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So sayeth Aggro in the thread down below:

“They should have measured eye and hair color — we don’t have any representative data! Seriously, they’ll take extra long to measure all kinds of weird things that only an anthropometer would know of, but not eye and hair color.”

I too have previously lamented this odd failure in easy measurement. A literature search had me coming up short for an adequate published sample of American eye and hair color. The best estimate I could cobble together from several small studies was that about 25% of American whites were blond. But, Ho Ho!, the National Longitudinal Survey of Youth is online and carries these simple treasures within its bosom.

The following hair and eye color information was self-reported in 1985 by a representative sample of those born between 1957-1965 (ages 20-28; currently 43-51). I’ve included blacks and Hispanics for the gender breakdown:

The first observation is that blond hair is exhibited by a little less than 20% of the white population; smaller than the estimates mentioned above. Second, consistent with Razib’s previous look at published data from Iceland and the Netherlands, blue eyes are more common in men than in women. Also like the European data, green eyes are more common in women, though the NLSY difference is not as extreme. Blond hair is also more common in females. The trend in all three groups is for females to report lighter hair pigmentation; 66% of white males report darker hair, compared with 55% of females, and both black and Hispanic females are much more likely than men to report ‘brown’ hair instead of ‘black’. Unfortunately, since the data are self-reported it’s difficult to know how much of this is subjective. Is this a further example of lighter pigmentation in women, or does sexual dimorphism in pigmentation lead men and/or women to view their own pigmentation as more “sex-typical”?

I was also curious about how these figures differ for various European-American ancestries:

English ancestry Americans and German Americans are very similar for eye and hair color. Hair color is somewhat darker with the French and Irish, and much darker for Italians. Eye color is not darker for the Irish, but is again somewhat darker for the French, and much darker for the Italians.

Finally, we’ve also discussed the link between personality, behavior, and light pigmentation before, so I took some quick, rough looks to see if there was any signal within the English/German sample. The answer is: not from what I could see. There were no meaningful differences between dark and light haired people in getting in trouble with the police, in getting into physical fights at school or work, or in pregnancy before marriage.

• Category: Science • Tags: Human Biodiversity, Pigmentation 
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Dear Readers,

Currently I’m compiling my own dataset of international cognitive test scores. Right now I’m moving on to China. China contains nearly 20% of the human species, with every province being the size of a large country, so it would be nice to get a fuller picture for China than other places. The good news here is that Chinese scientists have engaged in a good deal of intelligence testing. The bad news (for me) is that most of these studies are confined to Chinese language journals.

I’m looking for a temporary collaborator who can read Chinese to help me find and extract data from Chinese language studies. Ability to read Chinese and curiosity about the subject are all you really need.

If you are interested, please contact me by clicking my name above.

Also if any readers are at an institution with electronic access to many Chinese journals (such as the following) and are willing to share the wealth, please contact me as well.


• Category: Science 
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Recently Charles Murray has promoted the idea that too many people are seeking 4 year degrees: “Let’s stop this business of the B.A., this meaningless credential”. Last year he wrote in the Wall Street Journal:

If you want to do well [in college], you should have an IQ of 115 or higher. Put another way, it makes sense for only about 15% of the population, 25% if one stretches it, to get a college education. And yet more than … 40% of all persons in their late teens are trying to go to a four-year college–enough people to absorb everyone down through an IQ of 104.

Several months ago, the Inductivist found this to be a canny estimate: in the 1960s the average college graduate had an IQ very close to 115, and today the average college graduate has an IQ of 105.

But what does this mean for the individual? Murray suggests that college debt, lack of relevant job training, and years of lost workforce wages and experience await those below the 85th percentile:

They are in college to improve their chances of making a good living … and would do better in vocational training … two-year colleges … [are] about right for learning many technical specialties, while four years is unnecessarily long … Finding a good lawyer or physician is easy. Finding a good carpenter, painter, electrician, plumber, glazier, mason–the list goes on and on–is difficult, and it is a seller’s market. Journeymen craftsmen routinely make incomes in the top half of the income distribution while master craftsmen can make six figures.

I find the thinking here plausible, and these seem like testable enough ideas. Luckily, all the relevant variables are included in the General Social Survey.

It’s graph day on gnxp. The x axis in the figure below represents the number of correct answers on the 10 question WORDSUM mini IQ test included in the GSS. The y axis represents the respondent’s income in constant dollars. The colored lines represent five educational categories, and one occupational category. Moving left to right we see the average income of people in each category as their IQ score increases from 0-10 correct answers. ‘Junior college’ represents the two-year vocational degree Murray references. And ‘Craft and Trade Workers’ covers over 50 skilled trade categories like electrician, mason, plumber, carpenter, and mechanic, coded by the survey.

The first observation here is that educational degrees, whether they confer skills or credentials, are more important to income than IQ when minimum thresholds are met. Trade workers, and 2 and 4-year college graduates are not significantly represented in the lowest three IQ categories. Graduate holders have an even higher minimum IQ. Second, income rises within 5 of the 6 categories as IQ increases. Higher IQ generates the biggest pay-off differences between those with advanced degrees, which is consistent with IQ increasing in importance as jobs become more complex. Third, merely earning a Bachelor’s degree is a golden ticket. People with average and below average IQs are getting just as much of a financial return out of their 4-year degree as those above the 85th percentile. This suggests many more people of marginal ability should be seeking a Bachelor’s degree, not less. Fourth, the two lines for junior college and trade occupations overlap substantially, as we would expect if most people in trade occupations went to trade school. Fifth, and most directly related to Murray’s argument, people with 4-year degrees earn much more than people with 2-year degrees and trade jobs at every level of IQ. Average IQ people will get a much, much larger monetary reward from completing a 4 year school than a 2 year school. So the BA is far from being a “meaningless credential” when it comes to “chances of making a good living”.

It’s possible people with average IQs who complete college are exceptional in other ways. But there is no other empirical evidence that vocational school is better at generating income for those

• Category: Science 
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In DNA Era, Worries About Revival of Prejudice by NYT genetics reporter Amy Harmon is a frank and sensitive look at the burgeoning implications of genetic science to our political and social landscape.

Nothing quite like this article has ever really appeared in the press. The underlying message is that the biological information environment is changing rapidly and if we don’t start opening up the tightly monitored public forum for it right now, we are endangering our ability to handle its potential revelations with any sort of real preparedness or rationality. We, as a civilization, can’t just keep silencing and punishing everyone who broaches these topics in a way that challenges our hopes and visions about human equality. The result is to shut down the discussion completely and disarm ourselves to ideas that are most likely – to some degree – correct.

I appear in this article. The quote is a tiny part of many emails and phonecalls I shared with the reporter in which I stressed that the political implications of genetic differences are still open. I urged that liberals and people of all ethnic groups stake out a territory right now, so the rug doesn’t get pulled out from under them. I urged progressives to stop predicating their ideas of justice so religiously on empirical matters which might very well get falsified (leaving the door wide open for rival ideologies). When they do this, open talk or diverse public opinions about genetic differences will not evoke the same level of political threat. Ideally it would be irrelevant.

The time for taboos on this topic needs to end. It needs to end because these are issues we, as a diverse world and society, need to discuss and debate openly and fairly, in order to prepare for and accommodate our natural differences as human beings.

And for new readers coming in through the Times, my defense of James Watson mentioned by Harmon, James Watson Tells the Inconvenient Truth: Faces the Consequences, is here.

• Category: Science • Tags: Human Biodiversity, New York Times 
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… [M]ight it be fair also to say that the champions of ‘no difference’ in race or sex, or intelligence … are the guardians of a greater ‘untruth’ that allows people to live together in mutual harmony, implying that these critics really deserve to be praised as our protectors even when they are factually wrong? … it is roughly how the self-appointed guardians choose to present themselves – leaving aside, usually, the step of frankly admitting that they are promoting factual untruths when they know that they are.

W.D. Hamilton – (“… one of the greatest evolutionary theorists of the 20th century”). Narrow Roads of Gene Land. Vol. II: The Evolution of Sex, p 332.

The public intellectual forum is being manipulated with intimidation and coercion and you are being lied to. The media is not doing its job, and the scientific community is not playing its proper public role as a beacon of dispassionate truth seeking, as a conduit of knowledge to the public, or in fostering an open and fair intellectual climate. Both are abusing their power and authority to do the opposite of their honor bound social and intellectual roles; facts are being distorted in service of values.

This post is a very long and detailed examination of what James Watson said, what the data reveal about James Watson’s claims (i.e. are they, or are they not factually accurate), and what the media and scientists told the public about what the data reveal about James Watson’s claims.


It’s difficult to name many more important living figures in 20th century biology than James Watson. He ushered in the current age of molecular biology with his achievements in 1953, he built up one of the world’s greatest biological research facilities from damn near scratch, and he is a former head of the Human Genome Project.

Given such an august curriculum vitae, you would think that this man perhaps understands just a few things about genetics. But given only the condescending media coverage, you’d think this eminent geneticist was somehow “out of his depth” on this one.

In his interview with the Times on Oct. 14th, we learned that:

… [Watson] is “inherently gloomy about the prospect of Africa” because “all our social policies are based on the fact that their intelligence is the same as ours – whereas all the testing says not really”, and I know that this “hot potato” is going to be difficult to address.

These thoughts were a continuation of an important theme in his new book Avoid Boring People:

… there is no firm reason to anticipate that the intellectual capacities of peoples geographically separated in their evolution should prove to have evolved identically. Our wanting to reserve equal powers of reason as some universal heritage of humanity will not be enough to make it so.

Although Watson’s book had already been out for a month with these more euphemistic, but still obvious, comments on race and intelligence, no one expressed any outrage. In fact the reviews were reverential and universally positive.

The explicit reference to intelligence and people of African heritage in his interview was clearly a violation of a much more formidable taboo. Still I am not aware of there being much noise about it until Oct. 17th when the Independent caused an immediate stir by calling attention to the remarks: Africans are less intelligent than Westerners says DNA pioneer.

There’s no point in rehashing the rapid sequence of events in detail: several of Watson’s sold-out speaking engagements were cancelled, many critical articles appeared in the British press, trailed by the American press a few days later, hundreds of blogs were fuming with negative commentary, including ones by the editors of Scientific American and Wired Magazine, a number of associations issued statements condemning his words, and soon he was suspended from his chancellorship at Cold Spring Harbor. Watson cancelled his already ruined book tour and flew home to tend to the destruction. It was too late; the eminent biologist retired in disgrace on Oct. 26th.

One thing, though, was conspicuously missing from this whole irritating denouement: any semblance of factual refutation. There is good reason for this: everything Watson got in trouble for saying was entirely correct!


The “scientific community” is a broad and inappropriately encompassing term, but to the extent such a thing exists as a social or public entity (I’m not talking about the research literature), it is fair to say it has pronounced Watson’s claims not only false, but also outside the bounds of “legitimate” scientific discourse. Since only a small fraction of scientific disciplines have any relevance to Watson’s claims, it is clear almost all of these scientists are just evaluating the claims with the same ignorant, moralized mental framework people in the general public use to look at (and editorialize upon) scientific claims about evolution.

Watson’s claim was that intelligence testing shows lower intelligence scores in Africa than Europe. Is this or is this not true? The Science Museum in London responded by canceling Watson’s speaking engagement by deeming this claim, not only scientifically false, but outside the realm of “legitimate” scientific inquiry (Whatever that is!) altogether:

In a statement, [The Science Museum in London] said: “We know that eminent scientists can sometimes say things that cause controversy and the Science Museum does not shy away from debating controversial topics.

“However, the Science Museum feels that Nobel Prize winner James Watson’s recent comments have gone beyond the point of acceptable debate and we are as a result cancelling his talk at the museum.”

Watson’s claim was that intelligence testing shows lower intelligence scores in Africa than Europe. Is this or is this not true? Francis Collins, Watson’s successor over the Human Genome Project, told the media this is not true:

Dr. Francis Collins, director of the National Human Genome Research Institute, said that “I am deeply saddened by the events of the last week, and understand and agree with Dr. Watson’s undoubtedly painful decision to retire in the aftermath of a racist statement he made that was both profoundly offensive and utterly unsupported by scientific evidence.

Watson’s claim was that intelligence testing shows lower intelligence scores in Africa than Europe. Is this or is this not true? Rick Kittles told the media this is not true:

Rick Kittles, an associate professor of genetic medicine at the University of Chicago, said Watson’s remarks aren’t backed by science.

Watson’s claim was that intelligence testing shows lower intelligence scores in Africa than Europe. Is this or is this not true? Robert Sternberg told the media that the ‘scientific findings’ show otherwise:

Robert Sternb
erg, a prominent researcher on race and IQ at Tufts University, called Watson’s statement “racist and most regrettable.”

“It is unfortunate that some people with great expertise in one area sometimes lose their sense of perspective and come to view themselves as expert in areas about which they know nothing,” Sternberg said Thursday in an e-mail response to questions. “They then proceed to embarrass themselves as well as society in general with their comments that express their own ideology rather than scientific findings.”

Watson’s claim was that intelligence testing shows lower intelligence scores in Africa than Europe. Is this or is this not true? Steven Rose told the media that the scientific literature shows otherwise:

Steven Rose, a professor of biological sciences at the Open University and a founder member of the Society for Social Responsibility in Science, said: “… If [Watson] knew the literature in the subject he would know he was out of his depth scientifically, quite apart from socially and politically.”

Watson’s claim was that intelligence testing shows lower intelligence scores in Africa than Europe. Is this or is this not true? The Federation of American Scientists issued a statement condemning Watson, claiming that there is no scientific literature showing this:

The Federation of American Scientists condemns the comments of Dr. James Watson that appeared in the Sunday Times Magazine on October 14th… The scientific enterprise is based on the promotion and proof of new ideas through evidence, however controversial, but Dr. Watson chose to use his unique stature to promote personal prejudices that are racist, vicious and unsupported by science.

Unfortunately our esteemed band of sputtering media scientists forgot to provide, in all of these instances, any of their allegedly voluminous citations to the contrary. Allow me, then, to take a different position, with the added benefit of evidence:

James Watson is one of the most important living figures in American science. The claim in his new book Avoid Boring People, that basic evolutionary logic predicts we should expect intelligence differences between racial groups is, if anything, an uncomplicated truth. Watson’s claim in his recent interview with Charlotte Hunt-Grubbe that intelligence testing shows lower scores in Africa than Europe is likewise, entirely supported by the scientific literature. As is Dr. Watson’s statement that there are many talented people of African descent, which clarifies he is speaking of different average scores, not that said populations are homogenous.

Below I am adding 65 psychometric intelligence study citations for sub-Saharan Africa, collected in>IQ & Global Inequality, Race Differences in Intelligence, and IQ & the Wealth of Nations. The citations cover 47% of SS African countries or 78% of the people by national population numbers. The studies vary in quality, sample size, and representativeness, but broadly agree in their findings. Representative studies of the school age population with large sample sizes do not exhibit higher scores, much less scores that approach anything like European norms.


Sub-Saharan Africa
Countries: 43
W/ data: 20 (47% coun/78% pop)
Studies: 65
IQ: 68

West Africa
Countries: 20
W/ Data: 6 (30% coun/65% pop)
Studies: 15
IQ: 67

Central Africa
Countries: 5
W/ Data: 3 (60% coun/80% pop)
Studies: 9
IQ: 64

East Africa
Countries: 8
W/ Data: 5 (63% coun/93% pop)
Studies: 16
IQ: 72

Southern Africa
Countries: 10
W/ Data: 6 (60% coun/76% pop)
Studies: 25
IQ: 69


The recent August issue of the European Journal of Personality features a paper titled The g-factor of international cognitive ability comparisons: the homogeneity of results in PISA, TIMSS, PIRLS and IQ-tests across nations by German psychologist Heiner Rindermann. This paper includes an open peer commentary by 31 international scholars, as well as a response by Rindermann. The target paper provides valuable new IQ data from sub-Saharan African, or rather let’s us know we have an overlooked source of intelligence data. I am adding these papers to the gnxpforum files section for you to access.

Starting in the 1960s and picking up pace in the early 1990s various well-implemented student assessment tests have been conducted for the purposes of international educational comparisons, including the Trends in International Mathematics and Science Study (TIMSS), the International Educational Achievement (IEA) measures, and the OECD’s Programme for International Student Assessment (PISA). The cross-cultural test construction, sampling techniques, and quality control for these tests are exemplary. These international tests have also included half a dozen sub-Saharan African countries, and the test construction and sampling techniques are likewise very good. For example Ghana, Botswana, and South Africa were included in TIMSS 2003. For each tested grade level, at least 5000 random students from 150 schools were tested in these countries.

Gene Expression bloggers recognized the strong correlation between these types of tests and IQ as far back as 2004, but recently this has reached the academic literature. Last year Richard Lynn and Jaan Mikk reported correlations of .92-1.00 between IQ and TIMSS 2003 for math and science.

In his paper, Heiner Rindermann takes this sort of analysis to the next level by collecting data from all 20 total international student assessment tests encompassing some 78 countries and comparing them with measured IQ data from 128 countries. Rindermann finds, first of all that the combined national student results correlate perfectly with the combined national IQ data (.98), demonstrating the assessment scores and the IQ scores are the same measured construct. With all these diverse kinds of tests for each nation, Rindermann examines the data together through factor analysis and finds that the g factor of intelligence explains some 95% of the variance in the test results: “Thus, cognitive ability differences across nations are by and large unidimensional”. (p 681) The stable differences between nations in all cognitive type tests are explained by the g factor.

Furthermore Rinderman
n emphasizes that, consistent with previous IQ testing, the g loaded international assessment tests reveal sub-Saharan African IQ scores that characteristically range from 1.5-2.5+ standard deviations below European and East Asian norms:

… I do not believe that the [sub-Saharan testing] scores at the general level are largely incorrect: The low values correspond to too many other variables and aspects standing for low cognitive abilities like results of student assessment and Piaget studies (e.g. Botswana in IEA-Reading 14 year-old pupils 1991 330, as IQ 75; South-Africa in TIMSS 8th graders 1999 259, as IQ 64; Ghana in TIMSS 8th graders 2003 266, as IQ 65; South-Africa in TIMSS 8th graders 2003 254, as IQ 63; plausibility considerations lead to lower results for the youth of Africa because of low school attendance rates and unrepresentative participation of countries), poor quality school systems, high skipping rates, low rates of high school degrees, low patent application rates, no famous universities, and many reports of everyday behaviour from officials, traders, journalists, ethnologists and other scientists in 19th century to this day… (p 770)

Thus typical African IQ scores of 70 and below can still be taken as a reliable finding. It is not simply the manufactured data of racialist researchers, or a byproduct of inadequate testing procedures. And, more importantly from the standpoint of the Watson controversy, certainly no reliable body of evidence has shown anything like parity with typical European scores.

I’d like to reiterate, then, that IQs below 70 do not by themselves signify mental retardation, as it is commonly understood as a pathological state.

There are two types of retardation: familial and organic. The former is caused by normal population variation in intelligence while the latter is caused by diverse individual problems such as genetic defects or head injuries. Related to this, the IQ scores of people with familial retardation correlate normally with their parent and sibling’s IQ scores (.50), while the IQ scores of people with organic retardation are not much associated with the IQs in their family.

Retardation is measured by a combination of IQ and adaptive scales. Sometimes an IQ of 70 is used as the threshold of retardation. People with familial retardation and organic retardation of matched IQ perform the same in academic and training contexts, but organically retarded individuals do worse on the adaptive scales which measure things such as self-care, motor skills, and social functioning, signifying a broader range of mental dysfunction and some sort of developmental damage.

In the US, consistent with the normal bell curve, there are proportionately about five times as many blacks (16%) with an IQ of 70 or below than there are whites (3%). But basically the same proportional number of whites and blacks are organically retarded (whites 1.5%, blacks 2.0%). (>The g Factor, p 369)

The African scores indicate that there are proportionately about seventeen times as many sub-Saharan Africans with IQs below 70 (50%) than American whites (3%), and possibly even more. While organic retardation is probably somewhat higher among Africans, due to overall more challenging health conditions, this should in no way be regarded as characteristic of their normal intelligence variation.

There is nothing particularly meaningful or necessary about an IQ of 70 as a threshold for ‘retardation’. La Griffe Du Lion writes:

In 1959, [the American Association on Mental Deficiency] set the IQ threshold for mental retardation at 85. The civil rights movement of the next decade forced psychologists to rethink this boundary, because half the African American population fell below it. In 1973, responding to this concern, AAMD (by then AAMR) changed the threshold for retardation from IQ 85 to IQ 70. The boundary moved south by one standard deviation! The proportion of blacks below the threshold instantly dropped from about 50 percent to 12 percent.

In other words 50% of modern Africans are no more ‘mentally retarded’ than 50% of African-Americans were ‘mentally retarded’ in the 1960s. These are labels of convenience designed for normal within-population variation. But the real world academic and economic consequences of IQs of 70-85 and below are the same no matter what you label them.



Groups of people may differ genetically in their average talents and temperaments … proponents of ethnic and racial differences in the past have been targets of censorship, violence, and comparisons to Nazis. Large swaths of the intellectual landscape have been reengineered to try to rule these hypotheses out a priori (race does not exist, intelligence does not exist, the mind is a blank slate…)

Steven Pinker – The Edge Annual Question – 2006. “What is your dangerous idea?”

Of course pointing to the testing data alone is hardly sufficient to quell these latter-day inquisitors. There is, sadly, an infinite regress of obscurantist objections designed to intellectually moot these issues entirely. These objections are not scientific, and are at odds with the data, logic, and, more often, both.

Systematic media misrepresentations of psychometric science have been occurring for going on 40 years.

In 1988 Stanley Rothman and Mark Snyderman published>The IQ Controversy, the Media and Public Policy. Along with data from their 1987 study of over 1000 scholars in fields familiar with IQ testing, such as psychology, sociology, and behavioral genetics, Rothman and Snyderman took a quantitative look at media coverage of IQ and demonstrated how this media coverage habitually diverged with mainstream scholarly opinion.

This is particularly egregious during times of IQ controversy.

Media reports and editorials were quick to attack Watson on the premise that any statement about intelligence measures is scientifically indefensible, because science cannot study something so immeasurable and indefinable as intelligence. Cornelia Dean reporting for the New York Times did just this:

[T]here is wide disagreement about what intelligence consists of and how – or even if – it can be measured in the abstract.

Laura Blue in Time Magazine,8599,1673952,00.html>asserted:

… science has no agreed-upon definition of “intelligence” either – let alone an agreed-upon method to test it. All kinds of cultural biases have been identified in IQ tests, for example. If there is something fundamental in our brains that regulates our capacity to learn, we have yet to separate its effects from the effects of everything that we experience after we’re born.

Similarly, Steven Rose in the New Statesmen:

… the question of what constitutes ‘intelligence’ is itself problematic – the word has much broader and diverse meanings than what can be encompassed in IQ tests.

Robert Sternberg in the Chicago Tribune:

Sternberg, a critic of traditional intelligence testing, believes intelligence can mean something different for different cultures. In parts of Africa, a good gauge of intelligence might be how well someone avoids infection with malaria — a test of cleverness that most Americans likely would flunk.

In the same way, for many Africans who take Western IQ tests, “our problems aren’t relevant to them,” Sternberg said.”

