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Construction of an anti-Mexican American bias scale and its validation
Abstract
The purpose of the dissertation is to develop a meaningful measure of Anti-Mexican American attitudes and to test that measure for its utility in predicting biased attributions for Mexican Americans. Attention has mainly focused on bias against Blacks, and this has produced important gaps in the understanding of race/ethnic bias that must be addressed. For the past few decades, the number of racial minorities, especially the number of Latinos/Hispanics, has been on the rise. The psychometric properties and validation of the new Anti-Mexican American Attitude Scale (AMAAS) were investigated through study 1 and study 2. The principal components analysis pulled six factors (study 1), and confirmatory factor analysis (CFA) refined the scale to three viable factors (study 2). Using structural equation modeling (SEM; study 2), the final scale was found to be a reflection of cultural stereotypes and attitudes about Mexican Americans (construct validity). The relationship amongst the Mexican American bias scale with anti-Black and anti-immigrant scales supported hypotheses that AMAAS was indicative of cognitive bias (Model Level 2). Although the patterns of results were similar, the predictive validity of AMAAS was independent of the other group bias scales. The results of the study indicated that measures of individual differences (CSE, SDO, RWA-ACT) predicted bias against Mexican Americans, and the bias, in turn, predicted opposition to racial policies. The “real world” effect of having the ability to measure prejudice against Mexican Americans was one of the first steps in recognizing the ramifications of experiencing bias in the Latino community. In future studies, the exploration of perceived threat will add another level of depth to the understanding of anti-Mexican American bias.
Subject Area
Psychology|Hispanic American studies
Recommended Citation
Martinez, Leslie N, "Construction of an anti-Mexican American bias scale and its validation" (2015). ETD collection for University of Nebraska-Lincoln. AAI3738579.
https://digitalcommons.unl.edu/dissertations/AAI3738579