Jobs are notoriously gender-segregated. But examinations of companies’ hiring data often don’t show a female disadvantage, even for male-dominated jobs. Many audit studies, on the other hand, do. This discrepancy can be partially explained by accounting for “failed searches” – cases when employers decide not to hire anyone from the applicant pool they receive. Professor Leung presents research from gig-economy work showing failed searches are more likely when many of the applicants are demographically different from the typical job holder. When a lot of women apply to a male-heavy tech job, for example, employers see the pool as unlikely to contain someone who “seemed skilled enough for my job.”

Read more about Professor Leung here.

Ming Leung is an assistant professor at the Haas School of Business. He studies how a job applicant’s social categories (like gender or country of origin) affect their success in the labor market.