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Credit: Schimpanse Zoo Leipzig, Thomas Lersch

Credit: Schimpanse Zoo Leipzig, Thomas Lersch

Some recent research has just been published with the title Chimpanzee Intelligence Is Heritable. My first thought honestly was “No shit? Of course.” My friend Jason Goldman has already done a very good write up at io9 if you want read about it and don’t have access to the paper. In commenting on the results Jason notes (and I agree with the general thrust here):

That isn’t a particularly surprising or novel statement on its own [that chimpanzee intelligence is heritable -Razib]. We already knew that genes have an important job when it comes to intelligence and cognition. But what’s useful is that we can assume chimpanzee intelligence isn’t influenced by factors like socioeconomic status, the quality of their school districts, or any of the dozens of other variables, both obvious and subtle, that influence human development. That means we can examine the “genetic” side of their intelligence more easily.

Of course chimpanzees vary in intelligence, and, that variation has a genetic component. Part of the issue here is human essentialism. Chimpanzees are less intelligent than the average human, and so are classed into a general category of the second-most-intelligent-ape, as if their variation is totally irrelevant (and for practical day to day purposes it is). Pound for pound chimpanzees are also much stronger than we are. But would anyone be surprised if chimps varied in strength as a function of their genes (controlled for sex)? I doubt it. The issue, if there is one, is that intelligence is perceived as the sine qua non of humanity.

Horseshoe crabs, evolutionary success!

Horseshoe crabs, evolutionary success!

Jason suggests that chimpanzees could serve to explore issues in relation to the development of intelligence and its dependence upon genes and environment. Perhaps, though I think if that is what you want to explore in animal models birds or outbred rodent lineages would be more cost effective. I’m pretty sure they’d exhibit heritable variation in general intelligence as well.

Though obviously there seems to be selection for larger brains in the primate lineage, and perhaps in chordates in general, over hundreds of millions of years, I think it’s a huge step (which I would dispute) to suggest that intelligence itself is evolutionarily favored over shorter time scales (i.e., one can perhaps argue evolutionary success accrues to the brain in a macroevolutionary sense, but far less in a microevolutionary scale of operation). I bet a lot of the evolutionary action is in what cognitive psychologists would term “domain specific cognitive capacities.” E.g., our ability to learn and speak language with complex syntax, which is a human universal. In contrast there may not be that much selection in a directional sense for “domain general cognition.” From a population genetic perspective this would explain why there’s so much heritable variation in intelligence. Strong directional selection tends to purge that variation. The best evidence indicate that most of that variation is due to effects from many genes (on the order of thousands), and I doubt that chimpanzee-human comparative genomics will yield much fruit here.

 
• Category: Science • Tags: Intelligence 
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Prompted by my post Ta-Nehisi Coates reached out to Neil Risch for clarification on the nature (or lack thereof) of human races. All for the good. The interview is wide ranging, and I recommend you check it out. Read the comments too! Very enlightening (take that however you want).

When it comes to this debate I have focused on the issue of population substructure, or race. The reason is simple. Due to Lewontin’s Fallacy it is widely understood among the “well informed general public” that “biology has disproved race.” Actually, this is a disputable assertion. For a non-crank evolutionary biologist who is willing to defend the race concept for humans, see Jerry Coyne. When you move away from the term “race,” then you obtain even more support from biologists for the proposition that population structure matters. For example, a paper in PLoS GENETICS which came out last week: Analysis of the Genetic Basis of Disease in the Context of Worldwide Human Relationships and Migration. In other words, it is useful to understand the genetic relationships of populations, and individual population identity, because traits correlate with population history. Barring total omniscience population history will always probably matter to some extent, because population history influences suites of traits. If nothing in evolutionary biology makes sense except in light of phylogeny, much of human biology is illuminated by phylogeny.

But that doesn’t speak to the real third rail, intelligence. Very few people are offended by the idea of the correlation between lactase persistence and particular populations. Neil Risch says in the interview with Coates:

One last question. Your paper on assessing genetic contributions to phenotype, seemed skeptical that we would ever tease out a group-wide genetic component when looking at things like cognitive skills or personality disposition. Am I reading that right? Are “intelligence” and “disposition” just too complicated?

Joanna Mountain and I tried to explain this in our Nature Genetics paper on group differences. It is very challenging to assign causes to group differences. As far as genetics goes, if you have identified a particular gene which clearly influences a trait, and the frequency of that gene differs between populations, that would be pretty good evidence. But traits like “intelligence” or other behaviors (at least in the normal range), to the extent they are genetic, are “polygenic.” That means no single genes have large effects — there are many genes involved, each with a very small effect. Such gene effects are difficult if not impossible to find. The problem in assessing group differences is the confounding between genetic and social/cultural factors. If you had individuals who are genetically one thing but socially another, you might be able to tease it apart, but that is generally not the case.

In our paper, we tried to show that a trait can appear to have high “genetic heritability” in any particular population, but the explanation for a group difference for that trait could be either entirely genetic or entirely environmental or some combination in between.

So, in my view, at this point, any comment about the etiology of group differences, for “intelligence” or anything else, in the absence of specific identified genes (or environmental factors, for that matter), is speculation.

In response to this commenter Biologist states (note, I know who this is, and they are a biologist!):

Risch writes: “…the explanation for a group difference for that trait could be either entirely genetic or entirely environmental or some combination in between. … So, in my view, at this point, any comment about the etiology of group differences, for “intelligence” or anything else, in the absence of specific identified genes (or environmental factors, for that matter), is speculation.”

This is essentially correct. The quality of available evidence on which to estimate the contribution of genetic versus environmental factors to group differences in cognitive ability scores is quite poor by biomedical research standards — maybe more in line with standards for social science (I’m only half joking).

