Wednesday, October 31, 2007

James Watson Tells the Inconvenient Truth: Faces the Consequences   posted by Jason Malloy @ 10/31/2007 11:22:00 AM

... [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 Sternberg, 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 Rindermann 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 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, then 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 ancestry, 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 this 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.

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, 549-552.

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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Sunday, September 30, 2007

The importance of analogies in math and science   posted by agnostic @ 9/30/2007 02:50:00 PM

"Good mathematicians see analogies. Great mathematicians see analogies between analogies."
--Stefan Banach

A recent Cognitive Daily post called "Why aren't more women in science" (part 1) reviews some of the lit on sex differences in cognitive abilities. Dave Munger notes:

In the verbal portion of the [SAT] test, the male advantage is eliminated if the analogy portion of the test is eliminated; arguably this is more a test of mapping relationships than literacy.

The analogy portion was, of course, scrapped as of the spring 2005 SAT. [1] The boldfaced clause above shows why it matters more than the other Verbal portions: figuring out relationships between ideas matters, and reporting what some author said does not. Analogies are highly g-loaded, reading comprehension much less so. But aside from better detecting who the smarties are, analogies are more reflective of real-world math, science, and engineering. (And they matter in the humanities too [2].) If A got one more math question than B, but B got three more analogy questions than A, I'd bet on B doing better in math, even if an IQ test showed they had the same IQ.

What follows is mostly a diversion to show the importance of analogies in math, starting with high school material and moving to some college material. I hope you learn something new, but mostly the goal is to put it on the record, with examples, how important a person's verbal analogy score is in predicting their success in math and science.

Example 1. A bouncy-ball is dropped from 2 feet, and after hitting the ground, bounces up only 1/2 as high as its previous maximum height. Pretend that it bounces forever like this. In the long run, how much distance does the ball travel?

We can make a table that shows how much distance the ball travels in a particular trip, either up or down, like so:

Trip 1, 2, 3, 4, 5, 6, 7, ...
Dist. 2, 1, 1, 1/2, 1/2, 1/4, 1/4, ...

This problem is introduced in a pre-calculus class during the unit on the sum of an infinite geometric series -- infinite because it starts but never ends, and "geometric" meaning you multiply by the same number to get from one term to the next. The formula for such a sum is t1 / (1 - r), where t1 is the first term, and r is the constant that multiplies one term to get to the next. So if we only had these values, we'd be all set! Unfortunately, if we guess that r is 1/2, when we try to go from 1 to 1 -- we don't multiply by 1/2 anymore (or from 1/2 to 1/2). Damn. Plainly, the above series is not geometric, and at that point most students will opt to make better use of their time by yakking with friends on their cell phone.

Ah, but the students in the class who are good analogical thinkers will notice a geometric series hiding behind the series above -- in fact, they'll discover two of them. The terms of one are interlocking with the terms of the other, like two rows of teeth that complete a zipper. That analogy suggests a strategy: unzip the above series. Then we have two series that go:

2, 1, 1/2, 1/4, ... and
1, 1/2, 1/4, ...

Bingo! In each of these, you multiply by a constant (1/2) to get from one term to the next. And we know the first term of each, so we can plug in values for t1 and r in the sum formula. We get 2 / (1 - 1/2) = 4, and 1 / (1 - 1/2) = 2. So all together, the ball traveled 6 feet. That's a neat analogy, but it only makes sense when there are two series meshed into one. We'd like to generalize to any number of series that dovetail into one -- and no one makes zippers with more than two rows of teeth. So a better analogy might be the following:

Here there are two strands woven one around the other infinitely, with beads bearing numbers that face us, and there is a knot at the start where the strands fuse. Could we think up series with three or more geometric series hiding inside them? Sure, just as we could make a rope with three or more strands. And to make that series easy to solve, we would just unbraid the strands and work with the beads of each one separately. See note [3] for more uses of this braid analogy.

Example 2. Here are some (x,y) pairs associated with a function. What is the degree of this function? That is, does it look like x, x^2, x^3, etc.?
x = 1, 2, 3, 4, 5, 6...
y = 2, 14, 34, 62, 98, 142...

This problem also comes from high school math -- or middle school, if you took algebra then. There, you were taught to look for the difference between consecutive terms, and maybe repeat this process, until you got a sequence of the same number. The number of runs you have to make is the degree of the function. So for the above, the differences are:
12, 20, 28, 36, 44

OK, not the same number, but take the difference again:
8, 8, 8, 8

Ta-da. We had to go through 2 runs, so it must be some function like x^2 (in fact, it is 4x^2 - 2). I guarantee you never knew why this worked when you learned it -- and even after calculus or more advanced math, you may still have treated it as a mysterious trick. But there are analogies between discrete and continuous areas of math, and they are pervasive. If you took at least a semester of calculus, you know that if you take the 1st derivative of a function like 4x^2 - 2, you get something with the independent variable still in it -- 8x. And sure enough, in our discrete case, the first differences are 8x plus a constant 4.

But if you then take the derivative of the derivative, you get a constant -- 8, the same 8 that appeared in our constant sequence after the 2nd run. A constant second difference in the discrete case is analogous to a constant second derivative in the continuous case. That also shows why you knew, back in high school, that you didn't have a polynomial function like x or x^2 or x^3 when you saw something like this:
x = 1, 2, 3, 4, 5, 6...
y = 2, 4, 8, 16, 32, 64...

You can take differences of differences of differences of... and you'll never get a constnant sequence for this function, which is 2^x. In first-semester calculus, you learned that e^x is its own derivative, so that if you keep taking the derivative over and over, you always get back e^x -- the independent variable never goes away, so you never get a constant. This resilience to your effort to tease a constant derivative out of it is true of all exponential functions, which by analogy tells us that we'd never come up with a constant difference in the discrete case above.

Since there are a billion other discrete-continuous analogies, I'll leave it there. I don't think they're that neat since it's only like switching between a British and American accent, not like translating between Farsi and Chinese. On a closing note, the entire domain of represenation theory in algebra is based on finding good analogies: they attempt to better understand how some group works by casting the problem in terms of matrices and linear algebra, which are better understood. All of this shows how indispensable this way of thinking is to fields that many assume are primarily about visuospatial skills (though those are key too). Analogies are to all types of thinkers what SONAR and nets are to deep-sea fishermen regardless of which species they hunt.

[1] According to CollegeBoard's 2007 national report of college-bound seniors, it does appear that within the past couple of years, the male mean for Verbal is only about two points above the female mean, shrinking from a difference of about 11 to 12 points that had persisted since about 1980. And at the high end, in 2007, 1.98 % of males and 1.84 % of females scored 750 - 800. Data from other years on the elite scorers are not contained in the 2007 report, and I'm not interested enough in this topic to pursue them. The point is that gutting the analogy portion seems to have served its purpose.

[2] When the retiring of the analogy questions was announced, an educator named Ted Sutton got an op-ed into the very liberal Boston Globe and made a guest appearance on the very liberal radio show On Point (which airs on NPR). He lamented the change, focusing on the centrality of analogies to the great philosophical and humanistic traditions. Older-style liberals like Sutton appear unaware that their social engineering cousins are the ones responsible for flushing great ideas down the drain, so that the gap between the sexes on a test might close.

At least there are still analogies on the GRE -- despite a plan to re-vamp the test with the same gap-narrowing agenda in mind. And thank God for the Miller Analogies Test -- not a single "how does the author most likely feel about X" question at all!

[3] The braid idea can also guide your intuition when you have a homework problem in a college-level course that says: "Prove that a countable union of countable sets is countable." I provided a visual proof here (with a more detailed proof at the end), but I didn't think of the braid analogy, which makes it even easier to picture. The argument is as I wrote before, but when you're introducing yet another countable set into the union, it's like adding a new strand to a rope. You look at the place where the n strands have shown themselves once -- and before the first strand winds around the second time, you push it over and braid in your new strand. When they n strands have shown up twice, you push the first strand over before it winds around the third time, and there's the second place where the new strand goes. And so on to infinity. The union of these strands is a rope whose beads are countable and, more importantly, ordered in a straightforward way.

More explicitly, we can think of the strands as equivalence classes and the rope as the space they fill out. We can imagine a rope that extends infinitely in either direction, like the even and odd integers woven together. We've already seen a rope with a knot but which continues to weave itself forever in one direction. A rope with knots at both ends is pretty boring -- unless they were the same point, i.e. the rope circled back so that each strand fed back into itself, as with a sequence that's cyclic (for instance: x, y, x^2, y^2, x^3, y^3, x, y, ...).

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Friday, September 14, 2007

The Progression of IQ - a response to David Brooks   posted by Alex B. @ 9/14/2007 09:18:00 PM

In his September 14, 2007 op-ed piece in the New York Times, David Brooks tells his impression of the latest research in cognitive ability. Unfortunately, he not only misses the forest, but he bungles a few trees as well. Article and comments below.

A nice phenomenon of the past few years is the diminishing influence of I.Q.

Right out of the block he is off. In what domain was there once a non-zero IQ-outcome relation, but now, X number of years later, the relation has shown a systematic decrease? From the generality of the statement, one would expect this to hold across most, if not all, pertinent domains (e.g., occupation, academic success, etc.). However, that is not the case. Not only do the IQ-achievement, and IQ-occupation relationships still hold, but now there is a burgeoning new field in the area: cognitive epidemiology, that looks to see how health outcomes are related to cognitive ability. Deary et al give a terse summary here, and Gottfredson gives a conceptual overview here. But, perhaps more interesting, researchers who have no interest in intelligence per se are finding similar results: a case-in-point is Yakov Stern's cognitive reserve research that shows people with higher IQ scores tend to have have less severe symptoms of Alzheimer's symptoms. As this is a new area of inquiry, the exact nature of the relationship has not been identified, but one thing we can say for sure is that there is no diminishing influence of cognitive ability.

For a time, I.Q. was the most reliable method we had to capture mental aptitude. People had the impression that we are born with these information-processing engines in our heads and that smart people have more horsepower than dumb people.

