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December 19, 2017

Motivated reasoning in “science journalism.”

Filed under: Psychology,Psychometrics — Razib Khan @ 6:09 pm

The “reproducibility crisis” has really benefited some sectors of science journalism, as there is less credulous amplification of spurious results. That being said, motivated reasoning is powerful. They “want to believe.”

So when I saw this piece in Quartz, Highly motivated kids have a greater advantage in life than kids with a high IQ, I immediately scanned for what I usually look for, and found it:

Over the next four decades, the Gottfrieds and several colleagues collected a staggering trove of data on the study participants, yielding important insights into working parents, temperament, and other topics. Researchers collected information about participants from parents, teachers and transcripts, tested their IQ and motivation levels,and even visited their homes. In all, the Fullerton Longitudinal Study has amassed an estimated 18,000 pieces of information on each of the remaining 107 participants. “It’s our life’s work,” says Allen cheerfully. “We’ll take it to our grave.”

107 participants. Lots of information huh? Things that make you go hm….. Also, 19% of the children had IQs of 130 or above. About 2% of the population has an IQ at this level. The sample size was relatively small, and the sample was very unrepresentative.

This doesn’t mean that there aren’t real results in these data. But I don’t think they warrant the fanfare in the title, except for the fact that people want a silver bullet that will abolish social inequality.

Even the text itself doesn’t justify the title at all (to be fair, usually headline writers differ from the persons writing the text of a piece): “[Motivation] in itself is accounting for a certain amount of variance in achievement that goes above and beyond IQ….” That is, they don’t even say it accounts for more of the variance, only that there is variance that isn’t accounted for by IQ (which everyone already agreed upon).

Finally, I’ve spent my life around highly educated and intelligence people a bit perplexed and befuddled by my diverse interests. This includes in academia. So I can see that there is difference between people for whom learning is a means to a professional and social ends, and for those whom learning is the ends. I suspect the ancients could have told you this!

November 9, 2017

Patterns in international GRE scores

Filed under: GRE,Psychometrics — Razib Khan @ 12:52 am

Why writing up my earlier post I stumbled onto to some interesting GRE data for applicants for various countries. I transcribed the results for all nations with sample sizes greater than 500. What you see above is a plot which shows mean quantitative and verbal scores on the GRE by nations.

The correlation in this set of countries between subtests of the GRE are as so:

Quant & verbal = 0.33

Verbal & writing = 0.84

Quant & writing = 0.21

Basically, the writing score and verbal score seem to reflect the lack of English fluency in many nations.

Many of these results are not too surprising if you’ve ever seen graduate school applications in the sciences (I have). Applicants from the United States tend to have lower quantitative and higher verbal scores. This is what you see here. It’s rather unfair since the test is administered in English, and that’s the native language of the United States. No surprise the United Kingdom and Canada score high on verbal reasoning. Ireland, Australia, and New Zealand didn’t have enough test takers to make the cut, but they all do as well as the United Kingdom. Singapore has an elite group which uses English as the medium of instruction in school.

I didn’t include standard deviation information, even though it’s in there. India has a pretty high standard deviation on quantitative reasoning, at 9.1. In contrast, China only has a standard deviation of 5.2 for quantitative reasoning. More than twice as many Indians as Chinese take the GRE.

Finally, I want to observe Saudi Arabia, as opposed to Iran. Both countries have about 5,000 people taking the GRE every year. About 2.5 times as many people live in Iran as opposed to Saudi Arabia. But the results for Saudi Arabia are dismal, while Iranian students perform rather well on the quantitative portion of the GRE.* This is not surprising to me, having seen applications from Saudi and Iranian students.

Saudi Arabia wants to move beyond being purely a resource-driven economy. These sorts of results show why many people are skeptical: in the generations since the oil-boom began the Saudi state has not cultivated and matured the human capital of its population. To get a better sense, here are the scores with N’s of MENA nations and a few others:

Country N Quantitative
Saudi 4462 141.6
Libya 113 146.2
Iraq 148 146.6
Oman 98 146.9
UAE 238 147.2
Qatar 85 147.3
Kuwait 386 147.8
Algeria 86 149.5
Yemen 68 149.9
Bahrain 55 150.9
Ethiopia 353 151.3
Jordan 472 152.1
Egypt 1044 153.2
Morocco 191 153.7
Tunisia 128 154.1
Georgia 71 154.2
Lebanon 691 154.7
Armenia 84 154.9
Azerbaijan 125 155.1
Eritrea 223 155.2
Israel 344 156.8
Iran 5319 157.3
Turkey 2370 158.9

 The “natural break” is between the Saudis and everyone else. In recent years Saudis indigenized their non-essential workforce. I’m broadly skeptical of the consequences of this.