In light of that, one is forced fall back on to one’s priors. Without trying to speak for Risch, it is generally considered appropriate to adopt a uniform prior in the absence of other evidence. Under a uniform prior, “…the explanation for a group difference for that trait could be either entirely genetic or entirely environmental or some combination in between.” Maybe Risch would propose a different prior.

In fact, the uniform prior says that there’s a 25% chance that the explanation is 0% to 25% genetic, a 50% change that the explanation is 25% to 75% genetic, and a 25% chance that the explanation is 75% to 100% genetic. Obviously many people who write about this topic do not adopt a uniform prior. [my emphasis -Razib]

As Risch observes above intelligence is highly polygenic. There’s a fair amount of genomic evidence for this now. In other words the likelihood is not high that we will be able to account for the differential distribution of IQ between any two populations by differences in allele frequencies. Even if we do find the allelic differences, they’ll account for far too little of the variation in the trait. But there is another way we can get at the issues. Others have pointed out exactly how we can get more clarity on the race and IQ question before, so I’m not being original. And since I suspect that within the next decade this sort of analysis will likely be performed at some point somewhere because the methods are so simple, I might as well be explicit about it.

Let’s focus on the black-white case in the American context. On intelligence tests the average black American scores a bit less than 1 standard deviation below the average white American. As I’ve observed before the average black American is ~20% European, but there is variation around this value. Because the admixture is relatively recent (median ~150 years before the present) there is a wide range across the population of ancestry. In fact, the admixture is recent enough that siblings may even differ in the amount of European ancestry on a genomic level. An additional issue which is of relevance is that the correlation between ancestry and physical appearance in mixed populations is modest. By this, I mean that there are many individuals who are more European in ancestry in the African American population who have darker skins and more African features than those who have less European ancestry. Obviously on average more European ancestry predicts a more European appearance, but this is true only on average. There are many exceptions to this trend.

At this point many of you should have anticipated where I’m going. If the gap between blacks and whites on psychometric tests is totally driven by genetic differences between Africans and Europeans, then the gap should be obvious between pools of individuals of varying levels of European ancestry within the African American population. It seems unlikely that it would be that simple (i.e., all driven by genes without any sensitivity to environmental inputs or context). Therefore I suspect some design where you compare siblings would be more informative.

In a model where all of the between group differences are due to environmental inputs then genomic ancestry by geography within family should add little in terms of prediction of the phenotype. More plainly, when accounting for other variables which might correlate with ancestry (e.g., skin color), how African or European a sibling is should not influence outcomes on psychometric tests when looking at large cohorts of sibling pairs if those differences track nothing more than social construction/perception of race. If on the other hand there are many alleles of small effect distributed throughout the genome correlated with geographic ancestry which affect the final phenotype then adding ancestry as an independent variable into the model should be informative. This sort of indirect inference has already been performed with a character similar in genetic architecture to intelligence: height. Researchers have found that African Pygmies with more non-Pygmy ancestry are taller.

Ultimately I say that this issue might semi-resolve, because I think a hereditarian position in terms of group differences is not going to be tenable if the correlations with ancestry do not run in the direction expected within admixed populations. This sort of model is relatively straightforward in its predictions, and appeals to parsimony. Trying to salvage it with non-additive genetic variance is going to complicate matters. In contrast, those who champion the opposite position often dispute the very characterization of intelligence as a trait in the first place, so I presume that they would still exhibit skepticism if there was a correlation between genomic ancestry and the trait.

Addendum: I want to be clear: with the widespread availability of data sets and crappy security of said data sets this analysis is probably a few SQL joins away in 10 years.

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Genetics, I.Q., Intelligence, Psychology, Race 
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Update: First, people coming to this weblog for the first time should know that I moderate comments. So if you leave an obnoxious one it’s basically like an email to me (no one will see it). Second, the correlation between height and intelligence is not that high. This association is probably not going to be intuitively visible to anyone, but rather only shows up in large data sets. So please stop offering yourself as a counter-example of the trend (also, the key is to look within families, because the signal here is going to be swamped by other factors when you compare across populations). Third, a friend has sent me another paper which does confirm that even within sibling cohorts there does seem to be a correlation between height and I.Q. The problem is that it is a very small one, so you need large data sets with a lot of power to see it.

End Update

One moderately interesting social science finding is that there is a positive correlation between height and measured intelligence (e.g., on an I.Q. test). Setting aside the possibility that I.Q. tests designs are culturally biased against shorter people, one wonders why this is so. Height is a highly heritable trait where most of the variation within the population is due to variation as numerous genes. In other words, there isn’t a “tall” or “short” gene, but thousands and thousands of variants which shape the variation of the trait across the population. When I say it is highly heritable, I mean to imply that most of the variation in height in developed societies is due to genes (80-90%). As it happens intelligence is somewhat similar in its genetic architecture, heritable due to small effects across many genes. In general estimates for the heritability of intelligence tend to be somewhat lower, on the order of ~50% rather than 80-90%.

It is due to the highly polygenic nature that both of these traits have been posited as candidates for a “good genes” model of sexual selection. Presumably individuals with a higher mutational load will have lower intelligence and be shorter, all things equal, because these traits have extensive genome-wide coverage and are big targets. Geoffrey Miller’s The Mating Mind: How Sexual Choice Shaped the Evolution of Human Nature, was predicated on this logic. If the mutational load argument holds then the reduced I.Q. of shorter individuals may simply be due to the same cause: “bad genes.”