These two statements have little to do with each other. IQ (at least as derived from a Full Scale score) has been, and still is, very reliable for most age groups and subpopulations, no matter how you measure reliability. For example, the Woodcock-Johnson, one of the more theoretically sound measures of cognitive ability, reports in their new normative update that the coefficient alpha values (which are a lower bound of reliability) above .90 for all ages ranging from 3 to over 80. Given that the maximum value alpha can take is 1 (under almost all circumstances), this is pretty good evidence. If you look at the technical manual for the Wechsler, Stanford-Binet, or Reynolds Intellectual Assessment Scales, you'll find very similar values (I refer to these only because their norms span a very large age group, and the full scale score is derived from multiple subtests). I challenge Mr. Brooks to find a more reliably-measured psychological construct in psychology, nay, in the social sciences.

The second statement, while perhaps overstated, is true. People are born with brains, these brains process information, and smarter people (as measured by IQ scores) tend to process information faster (see, for example, here and here). What impression should people have instead? People are born with a blank slate and all of life is little more that the acquisition of stimulus-response patterns? Skinner died in the 1990s, and strict adherence to this view died long before that (a great book about this).

And in fact, there's something to that. There is such a thing as general intelligence; people who are good at one mental skill tend to be good at others. This intelligence is partly hereditary. A meta-analysis by Bernie Devlin of the University of Pittsburgh found that genes account for about 48 percent of the differences in I.Q. scores. There's even evidence that people with bigger brains tend to
have higher intelligence.

No disagreement here.

But there has always been something opaque about I.Q. In the first place, there's no consensus about what intelligence is. Some people think intelligence is the ability to adapt to an environment, others that capacity to think abstractly, and so on.

Ah, the slippery slope begins. These arguments are so old, and well-answered in the literature that it is almost painful to repeat them. I refer the interested (and Mr. Brooks) to Seligman's phenomenal, non-technical introduction, as well as Deary's brilliant literary corpuscle. First, IQ and intelligence are two different things. One is a measuring instrument's scale and the other is a psychological construct that is measured, to one degree or another, by an IQ test. We don't confuse inches and paper, so why do we confuse IQ and intelligence? Second, few scholars actually study intelligence. While the word might be used in common parlance, there is no common definition. Instead, most serious scholars study general intelligence (g) or one of its sub-constructs (e..g, fluid abilities, crystallized abilities; see here or here or here). Once you make the jump to g, the definition becomes much more consensual. There are technical debates (as there are in any branch of science), but it's measurement (by factor analysis of one flavor or another) is virtually undebated. For most purposes in daily life, it is OK to quasi-equate intelligence and g, as well as IQ scores and
intelligence, but they really are quite different concepts.

Then there are weird patterns. For example, over the past century, average I.Q. scores have risen at a rate of about 3 to 6 points per decade. This phenomenon, known as the Flynn effect, has been measured in many countries and across all age groups. Nobody seems to understand why this happens or why it seems to be petering out in some places, like Scandinavia.

IQ scores, across generations, need re-calibrated for valid comparisons. We have ways that do this very well (latent trait models), that have very sound theory behind them. You have to periodically re-calibrate your bathroom scale, and you have no question about what it is measuring; why should IQ be any different? As a side note, this phenomenon is not at all confined to IQ tests, and it has been known about in the psychometric literature for decades, although it is called item parameter drift there. Moreover, just because there is no consensus as to why cross-generational scores tended to rise in the mid-twentieth century, this does nothing to invalidate the validity of interpreting IQ scores within a generation.

I.Q. can also be powerfully affected by environment. As Eric Turkheimer of the University of Virginia and others have shown, growing up in poverty can affect your intelligence for the worse. Growing up in an emotionally strangled household also affects I.Q. One of the classic findings of this was made by H.M. Skeels back in the 1930s. He studied mentally retarded orphans who were put in foster homes. After four years, their I.Q.'s diverged an amazing 50 points from orphans who were not moved. And the remarkable thing is the mothers who adopted the orphans were themselves mentally retarded and living in a different institution. It wasn't tutoring that produced the I.Q. spike; it was love.

Brooks is telling all parents of children who have Mental Retardation or Borderline Intelligence that their children's low cognitive ability is a direct result of parental inadequacy. If these parents would love their children more, the Mental Retardation would go away. If I were king, I would mandate that any person with the gumption to make asinine statements like this do two things (a) read Spitz's chef d'oeuvre, and (b) spend a week with a family who have a child diagnosed with Mental Retardation. Not just a daily visit, but an in vivo experience. Then get back to me about how easy it is raise the cognitive ability of people with mental retardation.

By the way, Turkheimer's studies look at the ability of the environmental variance to modify heritabilty estimates. Specifically, people who grow up in more impoverished environment have a more variable environments, which, almost by definition, decreases heritability estimates. This is a very long cry from showing "growing up in poverty can affect your intelligence for the worse".

Then, finally, there are the various theories of multiple intelligences. We don't just have one thing called intelligence. We have a lot of distinct mental capacities. These theories thrive, despite resistance from the statisticians, because they explain everyday experience. I'm decent at processing words, but when it comes to calculating the caroms on a pool table, I have the aptitude of a sea slug.

What? A few paragraphs ago general intelligence existed, now it doesn't? Anyway, it is an awful shame when everyday experience does not map onto what data tell us: Beth Visser recently (gasp!) gathered data to test Gardner's theory. What did she find? Basically what John Carrol said she would find a decade ago: these multiple intelligence all positively correlate (sans kinesthetic intelligence) and a strong g factor can be extracted when the measures are factor analyzed.

I.Q., in other words, is a black box. It measures something, but it's not clear what it is or whether it's good at predicting how people will do in life. Over the past few years, scientists have opened the black box to investigate the brain itself, not a statistical artifact.

I wish I had the luxury of being able to write blatantly false statements in a national paper. There is over 100 years of empirical literature investigating the construct validity of IQ. There is also 100 years of literature examining what, and how well, IQ scores predict life outcomes. A simple perusing of Jensen's g factor or Brand's g factor (this one is even available for free!) would have sufficed here; but who wants data to interfere with a good opinion?

Now you can read books about mental capacities in which the subject of I.Q. and intelligence barely comes up. The authors are concerned instead with, say, the parallel processes that compete for attention in the brain, and how they integrate. They're discovering that far from being a cold engine for processing information, neural connections are shaped by emotion.

...and you can read books about journalism in which the subject of sophism barely comes up. Namely because the books are concerned about journalism, not logical arguments. Why would a cognitive scientist who is writing a book about attention necessarily include a chapter about intelligence? As a rule, cognitive scientists tend to be concerned with general processes, not individual differences. The field can learn much from each other, but they are concerned about very different areas of investigation.

Antonio Damasio of the University of Southern California had a patient rendered emotionless by damage to his frontal lobes. When asked what day he could come back for an appointment, he stood there for nearly half an hour describing the pros and cons of different dates, but was incapable of making a decision. This is not the Spock-like brain engine suggested by the I.Q.

By all means, lets infer from one person with severe brain damage to the entire population. But if we want to play this game, I had a patient once who had just started Kindergarten, but could do addition, subtraction, multiplication and long division (the latter of which he deduced how to do pretty much on his own). He did not need a school to teach him any of this, so lets get rid of elementary schools for everyone. After all, if my patient could figure out long division, so should every other 5 year old.

Today, the research that dominates public conversation is not about raw brain power but about the strengths and consequences of specific processes. Daniel Schacter of Harvard writes about the vices that flow from the way memory works. Daniel Gilbert, also of Harvard, describes the mistakes people make in perceiving the future. If people at Harvard are moving beyond general intelligence, you know something big is happening.

Harvard never was a bastion for the study of general intelligence. It was the University of London. In fact, except for Yerkes, Herrnstein, and, to some extent, Pinker, I can't think of too many profs. there who contributed much to the study of general intelligence. And since when did Harvard's Psychology department become the measuring stick by which the importance of a research agenda was measured? I'm sure much of the work they do there furthers the general field of psychology, but what makes their research more special than, say, Berkeley, Stanford, UT-Austin, etc.?

The cultural consequence is that judging intelligence is less like measuring horsepower in an engine and more like watching ballet. Speed and strength are part of intelligence, and these things can be measured numerically, but the essence of the activity is found in the rhythm and grace and personality — traits that are the products of an idiosyncratic blend of emotions, experiences, motivations and inheritances.

This paragraph is quite confusing, perhaps due to the mixing of automotive and ballet metaphors. I think Brooks is trying to tell his readers he thinks personality is important for modern culture. I agree. And that has absolutely no bearing on the importance (or lack thereof) of cognitive ability in the same culture.

Recent brain research, rather than reducing everything to electrical impulses and quantifiable pulses, actually enhances our appreciation of human complexity and richness. While psychometrics offered the false allure of objective fact, the new science brings us back into contact with literature, history and the humanities, and, ultimately, to the uniqueness of the individual.

What? First, psychometrics (and specifically, the study of cognitive ability) has always held as paramount the uniqueness of the individual. Second, how has the study of cognitive ability NOT shown the complexity of humanity? Sir Cyril Burt, one of the pioneers in the field, was enamored with the complexity of students he encountered while a school psychologist in London. In fact, he was such an ardent supporter of psychological measurement so that he could begin to quantify, and, ultimately, understand and predict, this variability(see a bibliography here). More modern techniques, such as fMRIs, extend the work of psychometrics, in that they add to our ability to quantify individual variability at a much more precise level. However the two are quite complementary. From here:

Despite the sometimes contentious controversy about whether intelligence can or should be measured, the array of neuroimaging studies reviewed here demonstrates that scores on many psychometrically-based measures of intellectual ability have robust correlates in brain structure and function. Moreover, the consistencies demonstrated among studies further undermine claims that intelligence testing has no empirical basis.

In the world of academia, to have your ideas printed in a reputable journal, you have to go through the peer-review process. While there are arguments for the pros and cons of this process, at least it frequently squashes ill-informed, blatantly false propaganda from reaching the masses. After reading op-ed like this, one wishes the NYT had a similar mechanism in place.

