+1, thanks for writing this. The male/female ratio seems unusually bad around forecasting for some reason. It seems clearly suboptimal, I’m really curious how to best change that.
Just conjecturing here but I think one reason the ratio is worse than it has to be is perhaps because EA jobs are usually somewhat atypical so it is difficult to figure out if you’re actually qualified (compared to more “normal” jobs) which makes people who have a tendency to feel underqualified even less likely to apply. Plus because the community is small and a lot of people hear about opportunities / get encouraged to apply to things via people in their social networks, and people are less likely to have these social connections if they are from a currently underrepresented group.
I also think mentorship programs are helpful. One-off or series of calls with a more experienced person are helpful for promising people (regardless of gender or other demographics) who don’t have friends or social connections already in a field to figure out how to enter it.
This is just speculation, but maybe this is also why women are less likely to participate in forecasting tournaments? It does take a certain level of confidence / arrogance to see a question about e.g. NATO expansion and think “Yeah, of course I can come up with a prediction on that”.
I think it is very good that FRI is looking to create a diverse team, but I also think that forecasting has a pipeline problem where the participants in tournaments seem to be overwhelmingly male. Maybe they are also the kind of organization that could do some work on figuring out why this is the case and what we can do to solve this?
I don’t think participants in the Good Judgment tournaments that IARPA sponsored back in the day were overwhemingly male. From memory, women were about 30% of the forecaster pool, which isn’t too bad, and really quite good when you compare to other nerdy online things like editing Wikipedia.
“women were about 30% of the forecaster pool” and “80% of research analyst applicants were male” aren’t very far apart, especially since the former is from memory and the latter is a small sample.
(I did a bit of looking trying to find the gender breakdown of Good Judgement Project volunteers, without success)
+1, thanks for writing this. The male/female ratio seems unusually bad around forecasting for some reason. It seems clearly suboptimal, I’m really curious how to best change that.
In the past, comments like Tegan’s post have been useful for getting me to apply to things.
Another thing that I liked was when a job post had a comment at the bottom saying that women and minorities are less likely to feel qualified to apply to things, mentioning something along the lines of this https://hbr.org/2014/08/why-women-dont-apply-for-jobs-unless-theyre-100-qualified and encouraging them to apply.
Just conjecturing here but I think one reason the ratio is worse than it has to be is perhaps because EA jobs are usually somewhat atypical so it is difficult to figure out if you’re actually qualified (compared to more “normal” jobs) which makes people who have a tendency to feel underqualified even less likely to apply. Plus because the community is small and a lot of people hear about opportunities / get encouraged to apply to things via people in their social networks, and people are less likely to have these social connections if they are from a currently underrepresented group.
I also think mentorship programs are helpful. One-off or series of calls with a more experienced person are helpful for promising people (regardless of gender or other demographics) who don’t have friends or social connections already in a field to figure out how to enter it.
This is just speculation, but maybe this is also why women are less likely to participate in forecasting tournaments? It does take a certain level of confidence / arrogance to see a question about e.g. NATO expansion and think “Yeah, of course I can come up with a prediction on that”.
I think it is very good that FRI is looking to create a diverse team, but I also think that forecasting has a pipeline problem where the participants in tournaments seem to be overwhelmingly male. Maybe they are also the kind of organization that could do some work on figuring out why this is the case and what we can do to solve this?
I don’t think participants in the Good Judgment tournaments that IARPA sponsored back in the day were overwhemingly male. From memory, women were about 30% of the forecaster pool, which isn’t too bad, and really quite good when you compare to other nerdy online things like editing Wikipedia.
“women were about 30% of the forecaster pool” and “80% of research analyst applicants were male” aren’t very far apart, especially since the former is from memory and the latter is a small sample.
(I did a bit of looking trying to find the gender breakdown of Good Judgement Project volunteers, without success)