When reading through the paper a few specific parts of it felt problematic for me
More specifically, we find significant gender gaps in activity: women are more likely to ask questions, while men provide more answers and cast more votes.
Which I guess could be an observation, but I didn't really find a great reason for the why and how we can help women actually fill that gap. Cause I'm pretty sure gender isn't a barrier to knowledge.
Using the Oaxaca-Blinder decomposition (Oaxaca 1973), a method from economics that to the best of our knowledge has not yet been previously applied to measure gender disparities in online communities, we decompose the outcome differences between men and women in terms of differences in their activity.
This bit is interesting. Unfortunately I'm not smart enough to actually get what Oaxaca-Blinder decomposition is, though since its novel to this application - I'm a little skeptical.
In the final part of the paper, we explore the consequences of a hypothetical redesign of the site’s reward system. The proposed alternative scoring system equalizes the rewards for well-liked questions and answers, a simple and justifiable change which does not penalize any group of users in absolute terms.
This sounds shiny.
Stack Overflow is itself a well-studied platform. Vasilescu et al. show that women are underrepresented in this community (Vasilescu et al. 2013). Interviews with a sample of Stack Overflow users highlight the barriers women have to greater participation. Women respondents listed the lack of awareness of some site features, the intimidating community size and their fear of lacking adequate qualifications as main barriers to participation (Ford et al. 2016).
Now this literally is a problem worth solving IMO. Why are these barriers there? How do we mitigate them? Getting engaged users is essential if you want a constant, vibrant representation of a specific segment of the community
Now the big problem I have with this paper
"We found that while the method performed very well on men (97% agreement with our manual check), our manual check agreed only in 44 out of 100 cases of women. This replicates the recent finding by Ford et al. (2017) that genderComputer sacrifices precision for greater recall when inferring women users."
They did run further rounds - but that also means that feels like selecting for women who use obviously female names, and men who use obviously male names. This basically doesn't select for anonymous users - and someone uncomfortable with being identified by their gender would do that or use an ambiguous name
Here's the frustrating part. I can't share more. Unlike our rogue moderator - I do respect the sanctity of folks trusting you not to share things.
Its worth considering, this wasn't in the final announcement. At best it was one of many things considered both in internal messaging and for external messaging.