Race and intelligence

Race and intelligence research investigates differences in the distributions of cognitive skills among human racial groups. Debates in popular science and academic research over the possible relation between racial divisions and differences in intelligence originally began as a comparison of African Americans and Caucasians in the United States, but were later extended to other ethno-racial groups and regions of the world. In the US, intelligence quotient (IQ) tests have consistently demonstrated statistical differences, with the average score of the African American population being significantly lower - and that of the Asian American population being significantly higher - than that of the White American population (based on the self-identification of those tested). At the same time, there is considerable overlap between these group scores, and members of each racial group can be found at all points on the IQ spectrum. Similar findings have been reported for related populations around the world, most notably in Africa, though these are generally considered far less reliable due to the relative paucity of test data and the difficulties inherent in the cross-cultural comparison of intelligence test scores.

There are no universally accepted definitions of either race or intelligence in academia, and many factors that could potentially influence the development of intelligence have been advanced to explain the racial IQ gap. There is general agreement that environmental and/or cultural factors affect individual IQ scores, and it is widely assumed that a significant portion of the racial IQ gap is attributable to such factors, though none are conclusively supported by direct empirical evidence. The more controversial view that a significant portion of the racial IQ gap is ultimately of genetic origin has been advanced by academics such as Arthur Jensen, J. Philippe Rushton and Richard Lynn, which according to the American Psychological Association has even less empirical support. The claim that the IQ gap has a genetic component met with widespread criticism in the popular media, particularly after the publication of "The Bell Curve", and has not to date gained acceptance by the wider academic community.

The racial IQ gap has remained relatively stable since IQ testing began, although IQ scores as a whole have themselves been subject to change over time. The APA has concluded that the racial IQ gap is not the result of any obvious biases in the content or administration of tests, but that no adequate explanation of it has so far been given.

History

Main article: History of the race and intelligence controversy

Alfred Binet (1857–1911), inventor of the first intelligence test

The history of the race and intelligence controversy concerns the historical development of a debate, primarily in the United States, concerning possible explanations of group differences in intelligence. Although it has never been disputed that there are systematic differences between average scores in IQ tests of different population groups, sometimes called "racial IQ gaps", there has been no agreement on whether this is mainly due to environmental and cultural factors, or whether some inherent hereditarian factor is at play, related to genetics.

In the late nineteenth and early twentieth century, group differences in intelligence were assumed to be due to race and, apart from intelligence tests, research relied on measurements such as brain size or reaction times. By the mid-1930s most psychologists had adopted the view that environmental and cultural factors played a dominant role. In 1969 the Harvard Educational Review published a 125-page invited article by the educational psychologist Arthur Jensen reviving the hereditarian point of view; it concluded, "The preponderance of the evidence is, in my opinion, less consistent with a strictly environmental hypothesis than with a genetic hypothesis, which, of course, does not exclude the influence of environment or its interaction with genetic factors". Jensen's work, publicized by the Nobel laureate William Shockley, sparked controversy amongst the academic community and even led to student unrest. A similar debate amongst academics followed publication in 1994 of The Bell Curve, a book by Richard Herrnstein and Charles Murray that argued in favor of the hereditarian viewpoint. It not only provoked the publication of several interdisciplinary books on the environmental point of view, some in popular science, but also led to a public statement from the American Psychological Association acknowledging a gap between average IQ scores of whites and blacks as well as the absence of any adequate explanation of it, either environmental or genetic. The hereditarian line of research continues to be pursued by a group of researchers, mostly psychologists, some of whom are supported by the Pioneer Fund.

Debate assumptions

In a review of the field, Hunt and Carlson while arguing that "research on group differences in intelligence is scientifically valid and socially important" identify four contemporary positions on the topic of racial differences in intelligence:

1. "There are differences in intelligence between races that are due in substantial part to genetically determined differences in brain structure and/or function (Rushton, 1995; Rushton &Jensen, 2005a)."
2. "Differences in cognitive competencies between races exist and are of social origin (Ogbu, 2002; Sowell, 2005)."
3. "Differences in test scores that are used to argue for differences in intelligence between races represent the inappropriate use of tests in different groups (Ogbu, 2002)."
4. "There is no such thing as race; it is a term motivated by social concerns and not a scientific concept (Fish, 2004; Smedley & Smedley, 2005; Cooper, 2005; Sternberg, Grigorenko, & Kidd, 2005)."