Another scenario is that assortative mating between tall and intelligent people has generated a correlation between alleles which tend toward this end of the trait distribution. The phenomenon is simple enough to describe; height and intelligence are both attractive, and even if they are not due to the same genetic loci the pairing of tall and smart results in the correlation between the traits. My own assumption is that something like this, perhaps with a mutational effect at the bottom of the distribution (due to large effect deleterious alleles knocking people down in height and intelligence), generates most of the correlation. Part of this is due to my reading of The g Factor:

It is now well established that both height and weight are correlated with IQ. When age is controlled, the correlations in different studies range mostly between 0.10 and 0.30, and the average about 0.20. Studies based on siblings find no significant within-family correlation, and gifted children (who are taller than their age mates in the general population) are not taller than their non-gifted siblings.

Whenever people posit a pleiotropic relationship between traits I am always curious about the possibility that the traits may be correlated (or not) in siblings. Population structure of some sort can produce correlations, but patterns within families are often more informative of the genuine genetic basis of these correlations.

A new paper in PLOS GENETICS tackles this with more sophisticated techniques. They conclude:

Traits that are attractive to the opposite sex are often positively correlated when scaled such that scores increase with attractiveness, and this correlation typically has a genetic component. Such traits can be genetically correlated due to genes that affect both traits (“pleiotropy”) and/or because assortative mating causes statistical correlations to develop between selected alleles across the traits (“gametic phase disequilibrium”). In this study, we modeled the covariation between monozygotic and dizygotic twins, their siblings, and their parents (total N = 7,905) to elucidate the nature of the correlation between two potentially sexually selected traits in humans: height and IQ. Unlike previous designs used to investigate the nature of the height–IQ correlation, the present design accounts for the effects of assortative mating and provides much less biased estimates of additive genetic, non-additive genetic, and shared environmental influences. Both traits were highly heritable, although there was greater evidence for non-additive genetic effects in males. After accounting for assortative mating, the correlation between height and IQ was found to be almost entirely genetic in nature. Model fits indicate that both pleiotropy and assortative mating contribute significantly and about equally to this genetic correlation.

Pleiotropy here means that the same gene is impacting different traits (height and I.Q.). The additive genetic correlation between height and I.Q. was 0.08 and 0.17 in males and females respectively. These are small correlations obviously, but it’s what we’d expect.

After the statistical modeling using a twin design there’s a lot of talk about sexual selection and the long arc of evolutionary genetics (e.g., additive genetic variation being exhausted by selection). This is what you have to do in discussions, but I’m not sure it really adds any value. How strong is sexual selection for intelligence and height? The data show that taller men have more sexual partners, but the problem here is that taller men have taller daughters, and these daughters are not necessarily so reproductively fit. Whenever you are talking about sexual selection you need to take into account the antagonism that might entail because of the differential value of a trait between the sexes (e.g., masculine men may have masculine daughters). As for I.Q., I’m not sure about the long term distribution of fitness for this trait. I have a suspicion that the “sweet spot” for mating is to be only somewhat smarter than than the average, but not so clever so as to be obnoxious.

In the end I’d really like to see a massive number of siblings compared. I think that’s doable with this data set, but I didn’t see it in the paper (tell me if I’ve missed something). At some point we’ll have accurate high coverage whole genomes for many pairs, and we can ascertain whether it’s mutational load and pleiotropy more directly when it comes to correlations like this. Since pedophiles tend to be shorter and less intelligent I’m willing to accept deep biological connections across many traits. But I feel that the whole area is somewhat of a muddle right now. And talking a lot about sexual selection strikes me as excessive hand waving.

Citation: Keller MC, Garver-Apgar CE, Wright MJ, Martin NG, Corley RP, et al. (2013) The Genetic Correlation between Height and IQ: Shared Genes or Assortative Mating? PLoS Genet 9(4): e1003451. doi:10.1371/journal.pgen.1003451

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Anthropology, Genetics, Genomics, Height, Intelligence, Select 
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A few years ago I put up a post, WORDSUM & IQ & the correlation, as a “reference” post. Basically if anyone objected to using WORDSUM, a variable in the General Social Survey, then I would point to that post and observe that the correlation between WORDSUM and general intelligence is 0.71. That makes sense, since WORDSUM is a vocabulary test, and verbal fluency is well correlated with intelligence.

But I realized over the years I’ve posted many posts using the GSS and WORDSUM, but never explicitly laid out the distribution of WORDSUM scores, which range from 0 (0 out of 10) to 10 (10 out of 10). I’ve used categories like “stupid, interval 0-4,” but often only mentioned the percentiles in the comments after prompting from a reader. This post is to fix that problem forever, and will serve as a reference for the future.

First, please keep in mind that I limited the sample to the year 2000 and later. The N is ~7,000, but far lower for some of variables crossed. Therefore, I invite you to replicate my results. After the charts I will list all the variables, so if you care you should be able to replicate displaying all the sample sizes in ~10 minutes. I am also going to attach a csv file with the raw table data. As for the charts, they are simple.

- The x-axis is a WORDSUM category, ranging from 0 to 10

- The y-axis is the percent of a given demographic class who received that score. I’ve labelled some of them where the chart doesn’t get too busy

All of the charts have a line which represents the total population in the sample (“All”).


Methods:

The “Row” variable in all cases was WORDSUM. I put in YEAR(2000-*) in “Selection Filter(s).”

For the columns:

Sex = SEX

Race/ethnicity = For non-Hispanic blacks and whites put HISPANIC(1) in the filter. Then RACE. For Hispanics just limiting the sample to Hispanics will do, HISPANIC(2-*). Nothing in the row needed.

