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Screenshot - 12012015 - 10:22:42 PM

The above is from an article in Nature, A test that fails. Two stories first. One of my good friends who went to grad school at MIT got a good ribbing from his roommates because he was the only one who didn’t get a perfect score on the math portion of the GRE. Luckily for him, he was a chemist, so they let him into the program. It is a truth universally acknowledged among the quantitatively ept that the quantitative GRE is just way too easy, and is compressed at the top scale and does not allow for differentiation of the good from the great. That is, there are a wide range of competencies which are bracketed among those who score a “perfect” 800 on the quantitative GRE. And there are many people in fields like physics who score 800; the average score on quantitative reasoning for those who intend to study physics in graduate school (not those who get accepted!) is in the 740s. Second, a friend of mine was complaining about the lack of underrepresented minorities in the biological sciences at my graduate school. To her surprise and irritation I just pointed out that all the underrepresented minorities within the range of GRE scores that our program takes would be going to Stanford or Berkeley. There weren’t enough of them that we’d be competitive. Data like the above is just not well known.

Another point is that the article above is very anti-GRE. They claim that the GRE score is not very predictive of ultimate outcome. One of my professors pointed to a study at University of California San Francisco (UCSF) where they tracked future successes (e.g., tenured position in academia x years out), and correlated them with GPA and GRE. Neither were very strong predictors. Rather, their Ph.D. research productivity was highly predictive. This isn’t that surprising, because GPA and GRE are just proxies to get at whether one can be a productive researcher, and being productive in graduate school is probably the best guide as to whether you’ll be productive later. But, one thing I want to point out is that UCSF is a very selective school. The range of GRE scores in particular is likely to be narrow, because they’re going to simply not even look at applicants with low scores. Whenever people point out that MCAT or GRE is poorly correlated with professional outcomes, remember that you’ve already compressed the distribution toward the higher end. If schools allowed a much wider range of applicants in, then these aptitude tests would be much more predictive.

Screenshot - 12012015 - 11:12:23 PM In fact, the reality is that there is variation in outcomes according to general intelligence among graduate students. As I stated above, the maximum score of the GRE, especially the quantitative reasoning section, is too low to get at that. But Camilla Benbow’s group has been tracking mathematically precocious children for decades. As the data to the left shows, the smartest-of-the-smart are more likely to become scientists, and much more likely to attain tenure. The cut-off was scoring in the top 1% of their age group on the mathematical SAT test, a 390 score. You can see how much better those very rare students who score 700 or more at age 13 are doing later in life.

Finally, obviously these tests are very robust and predictive, but they’re population statistics. There are people who do not do well on the GRE who do well in academia, and vice versa. But, the reality is that these tests are not useless, and just how “not useless” they are will become more obvious if no one made recourse to them.

Addendum: My physicist friends always enjoy a chuckle whenever I honestly state that physicists are smarter than biologists, as I am a biologist. There are rare cases, such as Ed Witten, of people entering physics from other fields, but in general it’s the physicists who are the imperialists. And that’s because they’re smart, able to decompose general problems rapidly and decisively. In contrast, biologists are somewhat narrow in their focus, and plodding in their reasoning. These are generalizations, but I think they’re roughly correct (I had a friend at a prominent non-profit who was irritated with how difficult it was to find Ph.D. biologists who were flexible thinkers in interviews). And standardized tests bear out my generalization (though honestly, it is a pleasure talking to physicists and mathematicians about out of topic fields compared to biologists partly because they’re so mentally acute; you don’t need GRE stats to get this).

But, another implication of this logic is that some minority groups are also not too bright. If you don’t think these tests are accurately reflecting real intellectual skills that groups have though you don’t have to go there. And my experience is that this is a common belief, including among physicists. But then I suppose they shouldn’t get so full of themselves about their GRE scores in relation to biologists?

• Category: Science • Tags: Academia, GRE, Psychometrics 
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As an aside in a fascinating City Journal piece on educational policy, A Wealth of Words:

Vocabulary doesn’t just help children do well on verbal exams. Studies have solidly established the correlation between vocabulary and real-world ability. Many of these studies examine the Armed Forces Qualification Test (AFQT), which the military devised in 1950 as an entrance requirement and a job-allocating device. The exam consists of two verbal sections (on vocabulary size and paragraph comprehension) and two math sections. The military has determined that the test predicts real-world job performance most accurately when you double the verbal score and add it to the math score. Once you perform that adjustment, according to a 1999 study by Christopher Winship and Sanders Korenman, a gain of one standard deviation on the AFQT raises one’s annual income by nearly $10,000 (in 2012 dollars). Other studies show that much of the disparity in the black-white wage gap disappears when you take AFQT scores—again, weighted toward the verbal side—into account.

