ATG may be viewed as possessing greater levels of old-fashioned prejudice toward gay men. A large body of evidence attesting to the psychometric soundness of the ATG exists (e.g., Herek, 1993; Morrison and Morrison, 2002; Morrison, Morrison, and Franklin, in press). The alpha coefficient for the ATG in the present study was .90 (95% CI = .89 - .92). Modern Homonegativity Scale-Gay (MHS-G; Morrison and Morrison, 2002). A description of this measure is provided in Study 1. The alpha coefficient for the MHS-G was .91 (95% CI = .90 - .92). Social Desirability Scale (SDS-Form C; Reynolds, 1982). A 13-item short-form version of the Marlowe-Crowne Social Desirability Scale was used. This measure is designed to assess individuals’ motivation to respond in culturally appropriate ways (e.g., “No matter who I’m talking to, I’m always a good listener”). The SDS-Form C uses a true/false response format, with higher scores indicating a greater tendency to respond in a socially desirable manner. Reynolds (1982) provides evidence attesting to the reliability and validity of Form C. In the current study, the alpha coefficient was .72 (95% CI = .66 - .77).
PROCEDURE Questionnaires were distributed to participants in mass-testing or small-group testing sessions. Instructions for completing the questionnaire materials were clearly articulated and the ethical obligations associated with the study were upheld. The questionnaire took
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approximately 30 minutes to complete. All participants were debriefed and thanked for their participation in the study.
RESULTS As 144 scale items were generated, it was necessary to employ various statistical techniques to establish a more parsimonious set. First, principle axis factor (PAF) analysis with oblique rotation7 was conducted. Bartlett’s test of sphericity was statistically significant and the KMO value (.97) was excellent suggesting the data were suitable for factor analysis. Results indicated that two factors should be retained (eigenvalue 1 = 52.64 and eigenvalue 2 = 8.66), with the factors accounting for 36.2% and 5.7% of the variance, respectively. The scree plot also confirmed the presence of two factors. The pattern matrix then was used to identify items that had minimum loadings of .6 and no cross-loadings greater than .3. The numbers of retained items were: 48 assessing modern prejudice (loading on Factor 1) and 28 assessing old-fashioned prejudice (loading on Factor 2). Reliability analysis was conducted for each scale, with items removed if their item-total correlations were ≤ .5 and ≥.70. (i.e., the lower bound suggests adequate cohesion with the other items and the upper bound prevents significant content overlap). Fourteen items assessing modern prejudice (i.e., Modern Prejudiced Attitudes toward Aboriginals Scale: M-PATAS) and 11 items assessing oldfashioned prejudice (i.e., Old-fashioned Prejudiced Attitudes toward Aboriginals Scale: OPATAS) were ultimately retained. Alpha coefficients for the M-PATAS and O-PATAS were .92 (95% CI = .91 - .93) and .91 (95% CI = .89 - .92), respectively. To ensure that item reduction had not compromised the factorial distinction between the modern and old-fashioned indicants of Aboriginal prejudice, another PAF was conducted. Bartlett’s test of sphericity was statistically significant and the KMO measure of sampling adequacy was .96 suggesting the data were factor analyzable. The eigenvalue for Factor 1 was 10.32 (accounting for 39.3% of the variance) and the eigenvalue for Factor 2 was 2.77 (accounting for 8.9% of the variance). The scree plot, again, clearly indicated the presence of two factors. The retained scale items and final factor loadings can be found in the Appendix. Participants scored above the midpoint on the M-PATAS (M = 61.75; SD = 15.06; midpoint = 56), but below the midpoint on the O-PATAS (M = 39.83; SD = 11.03; midpoint = 44). A paired t-test between the M-PATAS and O-PATAS scores revealed that modern prejudice toward Aboriginals (M = 4.41; SD = 1.08) was significantly higher than oldfashioned prejudice (M = 3.62; SD = 1.01), t (431) = 17.03, p < .001, d = .76. In terms of the measures of homonegativity, participants scored below the midpoints on the MHS-G (M = 44.82; SD = 13.73; midpoint = 48) and the ATG (M = 15.29; SD = 8.10; midpoint = 20). Pearson correlation coefficients were computed (see Table 7). As predicted, significant positive correlations were found between scores on the old-fashioned measures of prejudice (i.e., the O-PATAS and ATG) as well as the modern measures (i.e., the M-PATAS and MHSG). Further, Steiger’s Z indicated that the correlation between the two modern measures of prejudice (M-PATAS/MHS-G) was significantly stronger than the correlation between incon7
Oblique rotation was used because, in accordance with other research on old-fashioned and modern prejudice (e.g., Morrison and Morrison, 2002; Swim et al., 1995), we assumed that any resultant factors would be intercorrelated rather than orthogonal.
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Melanie A. Morrison, Todd. G. Morrison, Rebecca L. Harriman et al. Table 7. Intercorrelations among Key Variables O-PATAS
O-PATAS M-PATAS
M-PATAS
ATG
MHS-G
SDS
.58**
.28**
.38**
.00
.28**
.50**
-.05
.77**
-.01
ATG MHS-G
-.00
SDS Note. O-PATAS (Old-fashioned-Prejudice Attitudes toward Aboriginals Scale); M-PATAS (ModernPrejudiced Attitudes toward Aboriginals Scale); ATG (Attitudes toward Gay Men Scale – Oldfashioned); MHS-G (Modern Homonegativity Scale – Gay); SDS (Social Desirability Scale – Form C). **p < .001.
gruent forms; that is, the M-PATAS/ATG, Z = 5.77, p < .01, and the O-PATAS/MHS-G, Z = 3.24, p < .01.8 Gender differences on both the O-PATAS and M-PATAS were examined to test knowngroups validity. Independent samples t-tests, with Bonferroni correction for multiple comparisons, were conducted. Results indicated that men (M = 42.62; SD = 11.30) scored significantly higher than women (M = 38.60; SD = 11.10) on the O-PATAS, t (448) = 3.52, p < .001, d = .36. Similar results emerged for scores on the M-PATAS (M = 66.94; SD = 14.32 for men; M = 59.56; SD = 14.85 for women), t (442) = 4.84, p < .001, d = .51. With regard to homonegativity, male participants scored significantly higher than women on both forms (MHS-G: M = 52.81; SD = 13.76 for men; M = 41.28; SD = 12.17 for women, t [451] = 8.92, p < .001, d = .89 and ATG: M = 19.89; SD = 8.63 for men; M = 13.23, SD = 6.94 for women, t [227.89] = 8.13, p < .001, d = .85. Finally, the correlations between scores on the measures of prejudiced attitudes toward Aboriginals (i.e., the O-PATAS and M-PATAS) and social desirability (i.e., the SDS-Form C) were statistically non-significant. Thus, responses on the O-PATAS and the M-PATAS do not appear to be influenced by social desirability bias.
DISCUSSION The development and preliminary validation of instruments designed to assess oldfashioned and modern prejudice toward Aboriginal Canadians addresses an important gap in measurement. Using the theory of modern prejudice (McConahay, 1986; Morrison and 8
The difference in the magnitude of the correlations may be due to similarities in item content within the modern measures. For instance, a final retained M-PATAS item reads “Aboriginal people should stop complaining about the way they are treated in society and simply get on with their lives”, which is similar to the content of an item assessing modern homonegativity, “Gay men should stop complaining about the way they are treated in society and simply get on with their lives.” (However, the correlation between the two items was r [460] = .45, p < .01, which suggests only modest overlap.)
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Morrison, 2002; Swim, Aikin, Hall, and Hunter, 1995; Tougas, Brown, Beaton, and Joly, 1995) as a framework for the construction of a pool of scale items, two interrelated (34% shared variance), yet factorially distinct, measures of prejudice toward Aboriginal people (the O-PATAS and the M-PATAS) were created. Evidence attesting to the distinction between these two scales was obtained via correlational analyses that showed significantly stronger associations between the M-PATAS and the MHS-G (both measures of modern prejudice) than between the M-PATAS and the ATG (a measure of old-fashioned prejudice toward gay men). Thus, in the present study, the modern measures appear to possess greater similarity in either content or tone of items. Also, consistent with previous research (e.g., Morrison and Morrison, 2002), men scored significantly higher than women on all measures of prejudice. Finally, the scores on the O-PATAS and M-PATAS were not significantly associated with social desirability bias, a finding that provides evidence of divergent validity.
GENERAL DISCUSSION Previous research (Claxton-Oldfield and Keefe, 1999; Haddock et al., 1994; Mackie, 1974) indicates that stereotypes of Aboriginal persons in Canada are widespread and that their valence tends to be exceedingly negative. Study 1 was designed to examine contemporary stereotypes of Aboriginal men and women as a means of documenting any relative change in content over time and, in particular, whether positive beliefs about Aboriginals in Canada are beginning to emerge. Results indicated that the cultural stereotype of Aboriginal men and women remains unfavourable, with few positive traits thought to be representative of women and men of Aboriginal descent. The degree of similarity between the characteristics used to describe Aboriginal persons today and those used approximately 10 to 20 years ago is striking. For instance, stereotypes such as “uneducated” and “poor” remain at the forefront of people’s minds when asked what the culture-at-large believes about Aboriginal men and women. A limitation associated with Claxton-Oldfield and Keefe’s (1999) and Haddock et al.’s (1994) study was that they did not assess whether their participants personally agreed with the cultural stereotype. To this end, we investigated the correspondence between the stereotypes endorsed collectively and personally and found that there was a relatively strong degree of association between these two perceptual sets (i.e., participants’ personal endorsement of cultural stereotypes was not, in fact, weak). Unlike the participants in Claxton-Oldfield and Keefe’s (1999) study, who were asked to evaluate the Innu of Davis Inlet (a group living in an exceptionally remote location in Canada), our respondents likely have had contact experiences with the evaluative targets. In fact, Saskatchewan, proportionate to the total provincial population, is ranked first or second (comparable to Manitoba) for having the largest number of Aboriginal residents. However, unlike Haddock et al. (1994), we can only speculate as to whether this was the case because we did not examine contact and the various forms this construct can take (e.g., positive, negative, neutral past experiences). Since a substantial body of empirical research attests to the positive effects of intergroup contact (e.g., see Tropp and Pettigrew, 2005), we recommend including this variable in future research. It is important to highlight that participants in Study 1 personally endorse, to some extent, the stereotypes that Aboriginal men are “dangerous,” “violent,” and “aggressive.” Also,
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Aboriginal women were thought to possess socially undesirable characteristics such as being “bad parents,” “physically dirty,” and “undisciplined.” According to Stephan and Stephan (1985) and Corenblum and Stephan (2001), anxiety about meeting outgroup members can create considerable apprehension on the part of the ingroup and result in intergroup tension in the event that contact does occur. It is possible that perceived anxiety over a possible contact scenario with a person of Aboriginal descent may preclude contact experience in the first place and, ultimately, erect barriers to the reduction of culturally prescribed and personally endorsed stereotypes about Aboriginal women and men. Vorauer at al.’s (1998) research on White Canadians’ meta-stereotypes of Aboriginal persons confirms this apprehension. In the event that some individuals may be particularly wary of contact with Aboriginals either due to prejudiced attitudes or concern about appearing prejudiced (Dunton and Fazio, 1997; Plant and Devine, 1998; Vorauer et al., 1998), one intervention that might prove useful involves preparing for contact via imagining exercises. In previous research, Bargh, Chen, and Burrows (1996) had participants engage in virtual contact experiences by getting them to imagine a contact scenario with a member of an outgroup (in this case, African Americans). Results indicated that, contrary to what was expected, members of the ingroup (in this case, White Americans) were more likely to act in a hostile manner toward African Americans following virtual contact: Essentially, by envisioning an interaction with an African American, participants’ knowledge of the social category “encouraged” access to the cultural stereotype and resultant attitudes and behaviours were not favourable. According to Turner, Crisp, and Lambert (2007), if participants are to benefit from this type of bias reduction exercise, one must focus on components that may occur within the interaction itself and not merely think of an interaction taking place. For example, reductions in anxiety and prejudiced attitudes are noted when participants are asked to envision the topic of conversation, the nature of the interaction, what they might learn from the other person, and how they will behave while engaged in these interaction scenarios. A more nuanced approach, therefore, is recommended. In order to promote bidirectional contact and communication, it is imperative that social scientists examine Aboriginal men’s and women’s stereotypes of Caucasian men and women. To date, little research (however, see Corenblum and Stephan [2001] for a notable exception) has addressed the category-based beliefs and expectations Aboriginal women and men have when contemplating contact or when actively engaged in contact scenarios with nonAboriginals. In an exploratory exercise, anecdotal evidence of the types of beliefs Aboriginals see as part of the cultural stereotype of White Canadians was obtained by the first author. She asked an Aboriginal group of first year psychology students to generate stereotypes of “Whites” (after being asked to provide descriptors of the cultural stereotype of “Aboriginals”). The first few stereotypes were haltingly generated and included characteristics such as “oppressive,” “out for themselves,” “rude,” and “know-it-alls”. Once the first few descriptors were jotted on the board, however, the students gained momentum and, subsequently, generated enough characteristics to fill the blackboard. Insight also can be gained from the minority group critically examining the cultural stereotypes, both positive and negative, held by the majority culture. For instance, one student indicated that Whites romanticize Aboriginal culture (i.e., Whites believe that all Aboriginal cultural groups were historically comprised of congenial individuals who supported and nurtured one another). It was felt that this view serves to minimize the struggles endured by
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many Aboriginal cultural groups and erases features of their collective history (e.g., conflicts between rival Aboriginal communities). Although a handful of researchers have examined negative attitudes toward Native Canadians and Native Americans using a number of measures such as 1-item scales or indices of affect, prior to our research there were no existing instruments that adhered to rigorous scale development practices. Further, there was no measure that investigated negative attitudes as they pertain to the modern conceptualization of prejudice. We were able to reduce a large group of scale items to a more parsimonious number, and provide preliminary evidence for the conceptual distinction between the unidimensional O-PATAS (old-fashioned prejudice) and the M-PATAS (modern prejudice). It is intended that both the O-PATAS and M-PATAS be used to better understand the nature of anti-Aboriginal prejudice in Canada.