Education = DEGREE

Region = REGION

Political ideology = POLVIEWS(r:1-3″Liberal”;4″Moderate”;5-7″Conservative)

Political party = PARTYID(r:0-2″Democrat”;3″Independent”;4-6″Republican”)

Belief in God = GOD(r:1-2″Atheist & agnostic”;3-5″Theist”;6″Convinced Theist)

Religion = RELIG

Opinion about Bible = BIBLE

Income standardized to 1986 = REALINC(r:0-20000″0-20″;20000-40000″20-40″;40000-60000″40-60″;60000-80000″60-80″;80000-100000″80-100″;100000-120000″100-120″;120000-140000″120-140″;140-*”140-”)

Wealth = WEALTH(r:1-3″”)

Evolution = EVOLVED

You can find the raw table here.

(Republished from Discover/GNXP by permission of author or representative)
 
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In light of my previous posts on GRE scores and educational interests (by the way, Education Realist points out that the low GRE verbal scores are only marginally affected by international students) I was amused to see this write-up at LiveScience, Low IQ & Conservative Beliefs Linked to Prejudice. Naturally over at Jezebel there is a respectful treatment of this research. This is rather like the fact that people who would otherwise be skeptical of the predictive power of I.Q. tests become convinced of their precision of measurement when it comes to assessing whether a criminal facing the death penalty is mentally retarded or not! (also see this thread over at DailyKos). You can see some of the conservative response too.

The paper itself is Bright Minds and Dark Attitudes: Lower Cognitive Ability Predicts Greater Prejudice Through Right-Wing Ideology and Low Intergroup Contact:

Despite their important implications for interpersonal behaviors and relations, cognitive abilities have been largely ignored as explanations of prejudice. We proposed and tested mediation models in which lower cognitive ability predicts greater prejudice, an effect mediated through the endorsement of right-wing ideologies (social conservatism, right-wing authoritarianism) and low levels of contact with out-groups. In an analysis of two large-scale, nationally representative United Kingdom data sets (N = 15,874), we found that lower general intelligence (g) in childhood predicts greater racism in adulthood, and this effect was largely mediated via conservative ideology. A secondary analysis of a U.S. data set confirmed a predictive effect of poor abstract-reasoning skills on antihomosexual prejudice, a relation partially mediated by both authoritarianism and low levels of intergroup contact. All analyses controlled for education and socioeconomic status. Our results suggest that cognitive abilities play a critical, albeit underappreciated, role in prejudice. Consequently, we recommend a heightened focus on cognitive ability in research on prejudice and a better integration of cognitive ability into prejudice models.

I emphasized sections that I assume will answer some immediate questions, as not everyone has access to Psychological Science. Yes, they used different types of intelligence tests; verbal and spatial. Yes, they corrected for socioeconomic background. Their replication was in the UK and USA. Importantly, they focused on a few characteristics, attitudes toward homosexuals and race. It doesn’t seem like they explored an enormous range of opinions. And as noted in the paper they were looking at the social dimension of political ideology.

There is plenty of work on cognitive styles and political orientation. Recently it is moral foundations from Jon Haidt. Earlier you had George Lakoff’s models. Neither of these focused on general intelligence, the raw CPU power of the mind. Rather they surveyed moral intuition and personality profiles (for example, there is some evidence that those with a greater bias toward “openness” are more socially liberal).

Looking at the General Social Survey I too have found at a correlation between higher intelligence and social liberalism. On the other hand a good objection to this is that my estimator of intelligence, WORDSUM, was verbal, and liberals and conservatives may exhibit different cognitive profiles. This study takes that into account, adding spatial I.Q. tests to the mix.

It is important to emphasize that the authors do not posit an independent direct causal connection between low I.Q. and more reactionary attitudes towards race and homosexuality. Rather, they start out with a model where low cognitive ability people are drawn (or remain in) to conservative orientation, and this is further correlated with these specific racial and sexual attitudes. Like almost all psychology you can’t get the causation airtight (if you are a hardcore Humean you could probably say this for everything), but the correlation is suggestive in light of political and psychological models. The problem is the second. As Jonathan Haidth has articulated most recently most academic political scientists and psychologists have strongly social liberal views, and so they consciously or unconsciously tend to caricature and misrepresent the views of half their study population (notice that the authors assume that these socially conservative positions are ‘Dark Attitudes’; most people today would agree, but shouldn’t intellectuals avoid this sort of thing?). So though I have some confidence in the correlations, I’m a lot more skeptical of the explanatory models (though I don’t reject them out of had). There are so many models sitting around that how you chose models can be shaped by bias rather easily.

First, let’s hit the results.

The table above represents the results for the British cohorts and race, and the diagram to the left illustrates the outcome for the American sample and homosexuality. The primary point is that as per their hypothesis the effect of lower cognitive ability on prejudice toward other races and homosexuality is mediated more or less through ideology. Coarsely, stupid people aren’t racist, stupid people are more likely to be socially conservative, and more socially conservative people are more likely to be racist. How these join together though is something one can subject to more critical examination. The authors allude to this when they note that there is a finding that those who know people of other races tend to be less prejudiced, with the inference being that contact makes one less racist. But this is not an established causality. Rather, it could be that people with less prejudiced tendencies put themselves into situations where they are likely to meet other races. This tendency could be correlated with higher I.Q. through a mediation of a “cosmopolitanism index.” Who knows? There are many stories one could tell.