Some scientists argue that the history of eugenics makes this field of research difficult to reconcile with current ethical standards for science. Other scientists insist that, independent of ethical concerns, research into race and intelligence makes little sense because intelligence is poorly measured and because race is a social construction. According to this view, intelligence is ill-defined and multi-dimensional, or has definitions that vary between cultures. This would make contrasting the intelligence of groups of people, especially groups that came from different cultures, dependent mainly on which culture’s definition of intelligence is being used. Moreover, this view asserts that even if intelligence were as simple to measure as height, racial differences in intelligence would still be meaningless since race exists only as a social construct, with no basis in biology.

Unsurprisingly, almost all scientists actively engaged in research in race and intelligence disagree with these criticisms. For example, psychologist Richard Nisbett writes that:

Some laypeople I know — and some scientists as well — believe that it is a priori impossible for a genetic difference in intelligence to exist between the races. But such a conviction is entirely unfounded. There are a hundred ways that a genetic difference in intelligence could have arisen — either in favor of whites or in favor of blacks. The question is an empirical one, not answerable by a priori convictions about the essential equality of groups.

Researchers fall into two groups: hereditarians and environmentalists. Both argue that, although race and intelligence are fuzzy concepts, they can be operationalized enough to draw conclusions about the connections, if any, between the two. Hereditarians argue that genetics explain a significant portion (approximately 50%) of the differences in measured intelligence among human races. Leading scholars of this view include Arthur Jensen, Philippe Rushton, Richard Herrnstein, Linda Gottfredson, Charles Murray and Richard Lynn. Environmentalists argue that the hereditarians are wrong, and that genetic differences are not an important cause of differences in measured intelligence among human races. Leading scholars of this view include Richard Lewontin, Stephen J. Gould, James Flynn, Richard Nisbett and Stephen Ceci. Other scientists, although accepting the basic assumptions of the debate, believe that there is currently not enough evidence to determine what part, if any, genetics plays in racial differences.

According to Rushton and Jensen, the debate has remained unresolved for so long because of "the difficulty of the subject matter, the political issues associated with it and the emotions they arouse, and the different meta-theoretical perspectives of the experimental and correlational methodologies". Contrasting these methodologies, they write that:

Hereditarian heuristics include constructing better tests, developing better techniques for measuring mental abilities, and discovering biological correlates (e.g., heritability, inbreeding depression and heterosis, brain size, brain metabolic rate, brain evoked potentials, brain imaging) of these tests. The process then involves examining the similarities of the scores among people whose varying degrees of genetic resemblance can be predicted from Mendelian theory (Fisher, 1918). [Environmentalist] heuristics include searching for the environmental factors that cause differences in intellectual performance and discovering the bias in existing tests. If two groups differ in mean IQ, [environmentalist] theorists conjecture either that the lower scoring group has been exposed to one or more deleterious experience or been deprived of some beneficial environmental stimuli or that the tests are not valid measures of their true ability. Compensatory training might be initiated and the hypothesis confirmed if the groups then obtain more nearly equal scores, or if less biased tests are developed on which the group differences are reduced but still predict outside criteria. Of course, these two programs overlap to some degree, and a given experiment might well combine elements of the heuristics of each.

Group differences

Main article: Intelligence

Intelligence is most commonly measured using IQ tests. These tests are often geared to measure the psychometric variable g (for general intelligence factor). Other tests that measure g (e.g, the Armed Forces Qualifying Test, SAT, GRE, GMAT and LSAT) also serve as measures of cognitive ability. Several conclusions about these types of tests are now largely accepted:

• IQ scores measure many of the qualities that people mean by intelligent or smart.
• IQ scores are fairly stable over much of a person's life.
• IQ tests predict school and job performance to a degree that does not significantly vary by socio-economic or racial-ethnic background.
• Intelligence is heritable.
• Family environment and community culture affect IQ, more so in children than in adults.

Test scores

Most of the evidence of intelligence differences between racial groups is based on studies of IQ test scores, almost always using self-reported racial data. Self-reports have been shown to be reliable indicators of genetic race to the extent that they match up with genetic clusters derived from mathematical clustering techniques, but these techniques do not determine whether these clusters themselves have any relation to intelligence. According to psychologist David Rowe, self-report is the preferred method for racial classification in studies of racial differences because classification based on genetic markers alone ignore the "cultural, behavioral, sociological, psychological, and epidemiological variables" that distinguish racial groups.