LIMITATIONS AND DIRECTIONS FOR FUTURE RESEARCH First, the authors used convenience student-based samples in both Studies 1 and 2.9 As a result, assessing the degree of correspondence between these findings and those obtained with non-student samples would be informative. Second, although one of the purposes of Study 1 was to identify the characteristics attributed to Aboriginal men and women, separately, the current O-PATAS and M-PATAS use the superordinate category “Aboriginals” or “Aboriginal persons.” To address this limitation, the first author is conducting research that will test male- and female-specific versions of the O-PATAS and M-PATAS. Third, as with all new measures, ongoing psychometric testing is necessary. Given the small number of validation coefficients that were calculated in Study 2, additional measures are required to formulate a nomological network for the O-PATAS and M-PATAS. In conclusion, Aboriginal men and women in Canada are the objects of stereotyping, prejudice, and discrimination. Although attention has been paid by scholars in the disciplines of history, anthropology, and sociology, relatively little has been paid by psychologists and hence it is imperative that psychologists generally, and social psychologists in particular, assume a more active role with respect to these phenomena. If we are to begin addressing issues of inequity, the neglect that the psychological community has displayed toward Aboriginal Canadians must be redressed.
9
Reliance on student samples may provide a relatively conservative overview of the stereotypes and prejudicial attitudes currently directed toward Aboriginal men, women, and children in Saskatchewan.
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APPENDIX A Factor Loadings for the Old-fashioned Prejudiced Attitudes toward Aboriginals Scale (O-PATAS) and Modern Prejudiced Attitudes toward Aboriginals Scale (M-PATAS).
Old-fashioned Prejudice Items Most Aboriginal people can NOT take care of their children. Most Aboriginal people sound intoxicated (drunk). Most Aboriginal people are on welfare. Most Aboriginal people need classes on how to be better parents. Aboriginal people have way too many children. Aboriginal people have no sense of time. High standards of hygiene are NOT valued in Aboriginal culture. Diseases that affect Aboriginal people are simply due to the lifestyle they lead. Drug abuse is a key problem among Aboriginal people. Poverty on reserves is a direct result of Aboriginal people abusing drugs. Few Aboriginal people seem to take much pride in their personal appearance. Modern Prejudice Items Canada needs to stop apologizing for events that happened to Aboriginal people many years ago. Aboriginal people still need to protest for equal rights.* Aboriginal people should stop complaining about the way they are treated and simply get on with their lives. Aboriginal people should simply get over past generations’ experiences at residential schools. Aboriginal Canadians seem to use their cultural traditions to secure special rights denied to non-Aboriginal Canadians. Many of the requests made by Aboriginal people to the Canadian government are excessive. Special places in academics programmes should NOT be set aside for Aboriginal students. Aboriginal people should be satisfied with what the government has given them. It is now unnecessary to honour treaties established with Aboriginal people. Aboriginal people should NOT have reserved placements in universities unless they are qualified. Aboriginal people should pay taxes just like everyone else. The government should support programmes designed to place Aboriginal people in positions of power.* Non-Aboriginal people need to become sensitive to the needs of Aboriginal people.* Government agencies should make every effort to meet the needs of Aboriginal people.*
Factor 1
Factor 2
.10 .08 .05 -.30 .11 -.05 .03
.70 .68 .63 .76 .67 .62 .74
-.05 -.10 .01
.67 .62 .63
.11
.68
.69
-.01
.60
-.07
.65
.16
.65
.13
.68
.02
.67
.17
.73
-.06
.65
.18
.62
.10
.69 .71 .68
-.08 .04 -.10
.67
.04
.67
.01
Note. Items that are marked with an asterisk require reverse-scoring. Response format is: 1 = strongly disagree; 2 = disagree; 3 = somewhat disagree; 4 = don’t know; 5 = somewhat agree; 6 = agree; 7 = strongly agree.
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ABOUT THE AUTHORS EDITORS Melanie A. Morrison received her PhD in experimental social psychology from the University of Ottawa, Canada. She is currently an Associate Professor in the Department of Psychology at the University of Saskatchewan, Canada, and is a core faculty member within the Applied Social Psychology concentration. Her research is focused primarily in the areas of stereotyping, prejudice, and discrimination, and she is interested in these phenomena from both the perpetrators’ and targets’ perspectives. For the past four years, she has served as CoChair of the Canadian Psychological Association’s section on Sexual Orientation and Gender Identity Issues. Todd G. Morrison received his PhD in experimental social psychology from Queen’s University (Canada). He is a lecturer at the National University of Ireland, Galway and conducts research in the areas of stereotyping, prejudice, discrimination; male body image; and gay and lesbian psychology. He is the editor/co-editor of two books (Pornucopia: Eclectic views on gay male pornography and Male sex work: A business doing pleasure [both from Harrington Park Press]) and has published articles in various peer-reviewed journals including Journal of Social Psychology, Body Image, Journal of Cross-cultural Psychology, Psychology of Men and Masculinity, Sex Roles, and the European Journal of Psychological Assessment.
CONTRIBUTORS Dermot Barnes-Holmes, PhD, is foundation Professor and Head of the Department of Psychology at the National University of Ireland, Maynooth. He has published over 200 scientific articles, book chapters, and books, and he was recently ranked as the most prolific author in the world in the Experimental Analysis of Human Behavior during the period 1980 to 1999 (Dymond, 2002). He has served on, or is currently serving on, a number of editorial boards including: Experimental Analysis of Human Behavior Bulletin; Journal of the Experimental Analysis of Behavior; Behavior Analyst; European Journal of Psychology; International Journal of Psychology and Psychological Therapy (Associate Editor); and the Psychological Record. He served on the Health Research Board from 2002-2005 (appointed by the Minister for Health and Children) and was elected to the Council of the Psychological Society of Ireland from 2004-2007.
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Gerd Bohner received his doctorate in psychology (Dr. phil) from the University of Heidelberg (Germany) in 1990 and currently is Professor of Social Psychology at the University of Bielefeld (Germany). His areas of research include attitudes, social cognition, social influence, gender, and sexual aggression. He is editor-in-chief of Social Psychology (Hogrefe & Huber) and has published in various peer-reviewed journals including the Journal of Personality and Social Psychology, Personality and Social Psychology Bulletin, the European Journal of Social Psychology, and Group Processes and Intergroup Relations. Paula M. Brochu is a graduate student in social psychology at the University of Western Ontario, Canada. Broadly speaking, her research interests lie within intergroup relations, prejudice, stereotyping, and discrimination. In particular, much of her research currently focuses upon the domain of weight bias, or negativity directed toward individuals perceived to carry excess weight. Becky L. Choma is a SSHRC-funded postdoctoral fellow at York University, Canada. Her research interests include political ideology, prejudice and discrimination, individual differences, justice, social cognition, and prejudice reduction. Khaya D. Clark (PhD, University of Oregon, USA, 2008) is a Research Scientist at the Oregon Center for Applied Science (USA). Her areas of research include racial and gender attitudes in children, race and ethnic relations, social psychology, and methodology. Claire Cullen received her degree in psychology from the National University of Ireland, Maynooth (NUIM) in 2006 and is currently using the Implicit Relational Assessment Procedure (IRAP) to measure implicit homonegativity as part of her PhD research (also at NUIM). Her PhD is part funded by the National University of Ireland, Maynooth and the Irish Research Council for Science, Engineering and Technology (IRCSET). She is presently the chairperson of the Sexual Diversity and Gender Issues Interest Group of the Psychological Society of Ireland. Bella DePaulo (PhD, Harvard, 1979) is a social psychologist and the author of Singled out: How singles are stereotyped, stigmatized, and ignored, and still live happily ever after (St. Martin’s Press, 2006). DePaulo has also offered seminars and workshops on the science of singlehood. She is the recipient of a number of honors and awards, such as the James McKeen Cattell Award and the Research Scientist Development Award, and has served in various leadership positions in professional organizations. Dr. DePaulo has written op-ed essays for newspapers such as the New York Times, Newsday, and the San Francisco Chronicle, and she also is a contributor to the Huffington Post. She is currently a Visiting Professor of Psychology at the University of California, Santa Barbara. Visit her website at www.BellaDePaulo.com. John E. Edlund is completing his PhD in social and industrial/organizational psychology at Northern Illinois University, USA. His research interests include the effect of racial stereotypes on forensic psychology as well as human mating (broadly defined) explored from an evolutionary psychology perspective. He is the former president of the graduate student committee of the Society for Personality and Social Psychology. Victoria M. Esses is Professor of Psychology and Director of the Collaborative Graduate Program in Migration and Ethnic Relations at the University of Western Ontario, Canada. Her research examines prejudice, discrimination, and intergroup relations, with a particular focus on the role of threat and competition in determining attitudes and relations among groups. Dr. Esses is co-editor of Social Issues and Policy Review, a new publication of the Society for the Psychological Study of Social Issues. She is also on the editorial boards of Du Bois Review:
