Be careful implying causation here. We would want to investigate who identifies themselves as any sex vs who remains unidentified (or less obviously identified) and the skill levels represented in each group. Since GitHub does not request your gender for your profile, they used Google+ profiles, which I think would significantly slew the results; they did not sample from all pull requests, but from those that were linked to a G+ account AND whose owners decided to post their gender.
> Specifically, we extract users’ 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’ 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.
> This is awful - I think it would be good to have some discussion around what we can do as a community to improve this?
I don't agree that the result is as strong as "awful" indicate because the paper concludes that
> Women had higher acceptance of pull request than men
> Identifiable women had higher acceptance of pull request than men
> Insider identifiable women had higher acceptance of pull request than men
> Both outsider identifiable women and outsider identifiable men had lower acceptance rates than their insider counterparts
The study proposes the existence of gender bias because, in this last point, the drop for women was higher than the drop for men, regardless of all the other instances where the opposite was true.
I don't believe the study is representative for the whole industry at all (GitHub being mainly remote, voluntary and due to the FLOSS philosophy mostly liberal) but this seems to be one to be celebrated because of the positive conclusion it showed for women.
Given that from this article's stats it even admits there are 15 times more male self-identified programmers then women on github, a 4% difference in pull requests accepted is tiny.
The data is just convenient for anyone with a political agenda to make big claims. If the paper wanted to be genuine they could have gone further - what was rejected? Was there a valid reason? etc
Based on the findings about men, it seems that both men and women experience a drop when they identify gender. Women experience a greater drop than men, but it is worth considering this trend is not found in the treatment of any one gender.
So the question remains, why do both genders experience a drop. Once we answer that, we can look into why women experience a worse drop.
The difference between men and women when their gender is identifiable is 0.5% (63.5 vs 64.0). Lets first have some good discussion on how significant that difference is.
> Specifically, we extract users’ 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’ 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.