Finkelstein, Lisa M.
Ph.D. (Doctor of Philosophy)
Department of Psychology
Occupational stereotypes are preconceived notions about specific occupations, the people in those occupations, or one’s fit with an occupation (Lipton et al., 1991). Previous studies of occupational stereotyping have been useful to understand the impact of single demographic characteristics (e.g., gender; King et al., 2006) and multiple demographic characteristics (i.e., race-gender interaction; Bertrand & Mullainathan, 2004) on hiring preferences. A set of three studies were conducted to expand the field’s understanding of fit with occupational stereotypes as a mechanism of discrimination toward multiple combinations of social groups in the technology field.
The goal of the first study was to establish how the social groups targeted in this dissertation were perceived in terms of fit with both technology and non-technology occupations. Two hundred and sixty-one full-time working adults participated in this study, in which they primarily evaluated one of nine groups (i.e., white men, white women, Black men, Black women, white men with ADHD, white women with ADHD, Black men with ADHD, Black women with ADHD, and people with ADHD) based on fit with several occupations. The results of this study revealed that there were differences in perceived fit with an engineer position based on gender, race, disability status, and most of their intersections. The pattern of results for Study 1 was consistent with a multiplicative effect of social identities on stereotypes, which suggests that people are capable of forming, and are aware of, more complex stereotypes. It is important for the field to continue researching and understanding the intersectional nature of stereotypes because the perception of an individual changes meaningfully when considering more than one demographic characteristic.
The second study’s goal was to explore the consequences of poor occupational fit with a technology position. In this study, three hundred and eighty-eight full-time working adults who had made a previous hiring decision were randomly assigned to evaluate a candidate and their fit with either an electrical engineer position or a postal service clerk position. Participants saw the same materials for the respective positions with only the race, gender, and disability status of the candidate varying. Ultimately, the ratings of the candidates did not vary based on race, gender, and disability status. Interestingly, unlike the results of the previous study the perceived fit of the candidates with the electrical engineer position did not differ based on race, gender, and disability status. This inconsistency with the previous study may reflect a distinction between rating directions across the two studies. In study 1 perception of fit was determined by ratings of perceptions of what most Americans believe while in study 2 participants made their own ratings of a hypothetical job candidate. These inconsistencies may be indicative of difficulties in studying discrimination processes using experimental manipulation of qualities in hypothetical candidates with no real world consequences.
The goal of the third study was to examine how the social groups targeted in this dissertation differ in terms of callbacks and interview offers when applying for an electrical engineer opening in the real world. Eight hundred organizations were sent the same resume and cover letter that was used in the previous study. The results of this study, in contrast to study 2, revealed that interview offers differed based on candidate race. Black candidates received significantly fewer interview offers for an electrical engineer position than white candidates. An exploratory analysis revealed that white candidates with ADHD were more likely to receive an interview offer than Black candidates with ADHD. The results of Study 3 reinforce the need for bias training and blind evaluation of candidates.
Martinez, Jesus Jose, "Not A Good Fit For The Job: An intersectional Study of Occupational Stereotypes in The Field of Technology" (2022). Graduate Research Theses & Dissertations. 7405.
Northern Illinois University
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