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Social Science Research on Race, Journal of Personality and Social Psychology, and Social and Personality Psychology Compass. She is a Fellow of the American Psychological Association, the Association for Psychological Science, the Canadian Psychological Association, and the Society for the Psychological Study of Social Issues. Friederike Eyssel received her doctorate in psychology (Dr. phil) from the University of Bielefeld (Germany) in 2007, where she now works as a Post-Doctoral Researcher in the Department of Social Psychology. In her work, she investigates how rape myths and their acceptance influence behavioral intentions or, more generally, how rape myth acceptance affects information processing. She also is interested in the assessment of implicit and explicit gender prejudice, the social psychology of disability and infrahumanization. Dr. Eyssel’s research has been published in the European Journal of Social Psychology, Swiss Journal of Psychology, and Sex Roles. Bertram Gawronski received his PhD in psychology from Humboldt-University Berlin (Germany) in 2001 and currently holds a Tier II Canada Research Chair in Social Psychology at the Department of Psychology at the University of Western Ontario, Canada. His research lies at the intersection of social and cognitive psychology, addressing the interplay of automatic and controlled processes in social behavior and information processing. His research has been distinguished with several awards, including the 2006 Theoretical Innovation Prize from the Society for Personality and Social Psychology, the 2007 Early Researcher Award from the Ontario Ministry of Research and Innovation, and the 2007 Early Career Award from the International Social Cognition Network. Rebecca Harriman is a doctoral student in Clinical Psychology at the University of Saskatchewan, Canada. Her research interests include prejudice and discrimination, as well as scale development. Helen C. Harton received her doctorate in psychology (PhD) from Florida Atlantic University and is Professor and Coordinator of Graduate Studies in Psychology at the University of Northern Iowa (USA). Her areas of research include prejudice, social influence, and attitude change. She has published in various peer-reviewed journals in social psychology and related disciplines. Jeremy D. Heider received his PhD in social and industrial/organizational psychology from Northern Illinois University in 2005, and is currently an Assistant Professor of Psychology at Stephen F. Austin State University (USA). His two primary programs of research have investigated the relationship between implicit attitudes and interracial interaction behaviors, and the influence of stereotypes on social memory. Janine Hertel received her BA in psychology from the Chemnitz University of Technology (Germany) in 2003. She is currently pursuing her PhD in Psychology. Her areas of research include stereotypes and personality differences in singles and couples, emotional intelligence, and gender differences in mental disorders. Gordon Hodson is an Associate Professor at Brock University, Canada. He is currently a Consulting Editor at the Journal of Personality and Social Psychology. His research interests include prejudice and discrimination, individual differences, perceptions of intergroup threat, intergroup emotions, and group contact. Lisa Jewell received her MA in applied social psychology from the University of Saskatchewan, Canada in 2007 and is currently working on her PhD at the same university. Her research interests fall within the realm of prejudice and discrimination, and she is
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particularly interested in perpetrators' understanding of their own prejudices and discriminatory behaviours. Saera Khan received her doctorate in social psychology in 1999 from Washington University in St. Louis (USA). She is currently an Associate Professor at the University of San Francisco. Her research examines cognitive and motivational factors involved in the use of stereotypes to form impressions of others. Sei Jin Ko received her PhD in social psychology from the University of Groningen (The Netherlands) in 2007 and is currently a visiting Assistant Professor at Kellogg School of Management, Northwestern University. Her areas of research include auditory stereotyping and prejudice, person perception, impression formation, power, and conflict resolution. She has published in various peer-reviewed journals, including Journal of Personality and Social Psychology, Personality and Social Psychology Bulletin, and Journal of Experimental Social Psychology. Kristin A. Lane received her doctorate in social psychology from Harvard University. She is currently an Assistant Professor of Psychology at Bard College in Annandale-onHudson, NY. Her research interests include automatic social cognition, the psychology of stereotyping and prejudice, and self and identity. Kristi M. Lemm received a PhD in social psychology from Yale University in 2000. She is currently an Associate Professor of Psychology at Western Washington University. Her research and teaching interests include implicit social cognition with a focus on stereotyping and prejudice, particularly pertaining to sexual orientation. Wendy Morris received her PhD in Social Psychology from the University of Virginia (USA) in 2005. She is currently an Assistant Professor of Psychology at McDaniel College in Maryland. Her two main research interests include the stigmatization of singles and the psychology of lie detection. She has published her research in such journals as Group Processes and Intergroup Relations, Psychological Inquiry, Journal of Family Research, Current Directions in Psychological Science, and the Journal of Genetic Counseling. Paul R. Nail received his doctorate in psychology (PhD) from Texas Christian University (USA) in 1981 and is currently Assistant Professor of Psychology at the University of Central Arkansas (USA). His areas of research include social influence, social response models, cognitive dissonance theory (individual differences), self theory, and prejudice. He is a past president of the Southwestern Psychological Association (USA) and has published in various peer-reviewed journals including Psychological Bulletin, Journal of Personality and Social Psychology, Personality and Social Psychology Bulletin, and British Journal of Social Psychology. Brian Nosek received a PhD from Yale University in 2002 and is an Assistant Professor in the Department of Psychology at the University of Virginia. He directs Project Implicit (http://projectimplicit.net/) an Internet-based multi-university collaboration of research and education about implicit cognition – thoughts and feelings that exist outside of awareness or control. Nosek's research interests include implicit cognition, automaticity, memory, attitudes, beliefs, and identity, political and religious ideologies, morality, and the interface between theory, methods, and innovation. David N. Sattler received his doctorate in social psychology from Michigan State University (USA) and currently is Professor of Psychology at Western Washington University. His areas of research include group processes, social influence, and trauma and disasters. He established the International Tsunami Museum in Thailand to provide education
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about disaster threats and the worldwide actions to help with recovery following the Indian Ocean Tsunami. He is Associate Editor of Natural Hazards Review, has served on the editorial board of Journal of Traumatic Stress, and publishes his cross-cultural research in peer-reviewed journals. Sabine Sczesny received her doctorate in psychology (Dr. phil) from the University of Kiel (Germany) in 1997 and is currently an Assistant Professor of Social Psychology at the University of Bern (Switzerland). In her research, she focuses on basic and applied aspects of stereotyping and prejudice, language, aggression, and gender. Her research has been published in various peer-reviewed journals such as the European Journal of Social Psychology, Experimental Psychology, Personality and Social Psychology Bulletin, and Journal of Language and Social Psychology. Chuck Tate is an Assistant Professor of psychology at California State University, Bakersfield. He received his PhD in social psychology in 2006 from the University of Oregon (USA). He was a Research Associate at the Oregon Center for Applied Science from 20032006. His areas of research include (a) individual definitions of social categories such as ‘race,’ sexual orientation, and gender, and their relationships to social perception and prejudice, (b) the assessment of racial attitudes, as well as (c) the processes involved in the generation and evaluation of predictions. His work has appeared in American Psychologist, Theory & Psychology, and the edited volume Judgments over time: The interplay of thoughts, feelings and behavior (Oxford University Press, 2006). Lindsay Taylor received her BA in Psychology from the University of Virginia (USA) in 2003. She is currently studying veterinary medicine at Virginia-Maryland Regional College of Veterinary Medicine and is expecting to earn her DVM degree in 2010. She previously worked for Caliber Associates/ICF International in Virginia where she assisted in conducting research and writing a number of articles and manuals on topics including child abuse and neglect, community partnerships, and the well being and development of children in the child welfare system. N. Eugene Walls is an Assistant Professor in the Graduate School of Social Work at the University of Denver. He received his Masters in Social Work from the University of Texas at Austin and his PhD in sociology from the University of Notre Dame (USA). His teaching focuses on multicultural social work practice, issues of privilege, and research methods. He conducts research on homelessness, issues of lesbian and gay youth, multicultural education, and modern forms of sexism and heterosexism, with particular attention given to the role of positive stereotypes in maintaining social stratification.
INDEX A abnormalities, 5 aboriginal, vii, 100, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305 abusive, 287 academic, 1, 2, 3, 4, 52, 228, 236, 253, 301 academic performance, 236 academics, 69, 300 access, 9, 170, 206, 280, 298 accessibility, 10, 47, 157, 159, 219 accounting, 8, 11, 295 accuracy, 143, 151, 157, 166, 185, 199, 200, 210, 284 achievement, 178, 253, 302 acoustic, 151 activation, 31, 47, 49, 72, 90, 91, 98, 118, 119, 120, 121, 156, 160, 162, 219, 257, 301 activism, 232 ad hoc, 10 adaptation, 193, 212 addiction, 47, 218 adjustment, 107, 178, 183 administration, 124, 126, 218, 302 adolescents, 20, 201, 269 adult, 93, 97, 102, 103, 109, 137, 166, 167, 168, 194, 248 adult population, 166, 248 adulthood, 116, 168, 190 adults, 96, 98, 103, 104, 105, 114, 166, 167, 168, 171, 172, 174, 183, 184, 186, 187, 189, 193, 196, 197, 239, 278 advertisements, 150, 168 advertising, 167 affective reactions, 27, 28, 30, 32, 33, 34, 35, 36, 41, 42, 43, 45, 46, 283