I do want to emphasize though that this is a coarse measure of ‘conservatism.’ In the early to mid aughts Paul Wolfowitz was a hated figure on the American political Left because of his critical role in buttressing the intellectual armamentarium favoring the invasion of Iraq. But it is well known that Wolfowitz was and is a social liberal, like a subset of neoconservatives who focus on foreign policy. On the above measure Wolfowitz, who has undergraduate degrees in mathematics and chemistry from Cornell and a graduate degree in political science from University of Chicago, would come out as a high I.Q. social liberal. Is that right? As far as it goes it is right, but on some level the results would be misleading in the more complex terrain of coalitional politics. A substantial number of Americans shake out as social conservatives and fiscal moderates/liberals. And yet this faction is totally unrepresented in modern politics. In contrast, their inverse, libertarians, do have some representation, albeit a marginalized one. Why? Because the latter position has modest high I.Q./elite support, while the former position has far less. If you changed the question to attitudes toward global free trade there would be a correlation between lower I.Q. and the ‘more liberal’ (at last in American politics) position.

This qualification also dovetails with the broader point about styles of cognitive thinking, and reliance on traditional norms as opposed to think a priori. Ironically it makes intuitive sense that higher I.Q. people would be less reliant on intuition, impulse, and collective wisdom. But there are limits to this. For example, see the reaction to the proposition of sex between consenting adults who happen to be siblings on an atheism forum (assume they use birth control). But some moral philosophers posit that this is not harmful or immoral, and should be socially accepted. It’s an interesting illustration of the boundary condition of the power of disgust and emotion, as only the hyper-rational feel comfortable even entertaining the moral legitimacy of this proposition. More relevantly, educated liberals also make use of ‘stereotypes’ constantly. It’s just that those stereotypes are of conservatives. I know this because almost all my friends are educated liberals, and they often forget that I’m a conservative. So I hear a lot about conservatives are this and that without qualification, to great merriment and laughter (also, conservatives are genuinely evil and malevolent apparently!). The tendency toward generalization doesn’t bother me in an of itself, rather, I’m focused on whether the proposition is true. But the hypocrisy gets tiresome sometimes, as people will fluidly switch from a cognitive style which accepts generalization to one which rejects it. A stereotype is often a generalization whose robustness you don’t want to accept. Negative generalities need context when they’re unpalatable, but no qualification is necessary when their truth is congenial. Sometimes this veers into moderately politically incorrect territory. I was once an observer on a conversation between liberal white academics who were mulling over the unfortunate reality that their Asian American students were far more likely to cheat to obtain better grades. I suspect that this is actually true for various reasons. But I also suspect that these academics forgot that I was privy to the conversation, and wouldn’t have aired this truth in a more racially diverse social context.

More broadly what is the takeaway from this sort of research? Should we conclude that because the more intelligent tend to be socially liberal that socially liberal propositions are true? I think one should be skeptical of this position. There are two immediate rejoinders. First, politics is a matter of values. The reliance of reason vs. emotion, individual ratiocination vs. historical or social wisdom, may vary. But that does not speak to the truth of any given value judgement, as those judgments are embedded in a system of norms, as well as individual self-interest (e.g., the higher I.Q. tendency to favorable attitudes toward free trade may have less to do with an understanding of comparative advantage, than an implicit understanding that globalization favors them as opposed to less intelligent lower classes). Second, the moral arc of history is not always unidirectional. The ‘progressive’ position is sometimes reversed. In Better for All the World there is a broad history of the rise of a consensus among economic and intellectual elites about the wisdom of coercive eugenics as an instrument of progressive social engineering in the late 19th century. Religious conservatives, whether evangelical Protestant or Roman Catholic, were two of the greatest bulwarks against this force for progress. Arguably these two elements were more efficacious in resisting the spread of eugenics legislation than the Left critics, judging by the outcomes Southern Europe and the American South, as opposed to the more ‘forward thinking’ nation-states of Northern Europe and the American North. This fact is unknown to most of my friends and acquaintances, judging by repeated assumptions that any utilization of personal genomics for eugenic purposes will occur first in politically conservative jurisdictions.

With all these qualifications, I believe this sort of research is essential and insightful. We need to understand the patterns of cognitive variation, whether it be intelligence or personality, which may result in differences of opinion. At the end of the day no opinions may change, but one may be able to construct a crisper argument when taking into account the genuine roots of one’s political opponents viewpoints, rather than your own ill-informed caricature.

Addendum: I did not address the issue of revealed vs. avowed preferences and attitudes. But I think that this difference will not change the sign of correlation. For example, for various reasons I assume that the gap between white liberals and white conservatives when it comes to race is smaller in terms of the preference revealed in their choices, rather than the survey responses they give, but I don’t think it reverses the rank order of the correlation.

Citation: Bright Minds and Dark Attitudes: Lower Cognitive Ability Predicts Greater Prejudice Through Right-Wing Ideology and Low Intergroup Contact, Psychol Sci. 2012 Jan 5.

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Ideology, Science • Tags: Culture, I.Q., Intelligence, Liberalism, Politics 
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The post below on teachers elicited some strange responses. Its ultimate aim was to show that teachers are not as dull as the average education major may imply to you. Instead many people were highly offended at the idea that physical education teachers may not be the sharpest tools in the shed due to their weak standardized test scores. On average. It turns out that the idea of average, and the reality of variation, is so novel that unless you elaborate in exquisite detail all the common sense qualifications, people feel the need to emphasize exceptions to the rule. For example, over at Fark:

Apparently what had happened was this: He played college football. He majored in math, minored in education. When he went to go get a job, he took it as a math teacher. When the football coach retired/quit, he took over. When funding for an advance computer class was offered, he said he could teach it after he got the certs – he easily got them within a month.

So the anecdote here is a math teacher who also coached. Obviously the primary issue happens to be physical education teachers who become math teachers! (it happened to me, and it happened to other readers apparently) In the course of double checking the previous post I found some more interesting GRE numbers. You remember the post where I analyzed and reported on GRE scores by intended graduate school concentration? It was a very popular post (for example, philosophy departments like it because it highlights that people who want to study philosophy have very strong GRE scores).