First of all, an intelligence test cannot and is not designed to tell you the reasons people score differently. So the fact that the test by itself has nothing to say about genetics is not a failure of the test. Second, the assertion of widespread chaos within science over intelligence is false. The statement that there are a number of theoretical differences about the concept of intelligence is only trivially true. In the practical context of research, provisional understanding, and ‘normal science’ this is rhetorically equivalent to underlining evolution as “only a theory” in media reports. Intelligence as a working scientific research concept and tool is both widespread (as a search for terms such as ‘IQ’, ‘Intelligence’ or ‘cognitive ability’ on PubMed, Google Scholar, or similar publication databases will show), and broadly consistent in approaches and shared theory, methods, premises, and data. The American Psychological Association’s 11 member ‘taskforce’, assembled for a consensus statement on intelligence research, reported:

… [M]uch of our discussion is devoted to the dominant psychometric approach, which has not only inspired the most research and attracted the most attention (up to this time) but is by far the most widely used in practical settings.

Third, “All kinds of cultural biases” certainly have not been reported in IQ tests. The tests are not “biased” in the sense that psychometricians use this term. Again the APA taskforce showed consensus on this issue:

… the relevant question is whether the tests have a “predictive bias” against Blacks, Such a bias would exist if African-American performance on the criterion variables (school achievement, college GPA, etc.) were systematically higher than the same subjects’ test scores would predict. This is not the case. The actual regression lines (which show the mean criterion performance for individuals who got various scores on the predictor) for Blacks do not lie above those for Whites; there is even a slight tendency in the other direction (Jensen, 1980; Reynolds &:Brown, 1984). Considered as predictors of future performance, the tests do not seem to be biased against African Americans.

Similarly Robert Sternberg argues that the tests are biased because they allegedly don’t measure the sorts of abilities that are necessary for Africans to succeed in their unique environmental niche. This statement is not only a patronizing and idyllic caricature of African needs, but is also empirically false. This idea was addressed by psychologist Earl Hunt in his peer commentary on Rindermann:

There are two reasons that national-level differences in intelligence have been disregarded. One is that it can be argued that intelligence, as evaluated by these tests, is a Western concept, and that the abilities evaluated by the tests may not be the ones valued by non-western societies. This is a spurious argument for two reasons. First, the economic indicators we are trying to relate to intelligence are also Western concepts. As the commentator Thomas Friedman has said, the world is flat. We are not asking whether or not various national populations have the ability to compete in their own societies, we are asking about their ability to compete in the Western-defined international marketplace. The tests are appropriately designed to address this question. (p 727)

In fact, economists Eric A. Hanushek and Ludger Woessmann report that the association between economic outcomes and measured intelligence appear to be even higher within developing African countries than within Western countries. (pp 13-15) Similarly, at the national level, psychologists Earl Hunt and Werner Wittmann found that the relationship between GDP and national average IQ was stronger for the mostly African developing countries than it was among the developed industrial countries. (0.70 vs 0.58)

In their literature review, Kendall, Verster, and Von Mollendorf found that correlations between employee performance and educational outcomes and cognitive ability did not differ for blacks and whites in Southern Africa. In other words, at school or on the job, an African white with an IQ score of 70 will perform no different than an African black with the same score. Similarly an African black with an IQ of 115 performs the same as an African white with the same score.

So “our problems” certainly are relevant to Africans, and certainly are “their” problems. Unless issues such as child mortality, health, sanitation, rule of law, political stability, material comfort, global influence, and life expectancy are somehow not relevant to Africans.

Appearances to the contrary, the mendacious Robert Sternberg is, in fact, implicitly agreeing with Watson, while nevertheless shouting him down in the media. Sternberg does not deny that psychometric general intelligence is as low as reported in Africa, nor does he deny that this psychometric intelligence has the academic and economic consequences that the “racist… know-nothing” Watson implied it did. In fact, Sternberg himself has conducted intelligence studies in East Africa, and found the same characteristically 70ish IQ scores, as well as correlations between IQ and academic achievement in this region similar to the correlations reported in developed countries. Thus Sternberg’s reply to Watson in The New Scientist:

The tests as they stand show some differences between various groups of children. The size of the differences and what groups do best in the tests depend on what is tested. For example, with various collaborators I have found that analytical tests of the kind traditionally used to measure so-called general abilities tend to favour Americans of European and Asian origin, while tests of creative and practical thinking show quite different patterns. On a test of oral storytelling, for example, Native Americans outperform other groups.

Ok, so Sternberg agrees that people of European and Asian descent do better on the analytical and general ability tests that reflect the skills vital for functioning in a first-world globalized economy, and therefore must be claiming that Watson is a racist ignoramus only for privileging these general abstract reasoning abilities with the designation of ‘intelligence’ over the ‘oral storytelling intelligence’ of Native-Americans, or the ‘mosquito dodging intelligence’ of sub-Saharan Africans! But if oral storytelling or mosquito dodging are not useful “intelligences” for lifting an individual or a nation out of 1 dollar a day poverty, t
hen Watson can hardly be faulted for expressing concern about the kinds of intelligence not abundant in Africa.

Sternberg is perhaps the most blameworthy scientist to publicly condemn Watson, because he is familiar enough with the data to know Watson is right. His condescending statement that dodging mosquitoes is what characterizes the extent of African needs, is itself seemingly more “racist” than, if not completely identical in substance to, what Watson said. At least Watson appeared to show some sort of concern for what Africans countries require to industrialize, while Sternberg appears to be relativistically dismissing there are problems at all: “Africans are perfectly intelligent… for living like Africans!”

Actually, I believe Sternberg is taking the stage to condemn the factually correct Watson for his own petty academic reasons: Sternberg believes his own unpopular ‘practical intelligence’ (PDF) model could become more popular if the dominant psychometric model becomes increasingly professionally and personally dangerous to touch. Like Howard Gardner’s empirically unimpressive ‘Multiple Intelligences’, there is an intellectual market for politically correct ideas like Sternberg’s model, and fanning the flames of controversy around psychometrics is one way these ideas can cheat to become more popular.

Media red herrings about the supposed ineffability of intelligence or lies about the scientific worthlessness of intelligence testing are designed to moot honesty and openness on this issue, and simply side step the uncomfortable facts. But avoiding facts does not change reality or help shape it to our liking. Intelligence measures predict the kind of social and personal outcomes that people the world over agree are important and desirable. For this reason we need to start engaging this data instead of shooting the messengers. Especially when the messengers we are so casually discarding are important figures like James Watson.



Population genetics now provides a set of reasonably powerful statistical tools that allow us to determine whether… genes that play a role in the brain evolve much faster in certain human races than in others… The answers to such questions could clearly be awkward, if not incendiary… [O]ne of the most obvious questions about population genetic studies of human beings, especially human races [is s]hould they be performed?… The interesting point – and it’s not widely appreciated – is that this question is rapidly becoming moot. Vast quantities of information about the human genome now pour into publicly available databases on a daily basis. These data are collected with the noblest of intentions (often medical) and are also made public for perfectly good reasons: citizens should have ready access to the fruits of publicly funded science. Indeed it’s almost impossible to imagine how one could stop the sorts of studies I described above. In previous times, granting agencies, such as the NIH or NSF, could block funding for undesirable experiments or scientific journals could refuse to publish them. But with genomic data, minimal money is required (an Internet connection is enough) and any bright graduate student working in his parents’ garage could ask and answer any awkward question he likes. And the Internet thoroughly dashes any chance of preventing the publication of unpleasant results.

H. Allen Orr – ‘Talking Genes’, The New York Review of Books.

Ubiquitous and prepackaged media tropes about race, perhaps more than intelligence, serve not as rational arguments but as apotropaic charms to ward off inconvenient ideas.

Laura Blue in Time Magazine asserted:

… [T]here is no scientific basis for [Watson’s comments] … For one thing, science has no agreed-upon definition of “race”: however you slice up the population, the categories look pretty arbitrary.

Steven Rose in the New Statesman wrote:

Second, the idea that there is a genetically meaningful African ‘race’ is nonsense. There is wide cultural and genetic diversity amongst African populations from south to north, from Ethiopians to Nigerians. There are, for example probably genetic as well as environmental reasons why Ethiopians make good marathon runners whereas Nigerians on the whole do not.

To group the entire diverse populations of Africa together is a characteristically racist trick.

The Guardian reported:

Other scientists point out that our species is so young – Homo sapiens emerged from its African homeland only 100,000 years ago – that it simply has not had time to evolve any significant differences in intellectual capacity as its various groups of people have spread round the globe and settled in different regions. Only the most superficial differences – notably skin colour – separate the world’s different population groupings. Underneath that skin, people are remarkably alike.

The Chicago Tribue reported:

Damaging statements such as Watson’s — and the potential for misuse of research on race — has led many scientists to avoid the topic altogether. In a 1998 “Statement on ‘Race,'” the American Anthropological Association concluded that ordinary notions of race have little value for biological research in part because of the relatively minor genetic differences among racial groups.

Craig Venter offered this rebuttal to Watson:

As Craig Venter, who pioneered much of America’s work in decoding the human genome, put it: ‘There is no basis in scientific fact or in the human gene code for the notion that skin colour will be predictive of intelligence.’

And our friend Robert Sternberg similarly added:

… [T]here is nothing special about skin colour that serves as a basis for differentiating humans into so-called races… Curiously, we do not apply the concept of “race” to colours of dogs or cats… [These] problems with our understanding of … race show that the criticism being levelled at Watson is based on science rather than political correctness… race is a socially constructed concept, not a biological one.

Well, it’s good to see that Venter and Sternberg are basing their criticisms on SCIENCE instead of political correctness! Of course the purposefully obscurantist conflation between ‘skin color’ and ancestry is something I’ve dealt with before.


These individuals would not be classified by geneticists, sociologists, psychologists, physical anthropologists, or any sort of scientist as members of the European race. They would not self-identify as white Americans, nor would they be considered as such. They would be eligible for affirmative action.

Human races, like dog ‘breeds’, are defined in the biological context by shared ances
try, not by single appearance traits. With ancestry you can predict many genes and many traits, but with single genes or single traits, you can not predict many other genes or traits. Which is why you can still easily identify the ancestry of the depigmented individuals in the above picture. Population ancestry predicts the sum patterns of one’s genotype and phenotypical traits (e.g. general racial appearance) while any single variable – in this case, skin color – does not.

Denial of this fact was dubbed Lewontin’s Fallacy (PDF) by British geneticist A.W.F. Edwards. ‘Skin color’ is a false and intentionally misleading straw-definition of race, that dishonorable public scientists such as Sternberg and Venter use to manufacture consent for their ideological viewpoints about human equality.

Steven Rose argues that the racial grouping ‘sub-Saharan Africans’ racistly lumps “diverse populations”, but in the next breath uses such equally problematic and diversity encompassing racial categories as ‘Nigerians’ and ‘Ethiopians’. And that is the problem with ‘race’ criticism, any population concept is diverse and fuzzy – German, Northwest European, New Yorker, Ashkenazi Jew, Asian – and yet the population concept is an essential cog in evolutionary science. The Neo-Darwinian Synthesis that grounded evolutionary theory in genetics, was the vital fusion of Darwin and population genetics. A population is a race is a population. To deny the population is literally a denial of evolution.

Race critics don’t and could never explain satisfactorily why groupings like ‘sub-Saharan Africans’, ‘Mediterranean’, or ‘Dutch’ have no place in science, and more importantly the way scientists do use such groupings in practice belies the alleged uselessness (that is, like intelligence, the population concept clearly allows them to perform ‘normal science’). And, yes, Dr. Rose, ‘African’ is a genetically meaningful entity:

In one of the most extensive of these studies to date, considering 1,056 individuals from 52 human populations, with each individual genotyped for 377 autosomal microsatellite markers, we found that individuals could be partitioned into six main genetic clusters, five of which corresponded to Africa, Europe and the part of Asia south and west of the Himalayas, East Asia, Oceania, and the Americas

You’ll note, also, that this coauthor of the extreme anti-hereditarian tract Not In Our Genes also suggests marathon running ability in Ethiopia has a genetic component. This belief has become socially acceptable, but the evidence for genetic differences in population intelligence is hardly less spectacular than the evidence for this difference. I don’t recall the large transracial adoption study that tested for marathon running. Each of these inferences can be based on the cross-cultural consistency and physiological correlates (PDF) of performance. It is ideology, not data, which keeps Rose from drawing the same inferences about the intelligence difference. It is also ideology that allows Rose to keep his job for this comment, while Watson lost his job for his substantively identical, yet socially taboo comment.

The claim that there has not been enough time for evolution to act on non-superficial traits is not scientific. First because nonsuperficial traits take no more time to evolve than superficial traits. More importantly, reasonable selection parameters allow for significant differences to arise between populations in 100 years, much less 100,000. Richard Lynn argues that genetics account for 1.3 SD in intelligence between sub-Saharan Africans and Europeans. Genetic anthropologist Henry Harpending illustrates how a 1 SD difference in a hypothetical trait, with a lower additive heritability than intelligence, could evolve in 500 years:

… [A]ssume time preference has an additive heritability of 25%. Assume that everyone with time preference more than 1 sd above the mean of the distribution has double the fitness of everyone else. About 16% of the population then has twice the number of offspring as everyone else on average.

After a generation of reproduction the new mean time preference will be increased by (0.2 * .25) or 5% of a standard deviation. In 20 generations, 500 years, time preference should go up by a full standard deviation.

This is similar to Cochran and Harpending’s model (PDF) for the evolution of Ashkenazi intelligence. Also allowing for .5-1 SD higher intelligence in mere centuries.

Biologist Gerhard Meisenberg put it this way (PDF):

… the argument that the 100,000 years or so since the dispersal out of Africa were insufficient for the evolution of genetic differences is invalid. To create an IQ difference of, say, 15 points between two populations in 100,000 years, natural selection would have to drive their IQs apart by only 0.004 points every generation – about 1% of the selective pressure in late 20th-century America

Furthermore, is it true that races only differ in a few appearance related genes? Nope. We already have this data and it’s not true by a long shot. Nick Wade reported early last year in the New York Times:

In a study of East Asians, Europeans and Africans, Dr. Pritchard and his colleagues found 700 regions of the genome where genes appear to have been reshaped by natural selection in recent times. In East Asians, the average date of these selection events is 6,600 years ago.

Many of the reshaped genes are involved in taste, smell or digestion, suggesting that East Asians experienced some wrenching change in diet. Since the genetic changes occurred around the time that rice farming took hold, they may mark people’s adaptation to a historical event, the beginning of the Neolithic revolution as societies switched from wild to cultivated foods.

Some of the genes are active in the brain and, although their role is not known, may have affected behavior. So perhaps the brain gene changes seen by Dr. Pritchard in East Asians have some connection with the psychological traits described by Dr. Nisbett.

In fact, far from being identical, virtually all genes that are related to individual differences in human health and behavior differ to some degree in their frequency between racial populations. This is something you can and should test for yourself.

Gene Expression blogger p-ter recently wrote a very nice post titled So You Want to be a Population Geneticist. This is a How-2 for several genetic databases that can be used by anyone with an Internet connection to search for allele frequencies or signatures of selection. You can use these to look at the gene frequencies of the four population groups from the International HapMap Project: Utah whites, Nigerian Yoruba, Han
Chinese, and Tokyo Japanese.

You’ll note then that the International HapMap Project is designed to illuminate the genetic differences between these four “sliced-up”, “arbitrary”, “diverse”, “genetically meaningless” racial populations, that are “defined by skin color”. Didn’t the HapMap people get the memo from SCIENCE that these categories are a racist biological fiction???

Go into Google News, and look under search terms like ‘gene’ and ‘genes’, and pick any random recent news items reporting an association between some gene/s and some sort of individual differences. This would not include studies that e.g. talk about genes that differentiate humans or chimpanzees, or that claim no individual differences.

Take the genes you find in the news and plug them into the HapMap Genome Browser , using p-ter’s tips, and look how the frequencies differ. We even have an open thread for you to test your own hypotheses and report your findings from these databases. Unlike Watson’s righteous regulators, we don’t believe your hypotheses are immoral or “beyond the point of acceptable debate”.

Posters on the Half Sigma blog recently used p-ter’s post to see how CHRM2, a gene described as the first “yielding consistent evidence of association with IQ across multiple studies conducted by independent research groups”, was distributed across the HapMap populations:

T is *way* more present than A in rs324650 among East Asians (91%) relative to Europeans (47%) and blacks (27%). Since T is associated with an increase in 4-5 points of performance IQ (what is that, anyway? Is that different from G?) that is significant.

The poster ‘Marc’ continued by examining how alleles differed for DTNBP1:

Let’s look at rs:760761, rs:2619522 and rs:2619538, all of which are associated with increased or decreased intelligence in DTNBP1.

Regarding rs:760761, 18% of Europeans carry the T allele, which knocks about 8 points off the ol’ IQ, compared to around 7% of East Asians and 37% of blacks.

Regarding rs:2619522, the numbers are similar. 18% of whites carry the G allele, which knocks about 7 points off the ol’ IQ, versus around 8% of Asians and 35-36% of blacks…

Regarding rs:2619538, 61% of whites carry the T allele, which adds about 6.5 points to one’s IQ, versus about 1% of Asians and 67% of blacks…

If 6% more blacks carry the T allele than whites (67% vs. 61%) on rs:2619538, and the T allele codes for 6.5 FSIQ (full scale IQ) points, then this gives blacks an advantage of .4 IQ points over whites from this SNP.

Also, if 60% more whites carry the T allele than Asians, and the T allele codes for 6.5 FSIQ points, than this gives whites an advantage of 3.9 IQ points over Asians from this SNP.

So the cumulative effect thus far would be:
minus 3.6 points for blacks relative to whites;
and minus 0.2 points for East Asians relative to whites.

A difference in one or two “intelligence genes” does not by itself suggest that one population is smarter than another, because evolutionary environments select for phenotypes not genotypes. So when populations have many genetic differences, the genes may interact in different ways, and some of the genes that make individuals more intelligent in one population may not have the same effect in another. (In other words if we’d prefer to not take the above results at face value, we have to accept that races are even more genetically different, not less)

However, several pieces of evidence make it doubtful that most intelligence genes are like this. For one, mixed race people generally have IQ scores about midway between their parent populations. (save one study of Eurasian mixes) So I would say the gradual accumulation of similar results for other “intelligence genes” would certainly serve as evidence for the genetic viewpoint.

These differences do illustrate, in yet another way, the falseness of popular arguments that races are genetically identical, or that genetic differences can somehow only exist for “appearance genes”. But virtually any gene showing individual differences that you plug in those databases will also be distributed differently among racial groups and demonstrate the same points.



James Watson implied a belief that the uniquely low intelligence of both continental Africans and African-Americans are probably related to familiar genetic causes. This belief is deemed unacceptable to express in public, even in most academic contexts, or hold in private. This is despite the fact that the research evidence in support of this position is stronger than the research evidence that contradicts it. Thus even top scientists like Watson are punished for holding beliefs that are more scientific and logical, while scientists that hold to less scientific beliefs and illogical arguments are rewarded. This is a rot on the soul of science.

Many statements in the press asserted or implied that various environmental theories account for intelligence differences between ethnic groups. These statements do not, in fact, agree with the evidence.

The Chicago Tribune asserted:

The study of racial differences in IQ is among the most deeply contentious fields in all of science. Most researchers agree that tests have revealed some differences among racial groups — but even larger differences between people of different income levels.

Steven Rose asserted:

Even where there are such average differences in IQ score, as for instance between Black and White populations in the US, there are no scientifically valid methods to enable one to untangle the many interacting factors of the validity of IQ tests themselves, as measures of anything other than school performance, educational and social deprivation, the history of slave-owners versus slaves and continuing racism, which may account for them.

The Associated Press reported:

Jan Schnupp, a lecturer in neurophysiology at Oxford University, said Watson’s remarks “make it very clear that he is an expert on genetics, not on intelligence.”

Schnupp said undernourished and undereducated people often perform worse on intelligence tests than the well off.

“Race has nothing to do with it, and there is no fundamental obstacle to black people becoming exceptionally bright,” Schnupp said.”

Contrary to the above claims, differences in intelligence between income groups are not larger than intelligence differences between racial groups in the US, nor do differences in income or wealth account for the racial differences. Whites from households in the lowest income bracket have higher IQ scores than blacks from households in the highest income bracket:

One of the most disturbing, I think perhaps the most disturbing fact in our whole book is that black students coming from families earning over 70,000 are doing worse on their SATS, on average–it’s always on average–than white students from families in the lowest income group. You want to cry hearing that figure. I mean, it’s so terrible.

One of the largest modern sociology studies of American students found that ethnicity was the single most important predictor of academic achievement:

Chin quotes with approval a book, “Beyond the Classroom,” by Laurence Steinberg, B. Bradford Brown and Sanford M. Dornbusch, which says “of all the demographic factors we studied in relation to school performance, ethnicity was the most important. . . . In terms of school achievement, it is more advantageous to be Asian than to be wealthy, to have non-divorced parents, or to have a mother who is able to stay at home full time.”

Contra Rose, a number of experiments are able to test all of these environmental theories. For one transracial adoption experiments control for all the shared aspects of the environment that differ between whites and blacks (parenting, income, nutrition, neighborhood), while structural equation models test for possible uncommon factors between whites and blacks that could be acting on IQ (which would include things like racism). These experiments do not lend support to any existing or plausible environmental theories for the remaining lower intelligence scores of people of African descent in Western societies. The Minnesota Transracial Adoption Study found that, by adulthood, the difference in IQ scores between adopted black and adopted white children raised side by side in the same high income households in mostly homogeneous Northern US upper class neighborhoods was 18 IQ points (p 185):

The Minnesota Transracial Adoption Study

IQ at Age 7        IQ at Age 17

W-W 111.5        W-W 101.5
W-B 105.4        W-B 93.2
B-B 91.4        B-B 83.7

W-W = Adopted children with two white biological parents.
W-B = Adopted children with one black and one white biological parent.
B-B = Adopted children with two black biological parents.

The W-W/W-B difference is 8.3 IQ points. The B-W/B-B difference is 9.5 IQ points. And the W-W/B-B difference is 17.8 IQ points.

The difference in IQ scores between 2 black biological parent adoptees and 1 black biological parent adoptees is nearly 10 IQ points despite the fact that both share the exact same social identity.

Similarly a dozen mixed race children that were raised under some mistaken information that they had two black biological parents nevertheless developed IQ scores like the other mixed race children.

There are no simple or plausible environmental theories to explain these kinds of findings.

An additional popular argument is that the Flynn Effect, the observed rise in IQ scores over time, is evidence that African-Americans or African countries will eventually reach parity with white norms. This typically includes the premise that white intelligence in the recent past was even lower than modern black intelligence. A typical example:

US Blacks, with an average IQ today of 85, have the same IQ as US Whites with an IQ of 100 in 1957. If 1957 US Whites were not stupid, then neither are US Blacks today. It’s time to shut up about the “low Black IQ”, since by any reasonable standard, it is not really low at all.

These arguments are wrong for the simple fact that the Flynn Effect is not a gain in real g factor intelligence, while the differences between nations and ethnic groups are differences in g factor intelligence. These findings led a 2004 team to state:

It appears therefore that the nature of the Flynn effect is qualitatively different from the nature of B-W [Black-White] differences in the United States… [so] implications of the Flynn effect for B-W differences appear small

James Flynn, namesake of the secular increase, reiterates (DOC) these points:

Factor analysis is a way of measuring this tendency of some people to do better or worse than average across the board; and it yields something called g (a sort of super-correlation coefficient), which psychologists call the general intelligence factor…

When you analyze IQ gains over time, you often find that they do not constitute enhancement of these latent traits — they do not seem to be general intelligence gains, or quantitative factor gains, or verbal factor gains (Wicherts et al, in press). In the language of factor analysis, this means that IQ gains over time tend to display ‘measurement artifacts or cultural bias’. For a second time, we are driven to the conclusion that massive IQ gains are not intelligence gains or, indeed, any kind of significant cognitive gains. (pp 27-28)

Flynn believes the secular increase represents important changes in specific narrow aspects of developed cognitive style, but not a rise in g intelligence.