affirmative action, 2, 12, 29, 55, 79, 85, 118, 227, 253, 254, 257, 274 Afghanistan, 15 African American(s), 5, 31, 52, 56, 58, 72, 73, 79, 82, 84, 95, 100, 101, 106, 112, 117, 120, 131, 137, 159, 180, 185, 188, 189, 190, 222, 230, 236, 237, 253, 255, 258, 285, 298 age, 28, 53, 58, 59, 62, 63, 64, 67, 84, 97, 145, 166, 168, 169, 170, 171, 172, 173, 176, 177, 178, 179, 180, 183, 187, 188, 192, 197, 205, 206, 233, 234, 248, 269, 284 agents, 188 aggression, 4, 5, 7, 14, 15, 20, 22, 261, 264, 270, 271, 275, 308, 311 aggressiveness, 7 aging, 191, 194 aging society, 194 agreeableness, 239 aid, 107 AIDS, 233, 253, 255, 257 air, 25, 149 Alabama, 230 Alberta, 217, 252, 283, 284, 301, 303 alcohol, 218, 282, 305 alcohol abuse, 305 alcoholics, 282 algorithm, 82, 90, 118, 124, 127, 133, 134, 135, 136, 139, 141, 143, 144, 212, 219 alienation, 281 alpha, 144, 285, 286, 294, 304 alternative(s), 18, 33, 38, 62, 63, 79, 126, 135, 139, 144, 196, 200, 209, 210, 212, 213, 279 alters, 212 ambiguity, 7, 29, 149 ambivalence, 23, 49, 73, 78, 83, 84, 86, 87, 88, 90, 91, 110, 112, 113, 114, 115, 119, 232, 254, 256, 262, 275, 303 ambivalent, 108, 112, 113, 179, 253, 274, 302
314
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Ambivalent Sexism Inventory (ASI), 108, 109 American Community Survey, 194 American culture, 191 American Indian(s), 280, 291, 301, 302, 304, 305 AAmerican Psychological Association, 25, 89, 121, 161, 196, 221, 309 Amsterdam, 252 amygdala, 120, 121 analog, 301 androgyny, 160 anger, 4, 5, 70 ANOVA, 181 antagonism, 262, 265 antecedents, 88, 219, 253 anthropology, 90, 299 anti-Semitism, 90 anxiety, 8, 11, 15, 23, 28, 270, 298, 304 application, 70, 113, 150, 152, 153, 155, 162 applied research, 264 appraisals, 71 Arabs, 100 argument, 99, 102, 103, 108, 199, 235, 236 Arkansas, 51, 74, 310 Armed Forces, 239 armed robbery, 273 arousal, 5, 19, 30, 61, 66, 69, 72, 217 articulation, 161 artificial, 159 Asia, 205 Asian, 70, 82, 84, 100, 101, 105, 106, 117, 119, 126, 180, 185, 236, 237, 256 Asian American(s), 82, 84, 119, 126, 236, 237, 256 assault, 53, 273, 275, 276, 281 assessment, 23, 73, 79, 93, 94, 95, 97, 99, 100, 102, 103, 113, 114, 115, 123, 155, 162, 196, 198, 200, 206, 209, 211, 212, 215, 222, 270, 304, 309, 311 assets, 9 assignment, 31, 82, 98, 199 assimilation, 150, 278 associations, 30, 31, 32, 36, 46, 47, 49, 50, 65, 70, 77, 78, 79, 81, 84, 98, 105, 113, 116, 118, 119, 120, 124, 126, 145, 147, 149, 200, 210, 211, 218, 219, 220, 222, 283, 288, 297 assumptions, 89, 91, 96, 116, 221, 293 asymmetry, 22, 102, 118, 219 athletes, 236 Atlantic, 309 atrocities, 14 attachment, 181, 257 attacks, 11, 281 attention, viii, 2, 9, 23, 52, 53, 65, 71, 85, 94, 108, 161, 166, 178, 196, 199, 216, 221, 244, 249, 272, 291, 299, 311
attitude measurement, 28 attractiveness, 132, 150 attribution, 10, 50, 64, 68, 72, 74, 154, 162, 178, 194, 269, 271 atypical, 169, 193 audio, 106 auditory modality, 157 Australia, 205 authoritarianism, 2, 3, 5, 6, 7, 8, 19, 20, 21, 24, 25, 43, 204, 239, 253, 254, 259, 267 authority, 7, 19, 59 automatic stereotype activation, 48 automaticity, 47, 145, 160, 301, 310 availability, 154, 167 average earnings, 282 averaging, 214 aversion, 211, 230 avoidance, 73, 211 avoidant, 211 awareness, 14, 30, 45, 46, 49, 150, 189, 193, 206, 232, 285, 310 axis of evil, 74
B babies, 55 backfire, 9 backlash, 65, 222 barriers, 162, 280, 298 basic needs, 14, 15, 278 basic research, 46 basketball, 174 battery, 53 beaches, 143 beating, 52, 70 behavior, 10, 12, 13, 14, 17, 23, 42, 59, 65, 73, 78, 79, 81, 88, 89, 91, 98, 119, 124, 145, 168, 205, 207, 218, 219, 220, 222, 234, 252, 253, 254, 261, 262, 263, 273, 275, 311 behavioral intentions, 309 behavioral manifestations, 81, 117 behavioral sciences, 144, 191 behavioral theory, 211 behaviours, 216, 220, 281, 284, 298, 310 belief systems, 34, 95 beliefs, 6, 9, 14, 15, 25, 27, 28, 29, 31, 32, 41, 55, 57, 61, 71, 77, 79, 88, 95, 103, 115, 118, 124, 145, 147, 156, 179, 190, 196, 198, 203, 207, 211, 217, 218, 220, 221, 226, 227, 229, 231, 232, 253, 258, 262, 263, 265, 267, 269, 270, 271, 275, 276, 279, 281, 282, 283, 284, 285, 286, 297, 298, 310 benchmark, 115 beneficial effect, 264
Index benefits, 12, 17, 167, 179, 194 bias, 2, 7, 9, 10, 12, 13, 14, 19, 20, 21, 39, 42, 43, 44, 47, 48, 49, 50, 53, 54, 57, 59, 62, 69, 71, 89, 91, 92, 97, 98, 99, 101, 103, 104, 105, 108, 111, 112, 116, 117, 121, 143, 145, 148, 161, 189, 199, 202, 203, 204, 205, 206, 207, 208, 211, 214, 215, 216, 220, 221, 223, 294, 296, 297, 298, 308 bilingual, 265 biodiversity, 119 biological, 77, 94, 150, 162, 272 biology, 121 bipolar, 215 birth control, 167 black, 72, 82, 91, 97, 102, 117, 120, 136, 137, 138, 141, 205, 230, 255 black adolescents, 65 Blacks, 2, 6, 12, 14, 24, 36, 37, 38, 41, 43, 55, 68, 69, 78, 80, 82, 88, 100, 101, 108, 112, 122, 126 blame, 62, 63, 261, 263, 271, 273, 275 blaming, 63, 96, 265 blocks, 82, 85, 126, 127, 128, 129, 132, 133, 135, 136, 137, 138, 140, 141, 142, 212, 213, 214 body image, 307 body shape, 149 bonding, 163 bonds, 45 bonus, 187, 191 boredom, 280 Boston, 116, 252 boys, 275 brain, 21, 98 branching, 100 breakdown, 180 Britain, 22, 223 British, 21, 22, 24, 163, 218, 219, 255, 256, 276, 279, 302, 310 British Columbia, 256, 279 brutality, 14 Buddhist, 237 buffer, 270 buildings, 278 business, 53, 149, 307
C California, 52, 53, 93, 165, 173, 174, 193, 194, 253, 255, 308, 311 Canada, viii, 1, 11, 20, 36, 47, 205, 217, 259, 276, 277, 278, 280, 281, 282, 283, 291, 293, 294, 297, 299, 300, 301, 302, 303, 304, 305, 307, 308, 309 capacity, 155, 156, 227 capital, 161 capitalism, 193, 257
315
cardiac output, 69 cardiovascular, 69 case study, 301 categorization, 3, 10, 13, 25, 98, 136, 143, 147, 148, 149, 151, 152, 153, 156, 158, 161 categorization theory, 3, 25 category a, 153, 155, 157, 159 Catholic, 237, 240, 278 Catholic Church, 278 Caucasian(s), 52, 79, 82, 84, 95, 173, 180, 185, 190, 237, 284, 294, 298 causal attribution, 227 causal relationship, 227 CBS, 239, 252 Census Bureau, 101, 121, 166, 194 certainty, 103, 152, 153, 155, 156, 158 chaos, 25 Chicago, 72, 75, 119, 174, 221, 253, 255, 259 child abuse, 280, 311 child welfare, 311 childhood, 167, 280 childless, 191 children, 96, 97, 98, 102, 103, 104, 105, 107, 111, 112, 114, 116, 117, 119, 122, 166, 168, 169, 170, 174, 197, 201, 229, 239, 250, 272, 278, 280, 299, 300, 308, 311 Chinese, 38, 253 Christianity, 278 Christmas, 187 chronic, 8, 48, 285 chronic pain, 285 circadian, 19 citizens, 52, 64, 274 civil rights, 2, 52, 53, 78, 220, 232, 233, 235, 253, 258 classes, 104, 293, 300 classification, 238 classified, 2, 96, 152, 173, 238 classroom, 286 clients, 280, 301 climate change, 2 clinical, 5, 6, 160, 219 clinical approach, 5 clinical judgment, 160 close relationships, 167, 184 closure, 25, 258 clothing, 278 clusters, 229, 233 coding, 36, 98, 181 coercion, 226, 265 coffee, 272 cognition, 21, 22, 47, 48, 49, 73, 88, 90, 118, 144, 162, 192, 199, 209, 211, 218, 219, 220, 221, 310
316
Index
cognitive, 2, 4, 6, 9, 10, 16, 19, 20, 21, 27, 28, 30, 31, 32, 33, 42, 43, 44, 45, 47, 48, 49, 54, 59, 68, 72, 78, 90, 94, 99, 117, 119, 121, 126, 144, 145, 148, 153, 155, 156, 159, 161, 200, 201, 208, 210, 230, 231, 253, 269, 301, 304, 309, 310 cognitive capacity, 148, 153, 155, 156 cognitive development, 117, 301 cognitive dimension, 304 cognitive dissonance, 33, 42, 47, 59, 72, 310 cognitive dissonance theory, 310 cognitive load, 68 cognitive process, 2, 10, 54 cognitive processing, 10 cognitive psychology, 309 cognitive style, 6, 20 cognitive tool, 4, 19 cognitive variables, 208 coherence, 95 cohesion, 295 cohort, 269, 275 College Station, 258 college students, viii, 57, 61, 66, 132, 162, 165, 171, 172, 173, 174, 175, 176, 178, 180, 183, 186, 188, 199, 254, 302 colleges, 225, 237, 240 colonial, 277 colonialism, 277 colonization, 278 colors, 136 Columbia University, 252 combat, 86 commercialization, 193 communication, 150, 280, 298 communities, 194, 228, 278, 281, 283, 299 community, 62, 64, 165, 173, 180, 183, 190, 229, 232, 275, 278, 281, 299, 303, 311 community-based, 278 Comparative Fit Index, 140 compensation, 278, 303 competence, 70, 149, 150, 152, 155, 158, 160, 161, 162, 187, 302 competition, 9, 10, 13, 16, 20, 21, 72, 116, 302, 308 competitiveness, 20 complement, 284 complementary, 88, 99, 108, 166 complexity, vii, 17, 159, 215 compliance, 48, 71 components, 12, 27, 28, 30, 32, 33, 34, 35, 37, 38, 40, 41, 42, 45, 46, 47, 78, 79, 117, 160, 222, 226, 231, 233, 284, 298 composite, 169, 234 composition, 23, 166, 240 computation, 252, 268
computer(s), vii, 61, 66, 80, 82, 84, 96, 109, 123, 124, 125, 126, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 142, 143, 144, 174, 255 computer software, 255 computer technology, 109 computing, 82 concentration, 307 conception, 170 conceptualization, 27, 45, 172, 212, 230, 231, 233, 265, 299 conceptualizations, 29, 196 concrete, 79 conditioning, 120 condom, 222 conductance, 62, 206 confidence, 241 confidence intervals, 241 configuration, 100, 103 confirmatory factor analysis, 258 conflict, 3, 7, 11, 13, 15, 21, 23, 24, 25, 29, 41, 49, 51, 56, 57, 59, 61, 62, 63, 64, 65, 67, 68, 69, 74, 78, 90, 117, 119, 227, 230, 232, 255, 280, 310 conflict resolution, 117, 310 conformity, 116 Connecticut, 253 conscientiousness, 239 conscious awareness, 78, 79, 185 consciousness, 22, 191, 255 consensus, 215 consent, 233, 234, 258, 286 Constitution, 52, 53 constitutional, 53 constraints, 12, 18, 170 construct validity, 7, 145, 220, 221, 230, 238, 256 construction, viii, 104, 113, 114, 118, 228, 230, 256, 297 continuing, 73, 79, 247, 262 control, vii, 12, 15, 30, 42, 47, 48, 51, 59, 65, 77, 79, 84, 85, 86, 87, 88, 89, 95, 97, 115, 117, 152, 153, 156, 157, 158, 159, 169, 185, 195, 200, 201, 202, 205, 206, 207, 208, 212, 216, 218, 219, 221, 263, 302, 310 control condition, 157, 158, 169, 200 control group, 59, 152 controlled, 47, 67, 89, 117, 148, 153, 155, 160, 187, 204, 309 conventionalism, 7 conversion, 128, 139, 278 cooking, 174 correlation, 21, 24, 30, 48, 58, 83, 86, 102, 127, 129, 130, 131, 134, 136, 139, 140, 141, 174, 201, 204, 267, 269, 270, 273, 288, 293, 295, 296 correlation coefficient, 267, 288, 295
