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Data Analysis of Github Contributions Reveals ­nexpected Gender Bias


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An analysis of millions of GitHub pull requests found women's contributions were accepted more frequently than men's, as long as they were associated with gender-neutral profiles.

Credit: GitHub

A rigorous analysis of millions of GitHub pull requests for open source projects found women's contributions were accepted more frequently than men's, but only if they were associated with gender-neutral profiles.

However, women whose GitHub profiles indicated their genders had a much harder time.

The researchers note they "augmented this GHTorrent data by mining GitHub's Web pages for information about each pull request status, description, and comments," but the lack of gender information in GitHub profiles was a challenge.

The researchers met this challenge and determined the genders of more than 1.4 million users by linking their email addresses with Google+ profiles that list gender.

They originally expected women's GitHub contributions to be accepted with less frequency, but the reverse trend was observed when they examined the "merge rate" of women's contributions. The researchers found 78.6 percent of women's pull requests were accepted and merged into the code, versus only 74.4 percent of men's pull requests. They also found contributions from unknown women were accepted less often than contributions from unknown men, leading to the theory that some sort of social bias is at work.

From Ars Technica
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Abstracts Copyright © 2016 Information Inc., Bethesda, Maryland, USA


 

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