There are observed differences in average test score achievement between racial groups, which vary depending on the populations studied and the type of tests used. In the United States, self-identified Blacks and Whites have been the subjects of the greatest number of studies. Black-White average IQ differences appear to increase with age, reaching an average of nearly 17 points by age 24, which is slightly more than 1 standard deviation. The Black-White IQ difference is largest on those tests that best represent the general intelligence factor g. Using data primarily from the United States and Europe, Jensen and Rushton have estimated the average IQ of Blacks/Africans to be around 85; of whites/Europeans to be around 100, and of East Asians to be around 106. Estimates from other researchers are more or less similar. Gaps are also seen in other tests of cognitive ability or aptitude, including university admission exams, military aptitude tests and employment tests in corporate settings.

The American Psychological Association has concluded that the racial IQ gap is not the result of a simple bias in the content or administration of tests, and the tests are equally valid predictors of achievement for Black and White Americans. Arthur Jensen has found that when black and white individuals are matched for IQ, their relatives tend towards different means.

The IQ distributions of other racial and ethnic groups in the United States are less well studied. The few Amerindian populations that have been systematically tested, including Arctic Natives, tend to score worse on average than White populations but better on average than Black populations East Asian populations score higher on average than White populations in the United States as they do elsewhere.

IQ differences outside of the USA

According to Richard Lynn and others, racial differences in IQ scores are observed around the world. A commonly-cited review by Richard Lynn lists IQ scores for East Asians (105), Europeans (99), Inuit (91), Southeast Asians and Amerindians (87 each), Pacific Islanders (85), South Asians/North Africans (84), Non-Bushmen sub-Saharan Africans (67), Australian Aborigines (62) and Bushmen (54).

This data is generally considered less accurate than data from the United States and Europe, in part because of the inherent difficulty of comparing IQ scores between cultures.

Several researchers have argued that cultural differences limit the appropriateness of standard IQ tests in non-industrialized communities. In the mid-1970s, for example, the Soviet psychologist Alexander Luria concluded that it was impossible to devise an IQ test to assess peasant communities in Russia because taxonomy was alien to their way of reasoning.

Surveying the literature, Jelte Wicherts remarked that:

It is important to note that an observed IQ score does not necessarily equal a particular level of general intelligence or g (Bartholomew, 2004), as it is necessary to consider the issue of validity in interpreting an observed score as an indication of the position on a latent variable such as g. Several authors have questioned whether the IQ scores of Africans are valid and comparable to scores in western samples in terms of g ([Barnett and Williams, 2004], [Ervik, 2003], [Hunt and Carlson, 2007], [Hunt and Sternberg, 2006] and [Lane, 1994]). Some (e.g., Berry, 1974) reject the very possibility of obtaining a valid measure of g in Africa with western IQ tests, while others (e.g., [Herrnstein and Murray, 1994], [Lynn, 2006] and [Rushton and Jensen, 2005]) consider it relatively unproblematic. The psychometric issue of measurement invariance ([Mellenbergh, 1989] and [Millsap and Everson, 1993]) is crucial to the comparability of test scores across cultural groups in terms of latent variables, such as g. Alas, the number of studies addressing measurement invariance is small.

Moreover, in a review of Lynn's book Race Differences in Intelligence (2006), where some of these findings are presented, Nicholas Mackintosh has also criticized Lynn for manipulation of data, and raised doubts about the reliability of his findings

Debate overview

Richard Nisbett, in replying to hereditarian arguments, structures the debate into several major areas.

Heritability within and between groups

Main article: Heritability of IQ

There is consensus among intelligence researchers that IQ, like height, is significantly heritable within the same population. However, there is debate over whether the IQ test differences between the racial groups are caused by genetic differences or by cultural or environmental factors.

An environmental factor that varies between groups but not within groups can cause group differences in a trait that is otherwise 100% heritable. The height of this "ordinary genetically varied corn" is 100% heritable, but the difference between the groups is totally environmental. This is because the nutrient solution varies between populations, but not within populations.

Much of the research on this topic has been conducted by Arthur Jensen and James Flynn. Flynn and Jensen consider two general classes of environmental factors: common environmental factors, which vary both within and between groups; and X-factors, which vary between groups but not within groups. Flynn explains in Race, IQ and Jensen (1980) why common environmental factors are inadequate as an explanation for the IQ gap:

After all, if an environmental factor is potent enough to account for the 15-point performance gap between black and white, and if it varies much from person to person within the black population, it would be extremely odd if it accounted for none of the variable performance within the black population! And if it did, it would of course increase the role of environmental factors in explaining IQ variance and thus lower the h2 (within-group heritability) estimate for blacks. [...] If we seize on SES (socio-economic status) as a between-population explanation, who can deny that there are large differences in SES within black America; if we seize on education, who can deny that blacks differ significantly in terms of quality of education?