It is therefore incorrect that 1945 US whites were less intelligent than 2007 US blacks. The Flynn Effect has little apparent bearing on racial intelligence gaps.

This also applies to developing countries. The Flynn Effect reveals that IQ scores in the developed world were some 1.5-2 standard deviations lower in the beginning of the 20th century. (See this GNXP post for the data) These scores are similar to ones in modern African. Some studies also reveal even faster Flynn gains in developing countries than what we observe in developed countries, and it is argued these countries are simply experiencing, in slight delay, what happened in developed countries during the 20th century. But this interpretation is not tenable if there were no actual rises in g factor intelligence in developed countries. It is incorrect that developed countries had lower g intelligence in the first half of the 20th century corresponding to IQs of 70. Meanwhile, as the Rindermann paper reveals, the scores across modern nations do correspond to real intelligence differences. Likewise, extremely low IQ scores in modern Africa, unlike scores in developed countries prior to the mid-20th century, correspond to genuine deficits in g intelligence.

With improvements in nutrition it is likely that scores in Africa will rise over time. But these increases will probably be genuine and of a different nature than what we observed in developed countries. It is unlikely that scores in Africa will meet or rise above those of African-Americans in the next century.

All of this underlines the fact that IQ can’t always be taken at face value. Gains or differences in IQ exceeding 1 SD can sometimes be ‘hollow’, or
unreflective of real general intelligence, being manifested only at the lower order strata of intelligence. (See this paper examining how these false gains can arise through practice effects) Fortunately we have good methods for evaluating the construct validity of the tests and the integrity of the IQ scores.



Many intellectuals refuse to interpret psychometric claims or ideas about human diversity rationally. Despite 100 years of data showing that ethnic groups differ in their general intelligence, these claims are still rejected on moral grounds. Many of those who deny these claims either implicitly believe that ‘intelligence’ is a reflection of human worth, or believe any claim of such a difference must be a cryptic assertion of racial worth. Either way it prevents the claims from being interpreted fairly, in the factual, rather than normative, manner intended by the people who attempt to discuss this science in an open forum.

Watson’s original statements about the lower general intelligence of Africans were interpreted as statements about the lower human worth of Africans. When Watson then publicly apologized that his words were being misinterpreted in this way and clarified that claims about racial intelligence differences are not claims about human worth, the confused media reported that Watson had recanted his claims about intelligence differences!!

The science journal Nature ran an editorial claiming:

Watson has apologized and retracted the outburst… He acknowledged that there is no evidence for what he claimed about racial differences in intelligence.

Time magazine also suggested he retracted his intelligence claims:

Watson said in a statement he issued at the Royal Society Thursday. “That is not what I meant. More importantly from my point of view, there is no scientific basis for such a belief.”

And on that much at least, he’s right. For one thing, science has no agreed-upon definition of “race”: however you slice up the population, the categories look pretty arbitrary. For another, science has no agreed-upon definition of “intelligence” either

And Cornelia Dean at the New York Times asserted, not once, but in two separate reports that Watson retracted his intelligence claims. Even doctoring Watson’s apology by cut-and-pasting together two entirely separate Watson quotes:

In an interview published Sunday in The Times of London, Dr. Watson is quoted as saying that while “there are many people of color who are very talented,” he is “inherently gloomy about the prospect of Africa.”

“All our social policies are based on the fact that their intelligence is the same as ours – whereas all the testing says not really,” the newspaper quoted him as saying.

“I cannot understand how I could have said what I am quoted as having said,” Dr. Watson said in a statement given to The Associated Press. “There is no scientific basis for such a belief.”

And again in another article:

Dr. Watson… was quoted in The Times of London last week as suggesting that, overall, people of African descent are not as intelligent as people of European descent. In the ensuing uproar, he issued a statement apologizing “unreservedly” for the comments, adding “there is no scientific basis for such a belief”.

False. False. False.

Dear media,

Please read the actual text of James Watson’s apology printed in the Independent, instead of mangling it and interpolating it with your own claims:

To those who have drawn the inference from my words that Africa, as a continent, is somehow genetically inferior, I can only apologise unreservedly. That is not what I meant. More importantly from my point of view, there is no scientific basis for such a belief

The overwhelming desire of society today is to assume that equal powers of reason are a universal heritage of humanity….

To question this is not to give in to racism. This is not a discussion about superiority or inferiority, it is about seeking to understand differences, about why some of us are great musicians and others great engineers.

Watson would only be retracting his intelligence claims if he considered those claims tantamount to claims of ‘superiority’ or ‘inferiority’, which he clearly emphasizes he doesn’t. Watson is saying that questioning that all races are equal in intelligence is not racism, it is trying to figure out why the world looks the way it does, with the greatest engineers and the greatest musicians disproportionately coming, in a systematic way, from different racial backgrounds. In other words culturally separated people of African descent have been musical innovators across a diverse range of cultures (in the Middle East, Africa, Europe, North and South America, and the Caribbean), while culturally separated people of East Asian descent have excelled at math and science across a diverse range of cultures (in Asia, Europe, North and South America, and the Caribbean).

This is not a claim of racial ‘superiority’ or ‘inferiority’, either in terms of legal worth or even in terms of overall talent – since groups all have different strengths and weaknesses. It is simply the recognition that people of different genetic heritage, on average, reveal different talents wherever they are found in the world, and there is one explanation that best accounts for these observations: evolution.

In other words, Watson was thinking like a scientist. Which is exactly why he was punished.

The moral laws of our society dictate that we are not allowed to think scientifically about some issues. Especially not in public.



According to the media and members of the scientific community, James Watson hurt science itself.

An editorial in the top science journal Nature asserted:

Crass comments by Nobel laureates undermine our very ability to debate such issues, and thus damage science itself.

Similarly the Chicago Tribune featured this:

“The damage to Watson’s legacy from his statements may be difficult to mend,” said Jerry Coyne, a professor of evolutionary genetics at the University of Chicago.

“He’s done tremendous damage to science, to himself and to social equality,” Coyne said. “It makes us all look bad.”

Along with E.O. Wilson, James Watson is perhaps the most distinguished living figure in American biology, and yet even he was not immune to immediate expulsion from the very lab he created and built up over 40 years of his life, and excommunication from the scientific establishment that celebrated him. All this for one crime: voicing scientific facts and hypotheses that made this community uncomfortable. The same personal and professional fate befell former Harvard president Larry Summers in 2005 for a purely academic discussion of females in science during an economics conference intended for discussing t
his very subject!

What effect will this continuing intellectual mob violence have on future and current scientists and researchers who want to freely study human genetics, cross-cultural psychology, sociology, or any discipline that may reveal similar facts that have the potential to cause their professional or personal destruction by an intellectual community that resembles the medieval church?

Those who punish, those who lie, those who silence, those who condemn, those who intimidate… they have corrupted science.

They have injured the intellectual openness, freedom, and fairness of our society and our institutions, with untold costs to our collective human well-being.

Not James D. Watson.




IQ: 64
Age: Adults
N: 80
Test: CPM
Ref: Berlioz, L. (1955). Etude des progressive matrices faite sur les Africains de Douala. Bulletin du Centre Etude Recherce Psychotechnique, 4, 33-44.

Equatorial Guinea
IQ: 59
Age: 10-14
N: 48
Test: WISC-R
Ref: Fernandez-Bellesteros, R., Juan-Espinoza, M., Colom, R., and Calero, M. D. (1997). Contextual and personal sources of individual differences in intelligence. In J. S. Carlson (Ed.), Advances in Cognition and Educational Practice. Greenwich, Cnn.: JAI Press.

IQ: 67
Studies: 4

IQ: 80
Age: Adults
N: 225
Test: CF
Ref: Buj, V. (1981). Average IQ values in various European countries. Personality and Individual Differences, 2, 168-169.

IQ: 62
Age: 15
N: 1,693
Test: CPM
Ref: Glewwe, P. and Jaccoby, H. (1992). Estimating the determinants of Cognitive Achievement in Low Income Countries. Washington, D.C.: World Bank.

IQ: 65 (266)
Age: 16
N: 5,100
Test: TIMSS 2003
Ref: Martin, M.O., Mullis, I.V.S., & Chrostowski, S.J. (Eds.) (2004). TIMSS 2003 Technical Report. Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Boston College.

IQ: 67
TIMSS 2003: 266 (65)
TIMSS sum: 301
TIMSS+PIRLS sum: 304
Sum: 300

IQ: 67
Studies: 2

IQ: 63
Age: 5-14
N: 50
Test: AAB
Ref: Nissen, H. W., Machover, S. and Kinder, E. F. (1935). A study of performance tests given to a group of native African Negro children. British Journal of Psychology, 25, 308-355.

IQ: 70
Age: Adults
N: 1,144
Test: SPM
Ref: Faverge, J. M. and Falmagne, J. C. (1962). On the interpretation of data in intercultural psychology. Psychologia Africana, 9, 22-96.

IQ: 69
Studies: 5

IQ: 70
Age: Children
N: 480
Test: Leone
Ref: Farron, O. (1966). The test performance of coloured children. Educational Research, 8, 42-57.

IQ: 64
Age: Adults
N: 86
Test: SPM
Ref: Wober, M. (1969). The meaning and stability of Raven’s matrices test among Africans. International Journal of Psychology, 4, 220-235.

IQ: 69
Age: 6-13
N: 375
Test: CPM
Ref: Fahrmeier, E. D. (1975). The effect of school attendance on intellectual development in Northern Nigeria. Child Development, 46, 281-285.

IQ: 79 (401)
Age: 15
N: 2,368
Test: IEA-R 1991
Ref: Elley, W. B. (1992). How in the world do students read? The Hague: IEA.

IQ: 69
ISARS: 34 (69)

Sierra Leone
IQ: 64
Studies: 2

IQ: 64
Age: Adults
N: 122
Test: CPM
Ref: Berry, J. W. (1966). Temne and Eskimo perceptual skills. International Journal of Psychology, 1, 207-229.

IQ: 64
Age: Adults
N: 33
Test: CPM
Ref: Binnie-Dawson, J. L. (1984). Biosocial and endocrine bases of spatial ability. Psychologia, 27, 129-151.

Burkina Faso
Cote d’Ivoire
The Gambia
Sao Tome and Principe


Democratic Republic of Congo
IQ: 65
Studies: 5

IQ: 64
Age: Adults
N: 67
Test: SPM
Ref: Verhagen, P. (1956). Utilite actuelle des tests pour l’etude psychologique des autochones Congolese. Revue de Psychologie Appliquee, 6, 139-151.

IQ: 68
Age: 10-15
N: 222
Test: SPM
Ref: Laroche, J. L. (1959). Effets de repetition du Matrix 38 sur les resultats d’enfants Katangais. Bulletin du Centre d’etudes et Reserches Psychotechniques, 1, 85-99.

IQ: 62
Age: 8
N: 47
Test: KABC
Ref: Boivin, M. J. and Giordani, B. (1993). Improvements in cognitive performance for schoolchildren in Zaire following an iron supplement and treatment for intestinal parasites. Journal of Pediatric Psychology, 18, 249-264.

IQ: 68
Age: 7-12
N: 95
Test: LABC
Ref: Boivin, M. J., Giordani, B., and Bornfeld, B. (1995). Use of the tactual performance test for cognitive ability testing with African children. Neuropsychology, 9, 409-417.

IQ: 65
Age: 7-9
N: 130
Test: KABC
Ref: Giordani, B., Boivin, M. J., Opel, B., Nseyila, D. N., and Lauer, R. E. (1996). Use of the K-ABC with children in Zaire. International Journal of Disability, Development, and Education, 43, 5-24.

Republic of Congo
IQ: 64
Studies: 3

IQ: 64
Age: Adults
N: 1,596
Test: SPM
Ref: Latouche, G. L. and Dormeau, G. (1956). La foration professionelle rapide en Afrique Equatoriale Francaise. Brazzaville: Centre d’Etude des Problems du Travail.

IQ: 64
Age: 17-29
N: 320
Test: SPM
Ref: Ombredane, A., Robaye, F., and Robaye, E. (1952). Analyse des resultats d’une application experimentale du matrix 38 a 485 noirs Baluba. Bulletin Centre d’etudes et Reserches Psychotechniques, 7, 235-255.

IQ: 73
Age: 8
N: 73
Test: SPM
Ref: Nkaye, H. N., Huteau, M., and Bonnet, J. P. (1994). Retest effect on cognitive performance on the Raven Matrices in France and in the Congo. Perceptual and Motor Skills, 78, 503-510.

Central African Republic
IQ: 64
Age: Adults
N: 1,149
Test: SPM
Ref: Latouche, G. L. and Dormeau, G. (1956). La foration professionelle rapide en Afrique Equatoriale Francaise. Brazzaville: Centre d’Etude des Problems du Travail.



IQ: 71
Studies: 4

IQ: 69
Age: 7-16
N: 291
Test: Various
Ref: Fahmy, M. (1964). Initial exploring of the intelligence of Shilluk children. Vita Humana, 7, 164-177.

IQ: 64
Age: 6
N: 80
Test: DAM
Ref: Badri, M. B. (1965a). The use of finger drawing in measuring the Goodenough quotient of culturally deprived Sudanese children. Journal of Psychology, 59, 333-334.

IQ: 74
Age: 9
N: 292
Test: DAM
Ref: Badri, M. B. (1965b). Influence of modernization on Goodenough quotients of Sudanese children. Perceptual and Motor Skills, 20, 931-932.

IQ: 72
Age: 8-12
N: 148
Test: SPM
Ref: Ahmed, R. A. (1989). The development of number, space, quantity, and reasoning concepts in Sudanese schoolchildren. In L. L. Adler (Ed.), Cross Cultural Research in Human Development. Westport, Conn.: Praeger.

Kenya< br />IQ: 72
Studies: 6

IQ: 69
Age: Adults
N: 205
Test: CPM
Ref: Boissiere, M., Knight, J. B., and Sabot, R. H. (1985). Earnings, schooling, ability, and cognitive skills. American Economic Review, 75,1016-1030.

IQ: 75
Age: 6-10
N: 1,222
Test: CPM
Ref: Costenbader, V. and Ngari, S. M. (2000). A Kenya standardisation of the Coloured Progressive Matrices. School Psychology International, 22, 258-268.

IQ: 69
Age: 12-15
N: 85
Test: CPM-MH
Ref: Sternberg, R. J., Nokes, C., Geissler, P. W., Prince, R., Okatcha, F., Bundy, D. A., and Grigorenko, E. L. (2002). The relationship between academic and practical intelligence: A case study in Kenya. Intelligence, 29, 401-418.

IQ: 76
Age: 7
N: 118
Test: CPM
Ref: Daley, Y. C., Whaley, S. E., Sigman, M. D., Espinosa, M. P., and Neuman, C. (2003). IQ on the rise: the Flynn effect in rural Kenyan children. Psychological Science, 14, 215-219.

IQ: 89
Age: 7
N: 537
Test: CPM
Ref: Daley, Y. C., Whaley, S. E., Sigman, M. D., Espinosa, M. P., and Neuman, C. (2003). IQ on the rise: the Flynn effect in rural Kenyan children. Psychological Science, 14, 215-219.

IQ: 63
Age: 6
N: 184
Test: KABC
Ref: Holding, P. A., Taylor, H. G., Kazungu, S. D., and Mkala, T. (2004). Assessing cognitive outcomes in a rural African population: development of a neuropsychological battery in Kilifi district. Journal of the International Neuropsychological Society, 10, 246-260.

IQ: 72
Studies: 3

IQ: 78
Age: 13-17
N: 2,959
Test: SPM
Ref: Klingelhofer, E. L. (1967). Performance of Tanzanian secondary school pupils on the Raven Standard Progressive Matrices test. Journal of Social Psychology, 72, 205-215.

IQ: 65
Age: Adults
N: 179
Test: CPM
Ref: Boissiere, M., Knight, J. B., and Sabot, R. H. (1985). Earnings, schooling, ability,and cognitive skills. American Economic Review, 75,1016-1030.

IQ: 72
Age: 11-13
N: 458
Test: WCST
Ref: Sternberg, R. J., Grigorenko, E. L., Ngorosho, D., Tantufuye, E., Mbise, A., Nokes, C., Jukes, M., and Bundy, D. A. (2002). Assessing intellectual potential in rural Tanzanian school children. Intelligence, 30, 141-162.

IQ: 73
Age: 11
N: 2,019
Test: RPM
Ref: Heyneman, S. P. and Jamison, D. T. (1980). Student learning in Uganda. Comparative Education Review, 24, 207-220.

IQ: 64
Studies: 2

IQ: 65
Age: 15
N: 250
Test: SPM
Ref: Lynn, R. (1994). The intelligence of Ethiopian immigrant and Israeli adolescents. International Journal of Psychology, 29, 55-56.

IQ: 63
Age: 14-16
N: –
Test: SPM
Ref: Kazulin, A. (1998). Profiles of immigrant students’ cognitive performance on Raven’s Progressive Matrices. Perceptual and Motor Skills, 87, 1311-1314.



IQ: 76
Studies: 2

IQ: 77 (366)
Age: 15
N: 5,150
Test: TIMSS 2003
Ref: Martin, M.O., Mullis, I.V.S., & Chrostowski, S.J. (Eds.) (2004). TIMSS 2003 Technical Report. Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Boston College.

IQ: 75 (330)
Age: 15
N: 4,768
Test: IEA-R 1991
Ref: Elley, W. B. (1992). How in the world do students read? The Hague: IEA.

TIMSS sum: 396
TIMSS+PIRLS sum: 398
Sum: 391

IQ: 62
Studies: 2

IQ: 64
Age: 20
N: 149
Test: CPM
Ref: Kendall, I. M. (1976). The predictive validity of a possible alternative to the Classification Test Battery. Psychologia Africana, 16, 131-146.

IQ: 60
ISAMS: 24 (60)

South Africa (blacks)
IQ: 67
Studies: 13

IQ: 63
Age: 9
N: 350
Test: SPM
Ref: Lynn, R. and Holmshaw, M. (1990). Black-white differences in reaction times and intelligence. Social Behavior and Personality, 18, 299-308.

IQ: 67
Age: 8-10
N: 806
Test: CPM
Ref: Jinabhai, C. C., Taylor, M., Rangongo, N. J., Mkhize, S., Anderson, S., Pillay, B. J., and Sullivan, K. R. (2004). Investigating the mental abilities of rural primary school children in South Africa. Ethnicity and Health, 9, 17-36.

IQ: 67
Age: 14-17
N: 152
Test: WISC-R
Ref: Skuy, M., Schutte, E., Fridjhon, P., and O’Carroll, S. (2001). Suitability of published neuropsychological test norms for urban African secondary school students in South Africa. Personality and Individual Differences, 30, 1413-1425.

IQ: 65
Age: 10-12
N: 293
Test: AAB
Ref: Fick, M. L. (1929). Intelligence test results of poor white, native (Zulu), colored, and Indian school children and the social and educational implications. South Africa Journal of Science, 26, 904-920.

IQ: 75
Age: 8-16
N: 1,008
Test: SPM
Ref: Notcutt, B. (1950). The measurement of Zulu intelligence. Journal of Social Research, 1, 195-206.

IQ: 69
Age: Adults
N: 153
Test: WAIS-R
Ref: Nell, V. (2000). Cross-Cultural Neuropsychological Assessment. Mahwah, NJ: Lawrence Erlbaum.

IQ: 64
Age: Adults
N: 703
Test: SPM
Ref: Notcutt, B. (1950). The measurement of Zulu intelligence. Journal of Social Research, 1, 195-206.

IQ: 71
Age: Adults
N: 140
Test: WISC-R
Ref: Avenant, T. J. (1988). The Establishment of an Individual Intelligence Scale for Adult South Africans. Report No. P-91. Pretoria: Human Sciences Research Council.

IQ: 68
Age: 15-16
N: 1,093
Test: JAT
Ref: Lynn, R., and Owen, K. (1994). Spearman’s hypothesis and test score differences between whites, Indians and blacks in South Africa. Journal of General Psychology, 121, 27-36.

IQ: 63
Age: 16
N: 1,096
Test: SPM
Ref: Owen, K. (1992). The suitability of Raven’s Progressive Matrices for various groups in South Africa. Personality and Individual Differences, 13, 149-159.

IQ: 64 (259)
Age: 16
N: 8,146
Test: TIMSS 1999
Ref: Martin, M. O., Gregory, K. D., & Stemler, S. E. (Eds.) (2000). TIMSS Technical Report: IEA’s Third International Mathematics and Science Study at the Eighth Grade (Boston, Intrenational study Center, Boston College).

IQ: 63 (254)
Age: 15
N: 8,952
Test: TIMSS 2003
Ref: Martin, M.O., Mullis, I.V.S., & Chrostowski, S.J. (Eds.) (2004). TIMSS 2003 Technical Report. Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Boston College.

IQ: 69
TIMSS 1995: 270
TIMSS 1999: 259 (64)
TIMSS 2003: 254 (63)
TIMSS sum: 304
TIMSS+PIRLS sum: 328
Sum: 324

IQ: 64
ISAMS: 32 (64)

IQ: 71
Studies: 2

IQ: 77
Age: 13
N: 759
Test: SPM
Ref: MacArthur, R. S., Irvine, S. H., and Brimble, A. R. (1964). The Northern Rhodesia Mental Ability Survey. Lusaka: Rhodes Livingstone Institute.

IQ: 64
Age: Adults
N: 152
Test: SPM
Ref: Pons, A. L. (1974). Administration of tests outside the cultures of their origin. 26th Congress of the South African Psychological Association.

IQ: 70
Studies: 3

IQ: 61
Age: 12-14
N: 204
Test: WISC-R
Ref: Zindi, F. (1994). Differences in psychometric performance. The Psychologist, 7, 549-552.

IQ: 70
Age: 12-14
N: 204
Test: SPM
Ref: Zindi, F. (1994). Differences in psychometric performance. The Psychologist, 7, 549-55

IQ: 76 (372)
Age: 16
N: 2,749
Test: IEA-R 1991
Ref: Elley, W. B. (1992). How in the world do students read? The Hague: IEA.


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Tyler Cowen quotes from a new study testing the relationship between grades and delayed sexual activity.

Last December I passed a paper along to Razib showing that high-school age adolescents with higher IQs and extremely low IQs were less likely to have had first intercourse than those with average to below average intelligence. (i.e. for males with IQs under 70, 63.3% were still virgins, for those with IQs between 70-90 only 50.2% were virgin, 58.6% were virgins with IQs between 90-110, and 70.3% with IQs over 110 were virgins)

In fact, a more detailed study from 2000 is devoted strictly to this topic, and finds the same thing: Smart Teens Don’t Have Sex (or Kiss Much Either).

The team looked at 1000s of representative teens grades 7-12 in the National Longitudinal Study of Adolescent Health and The Biosocial Factors in Adolescent Development datasets, both of which include an IQ test, and include detailed sexual experience questions ranging from hand-holding to intercourse. As with the other study there was a curvilinear relationship: students with IQs above 100 and below 70 were significantly less likely to have had intercourse than those in between. Also like the other study, they found teens with IQs ranging from 75 to 90 had the lowest probability of virginity (the authors note this is also the same IQ range where propensity towards crime peaks).

