Like A Girl

Pushing the conversation on gender equality.

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Gender Bias in Open Source

A study published in the PeerJ Computer Science journal in May 2017 looked at how gender affected contributions on GitHub by studying pull requests. The researchers looked at 3 million pull requests from approximately 333,000 GitHub users. They found that women’s contributions to open source projects were accepted more frequently than men’s contribution when the gender was unknown. However when the gender was known, women’s contributions were accepted at a lower rate than men’s (Phys).

In a separate study, researchers got similar results when looking at a San Francisco open source community. These researchers found that women’s coding suggestions was accepted 71.8% of the time when their gender was kept a secret, but only 62.5% of the time when their gender was revealed (Editorial).

GitHub completed an open source survey in 2017 that covered a wide range of topics, but some of the gender insights were especially revealing. Only 3% of the 5500 randomly selected respondents were women. 25% of those women reported being exposed to language or content that made them uncomfortable, 12% experienced stereotyping and 6% received unsolicited sexual advances. The percentages for men were 15%, 2% and 3% respectively (Insights).

Based on their profile pictures and names, it seems that all of the active contributors on the open source projects I’ve been looking at are men. After seeing the data from GitHub’s survey, these results are no longer surprising. Open Source is supposed to be a place where anyone can contribute and find projects they are passionate about. Unfortunately, these studies and the survey show there is clearly a gender bias and conditions that can make it an uncomfortable place to be for women.

Work Cited

“EDITORIAL: Missouri Firm Applauded for Trying to Eliminate Gender Bias.” Columbia Missourian, The Columbia Missourian, 7 Sept. 2017.

“Insights.” Open Source Survey, GitHub, Inc.,

Shipman, Matt. “Study Finds Gender Bias in Open-Source Programming.”,, 1 May 2017.