Index correlations, 35, 80, 82, 83, 84, 86, 99, 129, 134, 135, 136, 139, 140, 141, 142, 143, 201, 203, 204, 214, 216, 241, 265, 266, 267, 269, 293, 295, 296 corruption, 198 costs, 12 counterfeiting, 202 couples, 167, 168, 183, 186, 188, 200, 205, 210, 239, 309 coupling, 167, 178, 194 courts, 83 credentials, 236, 256 credit, 131, 137, 284 crime, 52, 53, 70, 120, 235, 262, 272, 274, 279 criminal activity, 279 criminal justice, 303 criminal sentencing, 160 criticism, 17, 45 cross-cultural, 147, 160, 190, 253, 257, 274, 311 cross-sectional, 179 cues, 8, 56, 57, 71, 74, 119, 126, 147, 149, 150, 151, 152, 153, 155, 156, 157, 158, 159, 170 cultural, 2, 3, 4, 7, 11, 12, 14, 15, 17, 19, 21, 24, 44, 81, 166, 168, 180, 190, 191, 193, 227, 229, 230, 236, 255, 258, 262, 277, 278, 281, 284, 285, 286, 287, 289, 290, 293, 297, 298, 300, 301, 305, 307 cultural beliefs, 227 cultural character, 289 cultural differences, 258, 293 cultural factors, 7, 17 cultural norms, 2, 14, 190 cultural perspective, 301 cultural practices, 278 cultural stereotypes, 44, 284, 285, 287, 289, 290, 297, 298 cultural values, 24 culture, 21, 81, 118, 190, 202, 216, 232, 277, 282, 289, 297, 298, 300 curable, 161 cynicism, 5
D danger, 7 data analysis, 204 data collection, 58, 63, 83, 86, 98, 123, 124, 134, 143, 144, 171, 214 data set, 127, 128, 129, 130, 131, 133, 135, 141, 143, 214 dating, 69, 75, 168, 171, 172, 178, 183, 273 death, 6, 15, 72, 161 death penalty, 72 debt, 255 deception, 210, 211
317
decision making, 73, 88, 160 decisions, 12, 18, 20, 22, 47, 49, 74, 84, 90, 98, 149, 152, 188, 271 decoding, 89, 116, 217 defendants, 52, 53, 161, 279 defense, 5, 221 defense mechanisms, 5 defensiveness, 63 definition, 30, 31, 58, 117, 199, 262 degree, 55, 59, 67, 78, 99, 140, 151, 152, 153, 155, 156, 158, 159, 171, 173, 176, 178, 180, 183, 184, 185, 189, 190, 226, 289, 297, 299, 308, 311 degrees of freedom, 175 deindividuation, 14, 23, 25 delays, 2, 169 delusion, 275 demand, 200 democracy, 15 demographic, 53, 58, 63, 66, 82, 84, 132, 166, 167, 196, 204, 205 demographic change, 166, 167 demographic characteristics, 82, 84 demographic data, 53 demographics, 270 demography, 166 denial, 29, 45, 221, 262, 264 dependent variable, 53, 59, 82, 124, 125, 126, 172, 181, 183, 240 depressed, 219 depression, 282, 285, 302 depressive symptoms, 305 deprivation, 281 desensitization, 24 desert, 6 desire, 23, 28, 31, 55, 59, 62, 63, 65, 67, 68, 71, 79, 85, 86, 167, 182, 190, 191, 226, 247 destruction, 5, 221, 265, 273, 277 detection, 88, 310 devaluation, 156 developmental milestones, 169 deviation, 132, 214 diabetes, 282 diagnostic, 2, 8, 155 dichotomy, 212 diet, 44 differential treatment, 187, 189, 190 differentiation, 98, 229 direct measure, 30, 35, 149, 211, 217 directionality, 128, 129 disability, 309 disabled, 70 disaster, 28, 82, 311 discipline, 280, 282
318
Index
disclosure, 202, 207, 216, 222 discomfort, 28, 59, 61, 72, 211, 254 discourse, 230, 252 discriminatory, 19, 33, 43, 91, 119, 188, 207, 208, 220, 233, 234, 261, 262, 310 disorder, 228 displacement, 2 dissatisfaction, 179 dissociation, 43, 44 distal, 4, 89 distribution, 264 divergence, 80, 195, 208, 215 diversity, 117, 119, 160, 161, 255 divorce, 166, 167, 179 DNA, 4, 12 DNA testing, 4 doctors, 168 domestic violence, 280, 282, 303 dominance, 3, 6, 7, 8, 9, 11, 16, 20, 21, 23, 24, 25, 43, 49, 67, 96, 115, 120, 121, 149, 225, 226, 227, 228, 231, 232, 233, 235, 236, 237, 238, 239, 240, 241, 243, 244, 245, 246, 247, 248, 253, 254, 255, 257, 258, 259, 267 doors, 132 double jeopardy, 52, 53, 54, 55, 56, 57, 58, 59, 62, 68, 70 dropouts, 280 drugs, 282, 300 duality, 275 duties, 278 dysfunctional, 5, 6, 13, 16, 218
E ears, 12 East Asia, 253 economic, 4, 13, 14, 15, 21, 22, 28, 90, 186, 190, 225, 255, 265 economic crisis, 14 economic development, 15, 28 economic security, 190 economic status, 265 education, 63, 82, 85, 90, 170, 194, 197, 222, 256, 258, 270, 278, 279, 280, 283, 302, 304, 310 efficacy, 127, 135 egalitarian, 7, 12, 29, 30, 41, 56, 63, 67, 86, 103, 148, 195, 199, 207, 208, 227, 232, 262 egalitarianism, 13, 16, 27, 28, 29, 30, 32, 41, 63, 230, 232, 257 ego, 5, 7 eigenvalue, 295 elderly, 73, 188 election, 15, 257
electromyography, 61, 98 elementary school, 151 elephant, 217 emotion regulation, 48 emotional, 19, 69, 167, 168, 174, 230, 236, 309 emotional disorder, 19 emotional intelligence, 309 emotional responses, 69 emotional state, 236 emotion(s), 6, 9, 24, 31, 47, 48, 49, 50, 61, 70, 256, 309 empathy, 9, 126, 145 employers, 187 employment, 9, 82, 152, 153, 191, 194, 283 encoding, 91 enculturation, 305 endogenous, 18, 19 endorsements, 78, 202, 287 energy, 13 engagement, 234 England, 187, 191, 275 English, 131, 132, 137, 264, 265, 266, 267, 268, 272, 275, 279, 280 enhancement, 221 enlightenment, 167 enthusiasm, 165 envelope, 152 environment, 151, 280 environmental, 8, 265, 273 environmental factors, 8 epidemiological, 305 equality, 12, 13, 28, 63, 68, 167, 232, 233, 255, 259, 263 equity, 235 erosion, 277 estrangement, 281 ethical, 294 ethnic groups, 70, 73 ethnic minority, 7 ethnicity, 82, 117, 185, 205, 303 ethnocentrism, 5, 17, 20, 255, 256 etiology, 230 Euro, 283, 302 Europe, 17, 205 European, 20, 21, 22, 23, 48, 100, 101, 120, 131, 137, 145, 161, 162, 218, 219, 221, 254, 255, 257, 274, 275, 277, 302, 307, 308, 309, 311 European Americans, 255 evaluative conditioning, 45, 49 evening, 10 evidence, vii, viii, 1, 7, 12, 13, 14, 17, 22, 28, 41, 44, 51, 52, 59, 63, 65, 68, 70, 72, 80, 88, 95, 101, 104, 121, 126, 144, 148, 152, 155, 158, 165, 166,
Index 177, 179, 183, 184, 185, 189, 190, 193, 198, 201, 209, 211, 214, 215, 216, 217, 220, 235, 236, 238, 247, 255, 267, 269, 271, 275, 279, 293, 294, 297, 298, 299 evil, 22, 24, 125 evolution, 16, 117, 191, 194 evolutionary, 7, 170, 178, 190, 308 examinations, 234 exclusion, 17, 194 excuse, 57, 62, 63, 64, 67, 69 executive function, 99, 120 exercise, 44, 298 existential fear, 15 exogenous, 18, 19 experimental condition, 169, 205 experimental design, 271 exposure, 15, 49, 79, 126, 255 extraction, 265 extroversion, 239 eye(s), 44, 149, 159, 207 eye contact, 44, 207
F face recognition, 116 factor analysis, 223, 229, 265, 295 factorial, 295 failure, 14, 111, 131, 238 fairness, 57, 150 false, 22, 31, 149, 255, 262 family, 28, 63, 167, 168, 169, 180, 184, 187, 190, 191, 192, 194 fat, 39, 47, 126, 143, 145, 285, 286, 288, 292 fatigue, 115 FDA, 118 fear(s), 69, 197, 208, 209, 220, 222, 273, 302 federal government, 53, 278 feedback, 16, 264, 270, 280 feelings, 5, 13, 33, 35, 51, 55, 56, 57, 59, 61, 62, 63, 64, 65, 68, 69, 70, 71, 81, 102, 103, 169, 179, 182, 217, 281, 310, 311 females, 86, 151, 158, 200, 201, 203, 204, 205, 207, 241, 248, 269, 284, 302 femininity, 149, 151, 152, 157, 158, 162 fertility, 170 Fidel Castro, 9 film, 200 fines, 279 first dimension, 4 first language, 280 First Nations, 301, 302, 304 flexibility, 18, 19, 117 flow, 198
319
fluid, 169 fMRI, 98 focusing, 5, 9, 10, 16, 42, 45, 51, 96, 100, 196, 284 football, 52 forensic, 308 forensic psychology, 308 fragment completion, 79 framing, 252, 254 freedom, 19, 182 Freud, 56 friendship, 194 frustration, 13, 179 frustration-aggression hypothesis, 13 fulfillment, 81, 84, 166, 168, 173, 180, 190 fundamental attribution error, 68 funding, 278
G Gallup Poll, 197 galvanic skin response, 61, 69 gay marriage, 172 gay men, viii, 7, 8, 13, 23, 68, 70, 78, 91, 100, 108, 118, 194, 195, 196, 197, 198, 200, 201, 202, 203, 204, 206, 207, 209, 210, 212, 214, 216, 219, 220, 221, 222, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 238, 239, 244, 247, 248, 249, 253, 254, 255, 256, 258, 259, 283, 285, 286, 294, 297, 302, 303 gender, vii, 52, 65, 67, 85, 86, 108, 115, 118, 132, 137, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 168, 169, 172, 178, 179, 184, 185, 201, 202, 203, 204, 205, 207, 218, 219, 222, 239, 240, 248, 253, 254, 255, 257, 259, 261, 262, 266, 269, 270, 271, 273, 274, 302, 308, 309, 311 gender differences, 86, 118, 219, 254, 302, 309 gender equality, 85 gender identity, 207 gender inequality, 263 gender role, 153, 202, 207, 239, 269, 273 gender stereotyping, 147, 148, 149, 152, 153, 154, 155, 156, 158 gene, 98 generalizability, 5, 39, 248 generalizations, 98 generation, 311 genetic, 126 genocide, 4, 14, 15, 17, 24 Germany, 14, 83, 148, 162, 165, 184, 190, 203, 222, 261, 274, 275, 276, 308, 309, 311 gestures, 272 girls, 106, 107, 275
320
Index
glass, 161, 168 goals, vii, 7, 8, 10, 11, 27, 28, 29, 30, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 121, 181 God, 238 goodness of fit, 265 government, 53, 58, 197, 222, 278, 293, 300 grades, 152, 155 grain, 186 grants, 195 graph, 215 grass, 180 Great Britain, 234 grief, 304 group identification, 14 group interactions, 13 group membership, 10, 33, 35, 51, 63, 113, 119, 186, 190 group processes, 275, 310 groups, vii, 5, 8, 9, 10, 11, 12, 13, 14, 15, 19, 21, 27, 28, 29, 32, 33, 35, 41, 45, 46, 49, 51, 59, 63, 64, 66, 68, 70, 94, 95, 98, 101, 102, 104, 105, 107, 108, 109, 113, 114, 115, 143, 148, 149, 153, 159, 165, 180, 185, 186, 189, 190, 196, 200, 201, 202, 203, 204, 205, 210, 212, 214, 215, 216, 225, 226, 229, 239, 244, 247, 248, 262, 265, 269, 273, 283, 284, 285, 286, 287, 289, 293, 296, 298, 304, 308 growth, 45, 283 guidelines, 133, 140, 265 guilt, 69, 70, 279, 303 guilty, 12, 52, 70, 271, 279 gut, 210
H happiness, 167, 168, 179, 186, 193 harassment, 14, 273, 276, 281 harbour, 29 harm, 233 harmful, 196, 235, 279, 281 harmony, 233 Harvard, 19, 46, 91, 308, 310 hate, 14, 21, 117, 232, 235, 253 hate crime, 14, 21, 235, 253 head, 161 health, 9, 58, 179, 186, 278, 279, 280, 282, 283, 301, 304, 305 health care, 9, 58, 279, 280, 301 health care professionals, 281 health care system, 279 hearing, 281 heart, 61, 69, 98, 206, 282 heart disease, 282
heart rate, 61, 69, 206 hegemony, 118 height, 149, 186 helix, 117 helping behavior, 219 heterogeneity, 100, 119 heterogeneous, 184 heterosexuality, 201, 228, 229, 231, 234 heterosexuals, 118, 168, 194, 195, 200, 201, 203, 207, 214, 216, 219, 220, 232, 233, 247, 254, 256, 259 high school, 173, 253, 280 high scores, 36 hip, 159, 190, 244 hiring, 12, 49, 152 Hispanic(s), 82, 84, 100, 101, 105, 106, 117, 121, 122, 133, 194, 237 Hispanic origin, 194 historical trends, 1, 16, 191 HIV, 233, 282, 304 holistic, 94, 115 homeless, 70 homelessness, 311 homes, 50, 167, 279, 281 homogeneity, 100, 119, 120 homosexuality, 5, 25, 108, 194, 196, 197, 198, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 216, 217, 220, 222, 223, 229, 234, 235, 238, 248, 254, 256, 259, 294 homosexuals, 66, 67, 196, 217, 220, 238, 254, 257, 258 hopelessness, 282 hospital, 301 hospital care, 301 host, 293 hostile environment, 281 hostility, 2, 5, 6, 10, 12, 15, 63, 206, 267, 269 household(s), 166, 196 housing, 188, 189, 304 human(s), 6, 9, 11, 14, 15, 16, 25, 45, 49, 51, 54, 68, 74, 94, 117, 118, 119, 121, 130, 136, 143, 150, 159, 161, 191, 211, 214, 219, 253, 287, 308 human cognition, 211 human condition, 51 human motivation, 191 human rights, 253 human values, 74 Hurricane Katrina, 4 husband, 272 hybrid, 96 hygiene, 293, 300 hypersensitive, 63 hypertension, 282