Depending on the specific age and gender, an adolescent with an IQ of 100 was 1.5 to 5 times more likely to have had intercourse than a teen with a score of 120 or 130. Each additional point of IQ increased the odds of virginity by 2.7% for males and 1.7% for females. But higher IQ had a similar relationship across the entire range of romantic/sexual interactions, decreasing the odds that teens had ever kissed or even held hands with a member of the opposite sex at each age.

While these authors leave off at grade 12th, it would seem plausible to expect that this relationship extends beyond high school. To explore this, plenty of interesting facts come from a 2001 campus sex survey by the joint MIT/Wellesley college magazine Counterpoint (PDF). Looking within and between colleges, IQ appears to delay sexual activity on into young adulthood.

By the age of 19, 80% of US males and 75% of women have lost their virginity, and 87% of college students have had sex. But this number appears to be much lower at elite (i.e. more intelligent) colleges. According to the article, only 56% of Princeton undergraduates have had intercourse. At Harvard 59% of the undergraduates are non-virgins, and at MIT, only a slight majority, 51%, have had intercourse. Further, only 65% of MIT graduate students have had sex.

The student surveys at MIT and Wellesley also compared virginity by academic major. The chart for Wellesley displayed below shows that 0% of studio art majors were virgins, but 72% of biology majors were virgins, and 83% of biochem and math majors were virgins! Similarly, at MIT 20% of ‘humanities’ majors were virgins, but 73% of biology majors. (Apparently those most likely to read Darwin are also the least Darwinian!)

Looking at this chart it would strongly appear that higher complexity majors contain more virgins than majors with lower cognitive demand. This paper provides me with GRE scores by academic discipline, and, in fact, the correlation between the percentage of virgins in each Wellesley major and the average ‘Analytical’ GRE score associated with the discipline is 0.60.

One reason we might guess that smarter people in high school, or in more challenging colleges or majors, delay their sexual debuts is because they are delaying gratification in expectation of future reward. Sexual behavior (or at least the investment needed to procure a partner or sustain one) may compete with time/resources required for other goals, and intelligent people may have more demanding goals. James Watson even hinted at this in a recent Esquire magazine piece:

If I had been married earlier in life, I wouldn’t have seen the double helix. I would have been taking care of the kids on Saturday. On the other hand, I was lonely a lot of the time.

While sex may not be marriage, it may still require effort that intelligent people prefer to invest elsewhere. This would fit Aldus Huxley’s alleged definition of an intellectual as a person who’s found one thing that’s more interesting than sex.

Another idea is that smarter people are more risk averse, and delaying these activities is a byproduct of enhanced concerns about unwanted pregnancy and disease. While not avoiding sexual behaviors, per se, they are just less likely to seek it out or consent to it for fear of the potential consequences.

Another idea is that smarter people are more religious or more ethically conservative, and are trying harder to wait for marriage to have sex.

Another idea, consistent with popular media portrayals of geeks and nerds (males at least), is that intelligent people actually want to have sex, but are simply less likely or unable to obtain willing partners because they are disproportionately viewed as unattractive or undesirable as partners.

Another idea is that intelligent people have lower general sex drives. This shouldn’t be confused with the first theory, where their sex drives would be normal and they have greater self-restraint.

Some insightful digging by blogger Half Sigma into the General Social Survey, which also includes an abbreviated intelligence test, has turned up a number of associations that speak to these theories. The relationship between sexual activity and intelligence found across adolescence and young adulthood appears to continue on into adulthood proper.

Not only do intelligent people have a delayed onset of sexual behavior, Half Sigma found that they also have a lower number of premarital sex partners throughout adulthood (18-39). While this is consistent with the above theory that high IQ people are more religious and conservative, this is, of course, not true. Religiousness correlates with lower IQ, and as HS shows in the same post, intelligent people were also more likely to say that premarital sex was not immoral. (Leaving those who did think it was immoral to participate in the bulk of it!) Most of the other theories are still consistent with this finding though.

Perhaps more revealing, HS, also showed that intelligence correlates with less sex within marriage for the same age range. While still consistent with pregnancy fears and competing interests, lower sex drive seems like a better fit. In fact anothe
r revealing finding from the Counterpoint survey was that while 95% of US men and 70% of women masturbate, this number is only 68% of men and 20% of women at MIT!

Also the idea that more intelligent people are too busy for the opposite sex not just in 7th grade to college, but throughout adulthood and for their own spouse, seems unrealistic. In fact the GSS also shows (PDF) that smarter people spend more time socializing with their friends, indicating their hours aren’t spent as uniquely isolated and narrowly channeled as the theory would require.

But lower sex drive and anxiety about sex’s consequences can’t be the whole story either. Half Sigma also showed that the smartest men in the GSS (approx. IQ >120) were also more likely to visit a prostitute. (Hardly indicative of cautiousness) This may suggest intelligent men are less able to find willing sex partners. Are smart men less attractive to women? Perhaps in some ways. For instance HS found that smart men were less likely to be athletic, and this paper shows, unathletic men and women have fewer sex partners. Athletic men, with more willing sexual partners are also less likely to visit a prostitute. Athletic activity gives men more masculine bodies, which are more attractive to women. A more masculine physique correlates with (PDF) an increased number of sex partners.

So intelligent people have lower libidos and less masculine physiques. What hormone is responsible for both sex drive and masculine builds? That’s right: testosterone.

And two new papers suggest that testosterone may depress IQ. One team found that salivary testosterone levels were lower for preadolescent boys with IQs above 130 and below 70. (the same two groups most likely to be virgins in adolescence)

Another paper suggests that a gene responsible for androgen sensitivity and higher sperm counts may also create a tradeoff for intelligence.

• Category: Science • Tags: IQ, Sex, Testosterone 
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As of this morning the journal Intelligence has a positive review of Lynn’s Race Differences in Intelligence, from behavior geneticist John Loehlin. One issue raised earlier was the reliability of the numbers Lynn reports. Loehlin writes:

Are the numbers accurate? I checked a sample of 40 of the 615 rows in the IQ tables against their sources. . . Result: 14 of the 40, about 1 in 3, showed discrepancies, although mostly minor ones. For example, there were 9 with discrepancies in Ns, such as using an overall N from the study instead of the actual N on which the particular IQ was based. In a similar number of cases, the ages or age ranges were a bit off. . . my [IQ score] estimates and the values in the tables were typically within a couple of IQ points. I only came across one large discrepancy – an IQ 14 points too high (in Table 12.1, row 20; due, according to an e-mail from Lynn, to a clerical error in adding instead of subtracting a Flynn correction). The citations and references were, on the whole, accurate. In short: Yes, the general trends in the tables are probably dependable, if the assumptions regarding Flynn effects, etc., are correct, but it is prudent (as always) to check with original sources before quoting particular results.

Loehlin concludes in a manner similar to my review:

Is this book the final word on race differences in intelligence? Of course not. But Richard Lynn is a major player, and it is good to have his extensive work on this topic together in one place. Future workers who address these matters under this or any other label will find that Lynn has done a lot of spadework for them. And they will also find that there is plenty to ponder over within these pages.

• Category: Science 
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Bloggers Half Sigma and Inductivist are having ongoing fun with the General Social Survey data set: ethnic, gender, and religious comparisons galore! Half Sigma looks at the relationship between the GSS mini-IQ test and religious belief, and finds what we already knew.

• Category: Science • Tags: IQ 
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Gene Expression is 4 years old today, and Razib flexed his blog overlord muscles and made me write a retrospective. I don’t think I have quite the encyclopedic memory he thinks, but he’s right that I’ve followed the blog before there was a blog, as it were, back in April of 2002, when Razib and Godless Capitalist both had their own separate websites. So I’ll add some perspective for the 2002-2003 period.


The “blogosphere” was really starting to consolidate in 2001-2002. Bloggers like Glenn Reynolds, Andrew Sullivan, and Atrios were all growing in influence as grass-roots commentators, and were helping to build up a real, new Internet community of exchange, linking, and debate by highlighting and encouraging talent in smaller blogs.

By that time I had already read most of the canon of popular science books, and taken my position in the Sociobiology Wars (as first brought to my attention in 1999) firmly on the side of the genetics camp. I may have been riding the wave in, because it was, by that time, obvious and increasingly obvious, that the anti-sociobiologists had been lying and mud-slinging, like their Creationist brethren, for decades (the Bell Curve backlash of the mid 1990s perhaps – hopefully – serving as their last popular opinion “victory”. The Larry Summers backlash of 05 was pretty much an embarrassment for the Blank Slaters). Since sociobiology has so many implications for politics and society, and yet many liberals are hostile, indifferent or baffled by sociobiology, and many conservatives are embarrassed, hostile or baffled by biology, there was a peculiar and important intellectual vacuum waiting to be filled. One of the few pundits independent enough to fill that lonely void at the time was Steve Sailer, a conservative who is/was easy to find through any sociobiology related web searches, and yet fit none of the stereotypes of what those evil people who dare think seriously about genetics and human behavior should look like. Sailer was not afraid of race and his writings confounded both antiracists by accepting racial differences, and racists by not generally implying differences meant people/races were “inferior” or “superior” and by rejecting racial nationalism. That this niche was so empty is an indictment of the intellectual landscape of the time: the “realists” were the racists and they were not moderate, and the “moderates” were the antiracists, and they were not realist. It’s not surprising then that many realist whites and nonwhites would find Sailer’s oasis of moderate realism attractive.

It is fairly amazing how much Razib and Godless Capitalist had in common, even though they started both of their blogs in the first quarter of 2002 unaware of each other. Both were from first generation South Asian-American families (Razib a Muslim family from Bangladesh, GC a Hindu family from India) but both grew up in America as atheists. Both were in their mid 20s, had degrees in bioscience (Razib biochemistry, Godless genetics/bioinformatics), were race-realist sociobiologists, and could be described politically as neoconservative-libertarians (as was a majority of the blogosphere at the time, e.g. Sullivan and Reynolds), tempered with the unique bioconservative perspective developed earlier by intellectuals such as Steve Sailer, James Q. Wilson, Richard Herrnstein, and Charles Murray.

‘Race’ is the one word that best describes the underlying theme and focus of early Gene Expression and proto-GNXP. I say “early” because it has evolved into something somewhat different today, as a less political and more general science blog, but it started in a very real way as a blog about race and all surrounding issues – affirmative action, population genetics, IQ and crime differences, Rushton, Jensen, and Lynn, genetic differences, hapmap, race as a biological reality, identity politics, immigration, reparations, ethnology, racism, white nationalism, interracial dating, and multiracial hotties, were all the centermost topics.

Razib’s blog (which if I remember correctly was called Razib’s Rants, Raves. & Reflections) is no longer with us, not even in Wayback. It wasn’t really even a blog, per se, but a personal website where Razib toyed around with his web-development. Sailer started his blog in December 2001 and Razib had been lending his population genetic expertise to Sailer’s commentary. Sailer linked to Razib’s pseudo-blog in April 2002, calling it “a new human biodiversity-oriented blog”, and Razib was trapped by the label! Sailer soon received and advertised an email from Godless noting that he was, coincidentally, a different brown-American who had started a similar Hb-d themed blog the previous month. Godless Capitalist’s blogspot archives are still available.

Razib and GC soon had numerous exchanges on different race issues, including H-1B (skilled) immigration, race and homosexuality, Asian education, and Asian vs. White hotties

Godless also had debates with other bloggers and “debating the blogosphere” would carry over to Gene Expression as kind of a longstanding tradition that continues today. The key to these debates is that they were/are often on controversial race-related topics where the GNXP side always has the facts, so you quickly either see slow conversion/revision on the other side or a sorry flameout out on their part, where a GNXPer usually gets banned or threatened with a lawsuit – either way good times all around. Godless extensively debated race and IQ with early science bloggers Charles Murtaugh and Paul Orwin, and these debates carried over to Gene Expression.


Godless and Razib combined forces to create GNXP in June of 2002, together with three other bloggers that had the same interests in/opinions on Capitalism and sociobiology, but had much less to say on race. First there was Mary C. who had her own early science blog. Second there was Joel Grus, who designed the logo! Third was Elizabeth Spiers, maybe GNXP’s most famous alumna, she went on to found the popular celebrity gossip site Gawker, and now the popular wallstreet gossip site Dealbreaker, which is apparently pulling in something like 30,000 hits a day. She also has a book coming out.

Razib and Godless initially pushed race (and especially race and IQ) very hard, amounting to virtually all their posts. Godless continued his exchanges with Murtaugh and Orwin and began a similar one with his early nemesis Philip Shropshire. Glenn Reynolds blogrolled Gene Expression early on (and even
participated in some of the comment box discussions), and so these topics were forced into the mainstream of the blogospehere to the chagrin of many bloggers. Prominent early bloggers like Atrios and Anil Dash soon flocked into the comment box for debate but were quickly outgunned and sent into retreat by Godless and Razib, who were rearing to fight in those days. Razib’s I thought liberals wanted a bridge to the 21st century-not a bridge to the past! and Godless’ Modern Day Epicyclists are emblematic of the early character and focus of GNXP.

Turnover was quick, and all the initital bloggers but Razib, including Godless, dropped out by December, though Jason Soon and Suman Palit had become regulars in the meantime. Godless would return and drop out several more times over the years, though his participation in the comment box has been more continuous (newbies look for box regular “GC”). Razib recruited comment box participants to preserve the founding character as a group blog, and almost all the people commenting in the box from those first months have either been subsequently absorbed as GNXP bloggers or are still commenting in the box today. I was among the first batch of 2002 recruits along with the ponderous Duende, and David Nierengarten. During this time Razib started moving away from the early polemics and growing into more serious, thoughtful pieces such as The Germanization of the liberal idea and Volkswanderung exploring cultural and population genetic themes. Ironically this was also the time that GNXP’s reputation started to catch up with it. A peculiar lefty troll known as Mac Diva started leaving hysterical comments in many comment boxes about “the most racist of blogs”. Conservative Richard Bennett was just as outraged. It was one of our earliest and most amusing dustups, here was an old white conservative shouting down a blog with mostly South Asian, Jewish, East Asian and even black (Nierengarten is 1/4 black) posters as “Nazis”. Bennett didn’t know too much about the subjects he was bloviating about, but we all had fun anyway. It was certainly the most racially diverse Internet defense of race differences up to that date.

Duende and David Nierengarten didn’t continue much longer as posters either. Razib and I began recruiting heavy-hitters; Razib added David Burbridge, a British chap in the tradition of Haldane and Fisher, who has been one of GNXP’s best posters over the years – providing much intelligent and learned commentary on the sociobiological subjects we’ve always fixated on. I added Alex Beaujean, a professional psychometrician, to provide more serious commentary on the staple IQ issues. The belated antiracist backlash from early GNXP gradually slowed down, and in fact, 2003 began to see a push from the other side as well, as angry White Nationalists began to rebel against the consolidation of a race-realist world-view that did not accept their politics. Vituperation against Razib, Godless, and GNXP was common and very strong from both the Left, the far Left, the Right and the far Right during this time. Nevertheless GNXP was also very popular relative to the blogosphere during the 2002-2003 period; according to the Truth Laid Bear traffic ranking, we were one of the top 50 blogs. While the blog has grown from about 300 hits a day to 3000 hits a day today, the blogosphere has grown at a faster rate, and today we’re shy of 300. Before Pandas Thumb and PZ Myers, GNXP was the first popular science blog, the only one, for a surprisingly long while, really with a focus on evolution and genetics.

Since that time GNXP has also continued to develop and mature as a blog, covering a vast number of biology and psychology topics from population genetics to cognitive science, without losing any of the original human biodiversity perspective. Also, though sadly without Godless’ contributions, we have a more diversely science educated and/or well-read cast today than ever before: Razib, Rikurzhen. Agnostic, Coffeemug, David Boxenhorn, David Burbridge, JP, Tangoman, Fly, Theresa, Alex, Darth Quixote, Matt McIntosh, Dobeln, Tangoman, and even the occasional post from Gregory Cochran.

And, of course, as controversial as the blog may have been in its salad days, it has been rewarding to watch the intellectual landscape meet up with our point of view, as we can guess that it will continue to do over the next decade. There is no longer a hole in the intellectual landscape, extremists no longer have a monopoly on a certain realm of truth, and good people no longer need to rely on pseudoscientific “antiracist” arguments about world genetic sameness to maintain their liberal worldview.

But please don’t make my ramblings the final word! Hopefully GNXP guests and contributors have their own thoughts and memories to add for the comment box or front page. I know Godless Capitalist has to be itching to come out of his comment box hiding spot for an anniversary boast!

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A new study tracks the effects of alcohol drinking during each trimester of pregnancy for 636 mother-child pairs.

Light to moderate drinking during the second trimester led to the most pronounced cognitive deficits at age 10. The catch is the effect was found only for the African-Americans in the study and not for the white children, suggesting that race differences may make alcohol drinking more harmful for the babies of African-American mothers:

No such association was found for Caucasian children in the study. “This racial difference could not be explained by the amount or pattern of drinking during pregnancy or socioeconomic factors,” [study chief Dr. Jennifer A.] Willford told Reuters Health. This suggests that genetics play a role in these racial differences, the investigators add.


“Our study also showed that prenatal alcohol exposure was associated with lower IQ for African-American but not Caucasian children, said Willford. “Importantly, we know that this racial difference was not due to differences in the amount or pattern of alcohol use during pregnancy or by differences in socioeconomic status. We cannot say why the racial difference exists, but laboratory animal and human studies show that it may be partly explained by genetic factors.”

Levitt and Fryer type sophism using motor development scales aside, cognitive differences between African American and white children show up very early, and persist in a number of transracial adoption studies (I’m collecting this research into an Ebook that I’ll release here on gnxp when it can be finished). So studies like this are at least getting warmer than “acting white” type mythologies.

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A few papers out right now, like Jackson and Rushton, revolving around Frey and Detterman’s formulas for converting SAT scores into IQ scores. First, gnxp’s own A.A. Beaujean has a paper in the latest Personality and Individual Differences, providing additional evidence that the SAT is a reasonable measure of g, matching it up reliably to another set of undergraduate scores; though it is suggested that the conversion equations need to be improved, which will take additional research samples. Second, the versatile evolutionary psychologist Satoshi Kanazawa provides yet more IQ and the Wealth of Nations-inspired work with his new, in-press paper IQ and the Wealth of States. (PDF here) Chapter 5 of IQ&tWoN set the foundations for the book’s larger cross-national comparisons, by first showing that regional, sub-national IQ scores also predicted differences in economic prosperity between regions. For instance, within-city IQ differences between districts/boroughs in New York City and London in the 1930s were highly correlated with intra-city economic differences. Similarly, economic differences between a number of 1930s American cities showed a significant relationship with childhood IQ differences between these cities as well. A study of IQ differences between US states circa 1950 (using large-scale military data) found a correlation of .81 between IQ and state income. Other data is provided for regions of France, Britain and Spain.

Using Frey and Detterman’s equations, Kanazawa now attempts to update the 1950s study by comparing converted state SAT scores with state economic indicators. But a simple comparison is complicated by the fact that SATs are not taken by representative samples of the population, but by an upwardly biased group of college-bound high-school graduates. Also the percent of people taking the SAT differs dramatically by state. Kanazawa attempts to mathematically “correct” for this and his success seems mixed. The results go in the predicted direction; for instance the correlation between the converted state IQ scores and the Gross State Product (GSP) per capita is .50, with median family income is .57, and with % in poverty is -.35. These are fairly high associations (higher than the relationship between IQ and individual economic success, in fact), but it’s possible that the even higher 1950s state correlation is more accurate. The selection bias of the SAT is already missing at least one large part of the story – as Kanazawa notes, even unconverted state SAT scores do not correlate with % of the population that is black, despite the large, well-confirmed black-white IQ/SAT gap. He doesn’t attempt to explain this, but it could mean the number of blacks actually taking the test is fairly similar in each state regardless of the total number of blacks in each state. Perhaps readers have a better understanding of what’s going on.

Another anomaly is that the reported state IQ levels themselves are implausible, which is probably a function of both the Detterman equation and the Kanazawa conversion – or to put it another way, the imperfection of converting the SAT into IQ (or SAT as IQ) or to adequately “correct” for the SAT selection bias. For instance, the highest state IQ is New Hampshire with an IQ of 110.3 and the lowest is Mississippi with an amazing 62.7! That’s a spread of over 3 standard deviations – almost 50 IQ points. Fully 12 states are reported with IQs lower than 80, and this is with race not playing a detectable role. We get Utah with an IQ of 75.1 and Wisconsin with 78.4! We can compare this against other data to see if it’s compatible. For instance Henry Harpending provided Steve Sailer with Project Talent IQ data for 366,000 high-schoolers from 1960. This representative data only has a spread of about 1 standard deviation: from Montana with an IQ of 105 to Alabama with 89. The Encyclopedia of intelligence also provides Wechsler standardization differences by U.S. region. (by lumped states) which gives the modest spread of 101.6 for the Northeast, to 98 for the South (3.6 point difference). Kanazawa’s numbers lumped in the same way provide much different results, with regional differences exceeding 1 SD.

Kanazawa is aware of all this and suggests:

. . . while the state IQ estimates do correlate very highly with the macroeconomic performance measures and thus appear to have some validity, it is difficult to take the estimates at the face value. . . Until more accurate estimates of the absolute levels of state IQ appear (derived, for example, from actual IQ tests administered to large, representative samples of state populations), perhaps it is best to treat the current estimates as reflecting the relative standings of states. . . than estimating the absolute levels of state IQs.

Finally, it was worth applying this information to the infamous blue state/red state IQ hoax from 2004, and Kanazawa’s data were not kind to the red states. It matters not if we accept his relative or absolute scores, the states stack blue side up. In the link above, Steve Sailer showed only small differences on the NAEP achievement results, but with Kanazawa’s SAT aptitude results we find that 8 of the top 10 scoring states were Gore voters in the 2000 election (average blue state IQ = 99.3) and 8 of the bottom 10 scoring states were Bush voters (average red state IQ = 90.2). So, apparently, those ornery hoaxers were on to something after all.

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I just found the useful Freethought Multimedia website, which collects and archives the Internet audio/visual leavings of Richard Dawkins, Steven Pinker, Daniel Dennett, Michael Shermer, and a few related intellectuals. Courtesy of their Pinker section we get the video of Pinker’s January talk at the Institute for Jewish Research on the Cochran-Hardy-Harpending paper.

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WFMU blog points me to the infamous Experiments in the Revival of Organisms (1940) propaganda video at the always fascinating Prelinger archive, featuring Soviet stooge/scientific genius J.B.S. Haldane as narrator to Stalinist Russia Frankenstein experiments in reanimation. Gasp as a life-supported severed dog’s head licks its chops and dodges various irritants. Marvel as other lucky dogs are drained of all their blood and brought back to life 10 minutes later. And don’t feel bad if you’re a little more skeptical than Haldane, after all he pimped Lysenko too!

Anyway here is a direct link to the film. Should take about a minute or two to load. WFMU also has an entertaining little history of disembodied heads, including Robert White’s monkey head switching shenanigans.

Related: Stalin’s Humanzees.

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A review of Richard Lynn’s Race Differences in Intelligence: An Evolutionary Analysis
(Click here for summary chart. Warning: 20 page review.)

