Are There Common Dimensions Across the Separate Racial Prejudice Scales? Dayana Aghaie and Charlotte Tate San Francisco State University INTRODUCTION REFERENCES METHOD RESULTS DISCUSSION  Exploratory factor analysis was conducted using principal axis factoring method with varimax rotation  Factors extracted based on the last significant increase in variance accounted for  Exploratory factor analysis was conducted using principal axis factoring method with varimax rotation  Factors extracted based on the last significant increase in variance accounted for Factor Rotation and Extraction Factor Selection  Two commonly used factor selection methods were used to determine the appropriate number of factors to extract:  The Kaiser criterion to determine factors’ eigenvalues and variance accounted for  Cattell’s scree method to identify the last significant decrease in magnitude of eigenvalues  Two commonly used factor selection methods were used to determine the appropriate number of factors to extract:  The Kaiser criterion to determine factors’ eigenvalues and variance accounted for  Cattell’s scree method to identify the last significant decrease in magnitude of eigenvalues Quality of Solution Interpreting Factors  The Kaiser-Meyer-Olkin measure of sample adequacy indicated that the sample was adequate for analysis, KMO =.939 (above the.60 criterion)  An eight factor solution explained % of the variance based on the sums of squared loadings with varimax rotation  The Kaiser-Meyer-Olkin measure of sample adequacy indicated that the sample was adequate for analysis, KMO =.939 (above the.60 criterion)  An eight factor solution explained % of the variance based on the sums of squared loadings with varimax rotation The 8 Factor Solution Defined Aloof / competitive Resource burden Comfort with inter-racial interaction Comfort with inter-racial interaction Desire to marginalize α =.927α =.790α =.938α =.915  Participants: N = 455  Women: 244 (cis and trans combined)  Men: 209 (cis and trans combined)  Genderqueer/Non-binary: 2  Venue: Amazon Mechanical Turk (Mturk); U.S. only  Participant Ethnicity:  African-American: 33  Asian-American: 24  European-American: 349  Hispanic/Latin-American: 22  Native American: 4  Pacific Islander: 1  Mixed ethnicity: 22  Currently available measures of explicit racial prejudice may not capture all possible elements of prejudice because:  Focus on antipathy as the main or only feature of prejudice  Each scale focuses on different target groups  Because of the aforementioned features of explicit measures of racial prejudice, Clark and Tate (2008) argue that the discovery of new constructs may be concealed for the following reasons:  Prejudice involves elements other than negative attitudes  The overall structure of racial prejudice needs to focus on multiple target groups simultaneously  To discover other possibly hidden or latent constructs in addition to antipathy, we factor analyzed existing racial prejudice scales toward the following target groups:  African-American (AfAm)  Asian-American (AsAm)  European-American (EuAm)  Hispanic and Latino-Americans (H/LAm)  Exploratory factor analysis produced eight common dimensions across four discrete scales of racial prejudice:  Aloof/competitive  Comfort with inter-racial interaction  Resource burden  Desire to marginalize  Use of racial epithets  Self as racist  Refuting stereotypes  Social adjustment  Although some items came exclusively from one scale, this was not consistent across all factors:  Factors 2 and 7 include items from different scales  Scales broke up across multiple factors that did not correspond to original factor structure  Additionally, several items did not load, even onto their respective scales and were consequently excluded  While it may be the case that some groups are associated with the underlying dimensions more so than others, this may be a refection of the scales chosen rather than the phenomena itself  Future research can draw on eight possible themes in the development of racial prejudice scales:  Allows for the measurement of specific aspects of prejudice  Furthermore, future research may benefit from the use of different scales:  For example, replacing the ATB scale with the Modern Racism scale may produce item loadings onto factors such as use of racial epithets or refuting stereotypes Brigham, J. C. (1993). College students’ racial attitudes. Journal of Applied Social Psychology, 23(23), Clark, K. D., & Tate, C. (2008). Measuring racial prejudice in a multiracial world: New methods and new constructs. In M. A. Morrison & T. G. Morrison (Eds.), The Psychology of Modern Prejudice (pp ). Hauppauge, NY: Nova Science Publishers. Espinoza, R.K.E., & Hunt, J. S., (2002). The Development of Scales Measuring Prejudice Against Hispanics and Asians. Paper presented at the Midwestern Psychological Association Conference, Chicago, IL. Johnson, J. D., & Lecci, L. (2003). Assessing anti-white attitudes and predicting perceived racism: The Johnson-Lecci scale. Personality and Social Psychology Bulletin, 29(3), Lin, M. H., Kwan, V. S., Cheung, A., & Fiske, S. T. (2005). Stereotype content model explains prejudice for an envied outgroup: Scale of anti-Asian American stereotypes. Personality and Social Psychology Bulletin, 31(1), Attitudes Toward Blacks Scale strongly disagree strongly agree Johnson-Lecci Scale (attitudes toward Whites) not at all representative completely representative 0 Prejudice Against Hispanics Scale strongly disagree strongly agree 1 Scale of Anti-Asian American Stereotypes strongly disagree strongly agree 0 +All scales were presented in random order Criteria for eliminating poorly behaving items: Items with high loadings on more than one factor Items with small loadings on all factors Criteria for eliminating poorly defined factors: Factors on which items have less than two salient loadings Factors defined by items with loadings less than.30 cut-off Use of racial epithets Refuting stereotypes Self as racist Social adjustment α =.867 α =.781 r =.580 α =.507 r =.265 α =.703