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Because Git Hub is big and their study is automated, they manage to get a really nice sample size – about 2.5 million pull requests by men and 150,000 by women. ) requests accepted than men for all of the top ten programming languages.
They check some possible confounders – whether women make smaller changes (easier to get accepted) or whether their changes are more likely to serve an immediate project need (again, easier to get accepted) and in fact find the opposite – women’s changes are larger and less likely to serve project needs.
Most of this analysis is not original to me – Hacker News had figured a lot of it out before I even woke up this morning – but I think it’ll at least be helpful to collect all the information in one easily linkable place.
The study is Gender Bias In Open Source: Pull Request Acceptance Of Women Vs. It’s a pretty neat idea: “pull requests” are discrete units of contribution to an open source project which are either accepted or rejected by the community, so just check which ones are submitted by men vs.
women and whether one gender gets a higher acceptance rate than the other.
This is a little harder than it sounds – people on Git Hub use nicks that don’t always give gender cues – but the researchers wrote a program to automatically link contributor emails to Google Plus pages so they could figure out users’ genders.
So the big question is whether this changes based on obviousness of gender.
The study does not provide enough information to determine whether this is statistically significant.
Eyeballing it it looks like it might be, just barely. The study describes its main finding as being that women have fewer requests approved when their gender is known.
Eyeballing it, it looks about 2/3 the size of the female effect, and maybe? The study has no hypothesis for why both sexes have fewer requests approved when their gender is known, without which it seems kind of hard to speculate about the significance of the phenomenon for one gender in particular.
For example, suppose that the reason revealing gender decreases acceptance rates is because corporate contributors tend to use their (gendered) real names and non-corporate contributors tend to use handles like 133T_HAXX0R.