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Sunday, April 29, 2007

Improved assessment of national IQ   posted by the @ 4/29/2007 11:49:00 PM

Heiner Rindermann, Relevance of education and intelligence at the national level for the economic welfare of people, Intelligence, In Press
Cognitive abilities are important for the economic and non-economic success of individuals and societies. For international analyses, the collection of IQ-measures from Lynn and Vanhanen was supplemented and meliorated by data from international student assessment studies (IEA-Reading, TIMSS, PISA, PIRLS). The cognitive level of a nation is highly correlated with its educational level (r = .78, N = 173). In international comparisons, it also shows a high correlation with gross national product (GNP, r = .63, N = 185). However, in cross-sectional studies, the causal relationship between intelligence and national wealth is difficult to determine. In longitudinal analyses with various samples of nations, education and cognitive abilities appear to be more important as developmental factors for GNP than economic freedom. Education and intelligence are also more relevant to economic welfare than vice versa, but at the national level the influence of economic wealth on cognitive development is still substantial.

Combining IQ scores with a variety of other assessments of average cognitive ability at the national level has a lot to recommend it, and I'm glad others have caught on. The conclusions are quite interesting:
The results reported here show that during the last third of the 20th century, education and cognitive abilities were more important for economic wealth than economic wealth was for education and cognitive abilities. This result is stable across the different national samples of education and ability and remains after adding additional factors like economic freedom. Intelligence is even more important for wealth than economic freedom (see also Weede, 2006)! Whereas the importance of intelligence for many personal life outcomes has been recognized for some time (Gottfredson, 2003 and Herrnstein and Murray, 1994), we should realize that intelligence is also an important determinant for the economic and social development of nations (for example the functioning of institutions in the systems of law, economics and politics). The present study shows that a high level of cognitive development can be an antecedent and likely cause for economic growth, but other macro-social outcomes (e.g., democracy, rule of law, national power or health) are likely to be influenced by education and intelligence as well (Rindermann, submitted for publication and Rindermann, submitted for publication). Certainly the positive influence of young people's schooling and intelligence on the level of economic freedom 30 years later (Fig. 4 and Fig. 5) deserves further investigation. Future theoretical and empirical research has to analyze the causal mechanism underlying the effects of ability on development of societies in a more detailed manner. For example, there is a positive relationship with low government spending ratio (r = .47 and rp = .24). Abilities seem to enable a more liberal economic constitution and thriftiness of state interventions. Conversely, a population with low education and intelligence seems to necessitate more state intervention, which tends to widen the influence of powerful special-interest groups.

So higher IQ populations tend to be more libertarian?

A re-colored version of Figure 1 -- a world map -- is below the fold.

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Sunday, April 22, 2007

Validity of national skin color-IQ   posted by the @ 4/22/2007 10:36:00 AM

We previously reported that a measure of school achievement built from national test scores has a nearly perfect correlation with national IQ (at least in the range of scores tested). Subsequently, Lynn et al. (in press) published a very similar analysis:
This paper examines the relationship of the national IQs reported by Lynn & Vanhanen (2002, 2006) to national achievement in mathematics and science among 8th graders in 67 countries. The correlation between the two is 0.92 and is interpreted as establishing the validity of the national IQs. The correlation is so high that national IQs and educational achievement appear to be measures of the same construct. National differences in educational achievement are greater than differences in IQ, suggesting an amplifier effect such that national differences in IQs amplify differences in educational achievement. Controlling for national differences in IQ, slight inverse relationships of educational achievement are observed with political freedom, subjective well-being, income inequality, and GDP. However, public expenditure on education (as % of GDP) was not a significant predictor of differences in educational achievement.

The IQ's Corner blog has an interesting note about forthcoming commentary.

On a related note, recall that Templer & Arikawa (2006) reported a near perfect environmental correlation between national skin color and national IQ for old-world countries. An unfortunately confused commentary by Hunt & Sternberg accompanied the publication. They wrote: "We argue that the report by Templer and Arikawa contains misleading conclusions and is based upon faulty collection and analysis of data. The report fails to hold up for quality of data, statistical analysis, and the logic of science." The criticisms by Hunt & Sternberg are based largely on a misreading of Templer & Arikawa's methods, particularly the method for deriving national skin color values.

A paper published in 2000 by Jablonski & Chaplin ("The evolution of human skin coloration") can more directly address these criticisms. Jablonski & Chaplin published a table of skin color reflectance values from many old world populations (Table 6, also see the appendix). I very crudely averaged values from the same country to make a new measure of national skin color. This measure of national skin color correlates with the skin color index of Templer & Arikawa at r=-.91 (the negative is not important here). The reflectance measure of skin color correlates with national IQ at r=.87. The school achievement measure of Lynn et al. correlates r=-.79 with the skin color index of Templer & Arikawa and r=.75 with the skin color reflectance values crudely averaged from Jablonski & Chaplin. Thus, the skin color values derived by Templer & Arikawa are well validated by an external data source and the national IQ-skin color relationship is found to be robust across two measures of national IQ and two measures of national skin color.

Note that there are substantially more missing values in the school achievement and skin reflectance data sets (no imputation of missing values) with missing values skewed towards lower values of national IQ/school achievement and darker skin colors. Also note that the blind averaging use on the skin reflectance data most likely attenuates the correlations.

Templer & Arikawa had two abstracts at the 2006 ISIR conference, which provide additional support for the validity of the measures and their relationships:


Correlations of Skin Color and Continent with IQ
Donald I. Templer & Hiroko Arikawa

The present study determined (1) the correlations between skin color and IQ across the countries of three different continents; and (2) the correlations of both skin color and continent in the three pair combinations with the three continents. The product-moment correlations between IQ and skin color were -.86 across the 48 African countries, -.55 across the 48 Asian countries, and -.63 across the European countries. When the 96 countries of Africa and Asia were combined skin color correlated -.86 and continent correlated .75 with IQ. The respective correlations were -.97 and .89 across the 81 countries of Asia and Europe, and -.71 and .54 across the 81 countries of Europe and Asia. In multiple regression continent yielded minimal increment to skin color in predicting IQ. In an earlier study (Templer & Arikawa, 2006a) skin color correlated more highly with IQ than racial category, but racial category yielded greater increments in multiple regression than did continent in the present study. The present findings, combined with previous research relating skin color and IQ (Templer & Arikawa, 2006a; 2006b), indicate that skin color is a robust correlate of IQ in an international perspective.

Empirical Support for Rushton's K Differential Theory
Donald I. Templer & Hiroko Arikawa

The purpose of the present study was to empirically substantiate Rushton's Differential K Theory that purports that groups of persons with K (in contrast to r) characteristics have a life history and reproductive strategy that includes higher intelligence, less reproduction, less sexual activity, better care of offspring, lower birth rates, greater life expectancy, better impulse control, and greater social organization. The present research intercorrelated national mean IQ, infant mortality, HIV/AIDS rates, birth rates, prevalence rates, and life expectancy in 129 countries in Africa, Asia and Europe. All of the correlations were substantial and in the expected direction. Also supportive of Rushton's theory is that there was only one factor which accounted for 75% of the variance and was labeled "K-r continuum." All five variables were correlated with an economic variable (per capita income) and a biological variable (skin color, which correlated highly with intelligence in previous research). Skin color correlated more highly with all five variables than per capita income so as to support the contention of Rushton that this continuum is biologically based. Factor analysis with all seven variables yielded one factor that accounted for 73% of the variance.

Jason Malloy adds: Templer & Arikawa's research follows Lynn and Rushton in arguing that cold temperatures were a significant force in the evolution of human race differences in intelligence. I have stated some problems I find with this hypothesis here, although it is also largely consistent with the geographic distribution of global populations by IQ. A recent analysis by blogger Audacious Epigone adds yet another revealing data point to this association.

Latitude (and hence colder climate) is associated with IQ not only cross-nationally (.67) but within the US as well. AE found a correlation of .70 between his measure of state IQ and the latitude of the most populous city in each of the 50 states. Furthermore intelligence is associated with latitude equally for both US whites and blacks (.52 and .51).

It's not immediately apparent if and how this association is genetic or environmental. Either way it seems fair to seriously consider that global warming will provide yet another detrimental negative pressure on the intelligence of human populations in the coming decades.

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Wednesday, April 18, 2007

Genetics and the Flynn effect   posted by the @ 4/18/2007 07:47:00 PM

Follow up to IQ, height & Crooked Timber: John Quiggin @ Crooked Timber wrote "I'd be interested to read a GNXP view of the main developments in recent decades, taking account of the Flynn effect." I don't know that a "GNXP view" exists on this subject aside from what appears to be the scholarly consensus where such a consensus exists. However, as a down payment on a response, I've gathered several sources which should help to inform the interested reader about modern views on the genetics of IQ and the Flynn effect.

For a general background on IQ and intelligence, two publications in response to The Bell Curve:
* "Intelligence: Knowns and Unknowns", the APA task force report (1995)
* "Mainstream Science on Intelligence", signed by 52 professors (1994)

For a quick technical review of the genetics of g, see the review by Plomin (2003), which I pasted below the fold. (Lest you think there's nothing new, note the distribution of publication dates among the references.)

For a bleeding-edge discussion of the Flynn effect, I can recommend two sources. A draft of a new book by Flynn and a book review by Lynn (pasted below the fold).

Regulars may want to begin by reading below the fold.

Guest Editorial
Genetics, genes, genomics and g
Robert Plomin1

1Social, Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, London SE5 8AF, UK. Email:

Molecular Psychiatry (2003) 8, 1-5. doi:10.1038/

This issue includes three papers1,2,3 on a topic of increasing interest to molecular psychiatrists: the genetics of intelligence. There was also a related article in a previous issue of Molecular Psychiatry.4 These four papers represent the range of research on genetics (quantitative genetic twin studies), genes (molecular genetic attempts to identify genes) and genomics (understanding the function of genes). The goal of this editorial is to put these papers in perspective.

