[said]

Do you believe the vast physical differences between men and women end at the brainstem? Do you believe the flood of sex hormones during puberty don't result in different mental tendencies, including tolerances to rejection? Do you believe the different ratios of neurotransmitters between men and women across all cultures and haplogroups are a result of culture?

Before we explicitly institutionalize discrimination against men and boys to correct nebulous discrimination against women and girls, we must really make sure:

1. We aren't ignoring potential opportunity costs

2. We are okay with the fact that our policies will hurt disadvantaged men and boys the most

[geofft]

I certainly believe there are physical differences between (biological) men and women, in aggregate across men and women. I do think that the standard deviation is very high, though; I don't think that the vast physical differences make all men more suited to a task than all women, any more than all men are taller than all women.

And I think that defining particular "mental tendencies" as favorable or unfavorable to success in computing is a very difficult task. I do a lot of things at work; I figure out how to do a dynamic library upgrade smoothly, I work with other people to figure out what sort of capacity requirements their application needs, I Google for an answer to a problem I'm having, I report a bug when nobody else seems to have done so, I respond to a page and figure out what broke as quickly as possible, and I enter flow state and work on some algorithmic thing for an hour or so. It seems unlikely to me that I'm good at all these things, let alone that everyone of a certain gender is.

To say that men are better at programming because of some male-genetic-linked mental tendency seems as ill-reasoned as saying that men are better at cooking because we're taller and can reach the top shelf.

For 1, I believe in other people's agency. If someone says "I want to be part of this industry, but these are the reasons I'm being pushed out," I'm inclined to believe them on both fronts. If they say "I would rather join this other industry," I'm not going to try particularly hard to convince them they're wrong.

For 2, that doesn't seem plausible to me; won't it hurt disadvantaged women and girls even more?

[Shubley]

Let's compare this to height as you did.

Because of how gaussian distributions work, the differences at the outlying values are huge even for small differences in the average.

For example, men are taller than women in general, but of course some men are taller than some women.

But at the extreme heights, the ratio between men and women becomes stagger. At 6 feet tall, men outnumber women 30:1. At 6'3", 2000:1.

Now apply this to tech. If we imagine a relatively elite job, like being a professional programmer with significant responsibility, that is the kind of thing only someone at the extreme end of the bell curve of tech-proclivity is going to do. But because of the way gaussians work at extreme values, even if women on average have similar tech-proclivity to men, at that high level the ratio of men:women could be huge.

All this could just be due to a simple misunderstanding of the math of a bell curve distribution and how it works at the ends of the spectrum.

[geofft]

Sure. But the point of the height analogy was that, first, you don't need to be 6'3" to reach the top shelf of a kitchen, and second, there are so many skills required to cook, not just reaching the top shelf.

In the same way, even if we assume that women have a lower bell curve than men for, say, ability to focus on some algorithmic problem, first, you don't need to be the equivalent of 6'3" at algorithms to do a good job as a professional programmer, and two, algorithms is only a very small part of what you do.

For the bell-curve hypothesis to work for cooking, women would also have to be weaker at using knives, worse at visually comparing the volume of liquids, worse at keeping track of time, worse at tasting things for flavor balance, etc. etc. - every single one of these axes would need to have a bell curve lower for women than for men. That's just implausible. Same with programming.

Of course, if you set up your hiring / recognition processes to look for the 6'3" algorithmists and not for the 5'10" algorithmists or the people who do any of the other work than algorithms, you'll see a 2000:1 ratio. But I think that's a sign of the hiring and recognition process failing to find truly qualified candidates of any gender, and just using the easiest metrics instead of the best ones.