Yep...

here. Finally. (via

Kevin Drum)

The first thing that struck me, assuming this is a reasonably faithful transcription, is that the guy sucks at speaking. He's horribly obtuse, rambling, and unclear. He also seems to have the propensity to hide behind academia-speak, rather than just come out and say what the hell he means. It's all well and good to talk about standard deviation of divergent sampling methodologies, but then give us a friggin, "In other words...", or "What this means is...".

Let's take Summers' 2nd reason why there aren't many women in science and engineering. What he calls the "different availability of aptitude at the high end". Though when he starts out talking about this second point, he can't even spit the words out:

The second thing that I think one has to recognize is present is what I would call the combination of, and here, I'm focusing on something that would seek to answer the question of why is the pattern different in science and engineering, and why is the representation even lower and more problematic in science and engineering than it is in other fields.

Wha-huh? The second thing is...what, Larry? It takes him wandering all over the fuggin place before he actually sorta kinda says it:

And here, you can get a fair distance, it seems to me, looking at a relatively simple hypothesis. It does appear that on many, many different human attributes-height, weight, propensity for criminality, overall IQ, mathematical ability, scientific ability-there is relatively clear evidence that whatever the difference in means-which can be debated-there is a difference in the standard deviation, and variability of a male and a female population. And that is true with respect to attributes that are and are not plausibly, culturally determined. If one supposes, as I think is reasonable, that if one is talking about physicists at a top twenty-five research university, one is not talking about people who are two standard deviations above the mean. And perhaps it's not even talking about somebody who is three standard deviations above the mean. But it's talking about people who are three and a half, four standard deviations above the mean in the one in 5,000, one in 10,000 class. Even small differences in the standard deviation will translate into very large differences in the available pool substantially out. I did a very crude calculation, which I'm sure was wrong and certainly was unsubtle, twenty different ways. I looked at the Xie and Shauman paper-looked at the book, rather-looked at the evidence on the sex ratios in the top 5% of twelfth graders. If you look at those-they're all over the map, depends on which test, whether it's math, or science, and so forth-but 50% women, one woman for every two men, would be a high-end estimate from their estimates. From that, you can back out a difference in the implied standard deviations that works out to be about 20%. And from that, you can work out the difference out several standard deviations. If you do that calculation-and I have no reason to think that it couldn't be refined in a hundred ways-you get five to one, at the high end.

I wouldn't have necessarily walked out because I was offended. I would have walked out because the guy's so g-damned obtuse.

But here's what the guy is actually saying...

In other words, what this means is: In the average range of talent, the difference between men and women isn't that great. It's only at the high end where women are much dumber than men.

Good grief this guy is a doofwad. But at least they released a transcript. Have a look for yourself, if you can possibly wade through it.