Back to Search Start Over

Gender bias in open source: Pull request acceptance of women versus men

Authors :
Chris Parnin
Clarissa Rainear
Justin Middleton
Josh Terrell
Andrew Kofink
Emerson Murphy-Hill
Publication Year :
2016
Publisher :
PeerJ, 2016.

Abstract

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.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........6742b3ef4db89672f921727b7fcaf454
Full Text :
https://doi.org/10.7287/peerj.preprints.1733v1