As it happens the table which I reported on is relatively coarse. ETS has a much more fine-grained set of results. Want to know how aspiring geneticists stack up against aspiring ecologists? Look no further! There are a lot of disciplines. I wanted to focus on the ones of interest to me, and I limited them to cases where the N was 100 or greater (though many of these have N’s in the thousands).

You’re going to have to click the image to make out where the different disciplines are. But wait! First I need to tell you what I did. I looked at the average verbal and mathematical score for each discipline. Then I converted them to standard deviation units away from the mean. This is useful because there’s an unfortunate compression and inflation on the mathematical scores. Disciplines which are stronger in math are going to have a greater average because the math averages are higher all around. You can see that I divided the chart into quadrants. There are no great surprises. People who want to pursue a doctorate in physical education are in the bottom left quadrant. Sorry. As in my previous post physicists, economists, and philosophers do rather well. But there were some surprises at the more detailed scale. Historians of science, and those graduate students who wish to pursue classics or classical languages are very bright. Budding historians of science have a relatively balanced intellectual profile, and the strongest writing scores of any group except for philosophers. I think I know why: many of these individuals have a science background, but later became interested in history. They are by nature relatively broad generalists. I have no idea why people drawn to traditionally classical fields are bright, but I wonder if it is because these are not “sexy” domains, to the point where you have to have a proactive interest in the intellectual enterprise.

I also wanted to compare aggregate smarts to intellectual balance. In the plot to the right on the x-axis you have the combined value of math and verbal scores in standard deviation units. A negative value indicates lower values combined, and a positive value higher. Obviously though you can have a case where two disciplines have the same average, but the individual scores differ a lot. So I wanted to compare that with the difference between the two scores. You can see then in the plot that disciplines like classics are much more verbal, while engineering is more mathematical. Physical scientists tend to be more balanced and brighter than engineers. Interestingly linguists have a different profile than other social scientists, and cognitive psych people don’t cluster with others in their broader field. Economists are rather like duller physicists. Which makes sense since many economists are washed out or bored physicists. And political science and international relations people don’t stack up very well against the economists. Perhaps this is the source of the problem whereby economists think they’re smarter than they are? Some humility might be instilled if economics was always put in the same building as physics.

In regards to my own field of interest, the biological sciences, not too many surprises. As you should expect biologists are not as smart as physicists or chemists, but there seems to be two clusters, with a quant and verbal bias. This somewhat surprised me. I didn’t expect ecology to be more verbal than genetics! And much respect to the neuroscience people, they’re definitely the smartest biologists in this data set (unless you count biophysicists!). I think that points to the fact that neuroscience is sucking up a lot of talent right now.

The main caution I would offer is that converting to standard deviation units probably means that I underweighted the mathematical fields in their aptitudes, because such a large fraction max out at a perfect 800. That means you can’t get the full range of the distribution and impose an artificial ceiling. In any case, the raw data in the table below. SDU = standard deviation units.

 

