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The observation precisely follows the flow of power. See my other comment.

> Academic sciences also have large gender disparities; physics has very few women, while biology has lots.

Academia is less interesting to begin with because there is little difference in the power held by different fields (certainly between physics and biology today). Participation can therefore depend on many factors (perhaps side-products of some other process) that people have little interest to examine or change. Those differences are no different from the high participation of women relative to men in ballet dancing. It's hard to pinpoint the causes, and there's little reason or urgency to study them because there's little power imbalance involved (there is more funding directed to studying more serious diseases than less serious ones, unless there's some other good reason to study the less harmful ones).

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There is plenty of reason to study them; they provide validation/rejection of our theories.

If you claim that "power" drives everything, yet fields with no power difference have disparities which directly mirror the disparities you claim are driven by "power", that suggests there is an underlying theory that doesn't use power at all and which predicts more things.

By Occams razor, the latter theory is the one which should be used.

> There is plenty of reason to study them; they provide validation/rejection of our theories.

That's not always enough to fund sufficient research, especially as those avenues of research show no more promise in uncovering a more fundamental model or validating/rejecting theories better than the ones that are currently explored.

> yet fields with no power difference have disparities which directly mirror the disparities you claim are driven by "power", that suggests there is an underlying theory that doesn't use power at all and which predicts more things.

If only you were right about the facts then your (unique, I must say) theory -- which I can only guess at[1] because you won't state it clearly -- would merit a closer look, but you're not. You are equating existence of bias with existence of bias, but with no regard to effect size. Here are the facts: http://www.randalolson.com/2014/06/14/percentage-of-bachelor...

CS participation was the same or higher than math and physics, and now it's significantly lower. The difference today between participation in math and physics vs CS (and engineering) is far higher than the relative difference between biology and physics. Indeed, it is higher than the relative difference between English and physics.

The social power theory is currently the only theory that has enough evidence to support it, and it gathers more evidence every day, which is why it is the (current, at least) consensus of the scientific community. Your theory (whatever it is), describes neither the observed differences in academia nor in the industry and runs counter to the body of knowledge we've accumulated about power dynamics, group behavior etc.

[1]: If your theory claims innate ability is a major cause of the difference, then it has been disproven. No differences in innate ability were found to be even in the ballpark of the participation difference we see in society. At this point in time, we can say with a high degree of confidence that innate ability is not a major explanation. Even evolutionary theories would reject ability-based explanations, as there is little reason for such huge differences in ability (way beyond difference in physical strength) in a species where the two sexes play almost identical roles (compared to, say, insects). If you have another theory, please state it.

CS participation was the same or higher than math and physics, and now it's significantly lower.

Yes - and this contradicts belorn's theory.

My theory is very simple: more math less women, with other factors being secondary. Here is Scott Alexander doing some pretty good regressions (r=-0.82, p=0.0003): http://slatestarcodex.com/2015/01/24/perceptions-of-required...

There is lots of evidence of innate ability playing a significant role in this. Here are some papers:

http://www.ams.org/notices/201201/rtx120100010p.pdf http://itp.wceruw.org/Hyde%20Science%2008.pdf http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3057475/pdf/nihm...

(Note that putting agreement with me into an abstract is career suicide, so you'll actually need to skip ahead to the data tables.)

My theory predicts % of women in academia in bio vs physics, % women in IT office work vs softer office work, % women in quant trading vs back office, and many more. Do you have any evidence at all which contradicts this?

> Yes - and this contradicts belorn's theory.

Scientific consensus also disagrees with that theory. We believe that the reason is related to power disparity not simply being a minority group.

> Here is Scott Alexander doing some pretty good regressions (r=-0.82, p=0.0003).

Except that it explains little, as women participation in all fields is rising. So while it may always be the case that you'll find that correlation with mathematical ability, it matters little, as it explains smaller and smaller differences. In fact, a low analytical writing score may correlate better than a high math score. Where things get weird is in CS, and worse: the software industry.

> There is lots of evidence of innate ability playing a significant role in this. Here are some papers...

That's not what the papers show at all. The greatest difference I spotted was twice as many boys as girls over the 99th percentile. We are talking 5x-10x participation gap in software.

Dude, you can't use Occam’s razor to select between one theory and "the idea of there being a better theory" o_0

Fine, there might be an underlying theory that explains everything better than the "power" theory, BUT YOU HAVE TO PROVIDE IT before you can argue that it is superior.

Here it is:

http://philip.greenspun.com/careers/women-in-science

Obviously this is about averages, there will be several women here to whom the theory does not apply.

That's your theory? Women participation in math and the physical sciences is extremely high relative to their participation in software, where it used to be much, much higher (same as in other professions) and is constantly declining. That decline actually coincides with increasing, rather than decreasing salaries and prestige, and is not due to increasing work hours (that are lower in software than in medicine and law, where women participation is high). Software is a very clear anomaly.

That theory is even wrong for science in general, especially considering that women participation has been increasing, and that some scientific fields -- that are just as demanding -- are actually dominated by women.

My theory is very simple: more math less women.

This predicts the % of women in academic physics relative to academic bio, IT relative to HR, and quite a bit more. Anyone who disagrees is welcome to try and find cases where this theory fails to fit the data.

Except it doesn't, unless you squint really, really hard. Finding cases where this theory fails to fit the data is too easy: women participation in physics and math is growing and is far higher than in CS, where it's declining; more women go into biology than into history (women participation in history and physics is quite similar). It also doesn't explain the low women participation in politics (again, similar to or lower than in physics[1][2]).

That you continue to believe this theory despite so much contradictory evidence is perplexing.

Also, it's a bad theory in that it's a description rather than an explanation. Even supposing it fit the data better than it does, why would it be the case that more math = less women? I mean, no one suggests that men are 5x or 8x better at math than women as direct studies clearly show it is not the case. So even if it were a good description (though it isn't) it is not the least bit explanatory. The ultimate explanation of such a theory is still likely to be social.

It is probably true that women, on average, are more empathic than men, and therefore would prefer professions that involve working with others more, but that difference is nowhere near the actual participation rates that we find, so it can't be a major explanation.

A "theory" which fits the data -- on average, of course -- much, much better than yours would be "women choose professions with less money and less prestige". This "theory" is surprisingly predictive because, amazingly enough, women choose to be paid less money than men even while doing the very same job, so it must be right.

[1]: http://www.unwomen.org/en/what-we-do/leadership-and-politica...

[2]: https://www.american.edu/spa/wpi/upload/2012-Men-Rule-Report...

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