(I recognize this diary is redundant after JD’s, but I thought it important to promote a woman’s perspective in specific response to this odious trial balloon. Sigh. No rest for the weary, I suppose… – promoted by odum)
upon hearing Lawrence Summers’ name was, “Oh for Christ’s sake! Summers is a fucking idiot!”
Hack is too nice a word. He is a shining example of excelling past one’s Peter Principle courtesy of the privileges of unearned wealth. He is the very embodiment of the vaunted moron who achieves undeserved status simply because Daddy was able to pay full fare for his trip through the Ivy Leagues. He’s just like the rest of the extraordinary dullards whose “brilliant” financial “skills” have brought the world to its knees with the ponzi scheme to beat all ponzi schemes.
His prejudices about women and minorities got him booted from the hallowed halls of Hahvahd. His lack of ability to do even the most rudimentary critical thinking about monetary policy and the long term side effects thereof is legend.
My follow-up reaction to the short list was feeling my heart sink to the bottom of my stomach when I realized the entire list comprises such fools. They all either helped architect the financial massacre, or are sympathetic to the precepts and people who got us here.
If any one (or any combination) of them is tasked with bringing our death-spiraling world economy out of its tailspin, we, the “human element” will remain destitute for a whole lot longer than necessary – many years, in fact.
If these idiots are put in charge, we’ll probably only get out from under the train-wreck through brute force after food and fuel shortages combined with a complete lack of basic medical care kill enough people that the remainder are finally left to choose between violent death through fighting for justice and sustenance, or slow death through starvation.
I’m not kidding.
One need not look any further than any 3rd world country that has been subject to the “aid” of the economic hit men running the IMF and World Bank for examples.
The IMF has done a “Chapter 14 Consultation” for the US, and recommended austerity measures, couched in “reasonable” sounding terms: like ending “unsustainable social programs” and stabilizing the housing and financial industries.
We are deep, deep in the woods, and the wolves are circling.
If he chooses wrong, our President-elect will be handing them all a great big EZ-READ map so they can find us that much more easily.
I’ll reserve judgment … until the day my child goes to bed hungry because we can’t get or afford food, and it’s clear that that most subsequent days will be similar. Then I will sharpen up the tines on the pitchfork, light the torch, and call for their heads.
I hope the President-elect chooses a different course.
In response to the old canard that
He was making the valid scientific point that when considering explanations for how to explain the disproprotionate success of men in the sciences all possible explanations need to be on the table.
My reply:
He was asked to be provocative, but he didn’t simply make some offhand remarks, he did research and presented it. Pardon the long quote, but it’s the whole crux of his argument:
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. Now, it’s pointed out by one of the papers at this conference that these tests are not a very good measure and are not highly predictive with respect to people’s ability to do that. And that’s absolutely right. But I don’t think that resolves the issue at all. Because if my reading of the data is right-it’s something people can argue about-that there are some systematic differences in variability in different populations, then whatever the set of attributes are that are precisely defined to correlate with being an aeronautical engineer at MIT or being a chemist at Berkeley, those are probably different in their standard deviations as well. So my sense is that the unfortunate truth-I would far prefer to believe something else, because it would be easier to address what is surely a serious social problem if something else were true-is that the combination of the high-powered job hypothesis and the differing variances probably explains a fair amount of this problem.
Or in English:
He calculated that there is a 5 – 1 ratio of men to women who have the highest aptitude levels for the skills required for the math-heavy fields, such as physics, chemistry, and economics.
He outright dismisses cultural effects and biased testing, despite the research presented at the same conference showing that both were significant.
He presented lack of aptitude as one of the 3 reasons women don’t excel: Lack of willingness to work hard enough, lack of high end aptitude, and cultural influences pushing girls away from the sciences.
– He admitted that requiring insane hours for advancement (80 hrs/wk) could be considered a bad thing.
– He dismissed cultural effects and testing bias by claiming that they were really reflections of genetic abilities – outright dismissing boatloads of studies to the contrary, some of which had been presented earlier at the same conference.