The data for the plot at the top is below the fold.

Country Verbal Quant Writing
China 148.4 165.6 3
Taiwan 147.1 162.2 2.9
Hong Kong 150.2 161.1 3.4
Singapore 157.8 160.4 4.3
S Korea 149.9 160.3 3.2
Vietnam 147.6 159.1 3.2
Turkey 144.9 158.9 2.9
Japan 146.4 158.2 3.1
Iran 143.5 157.3 2.8
France 154 157.1 3.5
Greece 150.4 156.7 3.6
Germany 153.7 156.3 3.8
Thailand 144.7 156.2 2.9
Russia 149.3 156.1 3.2
Malaysia 150.8 155.8 3.6
Bangladesh 144.8 155.7 2.9
Italy 154.8 155.6 3.4
Sri Lanka 144.4 155.4 3.1
Chile 150.5 155.3 3.1
Nepal 144.8 155 3
Spain 152.3 155 3.4
Lebanon 147.5 154.7 3.3
Canada 156.1 154.6 4.2
UK 157.4 154.1 4.3
Egypt 145 153.2 3.1
India 144 153.2 2.9
Pakistan 147.9 152.5 3.4
Indonesia 147 152.2 3.1
Brazil 150.3 152.2 3.1
Philippines 150.7 150.9 3.6
Ecuador 147.4 150.5 3.1
USA 152.8 150.2 3.8
Colombia 148.6 150.1 3
Mexico 148.9 149.5 3.1
Kenya 147.3 147.8 3.4
Ghana 146.1 147.4 3.2
Nigeria 146.4 146.9 3.1
Saudi Arabia 137.5 141.6 2

* I suspect the poor English language skills of Iranian students is partly a function of the nation’s isolation the past two generations, but that’s speculation on my part.

November 8, 2017

GRE utility for graduate school and conditioning on the dependent variable

Filed under: GRE,Psychometrics — Razib Khan @ 8:43 pm

One of the things that seems to be popular in biological sciences right now is the push to get rid of the GRE as part of the criteria for entrance. Two of the major rationales are that it’s expensive, so discriminates against lower socioeconomic status candidates, and, that it makes it harder to recruit underrepresented minorities since on average they score lower on the GRE (many departments have either explicit or implicit GRE cut-offs).

I’m not going to litigate these issues. To be honest I believe it is a fait accompli that many departments will stop using the GRE. This will probably increase diversity in some ways. But I also suspect it will result in a greater bias toward more “polished” candidates since very high GRE scores sometimes indicate to admissions committees that applicants who are otherwise spotty or irregular may have promise.

But, I do want to enter into the record a major problem with the argument that GRE does not correlate with academic success at the graduate level (supported by research). Yes, part of the issue may simply be range restriction. But there is another issue which many biological scientists may not be familiar with.

First, right now this paper from early this year is getting a lot of attention, The Limitations of the GRE in Predicting Success in Biomedical Graduate School.

It was, of course, a political scientist who objected immediately:

This blog post is of interest for those curious, That one weird third variable problem nobody ever mentions: Conditioning on a collider. Basically, it is well known that at many universities graduate admittees exhibit a weak negative association between GRE scores and grade point averages. This was commented on as far back as the 1970s in ScienceGraduate Admission Variables and Future Success:

The standard variables considered in selecting students for graduate school do not correlate well with later measures of the success or attainments of the selected students (1, 2). The low correlations have led at least one investigator (3) to propose abandoning one of these standard variables, the Graduate Record Examination (GRE). The purpose of the present report is to demonstrate that variables that are the basis for admitting students to graduate school must have low correlations with future measures of the success of these students.

What’s going on?

As noted in the paper there are some universities which are first-choices for graduate school in a field to such an extent that they will admit candidates who have very high GPAs and very high GREs. In this case, neither of the criteria will predict success because there is very little variation to generate a correlation. But, at many universities, there is a negative correlation between admittee GRE score and undergraduate GPA. That is because very few applicants will be admitted with both low GRE and GPA scores, but some will be admitted with high GRE scores and low(er) GPAs and others with higher GPAs and low(er) GREs (usually there is still a GPA and GRE floor).

Consider the relation:

    \[ R^2 = \frac{r_1^2 + r_2^2 - 2r_1r_2r}{1 - r^2} \]

Where \R^2 is the proportion of the variance of the variable you want to predict, and r_1^2 and r_2^2 are the correlations between GRE and GPA and that the variable of interest, and r is the correlation between GRE and GPA.

Basically, when you have negative correlations you’re going to get into a situation where r_1^2 and r_2^2 are not going to be able to explain a lot of the variance in what you want to predict.

