The New Neo

The article of the day is this by Cynthia Lee entitled, “I’m a woman in computer science. Let me ladysplain the Google memo to you.”

Lee is “a lecturer in the computer science department at Stanford…[with] a PhD in high-performance computing.” That “ladysplaining” bit seems to be an attempt to be cute by alluding to a popular expression, “mansplaining,” which is a feminist criticism of the way men write/think. But what is she parodying there? Feminism—because, at least as far as I know, men don’t use the expression “ladysplaining” when they’re criticizing the way women write and/or think.

Lee doesn’t appear to address what I consider the most important part of the Google incident—not the memo itself or the discussion that ensued, but the fact that its writer was fired as a result of the pressure.

I’m not going to go through the whole article point by point. Suffice to say it seemed to be ignoring the problems I discussed in a recent post on the Google flap: the difficulty of judging whether equality of opportunity exists, versus a focus on equality of outcome. This is the heart of the matter for me. Instead, Lee writes:

Regardless of whether biological differences exist, there is no shortage of glaring evidence, in individual stories and in scientific studies, that women in tech experience bias and a general lack of a welcoming environment, as do underrepresented minorities. Until these problems are resolved, our focus should be on remedying that injustice. After that work is complete, we can reassess whether small effect size biological components have anything to do with lingering imbalances.

I find this incredibly confusing. These seem to be two separate (and possibly-related) issues: how many women are in tech jobs and why there might be fewer of them than some women would like, and the environment faced by the women who already do work there. I suppose there might be a connection if you assume that the women already employed are telling the women applying for jobs not to apply because the atmosphere is so bad, but nowhere does Lee indicate such a thing is happening. So, how does she justify the fact that the first needs to be worked on before the second is tackled?

Also, the word that jumped out at me in that paragraph was “injustice.” Why is it an injustice to not be met with a “welcoming environment”? It might not be nice, or pleasant, or satisfying, or comfortable. But feeling a lack of “welcome” is hardly unjust.

What does that word “unjust” signify on the part of Lee? What is she trying to say? Is she saying that welcoming environments at work are a right? It is such a different way of thinking than the one in which I was raised—old dinosaur that I am—that I keep teasing away at it and trying to divine what it signifies. Entitlement? Demands? I can recall many many environments, at work and at school, that were not just unwelcoming but were actively hostile to women, and the idea at the time was to qualify, break through, prove your worth, and tough it out, and slowly but surely things would improve. If tech is a relatively new field that relatively few women have entered till now, wouldn’t that sequence I just listed be a better solution than the idea that a welcome mat needs to be laid out or it’s unjust?

I’ve barely scratched the surface of what’s in the Lee piece that could be food for thought. But I have a busy day/evening ahead of me, so I’ll leave that to you folks for now.

Commenter Richard Aubrey makes a point that isn’t unusual, and seems quite logical:

To say men and women differ in their capability is gender essentialism, which I am told is a Very Bad Thing.

But you need to say it in order to justify exerting effort to get more women.

However—originally, at least—the push to accept more women in any given field rested on the idea of equal opportunity, not sheer equality of outcome. Equality of opportunity is an American ideal, and it justifies trying to get more of a certain group into a certain profession if in fact there is not equal opportunity for those people in that group who are qualified.

I realize that, under the leftist drive for equality of outcome, we may have lost the important distinction between the two, or at least it’s become blurred. In other words, for a lot of people today, particularly the Social Justice Warriors among us, equality of outcome is the only important metric. Their “logic” is that, since all groups are exactly equal in capability and talents, equality of outcome is prima facie evidence of inequality of opportunity. So we must have equality of outcome in order to guarantee equality of opportunity.

But they’re not the same, of course, if in fact groups differ on average in capability and talents in a particular field. And in that little phrase “on average” lies the heart of the matter. And even if groups differ on average in one capability or another, there could still be an inequality of opportunity that would be desirable to address. The question is how to measure it and how to address it.

One problem with this whole topic is that it’s extremely difficult to tease out the influence of nature and nurture, and so it’s very hard to know whether any observed or measured average differences between groups are due to nature or to nurture. That’s a biggee right there, and I’m not going to get into all the evidence either way except to say that I’ve read tons about it and don’t see an answer. But another large and important point is that we are only talking about average differences. There is a tremendous amount of overlap.

There are a few arenas in which there is no overlap. For example, if there was a job where, for some strange reason, the qualification included having given birth physically (I can’t think of such a job offhand, but it’s not outside the realm of possibility), it would of course be limited to women. For a job in which incredible upper-body strength was needed, it would be limited to strong men and the infinitesimal number of Amazonesque women who could meet that standard. But most jobs don’t have that kind of either/or set of qualifications. Most jobs have qualifications that some people of each sex can fill.

As a hypothetical, however, let’s say there’s a job for which the qualifications are more likely to be met, on average, by men. Let’s say, however, that there is a fair amount of overlap and that quite a few women are up to the task as well (the sexes could be reversed, depending on the job and its qualifications). Let’s also say that there are almost no women employed in that field. One could still say that the number of women in the field should be increased in the interests of fairness and non-discrimination.

The problem is that if we don’t use absolute parity of numbers as the way to measure non-discrimination, we’re in a gray area where we don’t know what the right numbers would be. Whether we’re talking about women or any other group against which there is a history of discrimination in jobs, how can we judge when enough redress is enough?

I think part of the ill will going around these days is that, particularly where hiring women is concerned, a lot of people feel that enough is enough, and that for many years now there’s been a preference for women, a preference that is not only unfair to men but has also resulted in the loosening and lessening of standards. This tends to be true of all preferences designed to combat previous discrimination.

I’m old-fashioned, and I believe that the way to end discrimination against a group is to end discrimination against that group, rather than to institute reverse preferences or to lower standards. The problem with that idea, though, is how to make it happen without instituting such preferences, and how to measure whether a disparity of outcome for groups in any given field is the result of actual discrimination or of natural differences on average in interests and aptitudes.