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.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.It hides on page 16 that men also have fewer requests approved when their gender is known.It describes the effect for women as larger, but does not report the size of the male effects, nor whether the difference is statistically significant.The paper doesn’t give a lot of the analyses I want to see, and doesn’t make its data public, so we’ll have to go with the limited information they provide.
Among insiders, women do the same as men when gender is hidden, but better than men when gender is revealed.
And suppose that the best people of all genders go to work at corporations, but a bigger percent of men go there than women.
Then being non-gendered would be a higher sign of quality in a man than in a woman.
That makes their better performance extra impressive.
So the big question is whether this changes based on obviousness of gender.