Are we surprised that high verbals can talk themselves into more generous remuneration? But in any case the power of vocabulary is why I believe that the GSS and IQ correlation is probably robust. And speaking of vocabulary, the author alludes to the now well known phenomenon that children from low socioeconomic status backgrounds tend have a much smaller vocabulary than than those from higher socioeconomic status backgrounds, and how that leads to a positive feedback loop that determines life trajectory. The main confound that comes to mind is that those from low vocab households are probably also from less intelligent households, and intelligence is heritable. But, proactive social engineering probably can break apart the gene-environment correlation at least, and dampen the variance in phenotypic outcomes.

And this is where the policy prescriptions may not be to anyone’s liking. On the one hand this social engineering is social engineering, and probably will cost money. Conservatives will not like that. But, I also suspect that much of the positive value of a non-home environment is going to be abolished as the child matures and begins to self-select peer groups from their own socioeconomic milieu. In other words you need to attack the milieu, the culture of poverty and anti-intellectualism. And I suspect many liberals will not be comfortable with the aggressive paternalism that that implies. So nothing will get done.

Addendum: Again, the best thing you can do to have smart well behaved children is to select a spouse with those characteristics.

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Psychology, Psychometrics 
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Above is the distribution of self-reported I.Q.s of the readers of this weblog according to the 2011 survey. I point this out because my friend Steve Hsu will be giving a talk at Google later today. Here are the details:

I’ll be giving a talk at Google tomorrow (Thursday August 18) at 5 pm. The slides are here. The video will probably be available on Google’s TechTalk channel on YouTube.

The Cognitive Genomics Lab at BGI is using this talk to kick off the drive for US participants in our intelligence GWAS. More information at, including automatic qualifying standards for the study, which are set just above +3 SD. Participants will receive free genotyping and help with interpreting the results. (The functional part of the site should be live after August 18.)

Title: Genetics and Intelligence

Abstract: How do genes affect cognitive ability? I begin with a brief review of psychometric measurements of intelligence, introducing the idea of a “general factor” or IQ score. The main results concern the stability, validity (predictive power), and heritability of adult IQ. Next, I discuss ongoing Genome Wide Association Studies which investigate the genetic basis of intelligence. Due mainly to the rapidly decreasing cost of sequencing, it is likely that within the next 5-10 years we will identify genes which account for a significant fraction of total IQ variation.

We are currently seeking volunteers for a study of high cognitive ability. Participants will receive free genotyping.

From what I recall of my discussion with Steve the aim here is to fish in the extreme tail of the distribution to see if that allows for an easier catchment of I.Q. upward incrementing alleles. 3 standard deviations above the mean I.Q. is about 1 out of 750 individuals or so.

(Republished from Discover/GNXP by permission of author or representative)
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In my experience most scientists are not too clear on the details of intelligence testing, perhaps because the whole area is somewhat in ill repute (except when you want to brag about your own SAT/GRE score!). This despite the fact that the profession of science is skewed toward the right end of the intelligence bell curve. Steve Hsu, a physicist at the University of Oregon (and someone I’ve known for a while in the interests of “full disclosure”) has a nice presentation up in PDF format which summarizes the major points of interest in this area. Worth a skim if you are unfamiliar. Additionally he alludes to future directions in the study of the genetic basis of intelligence using genomics. Here’s his abstract:

I begin with a brief review of psychometric results concerning intelligence (sometimes referred to as the g factor, or IQ). The main results concern the stability, validity (predictive power) and heritability of adult IQ. Next, I discuss ongoing Genome Wide Association Studies which investigate the genetic basis of intelligence. Due mainly to the rapidly decreasing cost of sequencing (currently below $5k per genome), it is likely that within the next 5-10 years we will identify genes which account for a significant fraction of total IQ variation. Finally, I end with an analysis of possible near term genetic engineering for intelligence.

