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This study aims to examine how gender variation in trans identities shape exposure to bias and discrimination. The authors then examine how trans identities intersect with race/ethnicity, education and social class to shape exposure risk to bias, discrimination and harassment in the workplace.Design/methodology/approachThe authors use data from the 2015 U.S. Transgender Survey with 24,391 trans-identified respondents. To account for the nested nature of trans people in state contexts, the authors use two-level logistic multilevel models. The authors are guided by Puwar’s bodies out of place as the theoretical grounding for this study.FindingsThe authors find significant differences in how trans women and men experience discrimination. The authors also find differences in race, education and social class. Finally, the presence of anti-discrimination policies presents mixed results.Originality/valueThe authors’ analysis reveals important differences in trans workers’ exposure to discrimination based on gender identity, social class, race/ethnicity and policy context, and draws upon a rich and large data set.
Gender in Management: An International Journal – Emerald Publishing
Published: Aug 16, 2022
Keywords: Transgender; Multilevel logistic regression; Workplace discrimination; US Transgender Survey; USTS; Workplace bias
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