Gender bias in open source: Pull request acceptance of women versus men
- Subject Areas
- Human-Computer Interaction, Social Computing, Programming Languages, Software Engineering
- gender, bias, open source, software development, software engineering
- © 2016 Terrell et al.
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2016. Gender bias in open source: Pull request acceptance of women versus men. PeerJ PrePrints 4:e1733v1 https://doi.org/10.7287/peerj.preprints.1733v1
Biases against women in the workplace have been documented in a variety of studies. This paper presents the largest study to date on gender bias, where we compare acceptance rates of contributions from men versus women in an open source software community. Surprisingly, our results show that women's contributions tend to be accepted more often than men's. However, when a woman's gender is identifiable, they are rejected more often. Our results suggest that although women on GitHub may be more competent overall, bias against them exists nonetheless.
This report has not yet been peer-reviewed, and thus the findings should be considered preliminary. Before citing this paper, please check for an updated version here: http://people.engr.ncsu.edu/ermurph3/pubs.html