What about the size effect in figure 11 ? What is the Cohen’s d for the gendered outsiders ?

I read in your study : “For outsiders, while men and women perform similarly when their genders are neutral, when their genders are apparent, men’s acceptance rate is 1.2% higher than women’s (χ2(df = 1, n = 419,411) = 7, p < .01).”

For outsiders, we can see that the acceptance rate for women is 0....

Can anyone help me to get github dataset. I want it for my research work. From the dataset, I would extract users' profile data, users' acceptance rate, merging rate, and how often a user makes contributions? And is there a way to extract data from the dataset which identifies leaders of each project in a community?

This is a very interesting study and I really like the idea of using GitHub data. I have a question regarding the effect of gendered vs gender-neutral avatars. One of your conclusions is that female outsiders experience gender bias. However, this conclusion seems to rest on the assumption that female coders with gendered avatars are as competent as female coders with gender neutral avatars. Di...

Gender -- whether determined by user ID or picture -- seems to be aggregated. Is there any disparity between treatment of accounts where the gender was determined by the picture versus the user ID?

The analysis in the paper seems to assume that people who choose to have gender-evident avatars or users IDs are a representative sample. Has this assumption been analyzed? I noticed from another answer that there's a large disparity between the proportion of women who choose to be gender-evident on...

You do understand that the premise of this is completely false? That an evaluation of how many pull requests are accepted/rejected is of no value at all of it doesn't consider why the request was accepted/rejected. ie was it rejected because of bad coding, or because it didn't fit with the project aims and/ethos. For example anyone of those rejected pulls (from either gender (identifiable or not)...

From my understanding of your methodology, you consider a profile that does not have a Google+ account as a gender-neutral account. How do you account for these "gender-neutral" profiles that have a profile picture that allows others to visually identify their gender?

You describe how you categorized profiles. But I imagine that lots of people sign their Pull Request with their name (as I do), so the Pull Request itself may signal information. Have you looked at those?

Do you have any data on the percentage of active male developers who contribute to open source projects compared to active female developers? "Active" here meaning working on independent projects or the like but not actually contributing to anything open-source? I think it would be interesting to see the percentage of women who contribute to open source, and their relative skill levels, compared t...

I'm guessing you don't have this data, but we'd be particularly interested in knowing whether the situation changes when you check for age. We ask because a discussion centred around your findings raised the idea that perhaps technical users who joined BBS/Internet/Online communities earlier (80s, 90s) tend towards abstract names (less gender-identifiable), partly as a result of the culture at the...

I was wondering if the difference in pull request acceptance rates by gender could be accounted for by the relative percent of profiles that are gendered for women versus men? You mention in the article:

...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 me...

Figure 5 shows the acceptance rate of Github pull requests based on:

1. Whether the person was an "insider" vs an "outsider" to the project
2. Whether the person was actually a man or a woman (based on linkages between github information and publicly-available social media information)
3. Whether the github account had gender-identifiable information in it (gender-neutral vs gendered).

You c...

Curious if this bias is predominantly men rejecting PRs from women, or if it also extends to women who review PRs.

Would you share your scripts/programs for the tasks described in the appendix? Your GitHub scraping tool, your data analysis pipeline, the data you generated?

You repeatedly display column (bar) graphs with truncated axes. This is well established to be a cognitively problematic visualization type: the “amount of ink” on a page projects sizes and draws attention.

At the same time, many of the points you are trying to convey really should have the kind of focus your truncated axes produce -- small enough but clearly significant variations that they wo...

tl;dr: are the results really as surprising as the text suggests?

You state

prior work on gender bias in hiring – that women tend to have resumes less favorably evaluated than men (5) – suggests that this hypothesis may be true.

and immediately after

The hypothesis is not only false, but it is in the opposite direction than expected; _women tend to have their pull requests accepted...