Date of Award

2019

Degree Type

Dissertation

Degree Name

Doctor of Philosophy in Psychology

Specialization

Behavioral Science

Department

Psychology

First Advisor

Lisa Harlow

Abstract

Bias and stereotypes, even in the professional realms are ubiquitous and are unfortunately an inescapable fact of life in society. Psychologists study bias and discrimination in order to more fully understand when it arises, as well as what can be done to confront it. Bias and discrimination researchers have demonstrated that women, racial/ethic minorities, members of the LBGTQ community, as well as other marginalized groups continue to suffer from the effects of discrimination. However, recent investigations have indicated that discrimination based on an individual’s stated political affiliation may also exist. Other researchers point out that political affiliation bias and discrimination may be particularly prevalent in the higher education community. Therefore, the aim of the present study was to use an audit-type quasi-experimental design to examine possible signs of bias and discrimination in a sample of undergraduate students and Amazon MTurk users. A structural equation model (SEM), specifically a path model, was used to investigate whether political affiliation contributed over and above a host of other variables to the subjective rating of a fictional applicant’s candidacy for graduate school and employment. Contrary to some reports, stated political affiliation of a particular party did not seem to influence the candidate’s rating. Further, the MTurk and undergraduate student samples showed remarkable consistency in their ratings. Future research may want to examine more salient cues of political affiliation as well as various operational definitions of discrimination and bias.

Available for download on Sunday, April 19, 2020

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