This alone can’t rule out that one gender is genuinely doing something differently than another, so they had another neat trick: they wrote another program that automatically scored accounts on obvious gender cues: for example, somebody whose nickname was Jane Smith01, or somebody who had a photo of themselves on their profile.By comparing obviously gendered participants with non-obviously gendered participants whom the researchers had nevertheless been able to find the gender of, they should be able to tell whether there’s gender bias in request acceptances.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.
Another day, another study purporting to find that Tech Is Sexist.
Since it’s showing up here, you probably already guessed how this is going to end.
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.
Once again, it’s hard to tell by graph-eyeballing whether these two numbers are within each other’s confidence intervals.