Appearance-Related Math Stereotypes and the Development of Gender Disparities in STEM

The gender gap in math-intensive STEM fields negatively impacts women and the global economy. STEM professionals are often stereotyped as unkempt, uninvested in their appearance, and unattractive. These appearance-related math stereotypes (ARMS) may negatively affect adolescent girls’ engagement with STEM fields, given that appearance investment is a key feminine norm. ARMS may differentially affect girls of diverse racial/ethnic backgrounds, yet an intersectional lens is rarely applied to understand disparities in STEM. Across 4 studies with U.S. adolescents using diverse methodological approaches, I investigate the prevalence of ARMS among adolescents, how ARMS endorsement is associated with math motivation and performance, and differences in these associations by gender and race/ethnicity. Study 1 (high school students, n = 323) piloted a novel experimental paradigm to investigate how adolescents use ARMS to evaluate others. In Study 2 (high school students, n = 168), I piloted a self-report ARMS Scale, finding preliminary evidence of associations between ARMS endorsement and worse math motivation. Study 3 (middle school students, n = 1654) replicated these preliminary findings and found evidence of differences by gender but no differences across intersections of gender and race/ethnicity. Study 4 (middle school students, n = 1604) further extended these results with a longitudinal design and a novel photo-rating task to capture implicit ARMS endorsement. Broadly, findings suggest that self-reporting agreement with ARMS is negatively associated with math motivation and performance among youth, with stronger links between ARMS endorsement and some math motivation components (e.g., math self-concept) among girls relative to boys.