Project level effects of gender on contribution evaluation on GitHub
- Published
- Accepted
- Subject Areas
- Human-Computer Interaction, Social Computing, Programming Languages, Software Engineering
- Keywords
- Github, open source, gender bias, pull requests, statistical analysis
- Copyright
- © 2017 Brokmeier
- Licence
- 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
- 2017. Project level effects of gender on contribution evaluation on GitHub. PeerJ Preprints 5:e2989v1 https://doi.org/10.7287/peerj.preprints.2989v1
Abstract
Distributed open source software development has largely turned to GitHub, a pull-based software development collaboration platform. Recent studies have deployed data science techniques on the large datasets available about millions of projects on GitHub. Some research has focused on pull request (PR) acceptance predictors and evidence was found of sexual discrimination among members. In this paper I analyzed the influence of gender on PR acceptance on a project level, comparing different popular projects regarding their discrimination factors. Several projects were identified that have significant differences between male and female PR acceptance rates.
Author Comment
This paper has been written by me during a seminar at the University of Cologne. I have received positive feedback from a number of sources inside and outside of the University environment and I'd like to share this with the world. Ideally because it can make a difference, most probably though, people will point out all the flaws of my research which will then give me a chance to improve myself.