Why not b? Or a combination of a and b? One room for everyone, all facilities, including urinals (if you can’t survive without them), in cubicles. It drives me nuts to stand in a queue for the ladies’ room whilst knowing there are probably several loos going unused in the men’s. And if I haven’t seen anyone go in after a couple of minutes, I sometimes use the mens’

For some time I hoped the same might be true of the gauge principle, which similarly suffers from an abundance of confusing explanations,

How about politics? An unphysical degree of freedom like “how well is the surge in Iraq working”, set to different values in the Obama gauge, the McCain gauge, and the Bush gauge.

I agree.

One reason to be skeptical of using “discrimination” as an explanation is that it so often fails on closer examination, at least in the US & similar societies. For example, a decade ago it was popular to accuse banks & mortgage lenders of discrimination because they turned down black & Hispanic mortgage applicants more often than white applicants. This claim was repeated long after careful observers had noted that white applicants were turned down more often than Asian applicants. Where discrimination is involved, the truth is no defense.

Additionally, it was pointed out that the mortgage default rate was higher for blacks than for whites. This suggests that more high-risk loans were made to blacks than to whites – the very opposite of discrimination.

(What a difference a decade makes. Back then banks were accused of discrimination because they didn’t lend to high-risk applicants. Now they are accused of “predatory” lending because they did. The term “predatory” is, to put it mildly, not well defined.)

Numerous other examples can be found in labor markets. For example, it is often claimed that women make 77% as men for the same work. Actually, no.

The basis for this claim is that the median income for women who work full time is about 77% of the median income of men who work full time. But, on average, male full-time workers put in more overtime; are more likely to work outside, exposed to the weather; have fewer career interruptions; have more experience; work in more dangerous occupations; and are more likely to work in math-intensive fields. Controlling for these kinds of variables, the disparity evaporates.

Another example comes from academia. Some years ago the University of Florida was presented by the faculty union with a discrimination claim on behalf of female faculty members. The union claimed that women were underpaid some $39 million annually.

Dr. Lawrence Kenney, a professor in the economics department with a background in both labor & educational economics, conducted his own study. He controlled for variables that the union-bought study did not take into account, such as the number of publications in peer-reviewed journals. When such variables were taken into account, the alleged disparities effectively vanished.

This pattern should be enough to make anyone skeptical of discrimination as explanation for the low proportion of women in math & science. This skepticism is only enhanced by various signs of the times: Scholarships for women in “non-traditional” fields; affirmative action; the fanatical persecution of President Summers; and other, smaller examples.

As for the other explanations, I have already sketched some of the reasons for thinking that the occupational choices made by female scholars play a major role.

So, what about cognitive differences between the sexes? Well, I am not an expert in the field, but I did this article interesting.

It is obvious to many that poor people can eat as healthily as rich people, but somehow chose to eat less healthily. So the naive conclusion is that “poor people must be less health conscious” than rich people. Which is of course nonsense, but is the kind of ‘thinking-in-a-vacuum’ that can get you into wrong conclusions like these. The truth is a lot more complicated, with stress factors, depression, food availability (e.g. rich neighbourhoods have more gourmet stalls, poor ones have McD).

But you won’t believe how many well-to-do people think that the problem of obese poor people is simply that “poor people made stupid choices and hence they have nothing but themselves to blame”.

Why? Do we really want to subsidize the practice of separating infants & children from their mothers? Because once the mothers of very young children go back to work, most of the time, their children get warehoused in commercial day-care centers.

What is the goal? Is the goal to find the best students, workers, & professors at the lowest opportunity cost? Or is the goal some arbitrary standard of numerical parity?

Uhhh, paid maternity leave would be the exact opposite of separating infants and children.

Pieter Kok:

…For example, affirmative action in higher education is generally a good tool to help underprivileged groups, but it is very unfair to the (white male) student who would otherwise have made it into Harvard/Yale/etc…

In many states, and in elite schools like Yale & Harvard, whites more or less break even because of affirmative action. While more black students are admitted, fewer Asian students are admitted, and the number of whites is about the same.

However, the claim that “affirmative action in higher education is generally a good tool to help underprivileged groups” is not supported by the evidence. Students admitted under affirmative action tend to have much lower graduation rates than other students, even if they would have had very good prospects at less demanding schools. And those affirmative action students that do get degrees tend to wind up in less demanding fields, including some fields that are highly politicized.

The evidence for affirmative action programs generally is not supportive of the claim that such programs benefit target groups. For example, American blacks, as a group, made faster economic progress prior to the advent of affirmative action policies than in the decades that followed the spread of racial preferences.