This may seem like a nerdy issue. And it is well known to social scientists. But since the people I see talking about the GRE are academics in the biological sciences I thought I would at least highlight this nerdy issue.

As I said above, I do think GRE is going to be dropped as a requirement at many universities for graduate programs. This is going to be a natural experiment, so we’ll be able to test many hypotheses. The paper above ends like so:

…Without a study in which a sample of the applicants-rather than of the selected students is evaluated, it is impossible to tell [the validity of the criteria -RK]. Yet such a study is completely infeasible. Even if rejected applicants are monitored throughout the rest of their working careers, it is impossible to evaluate how they would have done had they been admitted, because the rejection itself constitutes an important “treatment” difference between them and the selected students. The alternative is to admit a sample of the applicant population without using the standard admission variables to select them-preferably, to select at random.

Selection may not be random, but I believe we may be able to test some hypotheses in the next generation by testing a set of students later on after admittance on the GRE and see what the future correlation is.

September 4, 2017

The GRE is useful; range restriction is a thing

Filed under: Intelligence,Psychometrics — Razib Khan @ 8:05 pm

The above figure is from Beyond the Threshold Hypothesis: Even Among the Gifted and Top Math/Science Graduate Students, Cognitive Abilities, Vocational Interests, and Lifestyle Preferences Matter for Career Choice, Performance, and Persistence. It shows that even at very high levels of attainment on standardized tests there are differences in life outcome based on variation. The old joke is that results on intelligence tests don’t matter beyond a certain point…that point being whatever your own position is! But these results show that mathematics SAT outcomes at age 13 can still predict a lot of things across a wide range.

From personal experience people outside of psychology are pretty unaware of the power of cognitive aptitude testing. This includes many biologists. I was reminded of the above figure as I read portions of Richard Haier’s The Neuroscience of Intelligence. If you are a biologist curious about the topic, this is a highly recommended book.

The main reason I am posting this is that this it was asked of me by a friend in academia. There has recently been a backlash against the GRE exam, with support from the highest echelons of the science media. Additionally, many researchers in public forums are voicing objections to the GRE very vocally. Naturally this has resulted in counterarguments…but respondents have to be very careful how the couch their disagreement, because they fear being accused of being racist, sex, or classist. Such accusations might trigger social media mobs, which no one wants to be the target of (and if past experience is any guide, friends and colleagues will stand aside while the witch is virtually burned, hoping to avoid notice).

Because of the request above I finally decided to look at the two papers which are eliciting the current wave of GRE-skepticism, The Limitations of the GRE in Predicting Success in Biomedical Graduate School and Predictors of Student Productivity in Biomedical Graduate School Applications. To my eye they suffer from the same problem as all earlier criticisms: range restriction.

The issue is that if a university is using the GRE and other metrics well as filters for those admitted then there shouldn’t be that much variation in outcome left (the outcome being publications or some other important metric which actually leads to the production of science, as opposed to test scores and grades). The two papers above look at those admitted to biomedical programs at UNC and Vanderbilt, while another study looked at UCSF. These are all universities with standards high enough that there are either explicit or implicit cut-off scores so that many students are removed from the applicant pool immediately (the mean scores are well above the 50th percentile, you can see them in the paper yourself).

When I was in graduate school I was on a fellowship committee for several years, and I had access to GRE scores and grades. But I didn’t really pay much attention to them because there wasn’t that much range. And to be honest if the student was beyond their first year I didn’t look at all as time went on. In contrast, I did look really closely at the recommendations from their advisors. From talking to others on the committee this seemed typical. Once students were admitted they were judged based on how they were doing in graduate school. And how they were doing in graduate school had to do with research, not their graduate school GPA or what they scored on the GRE to get in.

As an empirical matter I do think that it is likely many universities will follow the University of Michigan in dropping the GRE as a requirement. There will be some resistance within academia, but there is a lot of reluctance to vocally defend the GRE in public, especially from younger faculty who fear the social and professional repercussions (every time a discussion pops up about the GRE I get a lot of Twitter DMs). My prediction is that after the GRE is gone people will simply rely on other proxies.

If the GRE is not required, but can be taken, then students who do well on the GRE will put that on their application. Sometimes strong students encounter tragedies in their undergraduate years which strongly impact their grade point averages, and very strong GREs can help show admissions committees that they can do the coursework despite their undergraduate record (I’m not positing a hypothetical, but recounting real individuals I’ve known of and seen). It seems cruel to deny these students the chance to submit their test scores. This means that those professors who believe the GRE is valid will show preference to students who take the test and have strong scores (and to be sure, many more care about the GRE when it means someone concretely joining their lab, as opposed to the abstraction of who gets admitted to the department).