Intelligence is the most complex¾and most controversial¾of all complex traits. So why study the genetics of such a complex and controversial trait? The word 'intelligence' has so many connotations that the symbol 'g' was proposed nearly a century ago to denote the operational definition of intelligence as a 'general cognitive ability' representing the substantial covariance among diverse tests of cognitive abilities such as abstract reasoning, spatial, verbal and memory abilities.5 In a meta-analysis of 322 studies, the average correlation among such diverse tests is about 0.306 and a general factor (first unrotated principal component) typically accounts for about 40% of the tests' total variance.7 As discussed below, multivariate genetic analysis shows that the genetic overlap among cognitive tests is twice as great as the phenotypic overlap, suggesting that g is where the genetic action is. Although g is not the whole story, trying to tell the story of cognitive abilities without g loses the plot entirely.

This strong genetic g factor running through diverse cognitive processes has important implications for genetic research in neuroscience since g is molar and flies in the face of the widespread assumption in cognitive neuroscience that the brain functions in a modular manner.8 In addition, the long-term stability of g after childhood is greater than for any other behavioral trait,9 it predicts important social outcomes such as educational and occupational levels far better than any other trait,10 and it is a key factor in cognitive aging.11 g is specifically relevant to molecular psychiatry because, as discussed below, mild mental retardation appears to be the low extreme of the normal distribution of g. Moreover, at least 200 single-gene disorders include mental retardation among their symptoms.12

Quantitative genetics

Quantitative genetic research¾twin and adoption studies¾estimates the net effect of genetic variation on phenotypic variation regardless of the number of genes involved or the complexity of their interactions. Such research charts the course for molecular genetic studies by identifying the most heritable components and constellations of phenotypes. The first twin and adoption studies were conducted in the 1920s on g and suggested substantial genetic influence.13,14,15 Since then, with the exception of personality assessed by self-report questionnaires, more research has addressed the genetics of g than any other human characteristic. Dozens of studies including more than 10 000 twin pairs and hundreds of adoptive families as well as more than 8000 parent-offspring pairs and 25 000 sibling pairs consistently indicate substantial heritability.16 Heritability estimates vary from 40 to 80% but meta-analyses based on the entire body of data yield estimates of about 50%,17,18 with increasing heritability from infancy (20%) to childhood (40%) to adulthood (60%).19 Most of the genetic variance for g is additive, which facilitates attempts to identify genes responsible for its heritability.20

Since the substantial heritability of g is better documented than for any other biological or behavioral dimension or disorder, quantitative genetic research has moved beyond heritability to ask more refined questions about development, about the interface between nature and nurture, and about multivariate issues.21 A finding of great significance for molecular psychiatry and neuroscience has emerged from multivariate genetic research that analyzes the covariance among cognitive tests rather than the variance of each test considered separately.20 As noted earlier, the average phenotypic correlation among diverse cognitive tests is about 0.30. In contrast, multivariate genetic research indicates that genetic correlations among such tests are at least 0.80 on average.22 (A genetic correlation indexes the extent to which genetic effects on one trait correlate with genetic effects on another trait independent of the heritability of the two traits.) The extremely high genetic correlation among diverse cognitive tests means that genes associated with one cognitive ability are highly likely to be associated with all other cognitive abilities. This evidence for 'genetic g' means that g is an excellent target for molecular genetic research in the cognitive domain.

It should be noted that genetic g does not necessarily imply that there is a single fundamental brain process that permeates all other brain processing, such as a 'speedy brain',8 neural plasticity,23 or the quality and quantity of neurons.24 It has been proposed that g exists in the brain in the sense that diverse brain processes are genetically correlated.25 For example, gray and white matter densities in diverse brain regions are highly heritable, substantially intercorrelated across brain regions, and correlated genetically with g.26,27

One of the papers in this issue provides a good example and description of multivariate genetic analysis.3 Rather than analyzing the covariance between cognitive tests, the study investigated the genetic and environmental origins of the covariance between normal variation in behavior problems and g in children. For 376 pairs of twins from 6 to 17 years of age, nearly all of the modest phenotypic correlation (-0.19) between behavior problems and g could be accounted for by genetic covariation. Similar results were obtained in another study of 4000 pairs of young twins assessed at 2, 3 and 4 years; the large sample made it possible to show that phenotypic and genetic links may be stronger at the extremes of behavior problems and cognitive problems.28

Another multivariate genetic finding of great importance concerns genetic links between common disorders and dimensions of normal variation. This research suggests that common disorders (but not rare disorders) are merely the quantitative extreme of the same genetic and environmental influences that operate throughout the normal distribution. For example, a sibling study of mental retardation found that the average IQ of siblings of severely retarded probands was normal, 103, which implies that severe mental retardation shows no familial links with normal variation in g.29 This finding makes sense in relation to the rare single-gene12 and chromosomal causes30 of severe retardation that are not usually inherited because they occur spontaneously. In contrast, siblings of mildly retarded probands showed a substantially lower mean IQ score of 85.29 In other words, mild mental retardation but not severe retardation shows familial (presumably genetic) links with normal g variation. The first twin study of mild mental retardation confirms that mild mental retardation is strongly linked genetically to normal variation in g.31 This evidence for strong genetic links between disorders and dimensions¾evidence that is typical of common disorders such as hyperactivity, depression and alcoholism¾provides support for the quantitative trait locus approach to molecular genetics, discussed later.

Identifying genes

There is a lot of life left in the old workhorse of quantitative genetics, especially in investigating developmental, multivariate and environmental issues that go beyond merely estimating heritability. However, the most exciting direction for research on intelligence and cognition is to move beyond genetics to genes, that is, to identify some of the genes responsible for the substantial heritability of g and other cognitive abilities and disabilities. In contrast to the slow progress in identifying genes for schizophrenia and manic-depression, greater progress has been made in the cognitive domain, most notably the well-documented association between apolipoprotein E gene and dementia32 and a solid 6p21 linkage with reading disability that is beginning to be narrowed down in association studies.33

The quantitative trait locus (QTL) perspective has come to dominate molecular genetic research on complex quantitative traits such as g as well as common disorders such as dementia and reading disability. The QTL perspective is the molecular genetic extension of quantitative genetics whereby multiple genes are assumed to be responsible for heritability, implying that genetic variation is distributed quantitatively.34 For this reason, a QTL perspective on g naturally leads to molecular genetic research on normal variation, as is also the case for personality research.35 Two papers on molecular genetics in this issue are distinctive in that they focus on normal variation in g using large unselected samples.1,4 They report positive associations between normal variation in g and two candidate genes: Cathepsin D (CTSD; 4) and cholinergic muscarinic 2 receptor (CHRM2; 1). The effect sizes are small (heritabilities of 3 and 1%, respectively) as expected for QTLs, but are easily detected as significant with the large sample sizes of these studies (767 and 828, respectively). Research on complex traits should be aiming to break the 1% QTL barrier, that is, 80% power to detect QTLs when they account for as little as 1% of the total variance (1% heritability), which requires an unselected sample of about 800 individuals when a single marker is studied (P = 0.05, two-tailed; 36).

The CTSD paper4 is especially interesting in relation to the extensive molecular genetic research on dementia, which will be the source of much more molecular genetic research on g. Beginning with individuals at least 50 years old, g was assessed during a 15-year period in order to investigate the cognitive decline indicative of dementia. As in other studies, initial g scores are correlated negatively with decline across the 15 years, supporting the brain reserve capacity theory of dementia, as explained in the paper. However, CTSD is not associated with cognitive decline, which confirms the results of several other studies that found no association between CTSD and dementia. The exciting finding is that CTSD is associated with g at the first test session. Longitudinal quantitative genetic research on g indicates that age-to-age stability is largely mediated genetically whereas change is largely environmental in origin.21 This suggests that the heritability of dementia defined as decline might be modest in contrast to the heritability of g. We do not yet know how heritable dementia is because only a few small twin studies have been reported and their results are mixed.37 What is needed is a multivariate genetic analysis of g and dementia in order to investigate the extent of their genetic overlap.

Other reports are beginning to emerge of candidate gene associations with g. Most notably, a functional polymorphism (VAL158MET) in the enzyme catechol O-methyltransferase (COMT) has been reported to be associated with g-related cognitive functioning in two studies.38,39 An association with g has also been reported for a gene involved in controlling homocystein/folate metabolism.40 Because research on dementia will be the immediate source of more molecular genetic research on g as in the CTSD study in this issue,4 it is worth noting that the apolipoprotein gene, which shows a strong association with dementia, shows no association with g in childhood41,42 or in adults.43

Despite the power of the two studies in this issue to detect QTL associations, replication will be crucial because the track record for replicating candidate gene associations is not good.44 This is of particular concern with studies using unselected samples because it is tempting to study many measures as well as many candidate genes thus increasing vulnerability to false positives. As a chastening confession to underline the need for replication, both papers cite our report of an association between IGF2R and g in two samples,45 but our new independent sample as large as the previous two samples combined has not replicated the association.46

Other molecular genetic issues relevant to these CTSD and CHRM2 reports are generic issues involved in any attempt to find QTLs for complex traits whether assessed as disorders or dimensions. One such issue is the use of functional polymorphisms. In the CTSD study,4 the candidate gene polymorphism is functional (C>T, Ala>Val); in the CHRM2 study,1 the single nucleotide polymorphism (SNP) is in the 3' untranslated region of the gene. The use of functional polymorphisms involves direct association that greatly increases power because it tests the hypothesis that the polymorphism is the QTL rather than relying on the marker being in linkage disequilibrium with the QTL associated with the trait (indirect association). Another advantage of using functional polymorphisms is that when associations are found, the usual house-to-house search for the culprit gene is circumvented, although it is always difficult to identify beyond reasonable doubt the QTL suspect from a line-up of genes in the neighborhood.