The generally listed “peak” age for scientific creativity and productivity is around the surprisingly young age range of 30-40, but the same exact age doesn’t apply to all scientific disciplines. The peak in fields that demand greater doses of pure reasoning, such as mathematics, theoretical physics, and molecular biology, appears to be somewhere in the twenties. So, for instance, James Watson discovered the double helix at 25 and then dropped off the radar as anything but a nerd celebrity. In contrast are fields such as evolutionary biology, where years of collecting and assimilating large amounts of data can be required for original analysis. So, for example, Charles Darwin was 50 years old when he published his landmark The Origin of Species, not to mention 62 for The Descent of Man and 63 for The Expression of the Emotions in Man and Animals. What’s true for evo-bio may also be true for the often belittled field of psychometrics, or the measurement and analysis of human intelligence, and for much the same reasons. So, to take some more obvious examples, we find that John B. Carroll published his seminal work, Human Cognitive Abilities, at the age of 77, while Arthur Jensen was similarly 75 when he published The g Factor in 1998 (This spring, in fact, Jensen releases his treatise on mental chronometry, Clocking the Mind, at 83).

Richard Lynn, Professor Emeritus of Psychology at the University of Ulster, is surely another example. Now 76, Lynn has released a large number of papers and 5 books since his “retirement”, 4 of them since 2001, starting with 1996’s Race Differences in Intelligence. Richard Lynn appears to be a surprising exception as a modern hereditarian researcher who has not had to fight an exasperating battle with his institution, but his reputation in the media has been characterized by much the same turbulence as his colleagues’ – most prominently during the Bell Curve backlash of the mid 1990s. Thus Leon Kamin’s review of the book in Scientific American included:

I will not mince words. Lynn’s distortions and misrepresentations of the data constitute a truly venomous racism, combined with scandalous disregard for scientific objectivity. But to anybody familiar with Lynn’s work and background this comes as no surprise . . . It is a matter of shame and disgrace that two eminent social scientists . . . [would cite the work of] Richard Lynn . . .

Similarly, New Republic senior editor Charles Lane used Richard Lynn as his launching pad for two jeremiads against The Bell Curve in the invidiously titled (and argued) Neo-Nazis! published in The New Republic , and an expanded version of this article which appeared in The New York Review of Books, titled The Tainted Sources of The Bell Curve, featuring Lynn as the eponymous “tainted source”. While these and similar articles in the popular press may have helped solidify Lynn’s reputation as a “fringe” researcher among certain segments of the literate public, his reputation as a scientist in differential psychology remains secure and respectable. Little known, for instance, is the book review of Richard Lynn’s Dysgenics (about the genotypic decline of socially valued traits) by the late scientific legend William Hamilton in the Annals of Human Genetics. This review is still available free at the journal’s website as a tribute, because it was actually Hamilton’s last published piece, submitted just two weeks before his tragically premature death in 2000. In comparison to Kamin’s recriminations, Hamilton had nothing but good words for Lynn’s character and work, calling Dysgenics a “brave and fertile book”, and Lynn himself “brave, thick-skinned, and very persistent to swim against. . . popular antirealistic currents.” and that “Lynn. . . does an excellent job with the facts”. The contrast between interchangeable talking heads rebuking Lynn as a crank in popular magazines with Hamilton, possibly the most eminent evolutionary theorist of the 20th century, praising him in a prestigious journal at about the same time, could hardly be more ironic. (Meanwhile it is actually Kamin himself who can most convincingly be charged with data distortion and heavily compromised objectivity, see Mackintosh 1998 pp 78-79, 98-102)

Lynn’s follow-up book Eugenics (about remedying the genotypic decline of socially valued traits) received similar praise in the American Psychological Association Review of Books (Lykken 2004) as “[an] excellent, scholarly book . . .one cannot reasonably disagree with him on any point unless one can find an argument he has not already refuted.”, as well as by the journal Nature (Martin 2001) as a “comprehensive histor[y]” and a welcome one, “given the importance of the topic” of dysgenic trends. Lynn’s third recent book, The Science of Human Diversity, a hagiography of the Pioneer Fund, also received supporting words in the APARoB from the psychologist Ulric Neisser (2004), who was also chairman of the APA’s Taskforce on Intelligence (that was convened largely to counter the proliferation of scientific misinformation against IQ in the Bell Curve aftermath). Despite Neisser’s repeated ostentatious and inappropriate insults against his hereditarian colleagues (such as saying that Lynn and Rushton’s work on race “turns [his] stomach”), he ultimately couldn’t avoid agreeing with Lynn’s main argument: “Lynn’s claim is exaggerated but not entirely without merit: “Over those 60 years, the research funded by Pioneer has helped change the face of social science””. Neisser tellingly concludes in agreement with Lynn (and against William Tucker’s Pioneer book, also reviewed) that the world was actually better off having the Pioneer Fund: “. . . Lynn reminds us that Pioneer has sometimes sponsored useful research – research that otherwise might not have been done at all. By that reckoning, I would give it a weak plus” (These words coming from the APARoB should come as some news to certain ‘watchdog’ outfits which are still attempting to anathemize this same position. Pehaps all these journals and scientists mentioned above should now be added to the list of ‘hate groups’?).

Lynn’s fourth recent book, along with Tatu Vanhanen, IQ & the Wealth of Nations, received more mixed reviews in academic journals, but this should be taken as a sign of its controversial importance. Heredity, for instance, hedged its bets and printed a hostile review back to back with a sympathetic one (Richardson, Palareit 2004), as is sometimes done with controversial books (APARoB did the same thing for The Bell Curve, The Nurture Asumption, etc.). Unfortunately, much of the criticism in the journals, as is common in the popular press, centered around an obsessive focus with and antipathy towards the book’s hereditary position on racial differences, far outstripping its relevance to the book’s thesis that national IQ is a major cause of differences in national wealth. Worse still, many negative reviewers were deeply ignorant of the subjects that made them most angry. Some economists were outraged in stereotypical form, over use of the “discredited” IQ measure. Almost nobody was qualified to understand the race research, which Lynn specializes in, though it deeply unsettled almost all of them. So, for example, most reviewers took offense at the reference to race and brain size but none had informed or adequate scientific ways to critique it. To date though, the book is already generating a surprising amount of original commentary and research given this radioactivity, (Barber 2005; Dickerson, in press; Hunt & Williams, in press; Jones & Schneider, in press; Jones 2005; McDaniel & Whetzel, in press; Voracek 2004), and it is clearly Lynn’s most important contribution to date. Also, while not referenced directly it is also influencing international policy. So, for instance, 2004’s international panel of economists in league with Britain’s Economist magazine, known as the “Copenhagen Consensus”, ranked improving micronutrient levels as the second most important action to help the developing world. The impact of nutrition on intelligence was a prominent part of their argument, with 54 references to the word “cognitive” and 10 references to “IQ” (Jones 2005). These issues and recommendations are quite clearly taken from IQ & the Wealth of Nations.

While Lynn has made valuable and original contributions to a number of psychometric issues, IQ&tWoN, and his recent work with sex differences, confirms that group differences in intelligence are clearly his forte, and since so few other researchers dare to touch the issue, the field is mostly wide open for discovery. Which brings me to Lynn’s fifth recent and latest book, Race Differences in Intelligence, which Lynn himself describes as “. . . the first fully comprehensive review that has ever been made of the evidence on race differences in intelligence worldwide”. (p. 2) In contrast to IQ&tWoN, RDiI does not contain a newly created thesis. This is not to say it is unoriginal, many of its ideas (and much of its copious data) certainly originates with Lynn himself, but the theory, its basic outline and many of the key references of this book were almost all first presented 15 years ago in Lynn’s Mankind Quarterly article ‘Race Differences in Intelligence: A Global Perspective’ and its companion piece ‘The Evolution of Racial Differences in Intelligence’, while an even more basic version appeared in his 1978 chapter ‘Ethnic and Racial Differences in Intelligence, International Comparisons’ in the book Human Variation.

The main strength of RDiI is just how much data Lynn has collected, totaling 620 different IQ studies from around the world and 813,778 tested individuals. While IQ&tWoN, published only a few years ago, presented data from 81 countries, RDil has boosted that number up to 100 different countries (additions include Cameroon, Central African Republic, Estonia, Iceland, Jordan, Kuwait, Laos, Lithuania, Madagascar, Malta, Mozambique, Pakistan, Samoa, Serbia, Sri Lanka, Syria, Yemen, and a few others), amounting to 137 newly referenced IQ studies. RDiI is seventeen chapters; the first 2 are on the concepts of race and intelligence. The next 10 chapters cover the psychometric data on 10 different racial groups: Europeans, Africans, Bushman and Pygmies, South Asians and North Africans, Southeast Asians, Australian Aborigines, Pacific Islanders, East Asians, Arctic Peoples, and Native Americans. The next chapter discusses the psychometric justifications for these results, while the last four chapters discuss the environmental and evolutionary nature of these differences according to Lynn’s assessment.

Chapter 1 & 2: Intelligence and Race

These chapters are small and polemical. IQ&tWoN had a similarly abbreviated, but fully adequate chapter on IQ and I recommend that one instead. Lynn’s chapter on race benefits less by squaring old scores with Ashley Montagu than it would by focusing more on the rapid advances in genetics. Lynn, for instance sourly demonstrates that Ashley Montagu and L.L. Cavalli-Sforza have continuously contradicted themselves trying to strategically deny that populations exist and are genetically differentiated even while ultimately admitting that they do. But these conceits ridicule themselves; Tan (2005) and Rosenberg (2002) , which both go sadly unreferenced, help illustrate and justify the use and meaning of Lynn’s clusters far more than years-old absurd quotes from race-deniers, which are already well on their way to becoming little but historical oddities. On the other hand, Lynn can’t be blamed that his book was published too late to catch the latest paper by Rosenberg in the December 05 issue of PLoS Genetics which again concludes, in the face of recent challenges stating otherwise, that:

. . . if enough markers are used with a sufficiently large worldwide sample, individuals can be partitioned into genetic clusters that match major geographic subdivisions of the globe. . .

Finally, as a tertiary complaint, Lynn also states:

In the 1830s, Samuel Morton (1849) in the United States assembled a collection of skulls, measured their volume, and calculated that Europeans had the largest brains followed by Chinese, Malays, and Native American Indians, while Africans and finally Australian Aborigines had the smallest brains. He concluded that these differences in brain size accounted for the race differences in intelligence.

This of course was also Stephen J. Gould’s argument in Mismeasure of Man. Both mens’ assertions should be read in light of science historian, William Stanton’s more qualified judgment that: “Morton himself never equated cranial capacity with intelligence” (Stanton 1960, p. 30), and that Morton’s collection was ethnographic in its aim.

Chapter 3: Europeans

Lynn first looked at European IQ in his 1978 chapter – it listed 14 studies from 13 different countries including the European repopulated territories of America, Australia, and New Zealand. Lynn found that they mostly scored extremely similar, with an average IQ of about 100. He also noted that results from Spain and Greece in Southern Europe were lower, although Italy was not. By 1991 the number of European countries covered was 23 with 35 studies
. In comparison RDiI now lists data for 36 majority European countries, as well as data for European peoples in 6 mostly nonwhite nations, for a total of 112 different studies and a combined sample of 175,950 people. Since IQ&tWoN, much valuable new data from Europe especially comes from the recent book Culture and Children’s Intelligence. The median IQ of European peoples is now listed as 99, and this mostly holds for rich countries in the North and poor ex-Communist ones in the East, as well as white Americans, Australians, etc., and whites in six different Latin American nations. But there also appear to be some differences too – Ireland, Portugal and Lithuania all have IQs, unlike their neighbors, in the low 90s. Multiple studies give similar results showing the scores are ‘reliable’ if not ‘valid’ (Ireland for instance has three studies with large standardization samples showing very similar results). Secondly, while Southern Europe does not score poorly as a block (Spain and Italy score “normally”), South east Europe does reflect a regional trend of lower scores that extends from the Balkans into Turkey and the Near East (so for instance Romania 94, Bulgaria 93, Croatia 90, Serbia 89, Greece 93 [5 studies], and Turkey 90). Lynn also compares 4 different regions of Europeans (including North America) on IQ and brain size, finding that North American whites have the largest brains and highest IQs (perhaps because of selective migration?) and Southeast Europeans the lowest test scores and brain size. Of course if there is a decline in the Balkans, Lynn’s Flynn reduced estimate of 99 for Europe is incorrect, and needs to be dropped probably even a few more points.

While Lynn looks at adoption studies for evidence of heredity for other races, he unfortunately does not consider it for this major difference within Europe, even though it would seem like an even more suitable test, since these adoptees are not visibly racially distinct, controlling for the possible social effects of e.g., racism or stereotypes. Also, I know that there are, in fact, a number of IQ studies of Romanian children adopted into American and British homes. It was unfortunate that they were not reviewed. My superficial impression is that they indeed show a lower IQ than other adoptees.

I don’t expect any of this to go uncontested, and Lynn’s accuracy and care with the data is a fitful concern. Lynn and colleagues go back and forth over differences of up to 5 points in the technical literature all the time, and these debates are resolved slowly as more literature accumulates on the controversial/disputed difference, but no one has ‘exposed’ Lynn fraudulently manufacturing a conclusion, as is sometimes hinted. As with Africa, Asia, and sex differences, Lynn seems adept at building up the case for his controversial estimates with more data over time. But getting overly concerned with values of several points in single European countries is probably unwarranted, as Lynn himself notes, it’s more helpful to concentrate on the general patterns.

Chapter 4: Africans

Lynn first looked at Sub-Saharan African IQ in his 1978 chapter – it listed 7 studies from 4 different countries including 1 Diaspora territory: Jamaica. By 1991 the number of African countries covered was 6 with 11 studies. In comparison RDiI now lists data for 23 majority black countries in and outside of Africa, as well as data for Diaspora blacks in 5 mostly nonblack nations, for a total of 155 different studies and a combined sample of 387,286 people.

References to the subject from the 60s and 70s typically gave Africans an IQ much like African Americans, thus Jensen (1973) wrote: “We do know that studies of the intelligence of Negroes in Africa have found them to average at least one sigma below Europeans on a variety of tests” (p. 66). Lynn (1978) is no exception. It wasn’t until 1991, that Lynn had revised this estimate dramatically to minus 2 standard deviations, which has been the source of much anger and controversy ever since. Well, the current volume drops it a little bit lower even, to an IQ of 67 as the median score from 57 studies collected from 18 different African countries. Similarly, the average IQ of black populations from 6 locations in Latin America and the Caribbean is 71. This is virtually the same as the score for Ethiopians in Israel. In developed, predominately white countries, a second cluster of scores emerge for black Africans. African-Americans, of course, score about 85, while the median IQ from 20 studies of blacks in Britain is 86. Similarly, West Africans from the Dutch Antilles living in the Netherlands were found to have an IQ of 85. Although an older reference, Lynn also leaves out an IQ study of an established black population in Canada, descended from US migrants (Tanser 1939, 1941) – the measured IQ was about 87. Given that the scores have not changed a bit in America for 100 years, the age should not matter, and the educational gap of blacks in Canada is still discussed as a problem and mystery to this day.

More than Asia, Europe, and other areas of the world, the accuracy of such a low IQ for Africa is popularly questioned, but more with reflexive incredulity than adequate methodology. A typical comment is that it is hard to believe that half of Africa is mentally retarded. It is also hard to believe that 16% of African-Americans are “mentally retarded”, but 16% of African-Americans do have IQs below 70, and the APA recognizes this as an accurate and factual reflection of ability – IQ tests are not biased against African-Americans (the criticism is fairly ignorant to begin with since diagnosing mental retardation is mostly orthogonal to the intelligence test, See Mackintosh 1998, p. 177). While this is not controversial now, among scientists, it certainly was as shocking to believe for many back in the 1970s as the 2 SD difference is to many today. While the logic of test bias has been around since at least the 1960s, a turning point in the scientific consensus on African-American IQ certainly came with Arthur Jensen’s Bias in Mental Testing (1981) which exhaustively laid out the tools and methods for accurately discerning bias in IQ test results. In principle these same methods can be used to answer if 70 is or is not a spurious estimate for Africa.

Lynn unfortunately is less than thorough and rather unconscientious on this topic, and since the estimate was his to begin with he should be the most careful and aggressive one defending it. Lynn skips the issue of internal test validity entirely, even though there are some key references from Africa that stand repeating, and speak directly to commonly raised issues such as, e.g. language bias. Key references for external validity are also omitted, though Lynn’s chapter 13 shows that IQ certainly doesn’t underpredict African academic performance where countries are included for International comparisons. So for instance, while African countries like Nigeria and South Africa may score 2 SD below European nations on IQ tests, Lynn shows that international indices of math and science performance between the 1960s and 1990s reveal an even more dramatic gap of about 2 and a half SD. (It was noted in the Wall Street Journal, for example, that in South Africa: ” . . . barely 1% of black high school students pass higher grade math”). Since East Asian nations score even higher than Europe, the gap approaches three standard deviations between Africa and Asia, consistent with earlier reports showing that there was almost no overlap between the highest and lowest scoring countries, e.g. TIMSS 2003 (PDF):

“Singaporean students had the highest average achievement at both grades, with their average eighth-grade performance exceeding performance at the 95th percentile in the lower-performing countries such as Botswana, Ghana, and South Africa.”

Lynn also reviews data of so-called Elementary Cognitive Tasks from Africa, such as reaction time tests (how quick you process and react to a lit button on a console), and EEGs, which monitor how quickly the brain responds to a stimulus, confirming the general picture of African IQ. Jensen’s upcoming book should have interesting things to say on this topic; a combined battery of ECTs correlate with IQ tests just as well as standard IQ tests correlate with each other (Detterman 1999), indicating that the pen and paper IQ test, as well as most attendant concerns about culturally biased tests, might very well become soon obsolete.

The issue of brain size is similar to that of test bias; I would think Lynn would want to up the arms race against his critics since this issue received so much attention in reviews of IQ&tWoN, despite being such a small and irrelevant part of that book. And yet brain size is prominently used to defend controversial hereditarian arguments in many chapters of this book, so it was unwise that key references are similarly omitted like with test bias. So, for instance, there is no discussion of the importance of, or tests for, a functional relationship between IQ and brain size, even though this is critical to the argument. And such research exists and would have made his argument much stronger and more immune to glib dismissal. Lynn does attempt to resolve one “contradiction” – that women have smaller brains but do just as well as men on IQ tests – by presenting data for his own theory that women actually average 5 IQ points below men. But since the difference between races is larger than the sex difference in IQ, and the brain size differences smaller, I don’t see what has been resolved, even if we accept the still controversial sex difference in IQ.

Particularly interesting (not only for Africans, but for other racial groups reviewed as well) isn’t just that racial groups score similarly on intelligence tests across an improbable number of different countries, but also have the same profiles (or “multiple intelligences” if you will) on these tests across nations as well. In the US, for instance, if we take poor and rich whites and look at their relative strengths and weaknesses on various test sections we will find the same pattern of strengths and weaknesses. Same for poor and rich US blacks, who have distinct strengths and weaknesses. African blacks show the same test profile as US and Jamaican blacks, for example with strengths on perceptual and short term memory tasks and weakness on tests of abstract reasoning (this is for matched total IQ, remember). The visuospatial profile that also distinguishes women and men and European and Asian/Amerindian populations has also long been noted by research of blacks in Africa and the United States, but this difference is not analyzed by Lynn.

For the first time I’ve seen, Lynn also reviews tests of “MQ” or musical intelligence for black and white Americans. While blacks score lower on almost all the items, commensurate with the fact that IQ correlates with musical ability, they also do much better, on average, than whites on rhythm items – Lynn calculates a rhythm IQ for Af-Ams of 106, though no cross-cultural results are presented, this has been recognized in a number of societies through time. Since Sub-Saharan Africans have been musical innovators across a number of different countries, this topic should have more attention.

Based on the IQs of transracially adopted black children, Lynn decides that the 1 SD IQ difference of American blacks (same as in Britain and the Netherlands) is 100% genetic, given the lack of any convincing environmental theory or data for the gap. Based on this he decides that poor nutrition primarily is depressing the African (and mostly identical black Latin-American/Caribbean) IQ about 13 points. Indeed, incredulity that African IQ could be any lower than African-American IQ is belied by known drastic comparative disadvantages of Africans on variables known to affect IQ. These include things such as higher lead exposure (which can lead to IQ reductions of 4-7 points) and micronutrient deprivation, such as iodine deficiency (reductions of 10 points). Indeed, critics are incredulous over the wrong gap! – after all, it is the 15 points between American blacks and whites that is hard to account for, not the 15 points between American blacks and Africans. 5 additional IQ points between African-Americans and African-Africans, Lynn attributes to the white admixture of American blacks. Lynn puts the level of white admixture in African-Americans at 25% based on references from 1971 and 1992, and northern black admixture at 50% (based on pure conjecture) and concludes from IQ studies that African-Americans gain 1 IQ point for every 5% of white admixture. Lynn’s estimate is compromised because his admixture references are outdated and his estimate of northern admixture is contradicted by the data. Parra et al. (1998) put the latest estimate of average admixture at 17%, not 25%, and don’t even find admixture higher than 23% in any sampled US region. It’s difficult to guess why he is using the obsolete reference, when he himself has previously cited the Parra paper and the 17% estimate (Lynn 2002).

On a final note, I will say that Lynn is especially talented at bringing new references to the table, so that while his 1991 report featured only three references of black IQ in Britain, this book delivers 20 – all in support of a black IQ in Britain typically much lower than all other ethnic groups, and much like that of blacks in the US. This is no small ability since critics are terrible at knowing or caring about the literature. But more important is this – Lynn should expand his research ability to cover a broader range of data points. An over-reliance on IQ tends to minimize just how strong these international racial patterns are because it limits the argument to just one kind of data. A book like Lynn’s, in my opinion, would be much more effective if it started with the race and worked up to the IQ data, where available, instead of vice versa. So for instance, a more thorough picture would be available of racial patterns if, instead of cataloguing nations where we have black IQ, we first catalogue nations that have blacks, and chart what we know about their comparative situation in each country up from that fact, given whatever data is available, be it IQ or educational or economic data – or even anecdotal (journalism/anthropology) reports or local viewpoints, if that is all that’s available. The point is that IQ data is limited and working up to the data from the people would make the patterns even more unavoidable. I have in mind the structure of Thomas Sowell’s Migrations and Cultures or Amy Chua’s World on Fire which didn’t even use IQ data, but demonstrated ethnic patterns through economic, political, and educational data. A merge of style and data between these books and Lynn’s would paint an even more persuasive picture of the differences that do, more or less, rather reliably follow race, and perhaps uncover which ones don’t as well.

pter 5: Bushmen and Pygmies

In Frank Miele and Vincent Sarich’s Race, an account is given by Henry Harpending of a resourceful young Bushman who repaired his Jeep by jumpstarting it with a rope, like a lawnmower. Harpending and his colleagues concluded that Bushmen were smarter than other Africans: “All of us have the impression that Bushmen are really quick and clever and are quite different than their neighbors . . . I expect there will soon be real data available from the Namibia school system” (p. 227). On the other hand, Lynn lists the average IQ of Bushmen, estimated from 3 studies, as 54! Lynn decides that this is a reasonable score by considering that it is equivalent to the average score of an American third-grader: ” An IQ of 54 represents the mental age of the average European 8-year-old child, and the average European 8-year-old can read, write, and do arithmetic and would have no difficulty in learning and performing the activities of gathering foods and hunting carried out by the San Bushmen” (p 76). Lynn’s estimate is not new, the same studies and same average IQ were listed in the 1978 chapter, the only thing that has changed is Lynn’s opinion, who then wrote: “. . . it strains one’s credulity that a population could long survive the rigors of the Kalahari with a true mean IQ around 55”. This should not serve as a “gotcha”, because I agree that the ‘age’ comparison is more appropriate than the ‘mentally retarded’ comparison for thinking about lower IQ population (such as the 16% of Af-Ams who score below 70). At the same time this also demonstrates a theoretical deficit in intelligence research of distinguishing exactly how an average child with an age unadjusted IQ of 63, a below-average non-retarded adult with an IQ of 63 and a mentally retarded adult with an IQ of 63 all differ in what are fairly considered intellectual abilities (real world indicators of independent self care and adjustment). Suggestions that these are just “personality’ differences are rather specious, especially when Lynn gets to the point of comparing young children and apes as well as humans and extinct hominids on the same linear IQ dimensions. Although I agree that test bias literature also confirms important aspects of intelligence are being captured across diverse groups.

