Steering Women out of Engineering: Career Assessment Tools as a Technology of Self‐Expressive Segregation

Abstract

Previous research has shown that gendered societal expectations are adopted by students as seemingly personal and individualistic self‐assessments and preferences, which then lead to gender‐normative choices about college majors and careers. This study examines one seemingly objective mechanism, which millions use each year for guidance on college majors and careers. We examine two Career Assessment Tools (CATs) with deep institutional presence: O*NET and Traitify. Analyzing an exemplar case of engineering majors, we find that CATs are less likely to recommend engineering occupations to women, even after controlling for GPA, satisfaction with the major, and planned persistence. Even in our sample of engineering majors, CATs apparently use small differences in students' gender‐normative self‐expressive preferences to drive sharply different occupational recommendations, thereby solidifying pathways toward gender‐segregated occupations and reinforcing men's dominance of engineering. If women similar to our study participants take CATs, they are likely to be steered away from engineering occupations or majors. More broadly, CATs illustrate how taken‐for‐granted, seemingly neutral technologies can reinforce gender segregation.