Field V-mean M-mean V-SDU M-SDU Average-SDU Difference-SDU
Anatomy 443 568 -0.16 -0.11 -0.13 -0.05
Biochemistry 486 669 0.20 0.56 0.38 -0.36
Biology 477 606 0.13 0.15 0.14 -0.02
Biophysics 523 727 0.51 0.95 0.73 -0.43
Botany 513 626 0.43 0.28 0.35 0.15
Cell & Mol Bio 497 658 0.29 0.49 0.39 -0.20
Ecology 535 638 0.61 0.36 0.49 0.26
Develop Bio 490 623 0.24 0.26 0.25 -0.02
Entomology 505 606 0.36 0.15 0.25 0.22
Genetics 496 651 0.29 0.44 0.36 -0.16
Marine Biology 499 611 0.31 0.18 0.24 0.13
Microbiology 482 615 0.17 0.21 0.19 -0.04
Neuroscience 533 665 0.60 0.54 0.57 0.06
Nutrition 432 542 -0.25 -0.28 -0.27 0.03
Pathology 468 594 0.05 0.07 0.06 -0.02
Pharmacology 429 634 -0.28 0.33 0.03 -0.61
Physiology 464 606 0.02 0.15 0.08 -0.13
Toxicology 465 610 0.03 0.17 0.10 -0.15
Zoology 505 609 0.36 0.17 0.26 0.20
Other Biology 473 626 0.09 0.28 0.19 -0.19
Chemistry, Gen 483 681 0.18 0.64 0.41 -0.47
Chemistry, Analytical 464 652 0.02 0.45 0.23 -0.43
Chemistry, Inorganic 502 690 0.34 0.70 0.52 -0.37
Chemistry, Organic 490 683 0.24 0.66 0.45 -0.42
Chemistry, Pharm 429 647 -0.28 0.42 0.07 -0.69
Chemistry, Physical 513 708 0.43 0.82 0.62 -0.39
Chemistry, Other 477 659 0.13 0.50 0.31 -0.37
Computer Programming 407 681 -0.46 0.64 0.09 -1.10
Computer Science 453 702 -0.08 0.78 0.35 -0.86
Information Science 446 621 -0.13 0.25 0.06 -0.38
Atmospheric Science 490 673 0.24 0.59 0.41 -0.35
Environ Science 493 615 0.26 0.21 0.23 0.06
Geochemistry 514 657 0.44 0.48 0.46 -0.05
Geology 495 625 0.28 0.27 0.27 0.01
Geophysics 487 676 0.21 0.61 0.41 -0.40
Paleontology 531 621 0.58 0.25 0.41 0.33
Meteology 470 663 0.07 0.52 0.30 -0.46
Epidemiology 485 610 0.19 0.17 0.18 0.02
Immunology 492 662 0.25 0.52 0.38 -0.26
Nursing 452 531 -0.08 -0.35 -0.22 0.27
Actuarial Science 460 726 -0.02 0.94 0.46 -0.96
Applied Math 487 730 0.21 0.97 0.59 -0.76
Mathematics 523 740 0.51 1.03 0.77 -0.52
Probability & Stats 486 728 0.20 0.95 0.58 -0.75
Math, Other 474 715 0.10 0.87 0.48 -0.77
Astronomy 525 706 0.53 0.81 0.67 -0.28
Astrophysics 540 727 0.66 0.95 0.80 -0.29
Atomic Physics 522 739 0.50 1.03 0.77 -0.52
Nuclear Physicsl 506 715 0.37 0.87 0.62 -0.50
Optics 495 729 0.28 0.96 0.62 -0.68
Physics 540 743 0.66 1.05 0.85 -0.40
Planetary Science 545 694 0.70 0.73 0.71 -0.03
Solid State Physics 514 743 0.44 1.05 0.74 -0.62
Physics, Other 519 723 0.48 0.92 0.70 -0.44
Chemical Engineering 490 729 0.24 0.96 0.60 -0.72
Civil Engineering 456 705 -0.05 0.80 0.38 -0.85
Computer Engineering 465 716 0.03 0.87 0.45 -0.85
Electrical Engineering 465 722 0.03 0.91 0.47 -0.89
Industrial Engineering 426 699 -0.30 0.76 0.23 -1.06
Operations Research 483 743 0.18 1.05 0.61 -0.88
Materials Science 509 728 0.39 0.95 0.67 -0.56
Mechanical Engineering 471 721 0.08 0.91 0.49 -0.83
Aerospace Engineering 498 725 0.30 0.93 0.62 -0.63
Biomedical Engineering 504 717 0.35 0.88 0.62 -0.53
Nuclear Engineering 500 720 0.32 0.90 0.61 -0.58
Petroleum Engineering 414 676 -0.40 0.61 0.10 -1.01
Anthropology 532 562 0.59 -0.15 0.22 0.73
Economics 508 707 0.39 0.81 0.60 -0.43
International Relations 531 588 0.58 0.03 0.30 0.55
Political Science 523 574 0.51 -0.07 0.22 0.58
Clinical Psychology 484 554 0.18 -0.20 -0.01 0.38
Cognitive Psychology 532 627 0.59 0.28 0.44 0.30
Community Psychology 441 493 -0.18 -0.60 -0.39 0.43
Counseling Psychology 444 500 -0.15 -0.56 -0.35 0.41
Developmental Psychology 476 563 0.12 -0.14 -0.01 0.26
Psychology 476 546 0.12 -0.25 -0.07 0.37
Quantitative Psychology 515 629 0.45 0.30 0.37 0.15
Social Psychology 518 594 0.47 0.07 0.27 0.40
Sociology 490 541 0.24 -0.28 -0.02 0.52
Criminal Justice/Criminology 418 477 -0.37 -0.71 -0.54 0.34
Art history 536 549 0.62 -0.23 0.20 0.85
Music History 536 596 0.62 0.08 0.35 0.54
Drama 514 541 0.44 -0.28 0.08 0.72
Music History 490 559 0.24 -0.17 0.03 0.40
Creative Writing 553 540 0.76 -0.29 0.24 1.06
Classical Language 619 633 1.32 0.32 0.82 0.99
Russian 584 611 1.03 0.18 0.60 0.85
American History 533 541 0.60 -0.28 0.16 0.88
European History 554 555 0.77 -0.19 0.29 0.97
History of Science 596 661 1.13 0.51 0.82 0.62
Philosophy 591 630 1.08 0.30 0.69 0.78
Classics 609 616 1.24 0.21 0.72 1.02
Comp Lit 591 588 1.08 0.03 0.56 1.06
Linguistics 566 630 0.87 0.30 0.59 0.57
Elementary Education 438 520 -0.20 -0.42 -0.31 0.22
Early Childhood Education 420 497 -0.35 -0.58 -0.46 0.22
Secondary Education 484 576 0.18 -0.05 0.07 0.24
Special Education 424 497 -0.32 -0.58 -0.45 0.26
Physical Education 389 487 -0.61 -0.64 -0.63 0.03
Finance 466 721 0.03 0.91 0.47 -0.87
Business Adminstraiton 434 570 -0.24 -0.09 -0.16 -0.14
Communication 458 517 -0.03 -0.44 -0.24 0.41
Theology 537 583 0.63 -0.01 0.31 0.64
Social Work 428 463 -0.29 -0.80 -0.54 0.52
(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Data Analysis, GRE, Intelligence, Social Science 
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Likely presidential candidate Rick Perry’s college transcript at Texas A & AM has been published. Here are the highlights:

…In his freshman and sophomore year, Perry struggled with core science classes, earning D’s in several organic chemistry classes and C’s in general chemistry and physics.

But after Perry switched his major at the beginning of his fall semester in 1970, his grades didn’t improve. Perry got a C in Reproduction in Farm Animals, a C in genetics, a D in Feeds & Feeding, a C in Sheep & Angora Goat Production and two C’s in animal breeding classes.

Many of Perry’s other classes involved military education. Perry has previously credited his time in the A&M Corps of Cadets with giving him the necessary discipline to complete school.

Perry got two C’s in Development of Air Power and took four levels of World Military Systems, earning two C’s, a B and an A. The A was one of only two Perry earned at college — the other was for a class called Improv. of Learning.

The future governor only took one political science class while he was in school — American National Government, for which he earned a B. Other classes outside of Perry’s major included Shakespeare and Writing for Professional Men, which earned him two D’s.

