Replication data for: Last Place? The Intersection of Ethnicity, Gender, and Race in Biomedical Authorship

Applying big data methods to biomedical science articles, we show that women and underrepresented racial and ethnic groups are less likely to be last authors, an indicator of career independence. We leverage the massive size of our data to highlight the importance of intersectionality, the idea that ethnicity, gender, and race are not necessarily additive, but interact to determine experiences and outcomes. In particular, gender gaps are smaller among blacks and Hispanics than among non-Hispanic whites. Our analysis is timely given serious concerns with under-representation of women and minorities in biomedicine and other STEM fields.