Index hypocrisy, 50, 75 hypothesis, 51, 57, 64, 176, 184, 193, 236, 293
I identification, 13, 22, 117, 122, 215, 218 identity, 9, 13, 14, 16, 19, 20, 21, 24, 25, 45, 48, 107, 117, 126, 141, 143, 168, 202, 222, 228, 252, 255, 310 ideology, 4, 6, 7, 8, 14, 20, 71, 72, 94, 101, 167, 168, 169, 171, 180, 184, 190, 192, 222, 238, 239, 247, 253, 255, 267, 275, 308 illegal drugs, 64, 70 Illinois, 77, 174, 265, 266, 268, 276, 308, 309 illusions, 255 illusory correlation, 10 images, 117, 202, 204, 205, 210, 211, 218, 304 imaging, 98 immersion, 202, 216 immigrants, 11, 20 immigration, 11, 20, 304 implicit association test, 73, 116, 118, 119, 120, 121, 192 implicit relational assessment procedure (IRAP), viii, 211, 212, 213, 214, 215, 216, 217, 218, 221, 308 impulsive, 50 in situ, 56, 216 in transition, 193 inadmissible, 22 inclusion, 22, 100, 110, 283 income, 173, 188, 238 incompatibility, 10, 13 incongruity, 149, 153 increased access, 157 incurable, 161 incus, 279 independence, 37, 38, 43, 170, 175, 181, 185 Indian(s), 278, 280, 282, 301, 302, 303, 311 Indian Ocean, 311 Indiana, 221, 222 indication, 55, 231, 283 indices, 22, 69, 265, 288, 299 indigenous, 278 indirect effect, 258 indirect measure, 30, 35, 38, 41, 47, 89, 120, 149, 199, 209, 211, 269 individual differences, 2, 5, 6, 7, 8, 12, 16, 17, 22, 44, 48, 73, 90, 118, 126, 127, 144, 192, 205, 219, 275, 308, 309, 310 individualism, 56 industrial, 308, 309 inequality, 11, 22, 24, 55, 96, 117, 226, 227, 239, 255, 256, 262, 263
321
inequity, 72, 299 inferences, 31, 50, 150, 151, 170 inferiority, 29, 293 infinite, 128 inflammatory, 230 inflation, 233 Information Age, 162 information processing, 147, 148, 153, 155, 159, 270, 275, 309 informed consent, 173 ingroup bias, 120 inhibition, 91, 160 injury, 212 injustice, 262, 281 inmates, 9 innovation, 309, 310 insects, 124, 127, 199 insecurity, 5, 6, 7, 182 insight, 123, 158, 248, 280 inspection, 241 inspiration, 108 in-state, 66 institutions, 226, 250, 278, 279, 293, 301 instruments, viii, 95, 102, 115, 198, 235, 247, 296, 299, 304 intangible, 13 integration, 17, 19, 29, 45, 78, 90, 230, 301 intellectual disabilities, 78, 89 intelligence, 2, 8, 227, 272 intelligence scores, 8 intelligence tests, 2, 227 intensity, 99, 114 intentions, 47, 67, 301 interaction, 17, 18, 27, 38, 44, 59, 67, 69, 81, 89, 99, 120, 179, 184, 201, 207, 248, 262, 298, 309 interaction effect, 201, 248 interactions, 11, 37, 38, 40, 61, 70, 71, 96, 98, 116, 120, 121, 152 interdependence, 302 interdisciplinary, 145 interface, 8, 257, 310 intergenerational, 278 internal consistency, 230, 304 internalization, 55 internet, 178, 194, 265, 266, 267, 274, 310 interpersonal contact, 220, 239, 291 interpretation, 15, 19, 44, 69, 99, 101, 102, 103, 104, 107, 117, 118, 161, 219, 269, 279 interval, 2, 130, 239 intervention, 264, 298, 301 interview(s), 64, 152, 160, 199, 293 intimacy, 167, 192 intonation, vii
322
Index
Iraq, 15, 66 Ireland, 195, 198, 277, 307, 308 Islamic, 237 isolation, 7, 278 Israel, 223
J Japanese, 253 Jews, 5, 14, 78, 95, 100, 122 jobs, 36, 150, 197 judge(s), 12, 52, 65, 151, 154, 279, 280 judgment, 31, 32, 33, 35, 68, 102, 116, 143, 150, 153, 155, 158, 160, 162 judgmental heuristics, 19 jurisdiction, 53 juror(s), 72, 84, 85, 279, 303 jury, 52, 88, 279 justice, 50, 255, 276, 279, 302, 308 justification, 3, 11, 22, 24, 41, 43, 47, 56, 70, 72, 192, 193, 220, 227, 234, 255, 271 juvenile justice, 73
K Kentucky, 253 killing, 25 kindergarten, 118
L labour, 278 lack of control, 148, 159 land, 283 language, 52, 79, 114, 211, 219, 230, 265, 280, 311 large-scale, 253 latency, 82, 85, 99, 109, 124, 126, 128, 133, 135, 139, 140, 142, 145, 212, 214 Latin America, 160 Latino(s), 101, 173, 180 law(s), 28, 52, 71, 187, 194, 229, 233, 239, 302 lawyers, 276, 279 lead, 8, 15, 32, 36, 57, 63, 64, 67, 68, 70, 71, 115, 156, 157, 158, 160, 196, 236, 272, 280, 300 leadership, 149, 150, 152, 153, 154, 155, 158, 162, 308 leadership abilities, 162 leadership characteristics, 149 learning, 98 lens, 194, 285 lesbian, 198, 201, 203, 204, 219, 221, 233, 234, 235, 239, 242, 253, 254, 259, 286, 292
lexical decision, 98 LGB, 232, 259 liberal, 12, 29, 52, 53, 57, 58, 63, 66, 81, 195, 197, 198, 205, 216, 238, 240, 269 liberalism, 52, 58, 70 liberalization, 198, 217, 220 life course, 168, 169 life cycle, 169, 193 life expectancy, 168 life span, 252, 283 lifestyle, 198, 249, 300 likelihood, 28, 187, 188, 236, 238, 240, 252, 265, 267, 270, 274 Likert scale, 238, 239, 264 limitation, 69, 209, 210, 211, 233, 247, 248, 293, 297, 299 limitations, 5, 15, 58, 69, 88, 197, 209, 218, 232, 247, 248 Lincoln, 25 linear, 4 linguistic, 92, 270 linkage, 283 links, 57, 58, 68 listening, 157 literacy, 105, 107 literature, viii, 1, 2, 4, 5, 6, 9, 11, 16, 18, 56, 80, 81, 94, 97, 100, 102, 109, 111, 114, 151, 165, 196, 215, 225, 226, 227, 231, 232, 233, 234, 235, 248, 262, 283, 284, 285 location, 4, 18, 125, 228, 282, 284, 297 locus, 104 London, 24, 47, 48, 192, 223, 276 loneliness, 182 longitudinal study, 117, 186 long-term, 167 Los Angeles, 52, 72, 253 love, 117, 125, 167, 168, 191, 192, 197 low back pain, 303
M magazines, 168 magnetic resonance imaging, 161 Maine, 173 mainstream, 190, 280, 301 mainstream society, 190, 280 maintenance, 11, 20, 29, 42, 91, 162, 226, 244, 248, 249, 263 maladaptive, 13, 15 maladaptive beliefs, 15 males, 86, 95, 151, 158, 200, 201, 203, 204, 205, 207, 210, 236, 237, 241, 248, 253, 270, 275, 276, 284, 302, 303
Index malnutrition, 282 management, 2, 152, 162, 204, 267, 302 manipulation, 15, 157, 200, 206 marginalization, 198 marital conflict, 179 marital status, 168, 171, 172, 173, 178, 184, 186, 187, 188, 189, 191, 192, 193, 194 market, 257 Marlowe-Crowne Social Desirability Scale, 222, 294, 303 marriage, 166, 167, 168, 169, 170, 171, 172, 177, 178, 179, 180, 182, 183, 184, 186, 187, 190, 191, 192, 194, 233, 252, 253 marriages, 167, 179, 190 married couples, 166, 167, 188 married women, 178, 179 Maryland, 310, 311 masculinity, 149, 162, 229 mask, 12, 127 masking, 39 mass media, 28 material resources, 225 mathematical, 127 matrix, 295 measurement, vii, viii, 49, 95, 109, 116, 122, 142, 148, 160, 201, 210, 220, 233, 255, 276, 277, 285, 296, 304 media, 15, 51, 81, 239, 249, 272, 279, 302 median, 134, 173, 180, 187 mediation, 18, 20, 25, 233, 240, 243, 244, 247, 248, 256, 258 mediational analyses, 24 mediators, 18, 70, 88, 244 membership, 94, 113, 148, 158 memory, 79, 199, 200, 309, 310 mental capacity, 145 mental disorder, 309 mental health, 22, 160, 193, 281, 304 mental illness, 7 mental processes, 30, 145 meritocratic, 227 messages, 28, 180 meta-analysis, 7, 11, 13, 23, 30, 48, 220, 270 methodological procedures, 96 metric, 251 middle class, 64, 65, 237 middle-aged, 193, 205 militant, 229, 230, 233 military, 58, 74, 234, 259 military spending, 58 minorities, viii, 7, 12, 51, 55, 56, 57, 59, 63, 64, 65, 67, 68, 71, 96, 121, 302
323
minority, 6, 9, 10, 12, 29, 53, 62, 64, 71, 85, 166, 236, 279, 280, 281, 298 minority groups, 10, 12, 29, 71, 279 mirror, 56, 232, 235 MIT, 22, 118, 145, 220 modalities, 157 modality, 157, 203, 208 model fitting, 140 model minority, 236 modeling, 240 models, 16, 17, 18, 56, 140, 148, 151, 158, 193, 244, 248, 310 moderates, 18, 51, 54, 57, 58, 59, 61, 65, 66, 68, 71, 230 moderators, 18, 88, 169, 183 Modern Racism Scale (MRS), 58, 78, 84 modern society, 170, 262 momentum, 298 money, 9, 187, 188, 208 monograph, 261 mood, 90, 163, 285, 301, 304 mood disorder, 301 morality, 21, 81, 197, 310 morning, 10 mortality, 2, 15, 21, 22, 24 motherhood, 191 mothers, 187 motivation, 25, 42, 47, 49, 63, 65, 74, 77, 80, 84, 85, 86, 87, 88, 89, 91, 97, 115, 117, 120, 145, 161, 163, 200, 201, 202, 205, 206, 207, 208, 216, 218, 219, 220, 221, 294, 302, 303 motives, 11, 12, 13, 161 movement, 2, 230, 233 multicultural, 85, 159, 247, 311 multicultural education, 311 multidimensional, viii, 2, 93, 94, 107, 108, 112, 114, 209, 217, 247, 255, 258, 280, 284 multidimensional scaling, 114 Multi-response Racial Attitude Measure (MRA), 97, 102 multivariate, 114, 240 murder, 199
N nation, 117, 166 national, 9, 11, 20, 22, 90, 106, 186, 196, 197, 220, 257, 283, 303 national identity, 9, 20 National Institutes of Health, 144 National Science Foundation, 93, 144 nationalism, 227 nationality, 205
324
Index
Native Americans, 237, 299 natural, 10, 13, 28, 121, 217, 229, 236, 265 Nazi Germany, 14, 15, 17 Nebraska, 25 Need to Evaluate, 44 negative attitudes, 7, 43, 58, 64, 67, 112, 114, 190, 196, 197, 202, 211, 218, 229, 261, 283, 285, 299, 303 negative consequences, 187 negative emotions, 27 negative experiences, 281 negative outcomes, 11 negative relation, 37, 41, 159, 244 negative valence, 30, 205, 210, 282 negativity, viii, 28, 29, 30, 32, 41, 43, 45, 78, 79, 80, 93, 97, 104, 109, 110, 111, 113, 124, 171, 214, 216, 284, 308 neglect, 299, 311 neighbourhoods, 282 Netherlands, 148, 258, 310 network, 184, 193, 194, 299 neurotic, 184, 185 neuroticism, 239 neutral stimulus, 210 New York, 14, 19, 20, 21, 22, 23, 24, 47, 49, 50, 71, 72, 73, 74, 90, 91, 116, 117, 119, 122, 144, 145, 146, 160, 161, 191, 192, 193, 194, 219, 220, 221, 222, 223, 239, 252, 253, 254, 255, 256, 257, 259, 273, 274, 275, 276, 304, 308 New York Times, 239, 252, 308 New Zealand, 255, 257 newspapers, 308 noise, 140, 249 nonconscious, 55 non-institutionalized, 197 Non-Normed Fit Index, 140 non-random, 8 normal, vii, 2, 4, 6, 7, 9, 10, 13, 14, 16, 17, 19, 54, 212, 267, 273 normal conditions, 16 normal distribution, 267 normative behavior, 14, 23 norms, 14, 52, 57, 148, 150, 157, 158, 168, 169, 193, 202, 222, 228, 254, 274 North America, 29, 74, 90, 168, 277, 282 North Carolina, 174 Notre Dame, 311 nurses, 280, 301
O obedience, 7, 192 obese, 126, 145, 188, 189
obesity, 49, 126, 168, 169, 189 obligations, 187, 294 observations, 28, 52, 53, 127 occupational, 236 offenders, 159, 282, 305 old age, 193 old-fashioned, viii, 27, 28, 29, 30, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 45, 46, 55, 77, 78, 79, 96, 97, 197, 198, 229, 230, 263, 264, 267, 269, 284, 293, 294, 295, 296, 299, 303 olfactory, 149, 152, 153, 155, 156, 158 omission, 57, 283 omnibus, 256 one dimension, 99 online, 66, 73, 238, 264 openness, 21, 233, 239 openness to experience, 21, 239 opposition, 79, 227, 230, 233, 234, 235, 237, 255, 258 oppression, 24, 121, 247, 257, 304 optimism, 71 Oregon, 93, 308, 311 organization(s), 4, 200, 234, 308 orientation, 3, 5, 7, 8, 20, 21, 23, 24, 25, 43, 49, 53, 54, 57, 58, 60, 62, 63, 64, 65, 67, 70, 72, 73, 74, 96, 103, 115, 120, 172, 201, 202, 204, 205, 212, 215, 216, 217, 220, 226, 227, 228, 231, 232, 233, 235, 239, 240, 241, 243, 244, 245, 246, 247, 248, 254, 257, 258, 267, 269, 273, 284 Ottawa, 301, 303, 307 overweight, 39, 40, 43, 44, 47, 126, 301, 303