This talk is aimed at physicists and should be accessible even to those with no specialized background in psychology or biology.

Also, in case you are skeptical, Steve is quite aware of the difficulties with the enterprise which he outlines in the presentation assuming that the genetic architecture of intelligence is as he assumes. As sequencing gets cheaper and the sample size of full genomes hits the tens of thousands someone will tackle this, so he and his colleagues figured why not now?

(Republished from Discover/GNXP by permission of author or representative)
🔊 Listen RSS One of the issues when talking about the effect of environment and genes on behavioral and social outcomes is that the entanglements are so complicated. People of various political and ideological commitments tend to see the complications as problems for the other side, and yet are often supremely confident of the likely efficacy of their predictions based on models which they shouldn’t even been too sure of. That is why cross-cultural studies are essential. Just as psychology has overly relied on the WEIRD nature of data sets, so it is that those interested in social science need to see if their models are robust across cultures (I’m looking at you economists!).

That is why this ScienceDaily headline, Family, Culture Affect Whether Intelligence Leads to Education, grabbed my attention. The original paper is Family Background Buys an Education in Minnesota but Not in Sweden:

Educational attainment, the highest degree or level of schooling obtained, is associated with important life outcomes, at both the individual level and the group level. Because of this, and because education is expensive, the allocation of education across society is an important social issue. A dynamic quantitative environmental-genetic model can help document the effects of social allocation patterns. We used this model to compare the moderating effect of general intelligence on the environmental and genetic factors that influence educational attainment in Sweden and the U.S. state of Minnesota. Patterns of genetic influence on educational outcomes were similar in these two regions, but patterns of shared environmental influence differed markedly. In Sweden, shared environmental influence on educational attainment was particularly important for people of high intelligence, whereas in Minnesota, shared environmental influences on educational attainment were particularly important for people of low intelligence. This difference may be the result of differing access to education: state-supported access (on the basis of ability) to a uniform higher-education system in Sweden versus family-supported access to a more diverse higher-education system in the United States.

Minnesota is to some extent the Scandinavia of America, so the cross-cultural difference is particularly notable. You wouldn’t be surprised for example by big differences between Mississippi and Sweden. But looking at a comparison between the Upper Midwest and Scandinavia is closer to seeing the impact of national culture and policy differences on populations which were originally very similar.

Their methodology was simple, though as with much of this sort of behavior genetic work the statistical analysis can be somewhat labored. In both Sweden and Minnesota you had samples of dizygotic and monozygotic twins which give you a way to compare the effect of genes on variation in life outcomes. Sweden has large data sets from male conscription for behavior genetics analysis. They compared this with the Minnesota Twin Family Study data set.

Since the topline results are pretty straightforward, I thought I’d give you some statistics. Table 1 has raw correlations. Note that they converted educational attainment into a seven-point scale, less than 9 years of education to completion of doctoral studies.


You see the expected drop off in correlation between identical and fraternal twins. Identical twins share more genetic identity than fraternal twins, so they’re going to be more identical on a host of metrics aside from appearance. Those are just raw correlation values of traits though across categories of twins. The core intent of the paper was to explore the relationship between genes, family environment, and other environmental factors, and educational attainment. To do this they constructed a model. Below you see estimates of the variance in the trait explained by variance in genes, shared environment (family), non-shared environment (basically “noise” or error, or it could be something like peer group), from Sweden to Minnesota, and, at three intelligence levels. Two standard deviations below the norm is borderline retarded, ~2.5% of the population or so, and two standard deviations above the norm is at Mensa level.


It’s interesting that as you move up the IQ scale the genetic variation explains more and more of variance the educational attainment. Someone with an IQ of 130 is likely to be university educated. But there are many who are not. Why? The way I interpret these results is that if you are that intelligent and do not manage to complete university you may have heritable dispositions of personality which result in you not completing university. If, for example, you come from a family which is very intelligent, but is low on conscientiousness, then there may be a high likelihood that you just won’t complete university because you can’t be bothered to focus. Or, you may have personality characteristics so that you don’t want to complete university. A second major finding here is that Sweden and the USA go in totally different directions when it comes to the sub-average and dull in prediction of years of education. Why? The explanation in the paper seems plausible: Sweden strongly constrains higher education supply, but makes it available to those with proven academic attainments at a nominal price. Family encouragement and connections don’t matter as much, if you can’t pass the university entrance examination you can’t pass it. In contrast in the USA if you’re dull, but come from a more educated or wealthier family, you can find some university or institution of higher education which you can matriculate in. Supply is more flexible to meet the demand. I actually know of a woman who is strongly suspected to be retarded by her friends. I have been told she actually tested in the retarded range in elementary school but was taken out of that track because her family demanded it (she’s the product of a later conception, and her family made their money in real estate, not through professional advancement). Over the years she has enrolled in various community colleges, but never to my knowledge has she completed a degree. If she had not had family connections there is a high probability she wouldn’t have completed high school. As it is, she can check off “some college” on demographic surveys despite likely be functionally retarded.

