The edge has a debate “on the research on mind, brain, and behavior that may be relevant to gender disparities in the sciences, including the studies of bias, discrimination and innate and acquired difference between the sexes”. The debate is between Steven Pinker, the Johnstone Family Professor in the Department of Psychology at Harvard University, and Elizabeth S. Spelke, Berkman Professor of Psychology at Harvard University, where she is Co-Director of the Mind, Brain, and Behavior Initiative.
PINKER: These are two Gaussian or normal distributions; two bell curves. The X axis stands for any ability you want to measure. The Yaxis stands for the proportion of people having that ability. The overlapping curves are what you get whenever you compare the sexes on any measure in which they differ. In this example, if we say that this is the male curve and this is the female curve, the means may be different, but at any particular ability level there are always representatives of both genders….
There are some important corollaries of having two overlapping normal distributions. One is that a normal distribution falls off according to the negative exponential of the square of the distance from the mean. That means that even when there is only a small difference in the means of two distributions, the more extreme a score, the greater the disparity there will be in the two kinds of individuals having such a score. That is, the ratios get more extreme as you go farther out along the tail. If we hold a magnifying glass to the tail of the distribution, we see that even though the distributions overlap in the bulk of the curves, when you get out to the extremes the difference between the two curves gets larger and larger.
For example, it’s obvious that distributions of height for men and women overlap: it’s not the case that all men are taller than all women. But while at five foot ten there are thirty men for every woman, at six feet there are two thousand men for every woman. Now, sex differences in cognition tend not to be so extreme, but the statistical phenomenon is the same.
A second important corollary is that tail ratios are affected by differences in variance. And biologists since Darwin have noted that for many traits and many species, males are the more variable gender. So even in cases where the mean for women and the mean for men are the same, the fact that men are more variable implies that the proportion of men would be higher at one tail, and also higher at the other. As it’s sometimes summarized: more prodigies, more idiots.
With these statistical points in mind, let me begin the substance of my presentation by connecting the political issue with the scientific one. Economists who study patterns of discrimination have long argued (generally to no avail) that there is a crucial conceptual difference between difference and discrimination. A departure from a 50-50 sex ratio in any profession does not, by itself, imply that we are seeing discrimination, unless the interests and aptitudes of the two groups are equated…
Now, all we need to do to explain sex differences without invoking the discrimination or invidious sexist comparisons is to suppose that whatever traits I have that predispose me to choose (say) child language over (say) mechanical engineering are not exactly equally distributed statistically among men and women. For those of you out there — of either gender — who also are not mechanical engineers, you should understand what I’m talking about.
Okay, so what are the similarities and differences between the sexes? There certainly are many similarities. Men and women show no differences in general intelligence or g — on average, they are exactly the same, right on the money. Also, when it comes to the basic categories of cognition — how we negotiate the world and live our lives; our concept of objects, of numbers, of people, of living things, and so on — there are no differences.
Indeed, in cases where there are differences, there are as many instances in which women do slightly better than men as ones in which men do slightly better than women. For example, men are better at throwing, but women are more dexterous. Men are better at mentally rotating shapes; women are better at visual memory. Men are better at mathematical problem-solving; women are better at mathematical calculation. And so on.
But there are at least six differences that are relevant to the datum we have been discussing. The literature on these differences is so enormous that I can only touch on a fraction of it. I’ll restrict my discussion to a few examples in which there are enormous data sets, or there are meta-analyses that boil down a literature.
It turned out to be a very good debate with both sides giving strong support for their views. Everything from stereotypes to the SAT-M was discussed. While, ultimately, I think Pinker did overall better, the debate has such a wealth of information that people on both sides of this debate are guaranteed to learn something new. ATSRTWT
Link via Duke University professor of political science Michael Munger, who has more on the topic.