The Google memo isn’t sexist or anti-diversity, it’s science

This defense of the "manifesto" is flawed just like the others. It picks out a small subset of the claims made in the document, discards the context and all the other claims, and then harangues us for having a problem with "science". I could argue "water is composed of two hydrogen molecules and one oxygen molecule, so women are bad at software development", and my argument would just be a difference of degree worse than hers.

We can talk straightforwardly about what makes the document problematic: whatever the validity of the "scientific" claims it makes about gender differences, there is no support (and likely no validity) to the connections it then makes to software development work. Despite that unjustified leap, the document goes on to suggest strongly that women working at Google are less qualified than men. There is no science Debrah Soh can cite to back up that assertion, however much she might want to.

Anyone can wrap an incendiary statement up in a pile of banal sentiment and ambiguous appeals to social science. When challenged, refocus the debate on the truisms and the footnotes and pretend you didn't write the nasty stuff you hid in the middle. And, as we can see, plenty of very smart people will fall for the trick.

Gender equity has been improving in the United States for several generations. As that has occurred, female participation in STEM fields (and in the professions, like medicine and law) has expanded dramatically. Many science fields are now approaching parity. Most have more than twice as much participation as computer science. That includes the field of mathematics, which is closely related to computer science and is certainly more intellectually challenging than "computer science" as practiced in the industry.

Among all STEM fields, computer science is distinguished for losing the participation of women over the last 10 years.

Unless the women of 1950 are somehow biologically different from those of 2017, the author's theory will somehow have to address the fact that her argument would have predicted the fields or law, medicine, biochem, mathematics, astronomy, statistics, accounting, and actuary would all be bereft of women over the 20th century --- obviously, the opposite occurred, despite the sexual revolution that was immediately to come.

The author of this article discusses a correlation between increasing gender equity and decreased STEM participation that does not appear in the evidence. There's a reason she does that: if you don't stipulate that correlation, the argument against gender bias in computer science has to confront another damning fact, which is that gender disparity in the field isn't global. Unless women in Asia are somehow biologically different than those of the US, her argument needs some way to address the fact that women make up the majority of STEM majors in many of those cultures.

Reading this article and then this thread, I find that there's really only two aspects of it that HN finds persuasive: the headline's appeal to "science", and the footnote observing that the author is a female scientist. That's not enough. Everything in between those things is wildly off.

In discussions about gender parity in CS, the word "preference" is a coded appeal to the Just World Hypothesis. There is a yawning chasm between neuroscience findings about "agreeableness" and "stress tolerance" and suitability for any particular kind of white-collar symbol-manipulation work. Ms. Soh must intuitively understand that, but mentions it not once in her piece, instead pretending that observations about the kinds of toys children play with allow us to reflect participation statistics directly into real preferences about work. Shenanigans.

Human brains simply aren't very good at thinking statistically. You can say something totally factual and benign, like, "Most nurses are women" and someone will immediately chime in, "My uncle is a nurse!" It happens every time. It's practically a law.

We're good at noticing patterns and exceptions to those patterns, but, for whatever reason, we're just not good at distinguishing statements about populations from statements about individuals. For most people, breaking this intuition takes a lot of education and training.

So, yeah, you shouldn't really be surprised when some random person on Twitter fails to grasp the argument. It's disappointing, but it shouldn't be surprising.

> just how does that itself prescribe that we should stop pushing for an expansion there?

You are the only one being "prescriptive". If a class of people doesn't prefer (in aggregate) to do the kinds of work you want them to do, what right do you have to insist that it is better for them if they are forced to do this work? When did it become feminist to lecture women about the sort of work environment they should want?

You write as if you know what is best for society, yet where do you get this knowledge? It seems to me you do not even understand the points you are criticizing. The author of the Google piece was arguing that Google should change its work environment if it is serious about changing its workforce composition. He didn't tell women what they should want or how they should behave -- you are the only one doing that.

I have a question to further this debate.

Would people consider it sexist to administer a completely automated test of technical and personality questions which was used by an unbiased program to hire only the best qualified candidates?

What would you say if the results were essentially the same as the status quo?

By the Article's Author's account, she believes that we would probably maintain the status quo with such a test, because she thinks people are self-selecting out of STEM. Others seem to think that there is some other barrier to entering -- would a test like this fix the issue, or is there something else going on?

The manifesto didn't stop at citing statistics.