2016's top 100 journal articlesBrain power

Gender differences and bias in an open source software community [2016’s top 100 journal articles]

This is part 3 of a miniseries reviewing selected papers from the top 100 most-discussed journal articles of 2016.

Biases against women in the workplace have been widely documented, and appear to pervade the open source software movement.

A new paper1 investigates gender bias in the open source software movement by looking at how software developers in GitHub, an open source software community, respond to “pull requests”. Pull requests are proposed changes to a software project’s code, documentation, or other resources. They can be made by “insiders”, who are project owners or collaborators, or “outsiders”, which is everyone else. The paper is article #28 of the top 100 most-discussed journal articles of 2016.

Surprisingly, the results show that contributions by women software developers tend to be accepted more often than contributions by men. However, women’s acceptance rates are higher only when their gender is not identifiable, suggesting that bias against them exists. In summary, the paper’s observations are that:

  1. Women are more likely to have pull requests accepted than men.
  2. Women continue to have high acceptance rates as they do pull requests on more projects.
  3. Women’s pull requests are less likely to serve a documented project need.
  4. Women’s changes are larger.
  5. Women’s acceptance rates are higher for some programming languages.
  6. Women outsiders’ acceptance rates are higher, but only when they are not identifiable as women.

The paper authors put forward several alternative theories that may explain their observations as a whole:

Given observations 1–5, one theory is that a bias against men exists, that is, a form of reverse discrimination. However, this theory runs counter to prior work, as well as observation 6.

Another theory is that women are taking fewer risks than men. This theory is consistent with Byrnes’ meta-analysis of risk-taking studies, which generally find women are more risk-averse than men. However, this theory is not consistent with observation 4, because women tend to change more lines of code, and changing more lines of code correlates with an increased risk of introducing bugs.

Another theory is that women in open source are, on average, more competent than men. This theory is consistent with observations 1–5. To be consistent with observation 6, we need to explain why women’s pull request acceptance rate drops when their gender is apparent. An addition to this theory that explains observation 6 … is that discrimination against women does exist in open source.


  1. Terrell J, Kofink A, Middleton J, Rainear C, Murphy-Hill E, Parnin C, Stallings J. (2016) Gender differences and bias in open source: Pull request acceptance of women versus men. PeerJ Preprints 4:e1733v2 https://doi.org/10.7287/peerj.preprints.1733v2

Also published on Medium.

Bruce Boyes

Bruce Boyes (www.bruceboyes.info) is editor, lead writer, and a director of the award-winning RealKM Magazine (www.realkm.com) and currently also teaches in the University of NSW (UNSW) Foundation Studies program in China. He has expertise and experience in a wide range of areas including knowledge management (KM), environmental management, program and project management, writing and editing, stakeholder engagement, communications, and research. Bruce holds a Master of Environmental Management with Distinction and a Certificate of Technology (Electronics). With a demonstrated ability to identify and implement innovative solutions to social and ecological complexity, Bruce's many career highlights include establishing RealKM Magazine as an award-winning resource for knowledge managers, using agile and knowledge management approaches to oversee the implementation of an award-winning $77.4 million river recovery program in western Sydney on time and under budget, leading a knowledge strategy process for Australia's 56 natural resource management (NRM) regional organisations, pioneering collaborative learning and governance approaches to support communities to sustainably manage landscapes and catchments, and initiating and teaching two new knowledge management subjects at Shanxi University in China.

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