P Pacific, 116 pairing, 127, 133, 135, 138, 140, 142 palliative, 302 palliative care, 302 paper, vii, 72, 94, 95, 123, 124, 125, 126, 127, 128, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 146, 218, 228, 231, 244, 256, 259 paradoxical, 158 parental authority, 5 parents, 4, 185, 239, 287, 293, 298, 300 Paris, 22 parole, 279, 305 partnerships, 311 passive, 275 paternalism, 12 pathology, 95, 196 patients, 219, 302 peer, 97, 307, 308, 309, 310, 311
Index peers, 61, 97, 165, 167, 174, 183, 184, 187 penalty, 191 pendulum, vii, 1, 4, 18, 19 Pennsylvania, 117, 253 perceived control, 193 perception, viii, 11, 21, 47, 101, 103, 148, 149, 153, 160, 168, 174, 177, 179, 186, 187, 192, 235, 281, 310 perceptions, vii, 11, 15, 20, 22, 27, 28, 30, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 46, 53, 61, 66, 68, 101, 115, 119, 151, 153, 169, 170, 171, 172, 173, 174, 175, 178, 180, 183, 184, 186, 187, 190, 192, 235, 281, 293, 302, 309 performance, 25, 126, 128, 129, 130, 156, 195, 200, 204, 206, 209, 215, 236, 257, 258 performers, 156 permit, 211, 212 personal, vii, 3, 6, 9, 10, 11, 12, 14, 16, 17, 18, 19, 28, 44, 49, 79, 81, 86, 97, 169, 187, 194, 279, 281, 285, 286, 287, 290, 297, 300 personal communication, 97 personal norms, 28 personality, 2, 4, 5, 6, 8, 9, 16, 17, 18, 19, 20, 21, 23, 49, 54, 71, 73, 95, 120, 168, 169, 178, 180, 181, 186, 204, 221, 222, 239, 252, 254, 256, 257, 258, 266, 285, 309 personality characteristics, 168, 169, 178 personality constructs, 239 personality differences, 309 personality dimensions, 2, 222 personality disorder, 6 personality factors, 8 personality traits, 180, 266, 285 persuasion, 200, 201 Philadelphia, 21, 257 philosophy, 94 phobia, 196, 220, 228 phone, 53 photographs, 79, 85, 98, 131, 137, 149, 157, 200, 210 physical health, 194 physicians, 280 physiological, 59, 61, 66, 69, 96, 98, 99 physiological arousal, 59, 61, 66, 69 physiology, 48 pilot study, 302 pitch, 151 planning, 53, 69 play, 4, 43, 44, 53, 104, 151, 190, 231, 236, 247, 272 pleasure, 307 pluralism, 15, 257 pluralistic, 121 poison, 82, 125
325
police, 52, 53, 70, 117, 274 political, 2, 11, 12, 14, 23, 25, 44, 49, 50, 51, 52, 53, 54, 56, 57, 58, 60, 62, 63, 64, 66, 67, 68, 70, 73, 77, 81, 83, 84, 87, 88, 90, 91, 93, 116, 120, 150, 199, 203, 205, 225, 227, 230, 231, 234, 235, 238, 239, 240, 252, 254, 256, 257, 262, 284, 308, 310 political power, 225 Political Support Scale (PSS), 81, 83, 84 politicians, 272 politics, 73, 74, 75, 118, 121, 223, 255, 259 poor, 5, 64, 70, 83, 143, 282, 287, 297 population, 5, 6, 30, 58, 59, 61, 101, 166, 194, 247, 248, 277, 280, 283, 284, 297 pornography, 275, 307 positive attitudes, 104, 112, 114, 202, 210 positive correlation, 84, 86, 102, 283, 295 positive feedback, 280 positive regard, 15 positive relation, 7, 41 positive relationship, 86 posture, 207 poverty, 226 power, 8, 9, 13, 16, 17, 118, 144, 191, 220, 221, 277, 300, 310 prediction, 8, 36, 89, 116, 151, 155, 170, 199, 217, 219 predictive validity, 90, 91, 144 predictors, 7, 18, 22, 73, 81, 88, 220, 231, 255 preference, 36, 37, 38, 82, 87, 88, 89, 101, 102, 103, 109, 110, 112, 117, 126, 127, 128, 133, 188, 231, 239, 269 pregnancy, 280 pregnant, 68 premium, 191 preparation, 47, 73, 194, 274, 275 preschool, 119 preschool children, 119 president, 308, 310 President Clinton, 259 pressure, 4, 156, 157, 272, 273, 278 pretrial, 72 prevention, 15 primacy, 31 priming, 15, 36, 38, 39, 49, 79, 90, 119, 210, 236 priming paradigm, 79 printing, 131 private, 21, 83, 85, 167, 206, 208, 212, 218, 219, 237, 240 proactive, 232 probability, 151, 156, 157, 158, 196, 197, 212, 239, 252 probability judgment, 157
326
Index
procedures, vii, 22, 126, 127, 128, 129, 130, 131, 135, 136, 142 production, 22, 255 profession, 173 professions, 187, 265 program, 2, 68, 82, 89, 238 promote, 7, 14, 16, 98, 237, 298 property, 188 proposition, 31, 32, 33, 42, 43, 78 prosecutor, 52 prosperity, 167 protection, 53, 229, 247 Protestants, 72 protocols, 108 prototype, 102 proximal, 89 proxy, 95, 232 psychodynamic perspective, 4 psychological, vii, 4, 11, 13, 14, 15, 16, 17, 19, 22, 24, 50, 59, 72, 73, 79, 88, 90, 94, 104, 160, 162, 192, 195, 196, 199, 204, 205, 220, 221, 222, 228, 230, 231, 247, 252, 255, 261, 271, 273, 275, 276, 279, 283, 284, 299 psychological functions, 271 psychological phenomena, 17 psychological processes, 4, 24 psychological variables, 196, 199 psychological well-being, 192 psychologist, 74, 308 psychologists, viii, 9, 12, 13, 15, 51, 52, 54, 165, 196, 277, 299 psychology, 5, 6, 16, 19, 20, 22, 23, 25, 74, 81, 84, 92, 95, 121, 145, 160, 170, 173, 217, 219, 252, 253, 254, 255, 256, 257, 282, 298, 307, 308, 309, 310, 311 psychometric properties, 5, 124, 126, 130, 132, 143, 144, 200, 229, 271 psychometric quality, 80, 265 psychopathology, 218, 304 PsycINFO, 2 public, 11, 29, 78, 91, 100, 206, 208, 218, 219, 222, 226, 227, 233, 234, 235, 236, 237, 238, 239, 240, 247, 248, 252, 259, 276, 279 public opinion, 29, 91, 100, 219, 238, 252, 259 public policy, 227, 233, 234, 259 public support, 222 pulse, 61 punitive, 4, 5, 64, 65, 70
Q qualifications, 12, 43 quality of life, 255, 278
query, 115 question mark, 106 questionnaire(s), 50, 53, 79, 96, 100, 109, 112, 122, 196, 199, 202, 211, 253, 265, 284, 286, 294 quotas, 78
R race, 2, 4, 6, 39, 49, 51, 52, 54, 55, 56, 57, 59, 60, 61, 62, 63, 64, 65, 68, 69, 71, 72, 73, 81, 89, 91, 94, 95, 97, 107, 115, 116, 119, 120, 121, 122, 130, 132, 136, 137, 143, 158, 160, 168, 194, 255, 262, 271, 304, 308, 311 race categories, 143 racial categories, 85, 95 racial groups, 94, 95, 97, 100, 101 racial preferences, 118, 123 racism, vii, 7, 12, 13, 20, 21, 22, 23, 24, 25, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 61, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 78, 88, 90, 91, 94, 96, 97, 101, 117, 118, 119, 121, 190, 199, 226, 228, 229, 230, 232, 234, 235, 253, 254, 256, 257, 258, 261, 262, 263, 264, 274, 275, 276, 280, 281, 302, 303, 304 radar, 166 radical, 230, 249 random, 8, 38, 127, 128, 197 range, 4, 6, 9, 10, 13, 16, 17, 83, 85, 95, 97, 127, 171, 187, 195, 196, 200, 202, 203, 205, 216, 238, 239, 263, 264, 266, 267, 273, 283, 286, 287, 288, 289, 290, 291 rape, 261, 262, 263, 264, 265, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 309 rape myth acceptance (RMA), 261, 263, 264, 265, 266, 267, 269, 270, 271 rapists, 274 rat, 33, 271 rating scale, 149, 173, 174, 183 ratings, 36, 45, 54, 56, 58, 59, 60, 65, 70, 71, 150, 151, 155, 157, 171, 175, 177, 178, 179, 183, 185, 186, 206, 279, 301, 303 reaction formation, 56 reaction time, 99, 114, 200 reactivity, 210 reading, 118, 155, 174, 181, 270 reality, 186 reasoning, 10, 31, 121, 148, 154, 157, 188 rebelliousness, 282 recognition, 101, 149, 150 recognition test, 149, 150 reconcile, 97 reconciliation, 15, 97 recovery, 311
Index reduction, 11, 13, 17, 22, 29, 42, 45, 48, 147, 148, 149, 153, 158, 159, 197, 295, 298, 308 reflection, 170 refugees, 15, 21 regression, 37, 38, 197 regression analysis, 37, 38 regulation, 89 rejection, 33, 35, 174, 227 relatives, 167 relativity, 255 relevance, 84, 257 reliability, 80, 83, 85, 90, 130, 134, 138, 140, 142, 144, 151, 181, 198, 201, 209, 216, 217, 229, 230, 238, 239, 241, 252, 259, 261, 266, 285, 286, 294, 295 religion, 229, 237, 258 religiosity, 239 religious, 43, 46, 67, 197, 199, 204, 217, 222, 229, 230, 232, 237, 240, 250, 253, 257, 278, 284, 310 religious belief, 237 religious fundamentalism, 43, 46, 67, 204, 217, 253, 257 remediation, 49 rent, 188, 189 repair, 249 replication, 38, 42, 58, 59, 88, 173, 202, 210, 257 repression, 6, 167 reproductive age, 170 research design, 88, 247 researchers, 1, 2, 3, 5, 8, 9, 11, 12, 14, 17, 18, 28, 54, 78, 79, 80, 93, 98, 99, 100, 101, 103, 109, 112, 114, 115, 124, 143, 157, 195, 196, 198, 199, 201, 203, 206, 207, 209, 214, 229, 231, 232, 247, 270, 271, 283, 284, 286, 299 resentment, 262, 281 reserves, 300, 301 residential, 13, 278, 283, 300, 302 resilience, 150 resistance, 11, 13, 16, 73, 230 resources, 9, 12, 193, 194 response format, 294 response time, 39, 127, 136, 217 restitution, 278 restoration, 278 retaliate, 273 returns, 18 rhetoric, 229, 230, 234, 235, 255 right-wing, 7, 19, 25, 254 rigidity, 7, 9, 16, 167 rings, 188 risk, 18, 132, 191, 194, 197, 270, 275, 280, 282, 305 risk assessment, 275 risk perception, 270
327
risks, 143 RMSEA, 140 robustness, 252 romantic relationship, 167, 168, 169, 170, 171, 172, 173, 174, 178, 181, 186 Root Mean Square Residual, 140 rural, 279 rural areas, 279 Rwanda, 15
S safety, 11 salaries, 191 salary, 187 sales, 44 same-sex friendships, 167 sample, 42, 58, 61, 62, 64, 82, 83, 84, 85, 86, 97, 132, 134, 138, 139, 165, 171, 173, 178, 180, 186, 187, 189, 196, 197, 201, 205, 207, 212, 213, 225, 237, 238, 240, 241, 247, 248, 252, 266, 267, 268, 269, 271, 280, 281, 287 sample mean, 134, 139 sampling, 240, 295 sanctions, 226 sand, 143 satisfaction, 169, 179 schema, 237, 269 schemas, 10 scholarship, 70, 226, 233, 234 school, 55, 64, 67, 68, 78, 95, 116, 121, 132, 141, 237, 240, 278, 280, 283, 293, 300, 301, 302 schooling, 278 science, 1, 2, 19, 94, 95, 121, 122, 133, 145, 192, 193, 222, 237, 308 scientific, 2, 5, 6, 94, 95, 112, 121, 262, 307 scientific understanding, 2 scientists, viii, 52, 96, 108, 168, 190, 191, 279, 298 scores, 7, 8, 13, 17, 36, 38, 39, 58, 61, 83, 88, 97, 99, 102, 126, 127, 128, 129, 130, 131, 133, 134, 136, 139, 140, 141, 142, 151, 176, 206, 212, 214, 215, 235, 236, 238, 239, 241, 264, 265, 267, 270, 271, 283, 285, 286, 287, 288, 292, 294, 295, 296, 297 scripts, 74, 227, 236 search, 2, 33, 74, 279 searching, 42, 44 secondary data, 128, 129 secondary education, 303 secondary students, 239 secret, 221 security, 8, 197 segregation, 2, 13, 29, 41, 118, 236 selecting, 16
328
Index
self, 10, 118, 142, 160, 175, 176, 177, 196, 198, 203, 204, 211, 220, 253 self-assessment, 58 self-awareness, 14, 15 self-concept, 144, 162 self-confidence, 151, 182 self-descriptions, 151 self-discipline, 150 self-esteem, 4, 21, 48, 90, 126, 141, 143, 144, 178, 184, 185, 193, 199, 217, 218, 219, 220, 255, 270, 274 self-help, 168, 180 self-identity, 107, 247 self-image, 29, 51, 55, 56, 57, 58, 59, 62, 63, 64, 68, 71, 73 self-interest, 12, 47 self-presentation, 79, 195, 202, 222 self-regulation, 14 self-report(s), 12, 28, 30, 32, 48, 53, 55, 56, 58, 65, 67, 79, 81, 83, 124, 195, 196, 197, 198, 202, 203, 204, 205, 207, 211, 212, 214, 263, 264, 270, 271, 274 self-report data, 195 self-worth, 281 semantic, 203, 209 semantics, 275 sensitivity, 6, 16, 85, 272 sensors, 61 sentences, 68, 159, 271 sentencing, 159, 161, 279 separation, 179 September 11, 2, 20 sequelae, 282 sequencing, 193 sequential priming task (SPT), 36, 39 series, vii, 36, 81, 84, 109, 113, 149, 151, 152, 154, 158, 166, 184, 187, 230, 237, 261, 265, 282, 287, 288 services, 197, 281, 284, 301 settlers, 277 sex, 61, 63, 69, 82, 86, 97, 162, 163, 167, 171, 173, 177, 178, 179, 188, 191, 192, 194, 197, 200, 204, 205, 206, 209, 211, 222, 229, 233, 234, 239, 253, 254, 256, 258, 263, 265, 266, 267, 272, 276, 278, 307 sex differences, 179, 191, 204, 206, 266, 267 sex role, 254, 256 sexism, 7, 13, 24, 90, 108, 118, 161, 191, 199, 204, 218, 228, 229, 232, 235, 244, 248, 253, 254, 255, 256, 257, 261, 262, 263, 264, 267, 269, 271, 273, 274, 275, 276, 304, 311 sexual activity, 197, 210 sexual assault, 264, 270, 273, 274, 275