Another generic issue is that more systematic approaches to candidate genes are needed because any of the tens of thousands of genes expressed in the brain could be proposed as candidate genes for g.47 One early association study of g examined 100 candidate genes (not including CTSD or CHRM2) but found no more replicated associations than expected by chance, although the design only provided power to detect QTLs of about 2% heritability.48 A more systematic strategy is to investigate all polymorphisms in particular gene systems.49

Another strategy is to conduct genome-wide scans for association analogous to genome scans for linkage except that many thousands of markers are needed in the case of association. The first genome-wide search for association with g has been reported using 1842 simple sequence repeat (SSR) markers using DNA pooling and groups selected for high g and controls.50 Despite a highly conservative replication procedure designed to avoid false positives, two SSRs replicated cleanly in two independent case-control samples but neither SSR association was replicated in a transmission disequilibrium test using parent-offspring trios. Genomic control analyses showed that the failure to replicate using the parent-offspring trios was not due to population stratification. Since SSR markers are unlikely to be functional, they rely on indirect association for which power falls off quickly as a function of the linkage disequilibrium distance between the marker and the QTL.51,52 Using indirect association, tens or hundreds of thousands of markers are needed for genome scans in order to exclude QTLs of 1% heritability, although haplotype maps can reduce the required number of markers.53,54

Ultimately what is needed for genome-wide association scans is to genotype every functional polymorphism in the genome. As a step in this direction, we are currently using DNA pooling to conduct a genome-wide g scan of all brain-expressed nonsynonymous SNPs in coding regions that are currently available in public databases with allele frequencies greater than 10% in Caucasian samples.55 Polymorphisms in promoters and other gene regulatory coding regions seem even better candidates for QTLs but they are much more difficult to identify and to demonstrate their functionality. Moreover, coding DNA does not have a monopoly on QTLs¾noncoding RNA is likely to be a source of QTLs too,56 although determining functionality of polymorphisms in noncoding RNA will be even more difficult.

It remains to be seen whether increasing power using large samples and direct association will yield replicable QTLs. DNA pooling will be useful in this context because it costs no more to genotype 1000 individuals than 100 individuals.57 Pessimists can reasonably worry about the gloomy prospect that the culprit genes will never be caught because the heritability of g might be caused by many genes with miniscule heritabilities. Some might hope that such research is never successful because of the ethical issues that would be raised if genes for g were found.21 Interesting discussions of these issues are available specifically in relation to genes and g58 and more generally in relation to behavioral genetic research.59

Behavioral genomics

Quantitative genetics assesses the net effect of genes on behavior without knowing anything about which genes are involved. Molecular genetics identifies genes associated with behavior without knowing anything about the mechanisms responsible for the association. As we approach the postgenomic era in which the complete human genome sequence and all functional variations in the genome sequence are identified, the future of behavioral genetics is functional genomics, that is, understanding how genes affect behavior.60

Functional genomics usually refers to the bottom-up agenda of molecular biology such as gene expression profiling and proteomics. However, there are higher levels of analysis for understanding how genes function which need not wait until the bottom-up approach reaches them. At the other end of the continuum is the top-down approach that investigates the function of genes in relation to behavior of the whole organism. For example, the issues about multivariate relationships of heterogeneity and comorbidity, developmental change and continuity, and the interface between genes and environment can be addressed with much greater precision once genes are identified. The term behavioral genomics has been proposed to emphasize the value of this top-down level of analysis.61

Rodent models will be valuable for functional genomic research because of their ability to manipulate both genes and environment and the power they offer for investigating brain processes such as single cell recordings, micro-stimulation, targeted gene mutations, antisense DNA that disrupts gene transcription, and DNA expression. The value of rodent models rests with understanding genetically driven brain processes, not with phenotypic validity. For example, mouse models have made the greatest progress in understanding the psychopharmacogenetics of alcohol-related processes even though mice do not become drunk of their own volition.62 In this sense, although it sounds absurd, mouse models of reading disability will be valuable for understanding the brain processes underlying the genetics of reading disability. The ultimate test is whether the same genes affect the same brain processes in mouse and man.

In terms of rodent models of g, clearly there are major differences in brain and mind between the human species and other animals, most notably in the use of language and the highly developed prefrontal cortex in the human species. However, g in man does not depend on the use of language¾a strong g factor emerges from a battery of completely nonverbal tests.7 Moreover, low-level tasks¾for example, information-processing tasks assessed by reaction time¾contribute to g.63 Indeed, g can be used as a criterion to identify animal models of individual differences in cognitive processes. If g represents the way in which genetically driven components of the brain work together to solve problems, it would not be unreasonable to hypothesize that g exists in all animals.64 Although much less well documented than g in humans, increasing evidence exists for a g factor in mice across diverse tasks of learning, memory and problem solving.65 A large-scale integrative program of research called genes-to-cognition is under way that uses mouse models for functional genomic research in the cognitive domain.66

One of the papers in this issue serves as an example of the value of rodent models for functional research.2 The research brings together neurotransmitter assays, brain anatomy, a broad battery of behavioral measures, a development approach from infancy to adolescence to adulthood, and pharmacology in an experimental study in which epidermal growth factor (EGF) was administered to neonatal rats. Although a test of learning ability did not appear to be affected by the neonatal treatment, other abnormalities were observed in adults but not in adolescents such as sensorimotor gating, motor activity and social interaction in a pattern reminiscent of schizophrenic symptoms and which were ameliorated by clozapine. This research covers a wide range of functional approaches, but the missing link from a functional genomics perspective is genetics. Although transgenic studies indicate the important role of the EGF gene family on brain structures and monoamine pharmacology, there is as yet no evidence that polymorphisms in genes related to EGF are involved in schizophrenia or other cognitive disabilities or abilities. This program of research showing the importance of EGF is likely to stimulate genetic research using EGF candidate genes.

In our age of increasing specialization, the most exciting prospect for functional genomic research in the postgenomic era is that DNA will integrate research in the life sciences from cells to societies and that bottom-up approaches will meet top-down approaches in the brain. g is an excellent target for such integrative research because an exciting synergy will quickly emerge simply by connecting the dots of knowledge already available, for example, in gene targeting studies of learning and memory in mice, brain imaging studies of cognitive processes in the human species, and extensive quantitative genetic research.

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Book review
J.R. Flynn, What is intelligence? Beyond the Flynn Effect, Cambridge University Press (2007).
doi:10.1016/j.intell.2007.03.003 How to Cite or Link Using DOI (Opens New Window)
Copyright © 2007 Elsevier B.V. All rights reserved.

Richard Lynna, E-mail The Corresponding Author
a4 Longwood House, Bristol BS8 3TL, UK
Received 2 March 2007; accepted 13 March 2007. Available online 17 April 2007.

A warm welcome must be extended to this book in which the author discusses the issues raised by the Flynn Effect. There are two major problems. First, what are the factors responsible for the increase of intelligence that has been observed in a number of countries during the last 80 years or so? Second, why has this increase been so much greater in reasoning ability/fluid intelligence, as measured by the Wechsler similarities and non-verbal tests where it has averaged around 3.6 IQ points a decade, and the Progressive Matrices, where in some samples it has averaged around 7 IQ points a decade, than in tests that measure acquired knowledge/crystallized intelligence (vocabulary, information and arithmetic), where it has averaged only around 0.5 IQ points a decade.

Flynn's answer to the problem of the cause of the Flynn Effect is that increases in education have led the people thinking more scientifically and logically (“science has engendered a sea change … formal education played a proximate role”). He uses Piaget's concepts of concrete and formal thought processes to explicate this. Previous generations were as good as later generations at concrete thinking, but more recent generations have advanced to the formal stage where they analyse problems in terms of abstract concepts. But he does not mention that this theory has been disconfirmed by Fleiller, Jautz, and Kop (1989) who demonstrated that concrete thinking has improved at the same rate as formal thinking.

Flynn is by no means the first to attribute the Flynn Effect to improvements in education. Many others have done the same, including several of the early observers of the Flynn Effect such as Cattell (1973, p. 275): “the inter-generational changes … probably represent the unquestionably marked improvement in schooling”.

The theory that improvements in education can explain the Flynn Effect encounters two problems. The first is that the cognitive abilities that are learned in schools (arithmetic, information, vocabulary, and math, science and reading tested in the American NAEP) have shown very little increase; it is the cognitive skills that are not learned in schools that have shown the large increases. This is the opposite of what would be expected if better or more education has enhanced cognitive abilities. A second problem is that the Flynn Effect has been found in 4–6 year olds who have had very little education, and even in infants (e.g. Hanson, Smith, & Hume, 1985). This suggests that an important contributor to the Effect lies in improvements in pre-natal and early post-natal nutrition, as argued in detail in Lynn, 1990 and Lynn, 1998. It may be, however, that some of the large gains in fluid intelligence found in military conscripts are attributable to later cohorts having had more education than earlier.

Flynn attempts to refute the nutrition theory of the Flynn Effect by asserting that there is no evidence that nutrition has improved in the second half of the twentieth century. He asserts that there have been no increases in height (improvements in nutrition are indexed by increases in height) in the United States in children born after about 1952, although intelligence has continued to increase. Contrary to this contention (1) the data compiled by Komlos and Lauderdale (in press) show that height in the United States increased in those born from 1955 to 1975 (white men from 177.8 to 179.5; white women from 164.1 to 164.9); (2) height stabilised after 1975 and Flynn's own data show that intelligence gains decelerated after 1985 and turned negative in children from 1989 to 1995. In Europe also heights increased from 1960 to 1990 (Larnkjaer, Schroder et al., 2006); from around 1990 heights and intelligence have both stabilized in Denmark and Norway. The case for improvements in height running parallel with increases in intelligence, as predicted by the nutrition theory, is much stronger that Flynn allows.

Furthermore, the nutrition theory of the Flynn Effect explains why fluid intelligence has increased so much more than crystallized intelligence. Several studies have shown that sub-optimal nutrition impairs fluid intelligence more than crystallized intelligence. Hence as nutrition has improved over time, fluid intelligence has increased more. It has even been shown that the Wechsler subtests that are most impaired by sub-optimal nutrition and improve most with nutritional supplements are those for which the Flynn Effects have been the greatest (e.g. arithmetic, similarities and block design) (Botez, Botez, & Maag, 1984).

Flynn proposes that the effect of better education on the increase in intelligence is enhanced by the “individual multiplier” and the “social multiplier”. The concept of the “individual multiplier” is that the intelligent have a thirst for cognitive stimulation and this increases their intelligence. This again encounters the problem that the Flynn Effect is present in infants. The “social multiplier” posits “that other people are the most important feature of our cognitive development and that the mean IQ of our social environs is a potent influence on our own IQ”. If this were so, the IQs of adopted children should be associated with the IQs of their adoptive parents, and there should also be a strong correlation between the IQs of unrelated children reared in the same adoptive families. Both these predictions have been disconfirmed. Scarr and Weinberg's (1978) study found that the correlation between the IQs of adopted children aged 18 and the IQs of their adoptive parents was .14 (i.e. zero), while the correlation between the IQs of unrelated children reared in the same adoptive families was − .03. The effectively zero correlation between the IQs of unrelated children reared in the same adoptive families has been confirmed in a study of 52 pairs aged 13 (r = − .16) (Plomin, 1986, p. 237).