– He focused his lecture on the concept that when you get further and further out from the norm (heading higher up the scale) on aptitude test results, the pool of women shrinks due to an innate genetic lack of aptitude. Once again, this is despite study after study showing that the tests were poorly designed and inaccurate.
There’s no defense.
Read the Q & A session for more, but here’s one telling bit:
Q: You know, in the spirit of speaking truth to power, I’m not an expert in this area but a lot of people in the room are, and they’ve written a lot of papers in here that address ….
LHS: I’ve read a lot of them.
Q: And, you know, a lot of us would disagree with your hypotheses and your premises…
LHS: Fair enough.
Q: So it’s not so clear.
LHS: It’s not clear at all. I think I said it wasn’t clear. I was giving you my best guess but I hope we could argue on the basis of as much evidence as we can marshal.
Q: It’s here.
LHS: No, no, no. Let me say. I have actually read that and I’m not saying there aren’t rooms to debate this in, but if somebody, but with the greatest respect-I think there’s an enormous amount one can learn from the papers in this conference and from those two books-but if somebody thinks that there is proof in these two books, that these phenomenon are caused by something else, I guess I would very respectfully have to disagree very very strongly with that. I don’t presume to have proved any view that I expressed here, but if you think there is proof for an alternative theory, I’d want you to be hesitant about that.
The response to that included:
And it does. I’m sorry if it rankles. I spent a lot of time really wanting to prove to myself that the differences are all cultural. But I can’t persuade myself that it’s scientifically responsible to just assume that it’s all cultural. When it comes to the narrow question of whether men are more likely to be mathematical geniuses, I have to say it’s entirely possible that they are. Doesn’t mean we shouldn’t make room for the women who also happen to be mathematical geniuses.
I responded with actual info, rather than, you know, a personal attempt to prove to myself that my wishful thinking could be true:
ONLY the SAT-M shows a difference in the tail, implying that it’s gender bias in the testing.
Long term studies of male and female children, including studies focused specifically on the high end of the tail show that there is NO difference.
Although boys outnumbered girls at the upper tail of the SAT-M, the SMPY girls got better grades in high school mathematics, as they have in less selected samples. In college, male and female SMPY veterans continued to take equally demanding classes and got equally good grades, as do college women and men generally. They also graduated at equal rates and obtained an equal number of doctoral degrees (Lubinski & Benbow, 1992; Lubinski et al., 2001; Webb et al., 2002)
In one SMPY cohort, for example, 10.3% of men and 9.7% of women received bachelor’s degrees in mathematics, and 2.2% of men and 2.1% of women went on to receive master’s degrees in mathematics (Benbow, Lubinski, Shea, & Eftekhari-Sanjani, 2000).
…
The conclusion from these findings is clear. Although most SMPY students with high scores on the SAT-M are male, male and female veterans of that program learn advanced mathematics at equal rates and with equal success. If one gauges students’ talent at mathematics by their successful mastery of the demanding material required of college mathematics majors, one will conclude that men and women have equal aptitude for mathematics, not only in the general population of college students but in selected samples of students with high talent.
…
If the genetic contribution were strong, however, then males should predominate at the upper tail of performance in all countries and at all times, and the male-female ratio should be of comparable size across different samples. Contrary to this prediction, the preponderance of high-scoring males is far smaller in some countries (e.g., Deary et al., 2003) and altogether absent in others (Feingold, 1994). Moreover, the preponderance of boys with high scores on the SAT-M has declined substantially in U.S. samples. In one sample of students selected for high talent, it declined from 10.7:1 in the 1980s to 2.8:1 in the 1990s (Goldstein & Stocking, 1994).
Just as the Bell Curve attempted to gloss over racism with pseudo science, Summers and his defenders have tried to paper over gender discrimination with the same worn out the eugenic arguments.
From the standpoint of intelligence, aptitude, etc., the female “bell” is is just as wide as the male “bell.”
I am sick and tired of people making excuses for discrimination, just because the discriminator has a “name” and likes to promote cherry-picked data to support the discriminatory claim.
Summers is a prejudiced old dolt and needs to be kept far away from any position that will influence policy.