sexual behavior, 171, 239 sexual contact, 272 sexual harassment, 272, 273 sexual orientation, 67, 115, 172, 196, 200, 201, 202, 203, 204, 205, 206, 207, 209, 210, 212, 214, 216, 218, 220, 222, 223, 230, 231, 233, 234, 239, 247, 248, 258, 285, 310, 311 sexual violence, 261, 262, 263, 264, 265, 267, 269, 270, 271, 272, 273, 275 sexuality, 198, 214, 217, 220, 222, 249, 256, 258, 272, 273 sexually abused, 278 sexually transmitted diseases, 282 shame, 276 shape, 25, 252 shaping, 5 shelter, 193 shock, 196 shoulder, 147 shoulders, 148 shy, 15, 174, 181 siblings, 167 sign, 169, 190, 208 signals, 272 signs, 165 similarity, 185, 297 simulation, 126 singular, 88 sites, 237, 265 skewness, 267 skin conductance, 62, 206 slavery, 70 sleep, 8 smiles, 207 social anxiety, 218 social attitudes, 7, 73 social behavior, 50, 159, 309 social behaviour, 301 social categorization, 116, 120 social category, 81, 153, 298 social change, 14, 166, 198, 230 social class, 240 social cognition, 10, 11, 19, 22, 48, 68, 71, 73, 79, 90, 97, 126, 145, 160, 219, 308, 310 social cohesion, 95 social construct, 121 social context, 2, 14, 17, 116, 193 social desirability, 79, 88, 218, 276, 294, 296, 297 Social Desirability Scale (SDS), 294, 296 social distance, 95, 116 social environment, 2, 301 social exclusion, 187 social factors, 4, 8
Index social group, viii, 10, 12, 25, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 39, 41, 42, 43, 45, 46, 78, 80, 189, 190, 205, 225, 226, 227, 231, 239, 281, 282, 283, 286, 288, 291 social hierarchy, 24, 256, 257 social identity, 3, 10, 11, 13, 14, 23, 24, 220 social identity theory, 3 social influence, 308, 309, 310 social learning, 7, 9 social network, 167 social norms, 4, 7, 17, 55, 147, 148, 159 social order, 11 social perception, 51, 72, 94, 95, 115, 159, 169, 311 social policy, 255, 257 social problems, 74 social psychology, 8, 19, 20, 23, 24, 25, 44, 47, 49, 51, 72, 74, 89, 91, 95, 117, 123, 161, 165, 193, 223, 252, 254, 259, 307, 308, 309, 310, 311 social relationships, 194 social roles, 274 social sciences, 94, 226 social status, 52, 225 social structure, 226, 247 social support, 191, 194 social systems, 12 social welfare, 227 social work, 174, 311 socialization, 7, 8 socially, 9, 12, 21, 30, 44, 79, 80, 81, 124, 168, 169, 170, 171, 172, 174, 176, 177, 181, 183, 185, 198, 205, 221, 228, 263, 294, 298 society, 13, 27, 50, 52, 55, 66, 71, 79, 157, 166, 168, 171, 190, 191, 192, 193, 226, 227, 230, 231, 244, 249, 262, 265, 267, 272, 273, 279, 284, 286, 296 socioeconomic, 52, 63, 64, 256, 302 socioeconomic status, 63, 64 sociological, 167 sociologists, 95 sociology, 95, 299, 311 software, 83, 85, 90 solutions, 6, 13, 17, 22 sounds, 111 South Africa, 24 spatial, 302 specialists, 145 species, 178, 253 specificity, 104, 111, 209 specter, 19, 46 spectrum, 185 speech, 162, 253 speed, 99, 126, 127, 128, 136, 141, 142, 199, 200, 210, 212 speed of response, 99, 128, 136
329
spheres, 167 spiritual, 278, 287, 289, 304 spirituality, 282 sports, 236 spousal relations, 190 spouse, 167, 184, 187, 190 St. Louis, 310 stability, 7, 8, 13, 16, 117, 144, 188, 194, 201, 218, 222, 230, 248, 252 stages, 69 standard deviation, 127, 128, 131, 133, 134, 139, 214, 241 standard error, 243, 245, 246 standards, 85, 134, 160, 293, 300 State of the Union, 252 statistical analysis, 95, 212 statistics, 268, 287 statutes, 194 stereotypical, 65, 85, 147, 149, 152, 161, 212, 263 stereotyping, vii, 22, 23, 47, 49, 72, 90, 91, 121, 122, 147, 148, 151, 153, 155, 156, 157, 158, 159, 160, 161, 165, 184, 189, 191, 192, 199, 218, 255, 277, 282, 283, 288, 299, 307, 308, 310, 311 stigma, 49, 165, 166, 168, 170, 171, 177, 183, 184, 189, 191, 193, 194, 254, 258, 276 stigmatization, 226, 247, 310 stigmatized, 27, 64, 68, 71, 116, 124, 165, 166, 168, 184, 188, 189, 192, 235, 247, 262, 308 stimuli, 134, 139 stimulus, 39, 49, 104, 105, 107, 109, 114, 124, 130, 132, 136, 143, 155, 203, 208, 210, 212 strategic, 19, 252 strategies, 17, 45, 135, 198, 202, 275 stratification, 225, 226, 227, 230, 231, 235, 236, 237, 244, 247, 248, 253, 255, 256, 311 strength, vii, 27, 47, 80, 124, 125, 136, 141, 209, 212, 219, 287, 292, 303 stress, viii, 82, 169, 280 structural equation model, 88, 90, 201, 237, 240, 258 Structural Equation Modeling (SEM), 88, 90, 140, 142, 144, 201, 240 student populations, 141 students, 57, 61, 117, 124, 132, 137, 151, 165, 171, 172, 174, 180, 181, 192, 203, 225, 232, 236, 237, 253, 264, 266, 269, 270, 280, 281, 282, 294, 298, 300, 301 subdomains, 225, 226, 230, 232, 237, 239, 240 subgroups, 71, 301 subjective, 31, 270, 279 subtraction, 98, 99, 102 suffering, 7 suicide, 282, 301 summaries, 96
330
Index
superiority, 8, 77 supplemental, 278 suppressing stereotype, 157, 158 suppression, 47, 56, 62, 72, 156, 157, 158, 162, 163, 192 surveillance, 56 survival, 178 susceptibility, 30 switching, 109 Switzerland, 207, 311 syllogisms, 95 symbiosis, 25 symbolic, 11, 13, 51, 52, 54, 55, 56, 57, 58, 61, 63, 64, 65, 66, 67, 68, 69, 70, 73, 74, 78, 232, 262, 283, 302 symbols, 55, 203, 232 sympathetic, 64, 78, 278 sympathy, 56, 70 symptoms, 282, 285, 304 syndrome, 5 synthesis, 252 systematic, 6, 7, 27, 38, 41, 51, 68, 70, 105, 114, 141 systematic desensitization, 6 systems, 11, 95, 225, 226, 228, 231
T tactics, 230 tangible, 9, 11, 13 tangible resources, 9 target stimuli, 210, 212 targets, 2, 33, 39, 46, 59, 61, 62, 65, 66, 68, 69, 71, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110, 111, 113, 114, 149, 150, 153, 155, 158, 159, 166, 169, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 188, 189, 203, 204, 210, 211, 284, 290, 297, 307 task performance, 99 taxes, 234, 300 teachers, 197, 280 teaching, 280, 310, 311 technology, 4 teenagers, 169 television, 167, 249 temporal, 63 tension, 14, 28, 88, 232, 298 tenure, 278, 281 Terror Management Theory, 2, 3, 15, 21, 24 terrorism, 2, 15, 25, 63 terrorist attack, 2, 15 test-retest reliability, 123, 130, 138, 141, 143, 201, 266
Texas, 255, 310, 311 Thailand, 310 theoretical, vii, 1, 2, 3, 4, 5, 8, 10, 11, 16, 19, 41, 45, 46, 59, 80, 93, 95, 96, 99, 109, 114, 123, 162, 196, 212, 215, 216, 226, 229, 232, 237, 244, 262, 283 theoretical assumptions, 96 theory, 1, 3, 4, 5, 6, 7, 13, 14, 15, 16, 18, 20, 22, 23, 24, 25, 29, 30, 33, 35, 47, 50, 54, 74, 80, 101, 102, 115, 116, 120, 121, 144, 149, 161, 193, 220, 225, 226, 227, 229, 230, 232, 233, 236, 237, 240, 241, 243, 244, 247, 253, 254, 255, 257, 293, 296, 302, 310 therapeutic, 6 therapy, 265, 273 thinking, 4, 5, 50, 71, 148 threat, 3, 5, 6, 7, 9, 11, 20, 22, 23, 25, 28, 50, 56, 69, 71, 116, 119, 120, 166, 236, 255, 258, 270, 302, 308, 309 threatened, 230 threatening, 8, 56, 117 threats, 9, 11, 17, 73, 311 three-dimensional space, 4 three-way interaction, 36, 37, 38, 40 throat, 249 time pressure, 274 timetable, 168 timing, 85, 143, 169, 194 title, 105 tolerance, 90, 150, 203 trade, 247 trade-off, 247 tradition, 44, 237 traditional gender role, 244 traditional practices, 305 training, 7, 45, 48, 49, 82, 118, 132, 137, 280 traits, 5, 6, 7, 149, 171, 174, 181, 202, 285, 292, 297 transfer, 55, 286 transformation(s), 127, 129, 162 transition, 14, 193 transition to adulthood, 193 translation, 265, 274 trauma, 278, 310 traumatic experiences, 278 treaties, 300 trend, 2, 68, 197, 269 trial, 52, 83, 132, 137, 144, 209, 210, 211, 212, 213, 214, 215 triggers, 159 true/false, 294 tsunami, 310 tutoring, 67 two-dimensional, 75, 105
Index Type I error, 240
U uncertainty, 22, 156 undergraduate, 132, 137, 180, 225, 232, 247, 248, 259, 282, 294 undergraduates, 81, 84, 131, 137, 185, 186, 237, 239, 248 undifferentiated, 276 unemployment, 14, 194, 282 unemployment rate, 14, 282 UNESCO, 22 unions, 233, 234, 257 United Kingdom (UK), 23, 71, 145, 228, 258, 262, 273 United States, 20, 24, 51, 55, 66, 70, 74, 83, 90, 95, 100, 101, 117, 118, 160, 166, 172, 190, 194, 219, 253, 276, 280, 281 universities, 225, 237, 240, 280, 300 university collaboration, 310 university community, 281 university students, 258, 284, 303 urban, 304
331
variety of domains, 209 vein, 44, 46, 271 velvet, 255 Vermont, 234, 257 veterinary medicine, 311 victimization, 281 victims, 39, 183, 262, 265, 267, 273, 275, 276, 279, 282 Victoria, vii, 27, 255, 308 video, 5 videotape, 53 violence, 14, 15, 24, 25, 72, 96, 226, 252, 262, 263, 265, 267, 271, 272 violent, 6, 13, 68, 105, 190, 287, 297 Virginia, 123, 165, 173, 180, 185, 193, 310, 311 virus, 253 visible, 188 visual, 143, 149, 153, 155, 156, 157, 158, 285, 286, 287, 301, 302, 303 visual analogue scales (VAS), 287, 290 visual field, 143 visual modality, 157 visual stimuli, 157 voice, 150, 151, 160, 161, 162, 236, 271, 275 voting, 57, 234 vulnerability, 216, 270, 274
V valence, 30, 32, 35, 38, 105, 132, 151, 157, 209, 285, 287, 289, 292, 297 validation, viii, 23, 31, 47, 91, 120, 215, 221, 223, 230, 256, 265, 273, 274, 275, 284, 296, 299, 303 validity, vii, 13, 31, 32, 80, 94, 99, 117, 121, 126, 127, 144, 198, 201, 209, 210, 214, 216, 217, 218, 229, 233, 238, 259, 261, 263, 265, 267, 269, 285, 293, 294, 296, 297 values, 7, 11, 12, 27, 29, 31, 33, 35, 36, 38, 39, 55, 56, 61, 63, 68, 73, 90, 127, 128, 129, 138, 140, 192, 225, 226, 227, 230, 232, 233, 238, 252, 255, 256, 262, 266, 281 vandalism, 14 variability, 7, 44, 151, 205, 208, 240 variable, 19, 23, 25, 49, 51, 57, 63, 120, 121, 140, 216, 220, 222, 240, 247, 248, 252, 256, 257, 264, 297 variables, vii, 6, 7, 8, 9, 11, 15, 17, 18, 19, 43, 52, 57, 59, 82, 87, 88, 145, 204, 206, 207, 208, 212, 216, 221, 233, 237, 240, 248, 252 variance, 8, 11, 17, 49, 124, 129, 140, 142, 145, 186, 254, 295, 297 variation, 7, 9, 148, 149, 151, 153, 154, 155, 159, 226 variegation, 108
W war, 6, 15, 22, 66 war on terror, 22 warrants, 279 Washington, 25, 46, 89, 90, 121, 123, 161, 194, 256, 310 waste, 279 water, 143 weakness, 88 wealth, 80, 196, 225 wear, 278 web, 50, 180, 221, 237 web-based, 180, 237 welfare, 9, 120, 287, 300 western culture, 190 Western Europe, 168 Western societies, 148 withdrawal, 193 wives, 167, 179, 191 work ethic, 43, 55, 77, 168, 227 workers, 90 workforce, 170 working class, 237 working women, 204 workplace, 187, 263
332 World War, 29, 167 worldview, 8, 11, 20, 21, 166 worry, 56 writing, 157, 158, 185, 214, 270, 311 Wyoming, 72, 174
Index
Y young adults, 170, 248