Although I have not been persuaded by Flynn's arguments on the causes of the Flynn Effect, and I could not find an answer to the question “What is Intelligence?” beyond what is already widely accepted, I found his book to contain many interesting ideas and observations and I recommend it in the confident expectation that many potential readers will find the same.

Botez, M. I., Botez, T., & Maag, U. (1984). The Wechsler subtests in
mind organic brain damage associated with folate deficiency.
Psychological Medicine, 14, 431−437.
Cattell, R. B. (1973). Abilities: Their structure, growth and action.
Boston: Houghton Mifflin.
Fleiller, A., Jautz, M., & Kop, J. -L. (1989). Les reponses au test
mosaique a quarante ans d'intervalle. Enfance, 42, 7−22.
Hanson, R., Smith, J. A., & Hume,W. (1985). Achievements of infants
on items of the Griffiths scales: 1980 compared with 1950. Child:
Care, Health and Development, 11, 91−104.
Komlos, J. and Lauderdale, B. E. (in press). The mysterious trend in
American heights in the 20 century. Annals of Human Biology.
Larnkjaer,A., Schroder, S.A., et al. (2006). Secular change in adult stature
has come to a halt in northern Europe and Italy. Acta Paediatrica, 95,
Lynn, R. (1990). The role of nutrition in secular increases of
intelligence. Personality and Individual Differences, 11, 273−285.
Lynn, R. (1998). In support of the nutrition theory. In U. Neisser (Ed.),
The rising curve: Long term gains in IQ and related matters
Washington, D.C.: American Psychological Association.
Plomin, R. (1986). Development, Genetics and Psychology. Hillsdale,
New Jersey: Lawrence Erlbaum.
Scarr, S., & Weinberg, R. A. (1978). The influence of family
background on intellectual attainment. American Sociological
Review, 43, 674−692.

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Wednesday, March 07, 2007

g: A precis   posted by Alex B. @ 3/07/2007 08:35:00 PM


The study of intelligence goes back many millennia, but, as such, it was usually defined as a nebulous construct and it fell more under the domain of philosophy than, say, science. Enter Francis Galton. With his Darwinian ancestry and precocious nature, Galton became fascinated by human variability and spent most of his life pursuing various distributaries from this river (e.g., dactylography, anthropology). Most important to the field of individual differences, was his study of the nature of human cognitive abilities. That is, he was one the first (if not the first) to make a systematic study of human variation in cognitive abilities. In doing so, he developed a cadre of "brass instruments" to measure various aspects of basic human abilities, which, to him, were all related to this underlying, general cognitive ability.

People lay too much stress on apparent specialities, thinking over-rashly that, because a man is devoted to some particular pursuit, he could not possibly have succeeded in anything else. They might as well say that, because a youth had fallen desperately in love with a brunette, he could not possibly have fallen in love with a blonde. He may or may not have more natural liking for the former type of beauty than the latter, but it is more probable a not the affair was mainly or wholly due to a general amorousness of disposition (Galton, 1869, p. 6)

While in his time, his elementary task/sensory discrimination data did not support his hypothesis that they were related to other "common sense" criteria such as education and occupation, later, when Fisherian analysis were applied, Galton was proved to be correct--that is, there were group differences in average scores (Johnson, McClearn, Yuen, Nagoshi, Ahern, & Cole, 1985).

In addition to his interest in elementary tasks, Galton was also interested in more traditional psychometrics. In fact, he convinced the British Association for the Advancement of Science to conduct a survey of mental capacities throughout British schools. William McDougal was appointed to head this up and his student, Sir Cyril Burt, got his initial taste of the field of applied psychometrics from this project (Burt, 1972).


As important as Galton was in developing the underpinnings to modern intelligence research, he was not able to conceive of a way to measure general cognitive ability. Instead, this task was accomplished by engineer-turned-psychologist Charles Spearman (1904). Spearman was able to accomplish this based on two of his mathematical "inventions:" Classical Test Theory (CTT) and Factor Analysis (FA). Neither one of these is particularly easy to explicate via BLOG form, but the bottom line is: (a) CTT allowed for one to find the correlation between two variables, disattenuated by (random) measurement error; and (b) FA allowed for one to extract commonalities in groups of correlations. That is: If variable A, variable B, and variable C are all highly correlated with each other, then they likely have something in common. FA allows one to "get at" the thing (loosely speaking) that they have in common.

For example, if we have the following correlations for A, B, and C, then the last row has the correlations between the variable and the common factor (i.e., factor loadings)


B 0.7

C 0.8 0.75

g loadings

0.864 0.810 0.926

Spearman called that underlying factor general intelligence, and that is still what is meant today when the moniker Spearman's g is used, even though the factor analytic techniques have greatly advanced since Spearman's day.

After Spearman's developments, there was a period of controversy as to (a) whether g existed, (b) if it existed, was it the only factor that could be extracted, and (c) if other factors could be extracted, could g be extracted at the same time? The details of this (needless?) argumentation need not concern this post (for a succinct summary, see Carroll, 1993), with the eventual conclusion being that, given a sufficient diversity of tests, g could be extracted, but other, more primary factors (e.g., Working memory, Long-term memory, Quantitative knowledge) could also be extracted. A picture is given below:

Spearman's g is at the apex, the more primary ability are the circles below, and the tests from which the factors were extracted are represented by the boxes [the circles are used as that is the common way of representing latent variables; likewise, boxes are common way of representing manifest variables]


Around the same time Spearman and his London School contemporaries were doing their work in g theory, the field of intelligence testing was arising--due in large part to Binet and Simon's work in France, Goddard and Terman's work in the US, and Burt's work in the UK. Today, intelligence is often used synonymously with IQ scores, which, outside of differential psychology and psychometrics, is also used synonymously with Spearman's g. They are similar concepts, undoubtedly, but they need distinction.

Intelligence. A nebulous construct at best, it had eluded a century of definition, and, in Arthur Jensen's (1998) own words, "psychologists are incapable of reaching a consensus on its definition" (p. 48) As it cannot be defined, we will not use it any further.

Spearman's g. It is the primary factor extracted from the correlation matrix of a group of variables that all measure some aspect of cognitive ability. That is, it is the part of the covariance that all the variables have in common with each other.

Intelligence Quotient (IQ). An imperfect measure of Spearman's g. That is, in modern IQ tests, IQ scores are the weighted average of performance all the subtests involved. This is sometimes referred to as "intelligence in general" as opposed to "general intelligence" (i.e., Spearman's g), but for general purposes an IQ score can be thought of as rough measure of Spearman's' g, plus some (random) measurement error. Usually these scores are scaled such that most people will have a score between 90 and 110; mental retardation is a serious consideration for people with IQs below 70, as giftedness is a serious consideration for people with IQs greater that 120.

Why All the Fuss?

As presented, one may easily come to the conclusion of, so what? IQ/g sounds like it is another entry in the massive world of psychobabble, along with mental bonds, closure, and life coaching. The fuss is this:

No other variable in the history of psychology has (strongly) predicted such a wide variety of life outcomes.

  • Educational Outcomes (Deary, Strand, Smith, & Fernandes, 2007; Kuncel, Hezlett, & Ones, 2004)

  • Physical Health/Accidents (Gottfredson, 2004; Gottfredson & Deary, 2004).

  • Reaction Time to Cognitive Tasks (Jensen, 2006)

  • Occupation Status (Gottfredson, 1986; Herrnstein & Murray, 1994)

  • Job Success (Schmidt & Hunter, 1998, 2004)

  • Crime (Ellis & Walsh, 2003).

  • Race Differences (Lynn, 2005; Rushton & Jensen, 2005)

  • Sex Differences (Lynn & Irwing, 2004)

  • GDP (Lynn & Vanhanen, 2006)

And this is to just name a few.

If I were to stop here, one might be under the impression that g/IQ are important, but (a) there are other forms of "intelligence"; and (b) that IQ is just a product of the environment and can be raised (almost) at will.

Multiple Intelligences

The theory of Multiple Intelligences (MI) stems from Howard Gardner who (now) posits that g exists, but so do other forms of independent "intelligences" that (equally) predict life success. His other forms are things like interpersonal skills, intrapersonal knowledge, and kinesthetic ability. Since in the 25 years since MI has been around, Gardner has refused to test his hypotheses, it really is not even worth mentioning anymore. Thus, I won't (for some empirical work showing why Gardner is, well, wrong, see Visser, Ashton, & Verson, 2006, under review).

Triarchic Theory of Intelligence

This works stem from the work of Robert Sternberg, and his theory of cognitive ability that, similar to Gardner, posits that g exists, but that there are independent cognitive entities that are useful in life, such as practical intelligence; he even goes so far as to say that these independent entities are better predictors of life outcomes than g. Unfortunately, like Gardner, he doesn't readily submit his theories to much empiricism, and his claims, to date, are unsubstantiated (for an excellent critique, see Gottfredson, 2003).

Stability and Raising g/IQ

If one is under the impression that the environment can have massive influence on g, the logical product of that belief is that massive government programs should be able to raise cognitive abilities. In short, they do not. They produce short-term gains, but the gains do not last long (see, for example, Spitz, 1986, 1992). This is not to say that other things, such as nutritional supplementation, might not be able to increase cognitive performance, but massive environmental programs, at least as implemented in the past 50 years, have not. Moreover, IQ scores measured when one is 10ish are consistent, very consistent, with IQ scores measured almost 70 years later on the same individuals (Deary, Whalley, Lemmon, Crawford & Starr, 2000). That is, despite a life's worth of diversity of experience, your IQ when you are in Middle School is very predictive of your IQ when you retire.

Take Home Message

g is ubiquitous in cognitive tasks, it is stable across time in individuals, and no other variable in the history of psychology has been able to predict so many life outcomes, so well.