More broadly, professors who are taking students will look more at proxies for GRE score, such as undergraduate institution, or the prestige of the recommendation letters. In some places, such as Britain, standardized testing emerged in part as a way to identify strong students from underprivileged backgrounds. These are not the type of students who would ever be able to present a prestigious letter of recommendation. This is a sort of student which still exists (often they are from non-academic backgrounds, being the first to graduate from college in their family; what they lack in polish they compensate for in aptitude, but that take the right environment to express).

The recourse to other variables besides the GRE score will likely have mixed results at best. Consider the successful campaign to ban asking for job applicants’ criminal records. It turns out that just increased discrimination against all young black men, because employers could not longer differentiate. In general I think removing the GRE would probably hurt graduates of less prestigious state universities the most if I had to guess (and of course students from East Asia, who tend to have a comparative advantage on standardized tests). I’m pretty sure we’ll see, as the experiment will be run.

Addendum: There are professors at relatively prestigious research universities who had mediocre or sub-par GRE scores. We all know them. To some extent I think many of these individuals almost take pride in the fact that they accomplished so much in science despite negative feedback due to their impressive test scores. But remember that we’re talking about trends and averages, not deterministic predictions.

April 13, 2017

The coming reign of the Baby Boomer gerontocracy

Filed under: Gerontocracy,Psychology,Psychometrics — Razib Khan @ 1:22 pm

From Dawn to Decadence: 1500 to the Present: 500 Years of Western Cultural Life is one of my favorite books. It’s one of those works whose breadth and depth is such that I would recommend it to anyone. Jacques Barzun began writing this work when he was 84, and it was published in his 93rd year. Born in 1907 Barzun saw the full efflorescence of 20th century Western culture across much of its span firsthand. When people say that when you age you gain wisdom, surely in the domain of scholarship Barzun’s production in the last few decades of his life would qualify.

But not everyone is Jacques Barzun. If you read Intelligence: All That Matters or peruse some of Eliott Tucker-Drob’s work you will know that cognitive function declines with age beyond your twenties. Different subcomponents may decline at different rates. And, they decline differently in different people (e.g., some people may develop dementia, so their faculties will decline far faster at an earlier age). But, by and large any gains in experience or wisdom are going to be balanced against declines in raw analytic ability, as well as the slow entropic loss of information.

This is not an inconsequential matter. Our governing class is quite old. The average age in Congress may be 55 to 60, but it is almost certainly true that more senior members with more power and authority are older. The president of the United States is 70 years old. If you look at the plots in these figures by 70 there has been a notable drop in intelligence by this age, though again, it may vary from person to person.

But most important in light of these figures is that the Supreme Court is a lifetime appointment, and many of its members are quite old, an anticipate serving until they are quite old if they are younger. In the mid-1970s justice William O. Douglas had a stroke and was basically not mentally competent to serve. Because of this fact, and Douglas’ reluctance to retire his fellow justices basically did not take his vote into account. Three of the justices today are over the age of 70, with Clarence Thomas nearing that age, and two are over the age of 80.

When it comes to Congress, or even the President, there seems to be some sort of institutional support as well as the larger collective vote in the case of Congress, which might buffer the cognitive impact of a gerontocracy. But aside from law clerks Supreme Court justices have to rely on their own individual mental capacities.

The Mormon Church has a gerontocracy among its we openleadership. Even my most devout friends in the church sometimes found it amusing how old their leadership was, and how quickly they died in succession due to the seniority principle. But The Supreme Court is not the leadership of a relatively small church. It impacts our whole nation. This sort of gerontocracy is no laughing matter.

Will we openly speak of the age issue? I doubt it. Today the Baby Boomers are between the ages of 53 an 71. They are coming into their own as a cohort into the highest reaches of the gerontocracy. If there is any generation with the grace and humility to step aside for the greater good, it will not be this generation.

August 17, 2011

Looking for a few good 145+ I.Q. individuals

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 www.cog-genomics.org, 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 ...

May 13, 2011

I.Q. and genomics

Filed under: B.G.I.,Behavior Genetics,Genomics,I.Q.,Psychology,Psychometrics — Razib Khan @ 9:15 pm

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 ...

September 27, 2010

American family values: where even the dull can dream!

ResearchBlogging.orgOne 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.

swed1

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.

swed2

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.

swed3

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

June 27, 2010

Psychometrics, epigenetics and economics

Filed under: IQ,Psychology,Psychometrics — Razib Khan @ 10:26 am

Two papers of interest. IQ in the Production Function: Evidence from Immigrant Earnings (ungated). And Human Intelligence and Polymorphisms in the DNA Methyltransferase Genes Involved in Epigenetic Marking. My impression is that the focus on epigenetics has a higher-order social motive; even the sort of humanists who are involved with N + 1 have asked me about the topic. But how many people know what methylation is?

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