Perry took two summer sessions before his senior year but still needed two more after the rest of his class graduated to complete a degree. He graduated in August of 1972.


The article goes on to note that George W. Bush, John F. Kerry, and Al Gore Jr. were all mediocre students. John McCain was famously a poor student at the Naval Academy (though the I.Q. scores of all four are in the 1.5 to 2 standard deviations above the mean, so a lot of this is laziness and complacency). But what about Perry’s rivals? I suspect Mitt Romney is not going to want his transcript released, but that’s because he’s smart enough that his stellar grades are going to accentuate his “pointy-headed” nerd reputation. Romney transferred from Stanford to be with his future wife at B.Y.U. and graduated as a valedictorian. He enrolled at a joint law & business program at Harvard, graduating cum laude in the former (top 1/3) and a Baker Scholar in the latter (top 5 percent). He later went on to become a management consultant, a profession which puts a premium on raw general intelligence (whether this sector as a whole adds that much value in the greater economy is a different issue, but it certainly adds value to the consultants, as they leverage their cleverness into big paychecks).

Finally there’s Barack H. Obama. He graduated magna cum laude from Harvard Law, but to my knowledge his standardized test scores and grades from Occidental and Columbia have never been released. Why? I can think of two possible reasons. He received some affirmative action considerations in his transfer to Columbia and acceptance into Harvard Law School, which he capitalized upon effectively (becoming editor of the law review and graduating magna cum laude). So he would want to emphasize the later upswing of his higher education career (recall that George W. Bush received class-based affirmative action to obtain a spot at Harvard Business School). Or, like Romney Obama does not want to release his transcripts because he already has a reputation of being a pointy-headed nerd, and doesn’t want to exacerbate that any further.

In general I’m for democracy. But I’m not a big fan of this fake populism whereby conventionality and mediocrity in academics is acceptable, even a badge of honor, in our candidates for head of state. In contrast our political executives are tall and slim, on the tails of the distribution in physical metrics! (shorter candidates like George W. Bush and John McCain are usually short only for politicians, not for the general male population) I don’t expect presidential candidates to have grasped the basics of topology or quantum chemistry. But do we really want the person who has their finger on the nuclear button to be that personable and likable guy whose primary aim was to not fail? I suspect we do if the range of candidates is a judge. My own personal sympathies in regards to Romney vs. Perry are probably obvious, but if I had to bet I would go with Perry. He has “people skills.” Romney is, as Mike Huckabee famously observed, the boss who is going to fire you. But sometimes people need to be fired, including the electorate. Though I guess that’s not a good attitude to take in a democracy.

Image credit: Gage Skidmore

(Republished from Discover/GNXP by permission of author or representative)
 
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Long time reader Ian comments:

A comparison with “the American public” isn’t really appropriate – to even be in the pool where you’re thinking about an academic career, you need to have a college degree. And that population if memory serves, is far more liberal than the population at large. More realistic would be a comparison with the population of people who have graduate degree….

Roughly about ~20% of Americans self-identify as “liberal,” and ~40% as conservative. The General Social Survey has a variable POLVIEWS, which asks individuals to assign themselves to a position on a political spectrum, from “extremely liberal” to “extremely conservative,” like so:

1 = Extremely liberal
2 = Liberal
3 = Slightly liberal
4 = Moderate
5 = Slightly conservative
6 = Conservative
7 = Extremely conservative

So in other words, the higher the integer, the more conservative the individual. The GSS has a variable, EDUCATION, which records the highest level attained. It falls into three classes, high school, bachelor’s, and graduate degrees (I assume those who did not complete high school are omitted because they didn’t attain an education?). Additionally, it has a 10 word vocabulary test, WORDSUM, which has a 0.71 correlation with general intelligence. I combined those on the interval 0-4 (they got 0 to 4 answers correct on the test), and labeled them “dull.” 5-8 I labelled “average. And finally, 9 and 10 I labeled smart (about 20% are dull, 65% average, and 15% smart, in the total data set). Constraining the sample to the year 2000 and later, I produced the following charts:


e

~9% of the sample have graduate degrees, while 25% have bachelor’s degrees. So you aren’t really seeing middling educational attainments. There is obviously some tendency toward an increase in the proportion of self-identified liberals at graduate levels of education, but the biggest notable trend is the collapse of self-described “moderates” among the more intelligent or educated cohorts. I sometimes wonder if the vacuousness of political moderation is one reason why the term “centrist” is popular among those who are neither liberal nor conservative, but have a higher socioeconomic status.

Long time readers know this fact about the dullness of moderates, but I thought I’d reiterate. It’s interesting, if consistent. For what it’s worth, I think my own political views are becoming more moderate. But don’t confuse correlation with causation!

(Republished from Discover/GNXP by permission of author or representative)
 
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The 800-Pound Mama Grizzly Problem:

Ms. Palin, in fact, draws almost as much search traffic worldwide as the man she would face if she wins the Republican nomination: Barack Obama. And her name is searched for about 30 percent more often than the President’s among Google users in the United States.

Some members of Ms. Palin’s family also draw as much attention has the other Presidential contenders. Todd Palin, her husband, gets about as much search traffic as Mr. Pawlenty. Bristol Palin, her daughter (and a finalist on “Dancing With the Stars”), gets several times more than any of them (as does her former boyfriend, Levi Johnston).

I thought of this News IQ Quiz from Pew. I got 12 out of 12, which apparently places me in the top 1% of quiz takers? The only question I hesitated on was #11 for what it’s worth. Check out how different demographics do in the aggregate and by question:


response

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Ideology, Science • Tags: Democracy, Intelligence, News, Politics 
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