Here is one (IMO) much more complete abstract (not to call it tl:dr) that covers the main hypothesis, and all the variables studied<p><i>Our main research question was: to what extent does gender bias exist among people who judge GitHub pull requests?<p>To answer this question, we approached the problem by examining whether men and women are equally likely to have their pull requests accepted on GitHub, then investigated why differences might exist.<p>We extract users&#x27; email addresses from GHTorrent, look up that email address on the Google+ social network, then, if that user has a profile, extract gender information from these users&#x27; profiles. Out of 4,037,953 GitHub user profiles with email addresses, we were able to identify 1,426,121 (35.3%) of them as men or women through their public Google+ profiles.<p>== Results ==<p>Are women&#x27;s pull requests less likely to be accepted?
The hypothesis is not only false, but it is in the opposite direction than expected; women tend to have their pull requests accepted at a higher rate than men!<p>== Do women&#x27;s pull request acceptance rates start low and increase over time? ==<p>[B]etween 1 and 64 pull requests, women&#x27;s higher acceptance rate remains. Thus, the evidence casts doubt on our hypothesis.<p>== Are women making pull requests that are more needed? ==<p>[T]he result suggests that women&#x27;s increased success rate is not explained by making more immediately needed pull requests.<p>== Are women making smaller changes? ==<p>(...) Women make pull requests that add and remove more lines of code, modify more files, and contain more commits.<p>== Are women&#x27;s pull requests more successful when contributing code? ==<p>(For instance, changes to HTML could be more likely to be accepted than changes to C code, and if women are more likely to change HTML)<p>[W]omen&#x27;s acceptance rates dominate over men&#x27;s for every programming language in the top ten, to various degrees<p>== Is a woman’s pull request accepted more often because she appears to be a woman? ==<p>For insiders, we observe little evidence of bias when we compare women with gender neutral profiles and women with gendered profiles, since both have about equivalent acceptance rates.<p>For outsiders, we see evidence for gender bias: women’s acceptance rates are 71.8% when they use gender neutral profiles, but drop to 62.5% when their gender is identifiable. There is a similar drop for men, but the effect is not as strong.<p>Women have a higher acceptance rate of pull requests overall (as we reported earlier), but when they’re outsiders and their gender is identifiable, they have a lower acceptance rate than men.</i><p>I hope that helps those who won&#x27;t read the whole paper but feel the need to comment on it.