Burt, C. L. (1972). Inheritance of general intelligence. American Psychologist, 27, 175–190

Carroll, J.B. (1993) Human cognitive abilities. Cambridge University Press.

Deary, I. J., Whalley, L. J., Lemmon, H., Crawford, J. R., & Starr, J. M. (2000). The stability of individual differences in mental ability from childhood to old age: Follow-up of the 1932 Scottish Mental Survey. Intelligence, 28, 49-55.

Deary, I. J., Strand, S., Smith, P., & Fernandes, C. (2007). Intelligence and educational achievement. Intelligence, 35, 13-21.

Ellis, L., & Walsh, A. (2003). Crime, delinquency, and intelligence: A review of the worldwide literature. In H. Nyborg (Ed.), The scientific study of general intelligence: Tribute to Arthur R. Jensen (pp. 343-365). New York: Pergamon.

Galton, F. (1869). Hereditary genius: An inquiry into its laws and consequences. London: MacMillan

Gottfredson, L. S. (Ed.) (1986). The g factor in employment. Journal of Vocational Behavior, 29 (3). (Special Issue)

Gottfredson, L. S. (2003). Dissecting practical intelligence theory: Its claims and evidence. Intelligence, 31(4), 343-397.

Gottfredson, L. S. (2004). Intelligence: Is it the epidemiologists' elusive "fundamental cause" of social class inequalities in health? Journal of Personality and Social Psychology, 86, 174-199.

Gottfredson, L., & Deary, I. J. (2004). Intelligence predicts health and longevity: but why? Current Directions in Psychological Science, 13, 1-4.

Herrnstein, R. & Murray (1994) The Bell Curve: Intelligence and class structure in american life. New York: Free Pres

Jensen, A. R. (1998). The g factor. Westport, CT: Praeger.

Jensen, A.R. (2006). Clocking the mind: Mental chronometry and individual differences. Oxford: Elsevier.

Johnson, R. C., McClearn, G. E., Yuen, S., Nagoshi, C. T., Ahern, F. M., & Cole, R. E. (1985). Galton’s data a century later. American Psychologist, 40, 875–892

Kuncel, N. R., Hezlett, S. A., & Ones, D. S. (2004). Academic performance, career potential, creativity, and job performance: Can one construct predict them all? Journal of Personality and Social Psychology, 86, 148-161.

Lynn R. (2005). Race differences in intelligence: An evolutionary analysis. Augusta, GA: Washington Summit.

Lynn, R. and Irwing, P. (2004) Sex differences on the Progressive Matrices: a meta-analysis. Intelligence, 32, 481-498.

Lynn, R. & Vanhanen, T. (2006). IQ and global inequality.
Atlanta, GA: Washington Summit.

Rushton, J. P., & Jensen, A. R. (2005). Thirty years of research on race differences in cognitive ability. Psychology, Public Policy, and Law, 11, 235-294.

Schmidt, F. L., & Hunter, J. (1998). The validity and utility of selection methods in personnel psychology practical and theoretical implications of 85 years of research findings. Psychological Bulletin, 124, 262-274.

Schmidt, F. L., & Hunter, J. (2004). General mental ability in the world of work: Occupational attainment and job performance. Journal of Personality and Social Psychology, 86, 162-173.

Spearman, C. E. (1904). “General intelligence”: Objectively defined and measured. American Journal of Psychology, 15, 201–292.

Spitz, H. H. (1986). The raising of intelligence: A selected history of attempts to raise retarded intelligence. Lawrence Erlbaum Associates.

Spitz, H. H. (1992). Does the Carolina Abecedarian Early Intervention Project prevent sociocultural mental retardation? Intelligence, 16, 225-237

Visser, B.A., Ashton, M.C., & Verson, P.A. (under review). Self-estimated general and "multiple" intelligence(s): Accuracy, sex differences, and personality.

Visser, B.A., Ashton, M.C., & Verson, P.A. (2006). Beyond g: putting Multiple Intelligences theory to the test. Intelligence, 34, 487-502.

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Tuesday, March 06, 2007

Validity of national IQ   posted by the @ 3/06/2007 08:11:00 PM

In IQ and the Wealth of Nations (2002; IQatWoN) and IQ and Global Inequality (2006; IQGI), Richard Lynn and Tatu Vanhanen (L&V) present measurements and estimates of average national IQ (national IQ). In IQatWoN, L&V argue that national IQ predicts per-capita GDP (sup Fig 1). In IQGI, L&V argue that national IQ predicts quality of life measures (sup Fig 2). A common criticism of both works is to question the validity of national IQ. This criticism is motivated in part by the very low scores reported for countries in sub-Saharan African. A look at the distribution of national IQ is instructive (Fig 1).

Figure 1. The distribution of national IQ values (192 countries from IQGI).

L&V address the issue of validity by comparison of national IQ values with international test scores in math and science such as TIMSS and PISA. IQGI presents data from 10 different tests, with different scoring scales, in the form of 3 tables. To get a better grasp on the question of the validity of national IQ, I reanalyzed the test score data from IQGI. For better comparison, I renormalized each set of test scores relative to the maximum test score for each assessment. This is an imperfect but sufficient technique. An unweighted average of the available test score data was used to calculate a composite national test score for the set of 62 countries for which at least 1 test score was available (Fig 2).

Figure 2. The association between national test scores and national IQ for 62 nations.

National test scores are available for a limited range of national IQ scores, with few test scores available for countries with national IQs below the mid 80s. I interpret this to mean that for countries with national IQs below ~85, the test score data is insufficient to inform the question of validity. However, for the available scores (i.e., mostly above ~85), the relationship between national IQ and national test scores is very strong (see Sup Table 1).

The validity of sub-80 national IQs is addressed in part by the finding that IQ correlates with GDP and QHC (Sup Figs 1,2) throughout the observed range of IQ.

Update: Although there are only four values, the sub-80 national IQs are outliers, all with positive residuals. While this is hardly informative, it trends in the direction of casting doubt on the validity of sub-80 national IQ values.

Supplemental Figure 1. National IQ correlates with GDP per-capita (192 countries from IQGI).

Supplemental Figure 2. National IQ correlates with a L&V's quality-of-life index (QHC; 192 countries from IQGI).

Supplemental Table 1. Correlation matrix for national IQ (IQ), national test score (Test), L&V's quality of life index (QHC) and log per-capita GDP (logGPD) for 62 countries.
r QHC logGDP IQ Test
QHC 1 0.898936 0.7933265 0.7803476
logGDP 0.898936 1 0.760138 0.7565582
IQ 0.7933265 0.760138 1 0.9008035
Test 0.7803476 0.7565582 0.9008035 1

Related papers:
* Earl Hunt and Werner Wittmann, National intelligence and national prosperity, Intelligence, In Press --examines PISA scores
* Richard Lynn and Jaan Mikk, National differences in intelligence and educational attainment, Intelligence, Volume 35, Issue 2, March-April 2007, Pages 115-121. --examines TIMSS scores

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Tuesday, February 27, 2007

CHRM2 and Intelligence   posted by Fly @ 2/27/2007 09:35:00 AM

CHRM2 Gene Variants Associated with Intelligence

"Some of the participants in the study also took the Wechsler Adult
Intelligence Scale-Revised, a traditional IQ test. In all, members of 200
families, including more than 2,150 individuals, took the Wechsler test, and those results were matched to differences in individuals' DNA.

By comparing individual differences embedded in DNA, the team zeroed in on CHRM2, the neuronal receptor gene on chromosome 7. The CHRM2 gene activates multitude of signaling pathways in the brain involved in learning, memory and other higher brain functions. The research team doesn't yet understand how the gene exerts its effects on intelligence."
Dick's team is not the first to notice a link between intelligence and the CHRM2 gene. In 2003, a group in Minnesota looked at a single marker in the gene and noted that the variation was related to an increase in IQ. A more recent Dutch study looked at three regions of DNA along the gene and also noticed influences on intelligence. In this new study, however, researchers tested multiple genetic markers throughout the gene.

"If we look at a single marker, a DNA variation might influence IQ scores between two and four points, depending on which variant a person carries," Dick explains. "We did that all up and down the gene and found that the variations had cumulative effects, so that if one person had all of the 'good' variations and another all of the 'bad' variations, the difference in IQ might be 15 to 20 points. Unfortunately, the numbers of people at those extremes were so small that the finding isn't statistically significant, but the point is we saw fairly substantial differences in our sample when we combined information across multiple regions of the gene."

Dick says the next step is to look at the gene and its numerous variants to learn what is going on biologically that might affect cognitive performance. Presently, she says it's too early to predict how small changes in the gene might be influencing communication in the brain to affect intelligence, and she says it's nearly certain CHRM2 is not the only gene involved.

Prior GNXP references to CHRM2:

Thompson and Gray: Neuroscience, genes, and IQ

More red meat

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Thursday, February 22, 2007

Race IQ and SES   posted by the @ 2/22/2007 12:31:00 AM

Jensen (1998) makes a point that is worth repeating:
The pernicious notion that IQ discriminates mainly along racial lines, however, is utterly false.

Jensen presents what should be a predictable pattern for a highly heritable trait:
Source % of Variance Average IQ Difference
Between races (within social classes)
14 30 12
Between social classes (within races)
8 6
Interaction of race and social class
Between families (within race and social class)
26 65 9
Within families (siblings)
39 11
Measurement error
5 4
100 17

This can be demonstrated most clearly in terms of a statistical method known as the analysis of variance. Table 11.1 shows this kind of analysis for IQ data obtained from equal-sized random samples of black and white children in California schools. Their parents' social class (based on education and occupation) was rated on a ten-point scale. In the first column in Table 11.1 the total variance of the entire data set is of course 100 percent and the percentage of total variance attributable to each of the sources6 is then listed in the first column. We see that only 30 percent of the total variance is associated with differences between race and social class, whereas 65 percent of the true-score variance is completely unrelated to IQ differences between the races and social classes, and exists entirely within each racial and social class group. The single largest source of IQ variance in the whole population exists within families, that is, between full siblings reared together in the same family. The second largest source of variance exists between families of the same race and the same social class. The last column of Table 11.1 shows what happens when each of the variances in the first column is transformed into the average IQ difference among members of the given classification. For example, the average difference between blacks and whites of the same social class is 12 IQ points. The average difference between full siblings (reared together) is 11 IQ points. Measurement error (i.e., the average difference between the same person tested on two occasions) is 4 IQ points. (By comparison, the average difference between persons picked at random from the total population is 17 IQ points.) Persons of different social class but of the same race differ, on average, only 6 points, more or less, depending on how far apart they are on the scale of socioeconomic status (SES). What is termed the interaction of race and social class (8 percent of the variance) results from the unequal IQ differences between blacks and whites across the Spectrum of SES, as shown in Figure 11.2. This interaction is a general finding in other studies as well. Typically, IQ in the black population is not as differentiated by SES as in the white population, and the size of the mean W-B difference increases with the level of SES.