The next table is a bit more confusing. It shows you the correlations between the effects of the variable on education and intelligence. In other words, does a change in X have the same directional effect on Y and Z, and what is the extent of the correspondence between the effect on Y and Z.


Shared environment had almost the same effect on intelligence and education, while genetics had a more modest simultaneous effect. Not too surprising that non-shared environment didn’t have a strong correlation in effect across the traits, the authors note that much of this is going to noise in the model, and so not systematically biased in any direction. Though the confidence intervals here are a little strange. I’m not going to get into the details of the model, because frankly I’m not going to replicate the analysis with their data myself. That’s why I wanted to present raw correlations first. That’s pretty straightforward. Estimates of variances out of models with a set of parameters is less so. Here’s an interesting point from the correlations in the last table:

The patterns of genetic correlations in the two samples differed. In Sweden, genetic correlation was steadily in excess of .50 across the range of intelligence, indicating a genetically influenced direct effect of intelligence on educational attainment that was weaker than the shared environmental effect on educational attainment. In the MTFS [Minnesota] population, however, genetic correlation was in excess of .50 when level of intelligence was low, but was halved at higher levels of intelligence. This indicated that genetic influences on intelligence tended to limit educational attainment when the level of intelligence was low, but not when the level of intelligence was average or high.

Now let me jump to conclusion:

This finding indicates that genetic influences common to intelligence and educational attainment may have been more effective in limiting educational attainment in individuals with low levels of intelligence than in encouraging educational attainment in those with high levels of intelligence. As in Sweden, shared environmental influences on intelligence and educational attainment were completely linked, indicating a direct contribution from shared environmental influences on intelligence to educational attainment. The decrease in shared environmental variance with higher intelligence, however, indicated that shared environmental influences were more effective in encouraging educational attainment in higher-intelligence individuals than in limiting educational attainment in lower-intelligence individuals. In other words, in populations in which shared environmental influences such as family history and values encouraged high levels of educational attainment, individuals were able to surmount limitations in intelligence.

Our analysis does not permit the conclusion that these differences in educational systems cause the differences in environmental and genetic influences on educational attainment observed in this study, but it is reasonable to hypothesize that this is likely. In particular, the greater expense of higher education and greater subjectivity of admission standards in the United States compared with Sweden may partially explain the very different patterns of shared environmental influences in the two population samples. Regardless of the causes underlying the differences we observed, the results of our study make clear that the degrees of environmental and genetic influences can vary substantially between groups with different circumstances, and even within such groups. Our results also suggest that the ways in which social systems are organized may have implications for how and to what extent environmental and genetic influences on behavior will be expressed.

This discussion about the role of environment, genes, and culture, on various outcomes should not hinge on one paper. But, these sorts of results are often not widely disseminated among the intellectual classes. One aspect of the American educational system in contrast to some other nations is that not-too-brights have university degrees. Education has long been a project for social engineering in the USA, going back to Horace Mann. Legacies, underrepresented minorities, the poor, those with particular talents, etc., are all part of the decentralized system of university admissions in the United States. In contrast, in nations such as Sweden or Japan there is a more centralized and universal set of criteria. This results is more perfect sorting by the metrics of interest without considerations of social engineering. I know that Sweden has traditionally had a small aristocratic class, while the Japanese aristocracy were basically abolished after World War II. Additionally, both are relatively homogeneous societies so considerations of racial representativeness are not operative. Or weren’t until recently in the case of Sweden. But consider one reality: if such a system is perfectly meritocratic over time if the traits being evaluated are heritable then you will have genetic stratification and reduction of social mobility assuming assortative mating at university.

