Open AccessThe intersections of race, gender, age, and socioeconomic status: Implications for reporting discrimination and attributions to discrimination.
Author(s) -
Lindsey N. Potter,
Matthew J. Zawadzki,
Collette P. Eccleston,
Jonathan E. Cook,
Shedra Amy Snipes,
Martin J. Sliwinski,
Joshua M. Smyth
Publication year - 2019
Publication title -
stigma and health
Language(s) - English
Resource type - Journals
eISSN - 2376-6972
pISSN - 2376-6964
DOI - 10.1037/sah0000099
Subject(s) - attribution , psychology , operationalization , race (biology) , socioeconomic status , social identity theory , social psychology , developmental psychology , population , demography , social group , sociology , gender studies , philosophy , epistemology
This study employed an intersectional approach (operationalized as the combination of more than one social identity) to examine the relationship between aspects of social identity (i.e., race, gender, age, SES), self-reported level of mistreatment, and attributions for discrimination. Self-reported discrimination has been researched extensively and there is substantial evidence of its association with adverse physical and psychological health outcomes. Few studies, however, have examined the relationship of multiple demographic variables (including social identities) to overall levels self-reported mistreatment as well the selection of attributions for discrimination. A diverse community sample ( N = 292; 42.12% Black; 47.26% male) reported on experiences of discrimination using the Everyday Discrimination Scale. General linear models were used to test the effect of sociodemographic characteristics (i.e., race, gender, age, SES) on total discrimination score and on attributions for discrimination. To test for intersectional relationships, we tested the effect of two-way interactions of sociodemographic characteristics on total discrimination score and attributions for discrimination. We found preliminary support for intersectional effects, as indicated by a significant race by age interaction on the selection of the race attribution for discrimination; gender by SES on the age attribution; age by gender on the education attribution; and race by SES on the economic situation attribution. Our study extends prior work by highlighting the importance of testing more than one factor as contributing to discrimination, particularly when examining to what sources individuals attribute discrimination.