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Sunday, February 11, 2007

Horizontal g   posted by Alex B. @ 2/11/2007 01:54:00 AM

Wherever the abilities involved are sufficiently distinct--and that is in the great majority of cases--our tetrad equation is satisfied with surprising exactitude, so that here each ability must be divisible into g and s. The letter g becomes, in this manner, a name for the factor--whatever it may be--that is common to mental tests of such a description. This is the very definition of g. (Spearman, 2005, p. 161)

General intelligence (g) has been one of the most, if not the most, aggressively studied constructs in psychology. Type the search string "general intelligence" in PsycInfo and you will return over 2000 entries, and a similar search in Pubmed pulls up over 400. If you broaden the term to just "intelligence", the respective number of entries are 65405 and 37166. While not all of the results focus on g , (e.g., AI, "social intelligence"), a large portion of them do, and the prospect of meandering your way through can be intimidating. Fortunately, the overall literature is consistent and, at least for me, highly engaging.

The study of g can be bifurcated into two distinct areas: vertical and horizontal g . Vertical g is the domain that studies g's biological relationships. It is the area that is going to eventually assimilate enough data and literature to elucidate, unquestionably, the causal mechanisms of g . From this field of study, we know that g is correlated with a variety of neural mechanisms, such at glucose metabolism (Haier, 2003), cortical development (Shaw et al., 2006), and biochemical activity (Jung et al., 2005). We know that g is highly heritable, both when measured psychometrically (Plomin & Spinath, 2002) or chronometrically (Beaujean, 2005). We know that g decreases with inbreeding (Jensen, 1983) and increases with hybrid vigor (Nagoshi & Johnson, 1986). As genome scanning becomingmore popular, we are now even beginning to see some specific genes that are implicated g.

As interesting as vertical g is, however, this entry is going to instead focus in the horizontal aspects of g . That is, how does g play out into "everyday life." Specifically, we will look three different, although related, areas: education, occupation, and general life outcomes. The reasons for doing so are twofold: (a) the more the science of horizontal g is positively promulgated, then, perhaps, the more likely people are to support the needed research into vertical g and (b) even though this area of research has been around for over a century (e.g., Galton, 1869), there are still new, important findings.

Before delving into horizontal g, however, it would behoove us to delineate a mechanism by which g could influence education, occupation, and general life outcomes.For our purposes, that mechanism is information processing. Generally defined, information processing is the pathway and mechanisms by which stimuli are perceived, attended to, retrieved, and/or used to solve problems and/or cope with exigencies in the environment (Jensen, 1998a). The cognitive psychology literature is chalked full of the nuances of the various information-processing theorists, the specifics are which cannot be delineated here (an easy-to-read intro: Ormrod, 2004). Yet, within all these theories lies the idea that people respond to stimuli in a way that involves many mechanisms (e.g., sensory register, primary memory)and a variety of neurological regions (e.g., hippocampus, amygdala, mammillary bodies). The consequence? There is ample room for individual differences in the speed and efficiency in which information is processed.

From another perspective (e.g., Kline, 1998), information is processed in irreducibly small pieces (often called bits) and the time it takes to process those bits is the BIP, the Basic period of Information Processing. Now, the time it takes Johnny to process the fact that the only integer between 2 and 4 is 3 is going to be different than the time it takes Jane. Multiply those differences by the number of people processing the fact, and voila! individual differences.

Educational Outcomes

This is probably the area most replete with data and, unsurprisingly, the g-educational achievement relationship is strong. In fact, although it differs by grade level (with it decreasing as grade level increases), most of the non-random variance in scholastic performance is accounted for by g (Thorndike, 1984). Jensen (1989, 1998b) writes that this is so due to the fact that "school learning" is, itself, quite g -loaded. Of course, there are those who write that g is just a product of education (e.g., Ceci, 1991; for a review of others, see Gottfredson, 1986), or, perhaps more egregious, that g and educational achievement are just products of the tests designed to measure them (for review and rebuttal, see Jensen, 1984). But these arguments quickly dissipate when looking at the evidence.

For example, in the latest issue of Intelligence, there were two longitudinal studies (Deary, Strand, Smith, & Fernandes, 2007; Watkins, Lei, & Canivez, 2007) that showed a strong IQ --> Educational Achievement relationship (approx. 70 from Deary), but reverse (i.e., EA --> IQ) was not there (from the Watkins study). Further evidence comes from the two major "We can improve you Education by improving your IQ" projects: Head Start and the Abecedarian Study. With regard to the former, Head Start just does not produce long-term IQ gains and, hence, does not produce long-term academic gains (Caruso, Taylor, & Detterman, 1982; Holden, 1990; Kreisman, 2003). With regard to the latter, while there has been acrimonious debate, the overall conclusion is that, like Head Start, the initial IQ gains do not last, giving even more evidence that educational achievement cannot be raised independently of g (Spitz, 1986, 1992, 1993b, 1993a).

Yet another line for arguing against the prominence of g in education is the idea that there are other traits that are just as necessary for academic success, such as motivation, personality, etc. To risk sounding like to broken record, the data shows that these traits are not nearly as potent predictors as g in predicting academic outcomes. For example, Gagne and St. Pere (2002) gives us reason to believe that motivation might just be an impotent variable in predicting academic achievement. Likewise, Laidra, Pullmann, and Allik (2007) have shown that while personality factors contribute some to the variance in educational achievement, they are dwarfed in comparison to the contribution of g.

Occupational Outcomes

There are many theories as to how g and occupational outcomes relate (see Gottfredson, 1986), but the one that is most supported by data is best explicated by Frank Schmidt and John Hunter

[g] predicts both the occupational level attained by individual and their performance within their chosen occupation. [g] correlates above .50 with later occupational level, performance in job training programs, and performance on the job. Relationships this large are rare in psychological literature and are considered "large" . . . weighted combinations of specific aptitudes (e.g., verbal, spatial, or quantitative aptitude) tailored to individual jobs do not predict job performance better than [g] measures alone, thus disconfirming the specific aptitude theory. It has been proposed that job experience is a better predictor of job performance than [g], but the research findings . . . support the opposite conclusion. . . . Nearly 100 years ago Spearman (1904) proposed that the construct of [g] is central to human affairs. The research . . . supports his proposal in the world of work, an area of life critical to individuals, organizations, and the economy as a whole.(Schmidt & Hunter, 2004, p.171; cf.Schmidt & Hunter, 1998)

One could argue that, given the high g -education relationship, that the g-occupation relationship is just a natural outgrowth.That is, once education is controlled, the g-occupation relationship significantly shrinks. But to make that argument, one would have to have a Sternberg-like approach to intelligence (Sternberg & Wagner, 1993). That is, that the cognitive skills needed for a successful education are somehow vastly different than those needed for everyday life. The data, however, indicate that the same generative process that tends to makes one successful in the educational arena is also the mechanism that tends to make one successful in the occupational arena: g (Kuncel, Hezlett, & Ones, 2004). This is not to say that other things are not important in occupational or educational outcomes; but, as with education, they are not nearly as potent predictors (Gottfredson, 2002).

Life Outcomes

Over the last decade or so, an area that has become of more interest to the intelligence community is the influence of g on general life outcomes. That is, beyond educational and occupational outcomes, does g contribute to life success? The answer here, too, seems to be a resounding yes.

IQ scores [a proxy for g] predict a wider range of important social outcomes and they correlate with more personal attributes than perhaps any other psychological trait. The ubiquity and often-considerable size of g's correlations across life's various domains suggest g truly is important in negotiating the corridors of daily life. (Gottfredson, 2003, p. 326)

But how does g relate to general life outcomes? Believe it or not, it appears that the same information-processing mechanisms that are so potent for educational and occupational outcomes also play a role in day-to-day life (Gottfredson & Deary, 2004). Gottfredson (2003, 2004b) elaborates this mechanism as follows: Life is is made up of many tasks with a wide array of complexity (Gordon, 1997). In the US and most Western nations, society is "free enough" for competence (read: g ) to make a substantial difference in who succeeds in life. As those who have "higher g" are more able to tackle the day-to-day activities of life successfully with less exerted effort, they are able to progress in life with fewer impediments (e.g., untreated illness, accidents; Gottfredson, 2004a), thus allowing them to (a) have more resources to successfully compete and (b) be able to use their resources more efficiently. This then not only allows for a higher probability of achieving satisfying life outcomes (e.g., adequate income, occupational autonomy), but also allows for a lower probability of being involved with unsatisfying life outcomes (e.g., having children without means to support them, crime/delinquency) (cf. Ellis & Walsh, 2003; Herrnstein & Murray, 1996)


Given the ubiquity of g in fostering success in many life outcomes from education achievement to occupational success, from health outcomes to criminal recidivism, social science in general and psychological science in particular would be remiss to "pretend it doesn't matter" (Gottfredson, 2000). Rather, if these fields want to strengthen their scientific integrity and acumen, they should do exact opposite. That is, bring the large, cumulative database on g and its influence on life outcomes to the forefront of a wide array of research agendas so that this corpus of data can serve as the strong underlying foundation of a generation of new investigations on g's life implications. While this line of investigation may never get to the underlying (vertical) mechanisms by which g operates, it can help foster the acceptance of doing such research and pave the way for its societal implications, whatever they may be.


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