| > Kinda looks like the submission process was biased. While skewed outcomes can make you suspect bias, they simply are not sufficient evidence to conclude that there is bias. For example, around 50% of the population is male. Yet 0% of all births are to males. Obvious discrimination against male fathers! Silly me, no, of course not bias. There is some other factor at work. Or take the 100m dash as Olympic discipline, or in fact most of the track and field running events. Extreme racial skew. Bias? And no, I am not saying that these same factors are at work here, just that you cannot conclude bias from unequal outcomes. In fact, as far as I know the science, it would be exactly matched outcomes that would actually be highly suspect. See also: Simpson's Paradox ( https://en.wikipedia.org/wiki/Simpson%27s_paradox ). Again, not saying that this is an instance of Simpson's paradox, but definitely saying that just because something looks like bias when superficially examining outcomes, that does not at all mean that bias is the actual cause. And of course there are a lot of potential reasons why there would be a skew, many of which have been identified as fairly reliable gender differences, including willingness to take risks, > 10% of OSS software programmers are women The numbers I found were lower, more in the 1-5% range, skewing toward the lower end: https://www.techrepublic.com/blog/software-engineer/it-gende... https://link.springer.com/chapter/10.1007/978-3-319-39225-7_... https://www.itprotoday.com/linux/gender-roles-search-open-so... To sum up, your argument is flawed for at least 3 reasons: 1. Your numbers for the baseline are wrong 2. Your assumption that any skew in outcomes proves bias is wrong 3. You ignore actual gender differences that can explain different outcomes |