Lynn notes there was a Pygmy intelligence study, but says that it does not permit an average IQ, though he does suggest it is lower than other Africans. Since no new data has been collected for Pygmies and Bushmen in over thirty years, these assessments are dead ends. As one caveat, I have to object to Lynn’s statement that ” Pygmy children up to the age of puberty have normal height, but when they become adolescents they do not have the growth spurt of other peoples because of their low output of the insulin-like growth factor 1″ (p. 77). This fact is outdated, a mixed longitudinal study from 1991 found that Pygmies were much smaller than other populations at birth and up until age 5, indicating a suite of adaptations for smaller size.

Chapter 6: Near East and South Asia

Lynn first looked at the Middle-East/South Asia region in his 1978 chapter – it listed 5 studies from Iraq, Iran and India and an average of 86 was given. Except for one study for India, this region was not addressed in the 1991 review. RDiI is pretty much the only survey of Middle Eastern IQ to date, now listing data from 15 predominately West/South Asian countries as well as data on these populations living in European countries for a total of 98 studies and a combined sample of 65,855. The median IQ is 84. 40 studies are also given for South Asians living in a variety of African, Asian and European countries – the median IQ for Indians in India is listed as 82, in South Africa as 86, and in Britain as 89. South Asian Americans have not been tested to my knowledge, but data from income and education indicate they probably have IQs significantly higher than average – this is likely due to selective top-tier migration. Unfortunately, no data for IQ diversity within India is discussed, even though some data probably exists right now and probably contains some fascinating information on caste and ethnic differences. In my opinion South Asia (the Indian subcontinent) should have been a chapter apart from West Asia (the Middle east), highlighted more by the fact that Lynn also lists a score of 89 for the Near East and 82 for South Asia, suggesting the 84 score is misleading.

Lynn argues for a partially environmental explanation for lower West/South Asian IQ with reference to nutrition as he does with other regions, but argues that since these populations perform much lower even in Western nations and have a lower brain size, that there are genetic causes too, which in his evolutionary framework is said due to their more limited exposure to two little Ice ages than Europeans and East Asians. Lynn leaves out an important genetic issue as well, one mediated by cultural events. While the prevalence of cousin marriage is less than 1% in Europe and its Diaspora nations, and low in much of Eastern Asia as well, the Middle East has the highest rates of inbreeding in the world, running to 20-50% of all marriages (see the work of Alan Bittles for more). Jensen (1998, p. 194) lists 14 studies of inbreeding depression on IQ, many of them done directly within the Middle East, and finds the typical cost of cousin marriage is 7-8 IQ points. It is doubtful that this is a major source of the average IQ difference between Europe and the Middle-East, though, since all, or even a majority of, the people of this region do not engage in cousin marriage, making the real effect, at maximum, only a few IQ points. Also most of South Asia, which has much less inbreeding, does not appear any higher.

While Lynn’s book lists the IQs of blacks, Asians, Indians, and other groups living as internationally dispersed minorities, this is not done for Ashkenazi Jews, who are largely – sadly -neglected, though a few examples are given to indicate they score highly in America and Britain. Earlier discussions of Israel’s IQ, when it was listed as 94 in IQ&tWoN treated it as a suspect score, because Ashkenazi Jews are thought to score 1 SD higher than other Europeans. Of course even if this were true (and Lynn himself (2004) estimates the IQ as only about 107), Ashkenazi Jews represent only about 40% of Israel’s population, and Oriental Jews and Arabs, who make up the majority, are thought to score nearly as far (if not more) below Europeans as Ashkenazi Jews score above them, so the estimate actually wasn’t unreasonable at all (although ’95’ in a country with a distinct, high scoring population is qualitatively different than a ’95’ country with a single bell curve). Lynn lists 8 studies for Israel with IQs ranging between 89 and 97 and with a median of 95, but none of the studies are broken down by ethnic background to provide direct estimates of the IQs of Oriental and Ashkenazi Jews. So Lynn uses population percentages (40% Ashkenazi, 40% Oriental, 20% Arab), results from one direct study of Israeli Arab IQ (86), and knowledge from several Israeli studies that indicate that Ashkenazi Jews score 12 points higher than Oriental Jews, to give indirect weighted estimates of 91 for the IQ of Oriental Jews and 103 for Ashkenazi Jews in Israel. No direct studies are given or listed for these groups in Israel, and if Lynn is correct that Jewish-American IQs are really only about 107, then that really isn’t different e
nough from his Israel estimate, in my opinion, that we can rule out their scores being identical in each nation – the estimate just isn’t that precise. Another puzzle left untouched is that the listed Oriental Jewish IQ is also 3-7 points above the regional average. Is it possible that for reasons of cultural and/or genetic amalgamation, the two populations are meeting each other in the middle; one being pulled up and the other being pulled down? Lynn does believe Ashkenazi Jews have some genes related to higher intelligence, which he attributes to medieval persecution. At his book’s cost, Lynn makes absolutely no mention of Gregory Cochran and Henry Harpending’s Ashkenazi paper at this point, which I find curious.

Chapter 8: Australian Aborigines

Lynn first looked at the Australian Aborigines in his 1978 chapter – it listed 3 studies, and he estimated their intelligence, much like Sub-Saharan Africans, as 85. In 1991 the same three studies were listed, and there is no suggestion Lynn lowered his estimate. When Ed Miller examined studies of Australoid intelligence in 1996, he too suggested something like 85. In comparison RDiI now lists data from 29 studies of Australoid populations, including those of New Guinea for a combined sample of 4,785. Since that time Lynn has dropped the Australoid IQ average a dramatic 23 points, down to 62. This is considerably lower than all previous estimates have suggested, but Lynn’s review also highlights just how neglected this populations intelligence has been, even by Lynn, until now. Small admixture and adoption studies exist for Australian Aborigine intelligence and both suggest something hereditary. These populations have had some of the lowest technological development of all populations and also have the smallest brains of any living population. An exception is the visual parts of the cortex, which are much larger than in Europeans. Interesting given their much lower intelligence, then, that their visual memory abilities are substantially superior – one researcher found a visual memory IQ of 119. Genetics are further suggested because the advantage is also true for very young children and for aborigines born into modern urban settings.

Jared Diamond famously stated that he believes the populations of New Guinea to be more intelligent, on average, than Europeans. The median of 5 intelligence studies in New Guinea is reported as 63, no different than Australian Aborigines. It seems that if what Diamond asserts is true, at the very least children from this stock raised in white homes should be able to, on average, reason through a Piagetian conservation of water volume problem as well or better than their environmental siblings, which is not what we find.

Lynn offers the opinion that the Australoids have lower intelligence than Africans because their population numbers were lower, and thus less likely to accrue advantageous chance alleles (he applies this theory to a number of other populations, such as the Mongolians, Eskimos, Polynesians and Amerindians). The rate at which these genes could spread is interesting in the light of Bruce Lahn’s ASPM and MCPH1 (also unmentioned!), which may be related to cognitive function, rising to high frequency among these populations but not among Africans. Especially the more recent ASPM, whose range across the entire span of Eurasia in 6000 years does not agree with Lynn’s estimate that an advantageous allele would spread only 800 miles per 25,000 years (p 222). Also interesting, if these alleles are related to increased brain size (possible, though yet to be demonstrated), that they exist in such high frequency in these populations.

Chapter 9: Pacific Islanders

As with the Middle East, Southeast Asia and Australoids, very little has been written to summarize the intelligence in Polynesian regions before this book. RDiI reviews 29 studies and a total sample of 7729 from the Pacific Islands.

In his 1938 book, Heredity and Politics, written largely as a riposte to the noxious racial politics of Nazi Germany, J.B.S. Haldane devoted two chapters to what evolutionary biology, or more specifically the Neo-Darwinian Synthesis, implies for racial differences in man. Much of what he says is level-headed. On the issue of race and intelligence, Haldane specifically compares the ability of Pacific Maoris with that of Australoids. For instance he cites Maui Pomare, a Maori who had actually for a time served as Prime Minister of New Zealand:

We cannot, I think, deny a very considerable difference in the behaviour of the Maoris and the Australian black-fellow, and we can ask whether it is due to nature or nurture? That is an exceedingly difficult question to answer. But I find it very hard to rule out nature. (p. 141)

Haldane’s assessment of ability finds support in intelligence tests. By world standards, Maori are bright, and perform much higher than Australoids. The median IQ of 15 studies of Maori from New Zealand is 90. This is probably higher than other Polynesians, as the median IQ of 14 additional studies from 6 non-Maori Polynesian territories is 85.

Chapters 7 and 10: Southeast Asians and East Asians

Starting in the late 1970s with Singapore and Japan, Richard Lynn discovered that East Asian countries obtained higher scores on IQ tests than the Western populations these tests were standardized on (See the picture from the 1982 Discover Magazine cover story on Lynn’s findings here). In 1978 he reviewed 5 studies from Singapore, Japan, and Taiwan. It wasn’t then expressly stated that East Asians had higher IQs, although Lynn noted that the result of 107 for Japan “appears to be the highest mean IQ ever recorded for a national population”. By 1991 Lynn had raised his number of studies to 15 from 4 countries, and integrated it into his climactic evolutionary theory to argue that East Asians had evolved higher intelligence than Europeans, with a mean IQ of about 106. A number of notable critiques of Lynn emerged in the academic realm since his first studies in the 70s, including an early charge by Stevenson and Azuma (1983) that Lynn’s Japanese IQs were inflated by socioeconomic and urban bias. Stevenson (1984) cast further doubt on Lynn by conducting a large international IQ study of his own, finding equal scores between a group of Chinese, Japanese, and Minnesotan elementary school kids. Finally, in Asian Americans: Achievement beyond IQ (1991), unusually principled hereditarian challenger James Flynn reanalyzed 100 years of IQ scores of North American Asians, which scholars had previously judged to average about 106. Although Flynn agreed with Lynn that IQs in Japan were higher than in America, he argued that earlier American studies were uncorrected for the secular increase in intelligence (the Flynn Effect), artificially inflating Asian-American IQs. In other studies, he argued, the Asian samples were not representative. Flynn re-estimated Asian-American IQ down to 98. All of these critiques (save aspects of Flynn’s) didn’t have much to stand on, even at the time they were leveled, much less now when the contrary data has grown exponentially. For instance, in a response to Stevenson and Azuma (printed on the same page as their critique) Lynn (1983) adjusted for the problematic demographic factor
s and found most of the difference was retained. As for Stevenson’s study that found no difference, this is not surprising since Minnesota whites score higher than any other US region, with scores identical to Lynn’s average for East Asia. And of course these same Asian countries with higher IQ scores also score higher on international records of math and science achievement than Western countries (see review of ‘test validity’ chapter below – these measures are almost perfectly correlated with IQ). As for Flynn, Flynn’s results only applied to the pre-1980’s – several studies from after that (coincidentally?) showed IQs much like what had previously been reported.

Whatever the merit of these previous challenges, Lynn has clearly upped the ante in Race Differences in Intelligence in defense of his argument of higher East Asian IQ. Lynn now presents 101 different studies of East Asians and a combined sample of 128,322, giving an average IQ of 105. From 5 different Asian countries alone (China, Japan, S. Korea, Singapore, Taiwan), we are presented with 59 studies4 times as many studies from East Asia as Lynn presented in 1991. 34 of these new just since IQ&tWoN! The median IQ from these studies is 105. In responses to Flynn’s earlier book, Lynn reanalyzes 27 studies of Asian-American IQ. In contrast to Flynn’s 98, Lynn finds a slightly higher average IQ of 101 for Asian-Americans, from 9 studies previous to 1950 (consistent with their higher academic and professional accomplishments at that time). For 9 studies since 1950, Lynn finds an IQ of 104, virtually identical to countries in East Asia. Additional studies show similar East Asian IQ in Canada, Britain, the Netherlands, Brazil, and Malaysia. Though educational and economic data not included in the book would paint a similar picture in over a dozen other countries from Jamaica to Russia.

In defense of a hereditary explanation, Lynn presents data from 4 studies of East Asians adopted into white homes, showing higher IQ scores. In fact here the data is even stronger than what Lynn presents – more IQ studies exist than what he presents, as well as other supporting evidence. In a month or two on GNXP I will present the first comprehensive investigation of international transracial adoption literature (a large expansion off this post), presenting much data not included in RDiI, particularly for East Asians.

Lynn also included an earlier chapter on Southeast Asians, but given an issue with their relationship with East Asians I’ve decided to review them together. The only native country from Southeast Asia to appear in 1978 was Indonesia, and, like the Middle-East, little data existed for this region until IQ&tWoN. RFiI lists data for 6 Southeast Asian countries in 18 studies for Southeast Asians living both in Asia and abroad for a total sample of 13,433. The median IQ is listed as 87. It is suggested based on brain size and scores abroad that these scores are partly genetic. As with the other chapters, Lynn justifies his racial division of East and Southeast Asia by reference of L.L. Cavalli-Sforza’s>History and Geography of Human Genes, but Lynn does not order his countries how they should be arranged according to this reference. This book tells us that South China lumps closer genetically with Southeast Asia than North China: ” Northern and southern Chinese are substantially different genetically” (p 100); “. . . the South Chinese . . . are more closely related to Southeast Asia than to Northeast Asia” (p 229). This is significant because many of the high IQ scores Lynn places in the ‘East Asian’ chapter are from various South Chinese populations, such as the Hong Kong studies, as well as much of the over-seas Chinese scores from America and Southeast Asia. This creates a potential problem for a genetic theory of either East Asian high ability or Southeast Asian low ability,>as noted by Ed Miller over ten years ago:

The importance of this finding of a relatively large difference between the North and South Chinese is that much research is done on American or Canadian born Chinese (Vernon, 1982), which are predominantly of South Chinese descent, coming from Hong Kong, Canton, or their vicinity. It may be risky to generalize from this to the whole of Han China.

For those interested in behavior and economic development, the resemblance between South Chinese and the Filipinos, Malays, etc. presents a problem. The South Chinese generally do well on intelligence and academic tests whether tested in the US or in Hong Kong, often better than Caucasoids. Filipinos generally don’t do as well. Within Malaysia, the Chinese test much better than the Malays. Within Southeast Asia, the overseas Chinese generally do much better economically than the Malays (Sowell 1994). Thus, it is surprising to see the small genetic differences between the South Chinese and adjacent populations.

In a related criticism, one of the adoption studies that Lynn uses to support a higher genetic East Asian IQ, (Clark & Hanisee 1982) is actually mostly comprised of Southeast Asians, about half the sample being Vietnamese. Lynn resolves this by asserting that most of the Vietnamese in this sample were actually Chinese-Vietnamese, but I see nothing in the original paper to indicate this, and since most of the higher achieving overseas Chinese in Southeast Asia are from the Southeast Asia genetic cluster anyways, I hardly see how this resolves anything. While one might posit a cline in IQ scores (and scores do seem to drop off from Thailand into Malaysia), the South Chinese show absolutely no deficit in ability or differentiated profile from East Asians. This makes an interesting contrast between Southeast Europe and the Middle-East where we see a cline in ability follow a genetic cline across a stark cultural boundary, suggesting genetics. Instead here we have another cline in genetics, but a stark difference in ability following a stark cultural boundary, suggesting environment. This might mean that underperforming Southeast Asian-American groups, such as the Hmong, have hidden potential after all. Then again, selection could have occurred in China independently for this trait, long after the formation of the races, but modern selection and subracial populations are at odds with the theoretical structure of this book. Likely much more data is required before simplified assumptions and approaches can relax.

Finally, at the risk of being too trivial in my criticisms (which I offer in benign spirit), Lynn asserts ” Only one study has been published on the heritability of intelligence in East Asians (Lynn and Hattori, 1990)” (p. 145), citing his own study from Japan. This is not correct. In the International Handbook of Intelligence, a group of Japanese psychologists write: “Since the beginning of the history of psychology in Japan the issue of the heredity of intelligence has been a major focus of inquiry. We can find a notable twin study in the very first volume of The Japanese Journal of Psychology” (pp. 310-311), and they go on to discuss several studies of heritability from Japan published in both American and Japanese journals stretching back to early in the 20th century.

Chapter 11: Arctic Peoples

The general consensus among the few scholars interested has long been that arctic groups, though living ‘primitive’ hunter-gatherer life-styles (much like some of the other extremely low-scoring groups reviewed here) do unusually well at IQ-type tests – in fact not much different than Eur
opeans. The earliest discussion of Eskimo intelligence that I know of (incidentally, not cited by Lynn) is in Robert Marshall’s Arctic Village (1933). Marshall gave all the Eskimo children in the small settlement town of Wiseman, Alaska the Stanford-Binet, and found them to outscore the American norms. Marshall commented that the “. . ..startling record shows these little Eskimos to far better advantage than normal American white children” (p. 79). Of course by that point the record was very small: Florence Goodenough found similar results with her Draw-a-man tests on a handful of other children, and Marshall discusses several other tests showing similar performance but does not clarify if this was his sample or another. With the advantage of 40 more years of data, John W. Berry (1971) indicated this view had not changed in his review of studies of Eskimo intelligence in the 1970s:

Probably the most interesting consistent finding is that Eskimos differ very little from [white] norms on tests involving perceptual skills or those abilities tapped by “perfornance scales” of conventional intelligence tests. It is often found, of course, that non-western peoples (e.g. in Africa and among American minority groups) perform significantly lower on these tests, and so this northern result is in many respects a unique finding.

Richard Lynn appears to be the first person to challenge this in his 1978 review, where he argued that one of Berry’s studies actually showed an IQ in the 80s instead of 100, due to an inappropriate age comparison. He also presented one more study showing a score in the 80s, although he allowed that another study did show comparable scores. RDiI, in contrast, includes 15 studies of Arctic populations and a total sample of 2,690 people. Lynn concludes that they are the (distant) third most intelligent racial group reviewed, with an average IQ of 91.

Even in Marshall’s book there is discussion of the Eskimos ability to draw detailed maps from memory. Like the Australian Aborigines, with whom they share a recent hunter-gatherer lifestyle, Lynn shows the Arctic people have an elevated visual memory IQ of 106. Although it is not shown that this likewise present in Eskimos removed from the hunter-gatherer lifestyle, it is also a feature shared by related groups such as East Asians and Native Americans.

Chapter 12: Amerindians

Several studies of Native American intelligence were discussed by Lynn (1978), though no exact average was given. By 1991, 15 studies of North American Indians groups were discussed and a median IQ of 89 was provided. In contrast, RDiI now discusses 63 studies of Amerindians with a total sample of 37,304. For 21 studies of North American Indian groups Lynn finds a median IQ of 86, and for 11 studies of Latin American Indian groups across five different countries, Lynn finds a median IQ of 86. Additionally, 20 studies of (mostly mixed race) Hispanic Americans reveal a median IQ of 89, identical to the meta-analysis by Roth (2001). Small hybrid and adoption studies are also presented.

In World on Fire Amy Chua describes the relationship between economic status and “Indian-blood” throughout Latin America: “Latin American society is fundamentally pigmentocratic: characterized by a social spectrum with taller, lighter-skinned, European-blooded elites at one end; shorter, darker, Indian-blooded masses at the other end . . .” (p 57). As an example she describes her experience in Mexico:

Almost without exception the Mexican officials, lawyers, and business executives we dealt with were light-skinned and foreign educated, with elegant European names. Meanwhile, the people doing the photocopying and cleaning the floors were all shorter, darker, and plainly more “Indian- blooded.” While considerable social fluidity exists in Mexico, it is also true that lightness of skin correlates directly and glaringly with increasing wealth and social status. (p 59)

The trends Chua observes within Latin American countries also appear to operate between these countries, with countries with mostly European populations, like Chile and Uruguay, being the most economically developed and countries with largely Amerindian populations, such as Bolivia and Ecuador being the least economically developed. Coblogger emeritus Godless Capitalist once compared 12 South American countries and found a correlation of .96 between GDP-per-capita and percentage of the population that is white.

Lynn’s data confirms this general picture with intelligence as well. Both with between country differences (e.g. Uruguay (96) and Chile (99) score like European countries, while Ecuador’s IQ scores range within the 80s), and within country differences; to use Chua’s Mexico as an example, last year Lynn tested a representative sample of 920 in Mexico with the Standard Progressive Matrices and found that whites had an IQ of 98, Mestizo (mixed race) 94, and Native Indians 83 – all compatible with Chua’s observations of a “spectrum” of “social status” by amount of “Indian-blood”.

Chapter 13: Validity and Reliability

I covered some of this topic prematurely in the Africa section, but this chapter deals with the appropriateness and accuracy of these cross-cultural IQ results. ‘Reliability’, in this case, is how replicable an IQ score is within each nation – telling us if a score is capturing something that can be fairly generalized. Despite the Flynn Effect, reliability is very high. If a nation is tested a second time or third time, the second and third score will look much like the first one – the cross-cultural reliability of the scores is .94. As an example, I noted last year that a 1997 test of almost 4000 Thai children (not included in RDiI) found an IQ the same as the only earlier result from Thailand, a much smaller sample from 1989. Evidently Thailand has an IQ about 8 points lower than the West. The second question though is if the replicable score reflects a replicable ability or just a replicable test score – is 92 an unfair reflection of Thai ability? That isn’t to say, “is it permanent or genetic”, just “is current performance in other domains in agreement with the measurement”. ‘Validity’, in this case, is if an IQ score predicts the same real world outcomes for one population as it does the reference population. For this Lynn looks at five data sets of international math and science performance, which span 30 years (Other IQ researchers have started matching up national scores with these data sets as well; Hunt & Wittman, in press). All the data sets correlate with the IQ measurements from .8 to .9, and Lynn even suggests that correction for attenuation gives them a perfect relationship. Typically the differences appear even larger on these scholastic measures than they do on the IQ measures, so while the difference in IQ between East Asian and European countries is about 0.33, or a third of a standard deviation higher, their achievement scores are 0.44 higher. And while Africa falls 2 SD lower in IQ, math and science achievement scores taken from West Africa, East Africa, and Southern Africa are 2.44 SD lower than European nations. These scores are, of course, related to national wealth as well, as demonstrated in IQ & the Wealth of Nations, where the correlation between IQ and economic development was .73. Lynn doesn’t mention that Jones & Schneider (in press) also found IQ to be the best international measure of economic human capital, better than all educational variables, all but a single one of which didn’t even pass a significance test for GDP growth between 1960 to 1992. Lynn gives a correlation of .51 between IQ and GDP growth between 1950 to 1990. The IQs were high before many of the rich countries got rich, suggesting a cause not a consequence of growth (Jones 2005). Jared Diamond (2004), quite inadvertently, illustrates the consequences of economists ignoring intelligence with this quote:

“. . . around 1950, when South Korea, Ghana and the Philippines were equally poor, most economists predicted that resource-rich Ghana and the Philippines were on the verge of wealth, whereas South Korea was doomed to remain mired in poverty. The result, of course, has been the opposite . . .”