Currently there is some handwringing by the elites about the fact that so few poor kids get admitted to Ivy League universities. I think there’s a simple way to change this: get rid of the implicit Asian quotas. After all, there was a lot of socioeconomic diversity after the Ivy League universities got rid of their Jewish quotas, but the children of the Jews who didn’t have to go to CUNY and went to Harvard are well off themselves. But more socioeconomic mobility through removing the implicit Asian quota would cause other difficulties, as elite private universities need their slots for both legacies as well as underrepresented minorities for purposes of social engineering/fostering diversity/encouraging donations. Additionally, just as with the Jews the welter of mobility in one generation of the children of Asian immigrants would settle into quiescence in the next if the traits which enable university admission are genetically or culturally heritable.

Citation: Johnson W, Deary IJ, Silventoinen K, Tynelius P, & Rasmussen F (2010). Family background buys an education in Minnesota but not in Sweden. Psychological science : a journal of the American Psychological Society / APS, 21 (9), 1266-73 PMID: 20679521

(Republished from Discover/GNXP by permission of author or representative)
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Readers might be interested in a new paper in PLoS ONE, General Intelligence in Another Primate: Individual Differences across Cognitive Task Performance in a New World Monkey (Saguinus oedipus):

Individual differences in cognitive abilities within at least one other primate species can be characterized by a general intelligence factor, supporting the hypothesis that important aspects of human cognitive function most likely evolved from ancient neural substrates.

(Republished from by permission of author or representative)
• Category: Science • Tags: Psychology, Psychometrics 
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Several people have emailed me (and emails and forward are appreciated by the way) about two articles in The New York Times about IQ. IQ Harmed by Epilepsy Drug in Utero, which Steve’s already commented on. And the most emailed article currently, Nicholas Kristof’s How to Raise Our IQ. Some of you who have been reading this blog since the beginning might have noticed that I long ago stopped talking much about psychometrics. Why? I’d rather not waste my time trying to convince smart people that they are actually smarter than stupid people. If I had a penny every time someone with an elite college education in the hard sciences explained that “they don’t believe in IQ”…. Of course, on the other hand these aren’t the huge majority of people. Many who were nerds or of high intelligence know that there’s a qualitative difference between themselves and the herd, in particular those from families with several siblings where psychometric variance is rather obvious. How much more “shared” can environment exactly get?

But in any case, many of the intelligent refuse to assent to the position that intelligence actually exists, and that it can be measured. A few conversations aren’t going change opinions here, as the opinions aren’t based on empirical data. Rather, it’s a theory to which one is socialized (and which socialization can reverse, but this requires a great deal of time investment which isn’t going to happen with most people). My own experience with the crowd that runs with Robin Hanson and Eliezer Yudkowsky is that 1) they tend toward the retarded end of social intelligence 2) are invariably accepting of, or open to, the reality of g. In other words, my assumption is that most people who “don’t believe in intelligence,” don’t for reasons of socialization, because they know the rewards built into the incentive structure of human groups for conformity. Of course, there is “believe,” and then there is believe. The same people who don’t believe in intelligence are proud of their GRE scores, convinced that Republicans and religious people have lower IQs, and outraged when the mentally deficient, as measured on IQ tests, are executed. This probably reflects some mental modularity. People might say they don’t believe in IQ, but the decisions they make are to some extent informed by the assumption that intelligence exists, and individuals vary. This shouldn’t be a surprise, our executive functions have only a loose control over the different subfunctions which define our cognition. Ironically it might reflect the limits of the conscious rationalin enforcing its well on subconsciously operating modules. The long arm of intelligence reaches only so far into the crevasses of one’s mind.

So the best way to increase the intelligence of your offspring? Fuse your gametes with someone intelligent! You don’t even have to believe in intelligence to do this, as many who do just this don’t. The main issue isn’t that people won’t be a position to fuse their gametes with individuals in the same range as themselves in terms of intelligence. Rather, it’s that they won’t let the fusion come to fruition!

(Republished from by permission of author or representative)
• Category: Science • Tags: IQ, Psychometrics 
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Razib Khan
About Razib Khan

"I have degrees in biology and biochemistry, a passion for genetics, history, and philosophy, and shrimp is my favorite food. If you want to know more, see the links at"