Chapter 14: Genes and Environment

While genes may have been mostly irrelevant to the main arguments of IQ&tWoN, the same could hardly be said about this book where genetics are freely stressed. This chapter again reviews the evidence for genetics, including that the same patterns reappear across numerous nations, admixture and adoption studies. But here Lynn also covers what aspects of the environment are likely causing racial differences too, which Lynn is able to do with more accuracy and sophistication than critics who are more concerned with protecting taboos than figuring out sociological puzzles. Many of the popular and politically acceptable “answers” such as aspects of the shared family and education fail direct and adequately controlled tests (Lynn does believe education has an important impact on achievement, if not intelligence, and has written a book on this topic, which was also adapted into a National Review cover story). Lynn focuses here on his own hypothesis – nutrition. Before any other psychologist Lynn (1990) had proposed and supported the hypothesis that nutrition is responsible for the Flynn Effect. He has also demonstrated previously why it the best supported environmental explanation for certain racial differences. In this chapter Lynn compares NGO reports of four different signs of severe malnutrition – underweight, anemia, wasting, and stunting – for five developing regions. This shows that Latin America suffers the least malnutrition, followed by the Middle-east, Asia/Pacific, Africa, and finally South Asia, which suffers the worst malnutrition of any region. Lynn decides half the African deficit is due to malnutrition, but that it can’t account for any of the American gap, where blacks show no other physical signs of malnutrition. But here Lynn doesn’t mention breast-feeding, which as Arthur Jensen has shown (1998, pp 506-507) is practiced almost three times as much among white Americans than African-Americans and has been associated with IQ gains of nearly 10 points. It is likely that effectively encouraging breast-feeding would have a positive impact on the next generation of African-Americans.

Chapter 15-17: Climate, Brain size, Intelligence and Evolution

These three, closely related last chapters, which begin with a summary of the work and theories of Harry Jerison, regarding intelligence, evolution and brain size, cover Lynn’s evolutionary theory of racial differences. As with most evolutionary psychology, as well as evolutionary anthropology of humans, the theory and its assumptions will remain controversial. Lynn’s main agent of racial differences in intelligence is relative exposure to two recent ice ages, one 77,000-50,000 years ago, and another, more severe one 28,000-10,000 years ago, which he argues increased the intelligence of Europeans and East Asians significantly above other world populations.

But is this theory plausible? Well, let’s ask that with several more specific questions, a) Does intelligence follow a pattern consistent with this theory? b) Do the differences look genetic?, and c) Is there evidence to suggest this evolutionary pressure?

As to the first question, the answer has long been regarded as ‘yes’. It has been noted since the 18th century that the more wealthy regions existed in the temperate regions with the poorer regions in the tropics/subtropics, something that economists and sociologists have also considered during the 20th century (see also David Landes). Evidence used to support Lynn’s theory, is often just indirect ways of restating this same fact. So for instance the upcoming paper by Templer & Arikawa (in press) is presented as evidence which finds that national IQ is strongly related to lowest national winter temperature, -.69, and that skin pigmentation (mostly a record of evolutionary latitude according to recent evidence) has a very strong correlation with intelligence, .92. These relationships hold within and between continents. The most notable example of this, though, is brain size. With several minor reversals, the 10 populations in Lynn’s book, stack almost in the exact same order on brain size as they do with IQ. Most people, even so-called “scientists”, deal with this uncomfortable fact by simply denying any association between brain size and intelligence, either in humans or across the evolutionary record, something clearly and overwhelmingly contradicted, in both cases, by the scientific evidence. The same folks, interestingly, often hedge their bets by also denying any race differences in brain size. This too has turned more and more desperate as the studies pile up. The same folks, interestingly, often hedge their bets by also saying the differences, which don’t matter and don’t exist, are probably not genetic. Since this is not likely either, the most scientific objection (compatible with these three well supported premises) is that the race differences in brain size are just yet another way of stating that high IQ/wealthy populations occupy the temperate zones and low IQ/poor populations, the tropics/subtropics. Bergmann’s rule states that animals in colder climates tend to be larger and rounder to conserve body heat, while ones in warmer conditions smaller and thinner to help shed excess heat more efficiently. On the one hand while this may be true for the heads of our races, it isn’t exactly true for the bodies, as head and body measurement data from the US shows that East Asians have much larger heads than African-Americans, but smaller, thinner bodies (Rushton 1997), which complicates the Bergmann explanation. In other words East Asians and Europeans don’t just have larger heads, they have larger Encephalization quotients (EQs), or brain size controlling for body size – which also tracks changes in intelligence across the evolutionary record, so Rhesus monkeys have an EQ of 2.10, chimps 2.60, Australopithecus 3.70, Homo habilis 4.30, Homo erectus 5.00, and the average modern human 7.5 (while average IQ of modern humans = 90). Before the second most recent ice age, Lynn reports, the Europeans had an EQ of 7.3, which had inflated to 8.1 by the end. So apparently current differences in EQ between human populations are comparable to differences between species, which also correlate with transfer index scores and performance on other animal intelligence tests.(e.g. chimpanzees outscore rhesus monkeys). Unfortunately, Lynn does not help disentangle possible confounding between climate and intelligence by calculating EQs for the various group
s, or detail if these scores are different from the raw sizes. And it matters for the evidence that suggests climate instead of intelligence. For instance, the head sizes continue to increase with latitude, while intelligence does not; the largest human head sizes of all are at the frigid southern tip of Tierra del Fuego and among the arctic populations such as the Eskimos. Interestingly here, Lynn may have undermined one of the best possible evidences for his theory, even if not completely. After all, scientists had long thought that the arctic group was the only group living a ‘primitive’ lifestyle that scored anywhere close to (much less the same as) white European populations on IQ tests. Lynn is the first one to dispute and revise the Eskimo score as such, down to 91, even though he is the biggest proponent of cold increasing intelligence. Still, though, the actual IQs of Eskimos and related groups still support Lynn’s theory as much as they undermine it, as they are still the third highest scoring population on earth behind Asians and Europeans (even if they cluster with the other populations). Even if northern brain sizes are entirely due to climate instead of selection for intelligence, it’s possible that, while other neurophysiological processes can modify intelligence independent of brain size (and Lynn puts this at some 75% of existing differences), increased intelligence in some measure is a likely by-product of brain expansion, given their intimate developmental associations. This is still consistent with what we find with larger-brained, higher IQ northern latitude populations. Interestingly the pattern may be even more consistent with Lynn’s theory than he himself recognizes. Take Amerindians – Lynn argues (pp 242-243) that North American Indians should have higher intelligence than South American Indians due to greater exposure to the second ice age, but he also decides that both groups have an IQ of 86. But this is due to Lynn’s method of taking the median, which doesn’t always appear to be the best average. It gives equal importance to throw-away studies with 20-30 people and demographically controlled standardization samples with 1 and 2 thousand people. Lynn’s number of 86 for North American Indians, for instance, is significantly lower than what was found by the largest study yet of Amerindian intelligence – the Coleman Report, which tested nearly 5000 Native-Americans and found an IQ about a half a standard deviation above African-Americans. When we take the weighted average of all the American groups, using the numbers in Lynn’s book, we get an IQ of 90 for the Arctic people, 88 for North American Indians, and 86 for South American Indians. Since the sub-Arctic Indians living below the Eskimos scored almost as highly, perhaps there is a cline in intelligence down the continent, that may have reversed approaching the frigid area of Tierra Del Fuego, where brain sizes again inflated.

As to the second question, ‘are race differences in intelligence genetic’, this is not one question but a different one for each race. Again, since adoption studies are perhaps one of the best clues for this in the existing literature, hopefully I’ll be able to provide some original insights to this shortly. Right now, the least convincing, I would say, are the low intelligence of other Eurasians, such as Middle Easterners, South Asians and Southeast Asians (this isn’t to say not convincing). Most convincing, at this point (due to the most data) would be that sub-Saharan Africans score somewhat below Europeans, and that East Asians score somewhat above Europeans for reasons relating to genetics. Intermediate levels of evidence also suggests Australoids and Amerindians are somewhat less intelligent.

I put Southeast Asians in the ‘least convincing’ category for reasons discussed above, and Middle Easterners and South Asians (as well as Southeast Europeans) partly for some studies I have not mentioned here. But another important reason is that Lynn is chronocentric. The Middle East and India are relatively underdeveloped today, but have been ahead of Europe in the past; the Middle East relatively recently even. While it’s possible that both these groups changed through time, this still seems to contradict Lynn who pushes the differences back deep in evolutionary time. According to Lynn, the Middle East and India never had high IQs (i.e. 100), because they were never exposed to the business end of ice age winters. But how to explain the times in semi-recent history when Islamic civilization, science and scholarship, was at a more advanced stage than Christian Europe? I suppose parallels exist even today, when a higher IQ Chinese population is temporarily more underdeveloped than the West, due to bad governance, etc. Still it’s doubtful both that all intelligence differences are genetic, and that all the ones that are genetic have stood still for over ten thousand years. Lynn rightly points out that differences across space is a basic expectation from evolutionary theory, but differences across time are as well, and that all the major differences were formed when Lynn hypothesizes, requires us to believe that intelligence would stand still all that time after the evolutionary pressures of the last ice age, despite culture and environment creating many new selection pressures. Why should this be so, when Lynn demonstrates major genotypic selection in Dysgenics, just during the 20th century? I would put the major candidates for either change through time or “totally” environmentally depressed in central Eurasia, where history provides notable counterexamples and novel genes could flow as freely as the ancient trade routes.

Third, is there evidence that life in Northern Eurasia would require more intelligence? If we know the pattern exists and have better reasons to suspect genes than to suspect not, it is reasonable to reverse engineer the problem.

Consistent with the relatively higher intelligence we find with Eskimos, one of Lynn’s best pieces of evidence that more intelligence is required in the northern latitudes than in tropical/subtropical ones are the tool kits manufactured by the hunter-gatherers in these respective latitudes. Hunter-gatherers in the latter group have on average about 10-20 tools, while the former have 25-60. These tools are also more complex, involving assembly of parts. This appears to be due to two main domains of challenge not faced in the tropical latitudes, warmth and hunting. Warmth of course, requires that iconic “caveman” challenge, of making and maintaining fire, more challenging in the cold snowy environment. It also requires making clothes for adults and infants and when necessary shelters. Where plant foods are available year round in the tropical/subtropics, diet consists almost entirely of gathering supplemented with minor hunting, while the opposite is true up north. Hunting required novel tools and techniques such as tracking and trapping large prey, as well as food storage.

Tools and tool complexity at least add a quantitative dimension to an otherwise verbal plausibility argument (of which Jared Diamond has provided more such evidence for his narrative). And as far as this goes we must ask why the cold is thought to raise intelligence, when it is the African environment, not the European one, that rapidly boosted and created human intelligence. Similarly, nowhere does Lynn mention a challenge in the Neanderthals who populated Europe. Neanderthals were not our ancestors, but our cousins. They were a non-human species (we know this through direct genetic evidence), but they had a recognizably human intelligence. They made skilled tools, and were excellent hunters. They made clothes, built fires and shelters, cared for their sick and buried their dead, and perhaps played music as well. They too migrated from Africa and became adapted to the European environment. While the Neanderthals may have been roughly equally intelligent, there is little reason to believe the frigid environment they were well adapted to had made
them smarter than their African human counterparts, even though they could adequately do all the things Lynn argues Europeans later needed additional cognitive abilities to do. In fact the African humans moved up into the unfamiliar environment during conditions which had pushed down previous waves, and quickly displaced Neanderthals who had evolved in these conditions. The migrants had trade routes, which the Neanderthals did not, and their more sophisticated tools were copied by the retreating Neanderthals, not vice versa. So it would seem that the Africans immediately mastered these tasks, such as hunting, cloth and fire making, etc, that were supposed to increase their intelligence later, with intelligence they already had. And this intelligence evolved in the lower latitudes. Lynn’s argument seems much smaller now since the important selective difference must not be between Africa and Europe, but between Europe and even colder Europe. Did making clothes and fire, storing food or trapping prey become even more complicated during the second ice age, because we know they already needed to and were able to do these things, with surprising superiority, before hand. Of course another genetic possibility is that these initial migrants were not a representative group, as they were able to move up into the Levant during an advancing ice age when previous groups of modern humans were unable to withstand these conditions. Richard Lewontin has argued that the high heritability of intelligence suggests that these between-individual differences, as relevant as they are to real-world outcomes today, haven’t been much of a fitness characteristic in our evolutionary history and that they may have not been expressed the same or at all in ancestral environments. If this is true, genetic drift could be an even more likely explanation, if not a particularly romantic one.

As Steve Pinker recently pointed out in the 2006 Edge question he submitted, as an idea that’s dangerous because it’s probably true is that males and females and races differ in their abilities. And he has already cast his lot with Greg and Henry’s Ashkenazi theory. Pinker highlights, as Charles Murray did in Commentary several months ago, that the tools now exist to test racial differences and they will probably be tested in this next ten years either directly or inadvertently. If even one well-done study finds a racial difference in cognitive ability, and this is likely, we can count on Lynn’s work and others like it, including this book, getting an immediate flood of attention, as curiosities are piqued, taboos crumble and ambitious researchers fill the newly opened niche and quickly educate themselves on the topic with the best information available. And like it or not, on this score Lynn remains one of the only games in town. But it’s a big topic for only a few scientists to take on by themselves and it is unlikely that they would get everything right as the first lonely ones to take a stab. So let’s invite a lot more research on this topic, and the data will become cleaner, more sophisticated and more accurate. Something all of us should want.

Fig. 1

This chart summarizes the data available in RDiI. It is my approximate tally. The ‘Majority’ vertical column contains information on populations taken in countries where they form the basic majority. For example, Lynn lists 59 studies of East Asians taken in 5 different Asian countries such as Japan and Taiwan. The ‘Minority’ vertical column contains information on these same populations taken in countries where they form minorities. So Lynn lists 42 additional studies of East Asians done in 7 other (mostly Western) countries such as America and Britain. The third vertical series of columns are the combined values (they don’t always add up perfectly because of coding issues. For instance admixture studies appear in the final tally but not the Majority/Minority columns because this complicates the issue). For Africa, ‘Western’ indicates the developed countries where blacks score about 85, and ‘Non-Western’ the developing countries (primarily in the Caribbean and Latin America) where they score about 70.

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Jones, G & Schneider, W (in press). Intelligence, human capital, and economic growth: An extreme-bounds analysis. Journal of Economic Growth, 11(1).

Jones, G. (2005). IQ in the Ramsey Model: A Naive Calibration. Working Paper, Southern Illinois University Edwardsville.

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Roth, P, Bevier, C, Bobko, P, Switzer, F, & Tyler, P. (2001). Ethnic group differences in cognitive ability in employment and educational settings: a meta-analysis. Personnel Psychology, 54, 297-330.

Rushton, J (1997). Cranial size and IQ in Asian Americans from birth to seven. Intelligence, 25, 7-20.

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• Category: Science • Tags: IQ 
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Fellow language evolution enthusiasts may be interested in the latest review by Simon Fisher and Gary Marcus in Nature Reviews Genetics now available in gnxpforum (PDF).

Carl Zimmer’s earlier discussion of Pinker vs. Chomsky, here and here, is also related and worthwhile.

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Seed magazine has an article on Pinker’s recent lecture at the Institute for Jewish Research, but the author recommends you listen to the podcast instead so you can hear her “authentic New York Jewish accent” which is vital to the piece, which doesn’t discuss the theory so much as make fun of the audience (the article is sarcastically titled Jews on Jews: Jews are Great).

The author, (who is sympathetic enough to Pinker’s presentation) is being light-hearted, but there is also a serious message:

And many [Jews] in attendance were there to hear that Jews are naturally smarter than everyone else.

So now they’ll head out into the world, and spread the twisted word in their homes, at parties, in op-ed columns. And a paper that proposed an intriguing and plausible theory, and the man who eloquently analyzed it, will cause an impassioned backlash. Would that people were like genes and the deleterious ones weren’t so darn dominant.

In reality though, a Jewish audience being open-minded for the “wrong” reasons and then heading to the media, is probably preferable (or at least more conducive to the scientific study of intelligence) than a Jewish audience being close-minded for the wrong reasons and heading to the media. Pinker and his audience are a welcome alternative to the vacuousness of much of Jennifer Senior’s cover story for New York Metro a couple of months ago, where we were informed that, despite passing peer-review, Greg and Henry’s paper is based on “exploit[ing] stereotypes” and does “not meet the standards of traditional scientific scholarship”. The Metro article was chock full of helpful critiques such as “I’d actually call the study bullshit”, along with de rigueur comparisons to cold fusion and Hitler (and Arthur Jensen’s earlier attempts to “prove the racial inferiority” of blacks, etc.), and plenty of strategically cultivated misunderstandings (e.g. all Jews are smart).

Take as another example this op-ed last week in the Jerusalem Post. This author uses scare-quotes to describe the study as “scientific”, and also suggests that most scientists think it’s so much crankishness. Worse still the author goes on to tell us – “as an educator”; his professional opinion, of course – that we all have equal potential, and that “Psychologists maintain that the average person uses only 5-7% of that potential”. It’s doubtful from what I’ve read that any psychologists maintain this, and it sounds suspiciously like he’s just parroting the sorry old wives’ tale that “you only use 10% of your brain” (his number might come from pathological scientific fraud, Margaret Mead, who asserted we only use 6%).

In other words those who are being supportive, may or may not being doing so out of a self-serving feeling of “superiority”, but at least they aren’t slipping into absurd arguments or emotional bendings of the truth to do so, which is more than can be said for most people who have decided to take a “skeptical” [sic] stance.

Another problem for those that use bad arguments, is that they may not need to, and in fact may needlessly discredit their position with all of their tom-foolery. In fact a much bigger potential problem with the Ashkenazi theory isn’t Jennifer Senior’s “damning” condemnation of the paper’s highly unscientific “lack of footnotes”[1], but may be with the psychometric data itself. As a new “In-Press” review of Richard Lynn’s upcoming book Race Differences in Intelligence points out:

Another anomaly is that the IQ of Israel is only about 95, which although substantially higher than the median IQ of 85 found elsewhere in the region, is much lower than the IQ of Jews outside of Israel, estimated at between 108 and 115. Lynn breaks the Israeli IQ into three components: 40% Ashkenazim (European Jewish) with a mean IQ of 103; 40% Sephardim (Oriental Jewish) with a mean IQ of 91; and 20% Arab with a mean IQ of 86, which is virtually the same as that of Arabs elsewhere. Lynn suggests these differences could have arisen from selective migration (more intelligent Jews emigrated to Britain and the USA), intermarriage with different IQ populations (those in Europe versus those in North Africa), selective survival through persecution (European Jews were the most persecuted), and the inclusion of ethnic non Jews among the Ashkenazim in Israel as a result of the immigration of people from the former Soviet Bloc countries who posed as Jews.

103 is not appreciably different from the IQ of US whites (103 in the NLSY data, 102 in other datasets), and is noticeably lower than the area of Europe where Ashkenazi IQ was supposedly forged (e.g., the region of the Netherlands and Germany has IQs in the area of 106-107[2]). Given that Lynn thinks this is an “anomaly” to be explained, he would seem to feel compelled by his data that Ashkenazi IQ in Israel is 103, rather than just manipulating a score he wants to see.

This would seem to pose a more significant problem for the Cochran-Harpending paper, than a lack of footnotes. I myself am skeptical of Lynn’s numbers though, and await his book. Earlier reports of Ashkenazi IQ in Israel have been cited in Miles Storfer’s>Intelligence and Giftedness as 115 and higher, so it will be interesting to see Lynn’s citations. And of course, there are other lines of evidence indicating a disproportionate amount of smart coming out of Israel.

Anyway, I’d rather skeptics exist but actually look skeptical in their criticisms, instead of, say, complaining about footnotes, misrepresenting the theory, or just using denial (e.g. asserting something was caused by genetic drift even after mathematical models point strongly against this).

[1] An ironic criticism, given that Charles Murray recently pointed out in How to Accuse the Other Guy of Lying with Statistics that many critics of The Bell Curve claimed that key bits of information were “buried” or “hidden” in footnotes – as if to deceive. Not sure how putting something in a footnote is “hiding” it, but just goes to show that you’re damned if you do, damned if you don’t with race and intelligence.

[2] According to Buj’s European data at least. It is likely that these are biased upward with urban samples. Averaged across multiple studies and standardizations, these countries have IQs just like American whites – about 102-103.

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According to the Australian, Mike Morwood, leader of the Homo floresiensis discovery team, has now raised the idea that they originally lived in Australia and were pushed out by the colonizing human aborigines.

The article doesn’t go into the details of Morwood’s hunch, but we’ll see if it goes further than the Hobbit-as-Monkey theory.

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Two new reports suggest that humans are nearing their limit of record-breaking running achievement, and that the sex difference provides no evidence of ever closing. Abstracts below the fold:

More males run fast: a stable sex difference in competitiveness in U.S. distance runners
Robert O. Deaner
Evolution and Human Behavior
Article in Press, Corrected Proof

Sex differences in competitiveness are well established, but it is unknown if they originate from sociocultural conditions or evolved predispositions. Testing these hypotheses requires a quantifiable sex difference in competitiveness and the application of a powerful sociocultural manipulation to eliminate it. Study 1 reviews previous work showing that more male distance runners are motivated by competition and maintain large training volumes, suggesting that more males should run fast relative to sex-specific world-class standards. I then use two independent statistical approaches to demonstrate that, in matched populations of male and female U.S. runners, two to four times as many males as females ran relatively fast in 2003. Study 2 investigates whether the growth in opportunities and incentives for female athletes in the past 30 years is eliminating this sex difference. I first show that there was a marked increase in the number of fast female runners in the 1970s and early 1980s, a period during which female participation increased dramatically. However, I found no indication of an absolute or relative increase in the number of fast female distance runners since the mid-1980s. These findings therefore support the hypothesis that sex differences in competitiveness partly reflect evolved predispositions.


Are There Limits to Running World Records?
Medicine & Science in Sports & Exercise. 37(10):1785-1788, October 2005.
Nevill, AM, Whyte, G

Purpose: Previous researchers have adopted linear models to predict athletic running world records, based on records recorded throughout the 20th century. These linear models imply that there is no limit to human performance and that, based on projected estimates, women will eventually run faster than men. The purpose of this article is to assess whether a more biologically sound, flattened “S-shaped” curve could provide a better and more interpretable fit to the data, suggesting that running world records could reach their asymptotic limits some time in the future.

Methods: Middle- and long-distance running world record speeds recorded during the 20th century were modeled using a flattened S-shaped logistic curve.

Results: The logistic curves produce significantly better fits to these world records than linear models (assessed by separating/partitioning the explained variance from the logistic and linear models using ANOVA). The models identify a slow rise in world-record speeds during the early year of the century, followed by a period of “acceleration” in the middle of the century (due to the professionalization of sport and advances in technology and science), and a subsequent reduction in the prevalence of record-breaking performances towards the end of the century. The model predicts that men’s world records are nearing their asymptotic limits (within 1-3%). Indeed, the current women’s 1500-m world record speed of 6.51 m[middle dot]s-1 may well have reached its limit (time 3:50.46).

Conclusions: Many of the established men’s and women’s endurance running world records are nearing their limits and, consequently, women’s world records are unlikely to ever reach those achieved by men.


Related: African Endurance Running and Genetics, The Physiology of Kenyan Runners, Baby, we were born to run, Born to run!, Born to Run. (Three times the same title; pretty lame, I know. On the other hand 1) I did it first 2) I came up with Homo Secretariat – I mean c’mon!)

Also see Steve’s The Gender Gap: Elite Women Are Running Further Behind

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Uh oh, the backlash against Bruce Lahn is beginning. At first report of the big news, many “Science for the People” [sic] types, tried to play it cool, like none of it threatened them: Lahn and his research were Good, it was just those awful racists misinterpreting his work. But as the reality sets in of what’s to come and what it all means, Lahn will find his “mainstream” defense on the wane (if you think critics denying to the high heavens clear evidence for selection was troubling, just wait until issues like intelligence testing enter the mix, that’s when the real obfuscation begins). The “editors” at ScienceWeek blog take issue with John Derbyshire’s recent National Review piece on Lahn, but that’s not surprising, more interesting is the fact that Derbyshire isn’t the point, he’s just their brief launching pad for slamming the Lahn team themselves; and I must say it’s a real pathetic sight. Foremost they take umbrage at the implication that brain size has anything to do with intelligence – of course as the most encephalized animal we are smart enough to know that such an idea is ridiculous:

. . . [the research group of Bruce T. Lahn] nowhere discuss the important fact that within and across present human populations, studies of brains without pathology show no evidence of correlation of brain size with brain function or cultural “achievement”. Certainly, if the authors are working on genes apparently associated with brain size, and the authors are also interested in relating their work to current anthropology, one would expect some discussion of their problem, to wit: If greater human brain size is still undergoing evolutionary selection, how come we have no strong correlations between brain size and important functional attributes of the human nervous system? If the brain is still evolving in size, what are the conceivable selection pressures, given no apparent correlation between non-pathological brain size and function? We’re unhappy that the authors were not urged by the referees to make some statements about these questions.

Hmm, these quote-unquote “facts” sound a little a lot like complete lies. Not to mince words, I’m just going to quote at length from Thompson and Grey’s 2004 paper (PDF) from Nature Reviews Neuroscience:

Imaging studies of intelligence and brain structure. Correlations between intelligence and total brain volume or grey matter volume have been replicated in magnetic resonance imaging (MRI) studies, to the extent that intelligence is now commonly used as a confounding variable in morphometric studies of disease. [compare with “brains without pathology show no evidence of correlation of brain size with brain function”] MRI-based studies estimate a moderate correlation between brain size and intelligence of 0.40 to 0.51. [compare with “no apparent correlation between non-pathological brain size and function”] One MRI study determined the volume of 13 brain regions, and found that the brain regions intercorrelated substantially – a general factor (the first unrotated principal component in a factor analysis) accounted for 48% of the variance. We found that g was significantly linked to differences in the volume of frontal grey matter, which were determined primarily by genetic factors . . . this analysis underestimated the extent to which grey matter volume in each brain region correlates with g. We reported partial correlations that indicated the association between the volume of each brain region and g, independent of other brain regions. In other words, the volume of frontal grey matter had additional predictive validity for g even after the predictive effect of total brain volume was factored out (as is common in morphometric studies).

Posthuma et al. extended these findings using a cross-twin cross-trait (bivariate genetic) analysis to compute genetic correlations. They showed that the linkage between volume of grey matter and g is mediated by a common set of genes. Intelligence therefore depends, to some extent, on structural differences in the brain that are under genetic control, indicating a partly neuroanatomical (structural) explanation for the high heritability of intelligence.However, brain structure is not completely determined by genes – learning a difficult perceptual-motor skill (juggling) induced a 3% increase in the volume of grey matter in visual attention areas. Although such plasticity has not been shown in all regions of the brain, it is possible that the volume of grey matter is correlated with intelligence partly because more intelligent individuals seek mentally challenging activities that increase the volume of their grey matter.”

I encourage you to read the PDF and note the references. I also encourage you to read two more references. First yet another brain size and intelligence meta-analysis (PDF) was published this year by Michael McDaniel. The correlation between brain size and measured intelligence is again about .4 for adult men and women, and a little bit lower for children. Second, for the functional relationship of this correlation, you should read Gilles Gignac et al’s chapter 6 in Scientific Study of General Intelligence.

Bottom line: the editors at ScienceWeek are blaming Bruce Lahn for their own ignorance. Besides lying about what the literature does show, they also have the gall to be outraged that Lahn doesn’t similarly rely on their own poor sources from the 1960s:

We’re also fascinated by the opening sentence of the first paper: “The most distinct trait of Homo sapiens is the exceptional size and complexity of the brain (1,2). That’s good, but the problem is the two references are 46 years old and 32 years old, respectively, and we’re trying to imagine why anyone would choose these particular references for a report of such research. If we’re to choose old references, why not choose von Bonin? But maybe that would be against the approach of these authors. Consider, for example, the following quotation from von Bonin:

“The results of our inquiries into the brains of fossil men are somewhat meager: we cannot deduce any details about their mental life, whether they believed in God, whether they could speak or not, or how they felt about the world around them… That the brain increases in size as we go from the Australopithecinae to modern man — or to the Upper Paleolithics, for that matter –is quite obvious and, of course, gratifying. But the meaning of the increase is again not quite clear because, as we all know, brain size as such is a very poor indicator of mental ability. This has been shown best perhaps by Pearson (1925) some years ago. In his series, very gifted persons, such as Leon Gambetta, Anatole France, or Franz Joseph Gall, had very small brains, of about 1100 grams. Other equally gifted persons had very large brains; thus Byron and Dr. Johnson had brains of about 2000 grams. And, of course, some very ordinary persons had equally large brains. So brain size was certainly not very important, and the correlation between brain size and mental capacity was insignificant. But whether this argument can be extended to an evolutionary series is again another matter. For one t
hing, we know far too little about the bodily proportions of fossil forms. Obviously, the brain stands in a certain relation to the rest of the body, and this rest is still largely hidden from us. Brain size as such is none too meaningful. Moreover, mere size completely leaves out of account the inner structure of the brain, which may be different in different forms and which may determine to a great extent what the brain can do.” Gerhardt von Bonin: THE EVOLUTION OF THE HUMAN BRAIN University of Chicago Press, 1963, p.76

So why cite Spuhler (1959) and Jerison (1973) rather than von Bonin (1963)?

Its hard to emphasize how stupid and ignorant this argument is, so I’ve thought of a good way to illustrate it. Why did the Lahn team reference Harry Jerison’s book, Evolution of the Brain and Intelligence, that ScienceWeek finds so archaic and stupid, and not Gerhardt vo Bonin’s? Maybe because Jerison’s work was revolutionary and is still wildly relevant to the subject and area of study, while Bonin’s is a fossil. In the Preface to 2001’s>Evolutionary Anatomy of the Primate Cerebral Cortex Dean Falk writes:

Beginning with 1973 publication of his classic monograph, Evolution of the Brain and Intelligence, Harry Jerison’s ongoing research has had a profound impact on the questions, methods, and theoretical framework that continues to shape the field of brain evolution. On April 2 1998, researchers from Europe, Africa, and the United States gathered in Salt Lake City at the sixty-seventh annual meeting of the American Association of Physical Anthropologists to take part in a symposium that recognized and celebrated Harry Jerison’s intellectual influence on the development of our discipline.

The prologue is written by none other than Stephen Jay Gould, widely celebrated among lay intellectuals for his Mismeasure of Man which lampooned many 19th researchers for seeking a link between brain size and intelligence. Gould describes his early resistance and eventual conversion to Jerison’s work after realizing that Jerison truly “delivered the goods” – or, as Gould’s title pithily informs us, “Size Matters”.[1]

But the semi-recent Internet tool of Google Scholar gives us an even better way to demonstrate it is the ScienceWeek editors, not Bruce Lahn and company, that are truly out of date. In addition to finding papers, GS also gives us a rough indication of how important (or unimportant) a reference has been, by telling us how many other scholarly works have cited it. Then by clicking on that number we get a list of those references, including their dates, and also how many times those references have been cited – giving us an important glimpse into where the beefs at. For instance typing in ‘HJ Jerison Evolution of the brain and intelligence’, we see that Jerison’s book has 231 citations. Clicking on that we see that many of those citations are also highly cited. All of the ones on the first page are cited at least over 50 times. The citations are also very recent, indicating, contra ScienceWeek, that Jerison’s book is still relevant to current research. All of the references on the first page are post 1980, a majority are from mid to late 90s, and the rest are post-2000 (including the Falk volume above) . In contrast, we find that ‘G von Bonin The evolution of the human brain’ has 1 citation! And that citation has 4 citations which themselves trail off to nowhere.

In other words it’s a no-brainer why Lahn’s team cited Jerison’s book instead of von Bonin’s. To steal their condescending rhetoric, I suggest the editors “do more homework”. But given their editorial earlier this year that Larry Summers comments might be “possible evidence of brain damage”, the possibility of their objectivity and honesty on these issues is, of course, highly in doubt. I expect many more shoddy, deceptive attacks on Bruce Lahn and similar genetic researchers in the coming years.

[1] Also, at the risk of being obvious, I should point out that referencing a book first published in the 1970s because it pioneered a set of ideas is not the same as saying those ideas ended or stopped developing in the 70s. The Falk book is just one collection proving that Jerison and the field have expanded on those original insights ever since.

Actually, given the transparent reason for their opposition, the ScienceWeek folks should be grateful that the Lahn team didn’t instead point to the most recent Jerison summary, which is in the 2002 psychometric volume The Handbook of Intelligence, where Jerison not only states that the distinction between the significance of brain size between species and within species is false, but affirms the existence of human race differences in brain size too. He don’t connect them, but the dots they ain’ts hard to connect.

• Category: Science 
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Via my co-blogger and pro psychologist, Alex, I learn that the International Society for Intelligence Research is holding its 6th annual conference this December in Albuquerque, New Mexico, and by the looks of it, some very interesting research will be presented. Scientists exploring this important, difficult, controversial concept known as intelligence from many different disciplines and research paradigms – differential psychology, economics, sociology, neuroscience, evolutionary biology, paleoneurology, cognitive psychology, evolutionary psychology, artificial intelligence, genetics, animal cognition – are increasingly working together and combining their discoveries to powerful theoretical and empirical effect. For those interested, a PDF is available here with about 50 new abstracts for almost 60 presentations. Below the fold is a summary of the ones that I find the most interesting sorted by subject.

The Flynn Effect

Probably the most puzzling issue in psychometrics today is the Flynn Effect – the phenomenon of obsolete test norms as IQ scores continue to rise. The effect has caused problems or has had uncertain implications for any number of psychometric issues, including the authenticity of the rise itself, the black-white test score gap, the stability of intelligence with age, the effect of adoption studies, the actual IQ of the earlier generations of Asian Americans, and the existence of dysgenic trends.

Alexander Beaujean and Steven J. Osterlind follow recent reports of the Flynn Effect finally stopping, and even reversing, in Europe (see Alex’s post here) in a presentation called Assessing the Lynn-Flynn Effect in the College Basic Academic Subjects Examination (Alex and David Burbridge have previously debated the nomenclature of the rise on GNXP here). Alex finds evidence, using special methods of test analysis based on Item response theory, that the Flynn Effect has started to reverse course in America as well.

And Jelte Wicherts, in Flynn Effect in the Woodcock-Johnson Cognitive Ability and Achievement Tests 1976-1999, uses Structural equation modeling techniques to explore whether Flynn gains have been an artificial score inflation (as Alex and I believe) or genuine gains in ability. Equally important, Wicherts attempts to explore whether the FE occurs between cohorts or to everybody at time of measurement (i.e. if you took an IQ test when you were 30, 40, and 50 would it be higher at each successive age (time of measurement), or would it remain stable for individuals across their lifespan, but three brothers age 6, 10, and 15 would be progressively stupider (cohort). Which one it is has meaningful implications for what’s causing the rise (e.g. heterosis – a genetic cause – is only consistent with cohort). Previous evidence, such as the stability of IQ across 50+ year longitudinal studies, seem to falsify the TOM model.

On a related issue, Jan te Nijenhuis, et al. look into another area that might be plagued by “hollow” or fake IQ gains. IQ scores go up after retesting and through training programs. In Score Gains on g-Loaded Tests: No g the team demonstrate that these kinds of IQ boosts are not on the g factor (the business end of IQ), and suggest their results have implications for experiments that show schooling increases IQ. These increases may well be hollow.

Measurement and Mental Chronometry

One way to maybe better overcome this problem of “fake IQ gains” is getting at the underlying physical reality of intelligence. For instance, to determine if intelligence gains were “real” or not, we could measure the areas, tissues or structures of the brain that indicate intelligence or monitor more primal functions, such as things like how quickly or efficiently the brain registers simple stimuli through brain waves or glucose metabolism during problem solving. Issues of test bias and the potential of artifactual test gain would no longer be a problem because we could just clock the brain itself. Simple, more accurate, more efficient intelligence measurement is desirable and was Francis Galton’s original vision for intelligence testing that ultimately lost out to Binet’s measurement method.

One researcher who has helped revive Galton’s model is Joseph Fagan, through his work with infants and young children. Habituation is a method for determining what’s going on in the heads’ of infants less than one year old. By monitoring a baby’s time spent discriminating stimuli, cognitive psychologists have determined innate or early notions of number and causality, evolutionary psychologists have determined culturally neutral standards of beauty and sex differences in social and object interests, and differential psychologists have tracked intelligence differences to the earliest months of life. In The Prediction, from Infancy, of Adult IQ and Achievement, Fagan et al. find that the correlation between the IQs of a sample of 20 year olds and their intelligence measured before the age of 1 is about .60. This is similar to earlier studies, which found the correlation between age 1 and age 11 was about .50.

Moving to the brain itself, a number of presentations come from Richard Haier and Rex Jung. Along with lead author Richard Colom in Correlated Vectors, g, and Gray Matter: A Frontal-Parietal Network and the Einstein Hypothesis they test the theory (named for the enhancement of this particular region in its namesake), through a number of lines of evidence, that the frontal-parietal network is key to individual differences in intelligence. They also review the current regions and structures of the brain known to be associated with intelligence.

Jung et al. also turn to the neurochemistry of intelligence in Biochemical Markers of Individual Differences in Cognitive Functioning, and “highlight the importance of white matter structural and chemical integrity to intellectual performance” which supports “the “neural efficiency” hypothesis that suggests optimal brain organization underlying individual differences in cognitive processes”.

Finally, in Investigating the Cortical Temporal Dynamics of the Speed-Intelligence Relationship Using Magnetoencephalography (MEG), Robert Thoma uses MEGs to monitor the activity of the brain, to show that the regions involved in reaction time (RT) experiments (how quickly you lift your finger off a panel to turn off a light) are the same areas that show activity during complex intellectual tasks, suggesting RT is a simple and accurate measure of intelligence (something disputed by NJ Mackintosh in IQ and Human Intelligence, where it is argued that RT is a very nongeneralizable mental ability, not the same as g).

Group Differences

Those interested in HBD will not be disappointed, there are a number of presentations on race and sex differences, including a biggie from Greg Cochran and Henry Harpending titled The Evolutionary Biology of Human IQ Diversity: Some Current Directions and Hints. Fresh from their Ashkenazi notoriety, they discuss the far more contentious issue of Eurasian intelligence, with a new theory that fingers the Neanderthals!:

Modern humans apparently left Africa ca. 40,000 years ago and appeared soon afterwards in
western Eurasia and in Australia. The southern arm peoples arrived with middle Paleolithic technology that persisted unchanged for tens of millenia while the northern arm peoples were host to the famous “creative explosion” of the upper Paleolithic with elaborate tools, worked bone, beadword and other adornment, sculpture, and painting. We discuss the hypothesis that incorporation of Neanderthal genes led to elevated intelligence (or something closely related) in the northern arm. We will mention some likely examples of such assimilated genes . . . We discuss the appearance and spread of an ASPM variant, one of the microcephalin complex genes, as an example. A puzzling pattern among candidate genes for elevating IQ is that they seem not to have spread in Africa

Additionally, two more talks add to and work off of Lynn and Vanhanen’s Important book. In IQ & Wealth of Nations: Prediction of National Wealth, Deborah Whetzel and Michael McDaniel replicate Lynn and Vanhanen’s findings and also find that education spending per student provides no incremental prediction of GDP beyond IQ. They examine a set of the highest predictors of GDP and find that economic freedom, health spending per capita and IQ explain 90% of the variance in national wealth (See also the Jones & Schneider paper and Garett Jones’ newer paper (PDF)). Earl Hunt and Werner Wittmann also replicate Lynn and Vanhanen’s finding in Relations Between National Intelligence and Indicators of National Prosperity, and add to it by examining cross-national student scholastic achievement from international datasets like PISA and TIMSS. They find a strong relationship between intellectual competence and economic indicators. In Criteria For Studies of Race and Intelligence, Earl Hunt also makes the case for agnosticism about genetics being the source of these (real and important) differences, with discussion of research ethics and study design for racial behavior genetics.

In Race Difference in General Intelligence g in Relation to Blood Pressure, Body Proportions, Hormones, and Personality, Helmuth Nyborg et al. test and reject another theory for the black-white IQ gap – that greater black hypertension plays a role in the difference.

Of course these kind of theories are DOA. The real problem is how to test the factor X theory, that the black-white IQ gap is due to something unique to the black environment that affects all blacks equally but is completely absent from the white environment in a way that could evade all detection thus far. A team of researchers published a paper (PDF) in 2003 responding to the well known argument that high within-group white and black heritability has no implications for their between-group IQ difference, showing that a common factor model “approach clarifies that absence of measurement bias implies common sources of within- and between-group variation” (earlier, the late David Rowe similarly showed, through an ingenious method of structural equation models using blacks and whites and their full and half siblings, that the source of the within group differences was also causing the between group difference). In Factorial Invariance and the Representation of Within-Groups and Between-Groups Differences: A Reconsideration Keith Widaman disputes their argument, but offers his own methods “for study design that will enable a test of the hypothesis that sources of within-group differences are also responsible for between-group differences”.

On the sex difference front, Paul Irwing presents Sex Differences in General Cognitive Ability: A Reexamination of the Evidence, which seeks to question whether the 100 year old position in psychometrics – that there is no mean difference between men and women on IQ – is correct (as Jensen also concluded in 1998’s>The g Factor), or whether Richard Lynn’s newer (1990>) position – that men have somewhat higher average IQs – is correct. Irwing concludes from large SPM samples that Lynn is correct (as was reported in the media a few months ago). Furthermore, he finds no evidence that this is due primarily to the male advantage in spatial visualization. Also, he finds that some research previously presented to show that there are no sex differences shows exactly the opposite.

David Puts et al. also present a meta-analysis titled Possible Organizational Effects of Early Androgens on Human Spatial Ability: Meta-Analyses of CAH and Digit Ratio Studies Showing that females that get a heavy dose of male hormones in utero also perform higher on spatial tasks like men do.


David Puts’ finding has implications for the ridiculous Larry Summers’ witch-hunt earlier this year as well. Rose Mary Webb et al. study the geniuses among us in Spatial Ability: A Neglected Dimension in Talent Searches for Intellectually Precocious Youth, and find using longitudinal data that children with high spatial abilities (who – a la Puts – are going to be disproportionately male) have higher levels of interest in math and science (“theoretical” endeavors) and that the ability can be used to predict which gifted students follow scientific or humanities pathways. Similarly, Summers’ critics have tried to rebuff the annoying fact that many more men score at the top of the ability distribution by asserting that IQ/test score ability stops being meaningful at the higher levels of ability anyway (that is, conveniently, at the precise point where the male/female ratio starts to get ridiculously incongruous. e.g. 7 to 1 in the top 1%). In Creative Accomplishments Covary With Ability Even Among the Top 1%, Jonathan Wai et al. show this is nonsense; IQ keeps discriminating between levels of creative and career achievement (such as earning a math-science PhD, securing a patent, and achieving tenure at a top 50 U.S. university), even at the very skinny right tail of the ability distribution. (and it keeps on going: IQ even distinguishes those in the top .0001%!)

Two additional presentations on those at the right tail, An Examination of Spearman’s Law of Diminishing Returns by Christopher Condon and David Schroeder and A Test of Spearman’s Law of Diminishing Returns in the Kaufman Assessment Battery for Children, Second Edition by Matthew Reynolds and Timothy Keith, test Spearmen’s idea that the g factor is more important at low IQ levels, and that lower order factors are more independent and important at progressively higher ability levels. Using different data sets both studies find support for this. “Multiple intelligences” (and not the fictional Gardner ones) are only something for the very smart, for people at the left tail it’s all about g.

The Evolution of Human Intelligence

A number of presentations attempt to tie general intelligence into the framework of human evolution. James Lee’s The Evolution of General Intelligence in the Primate Clade, for instance, talks about research showing that mental testing across primate genre best distinguishes them by a single general factor (see also the latest issue of Behavior Genetics for a detailed exploration of the g factor in mice). The correlation between brain size and the g factor across 25 primate genre is .77. Lee discusses this in the context of Bruce Lahn’s recent papers.

David C. Geary uses material from his fascinating new book in The Origin of Mind: Evolution of Brain, Cognition, and General Intelligence. Geary argues that “The primary dynamic that has driven and is currently driving human evolution is competition with other people and groups of other people for resource control” and that intelligence involves the ability to form more accurate “mental models” of the outside world, and that the systems to build these models “are known as general fluid intelligence, working memory, and attentional control” and that “The combination of these systems and folk knowledge is the foundation upon which human intellectual and cultural advances have been built”.

In contrast to Geary, Linda Gottfredson argues in Innovation, Fatal Accidents, and the Evolution of General Intelligence that competition with other people hasn’t been the primary engine of human intellectual evolution, but instead that each boost in intelligence led to new technologies which created new dangers that continuously pruned off those at the bottom of the spectrum. Innovation then would boost IQs through increased selection, which would thus lead to even more innovation, and the cycle fuels itself. (her paper, by the way, is one of the few that can already be found online. Here (PDF).

Kim Hill presents The Adaptive Function of High Cognitive Ability in Hunter-Gatherers: Feeding Niche or Social Complexity?, where an IQ study of modern hunter-gatherers is discussed. In support of David Geary and the modern consensus of “Machiavellian intelligence”, it was found that higher IQs in this group were associated with higher social status. Contradicting the old “Man the Hunter” theory of intelligence, Hill reports that there was no association between hunting prowess and measured intelligence.

In Mutual Mate Choice for Intelligence as a Fitness Indicator, Geoffrey Miller uses research from evolutionary psychology to support his theory that sexual selection was responsible for driving up human intelligence. And in a related lecture, Intelligence and Mate Choice, Mark Prokosch explores the assumptions behind the sexual selection theory (e.g. how important is intelligence in long and short term mates? How accurately do females judge intelligence?) and tests some of them directly.


A number of other presentations deal with the issue of “Emotional Intelligence” (empty) and “Life History Theory” (all the presented papers fail to support it). I do not find those issues interesting, but the abstracts are in there for you. A few more deal with technical issues, such as test refinement, which are no doubt important to the field but less fun to talk about. The last one I’ll leave you with, though, might be of interest if you’ve ever had the misfortune to encounter Internet ads, and says all it needs to just in the title: Web-Based IQ Tests: A Concept Whose Time Has Not Yet Come.

• Category: Science • Tags: IQ 
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