The alternative to common environmental factors is the hypothesis that the racial IQ gap can be accounted for by X-factors: factors that vary between groups but not within groups. A frequently-cited example of an X-factor from Richard Lewontin describes two populations of corn, one grown in a normal environment, and the other in a nutrient-deficient environment. The height of this corn is 100% heritable when grown in a uniform environment. Therefore, in such a scenario the within-group heritability of height is 100% in both populations, but the substantial differences between groups are due entirely to environmental factors. Jensen and Flynn agree that no X-factors have yet been identified that could account for the racial IQ gap. Jensen believes that under these circumstances, the “default hypothesis” should be that the differences in average IQ between races is caused by the same factors that cause within-group variance in IQ, while Flynn believes that the racial IQ gap is caused by X-factors that have yet to be discovered.

Score convergence

The overall average Black-White gap has reduced by one third over the course of the 20th century. For example, the black men inducted into the US armed forces during World War II averaged about 1.5 standard deviations below their white counterparts. This improvement is also reflected in Black-White differences on school achievement tests, which have shrunk from about 1.2 to about 0.8 standard deviations. Flynn claims that the Black-White gap has reduced throughout the 20th century. However, Murray claims that these improvements may have stalled for people born after the early 1970s .

Flynn effect

Main article: Flynn effect

Although modern IQ tests are unbiased, average test scores over the last century have risen steadily around the world. This rise is known as the "Flynn effect," named for James R. Flynn, who did much to document it and promote awareness of its implications. The effect increase has been continuous and approximately linear from the earliest years of testing to the present.

This means, given the same test, the mean performance of Blacks today could be higher than the mean for Whites in 1920, though the gains causing this appear to have occurred predominantly in the lower half of the IQ distribution. If an unknown environmental factor can cause changes in IQ over time, then contemporary differences between groups could also be due to an unknown environmental factor.

Nichols (1987) critically summarized the argument as follows:

1. We do not know what causes the test score changes over time.
2. We do not know what causes racial differences in intelligence.
3. Since both causes are unknown, they must, therefore, be the same.
4. Since the unknown cause of changes over time cannot be shown to be genetic, it must be environmental.
5. Therefore, racial differences in intelligence are environmental in origin.

Dickens (2005) states that "Although the direct evidence on the role of environment is not definitive, it mostly suggests that genetic differences are not necessary to explain racial differences. Advocates of the hereditarian position have therefore turned to indirect evidence ... The indirect evidence on the role of genes in explaining the Black-White gap does not tell us how much of the gap genes explain and may be of no value at all in deciding whether genes do play a role. Because the direct evidence on ancestry, adoption, and cross-fostering is most consistent with little or no role for genes, it is unlikely that the Black-White gap has a large genetic component."

Spearman's Hypothesis

Main article: general intelligence factor

An illustration of Charles Spearman's two-factor intelligence theory. Each small oval is a hypothetical mental test. The blue areas show the variance attributed to a specific content of the test and the purple areas the variance attributed to g, the general intelligence factor. Newer and more complex theories of g now exist.

Spearman's hypothesis asserts that group differences on intelligence test scores are caused primarily by group differences on the general intelligence factor (abbreviated g). The general factor is a statistical construct that measures what is common to the scores of all IQ test items. How well a person does on one IQ sub-test is usually correlated with how well he or she does on other sub-tests. This is the essence of g.

Jensen developed a statistical technique known as the method of correlated vectors to test Spearman's hypothesis. The idea is that a rank ordering of IQ sub-test items by g-loadings should correlate with the magnitude of the race difference on those items, if indeed g is their cause. For example, digit span backward is more g-loaded than is digit-span forward. And, the race difference on the former is about twice as large as the race difference on the latter.

Spearman's hypothesis is not without its critics. Psychologists Hunt and Carlson write:

One of the most widely cited pieces of evidence (although not the only one) for biological differences in intelligence, sometimes referred to as Spearman's hypothesis (Jensen, 1998), rests on an indirect argument constructed from three facts. The first is that various IQ measures are substantially correlated, providing evidence for general intelligence. Although tests do vary in the extent of their g loading, factor structures are similar over several test batteries (Johnson, Bouchard, Krueger, McGue, & Gottesman, 2004). The second is that, within Whites, the g factor appears to have a substantial genetic component (see citations in Rushton & Jensen, 2005a). The third fact is that the g loadings of tests are substantially and positively correlated with the difference between the mean White and African American score on each subtest within a battery of tests. This analysis has been referred to as the "method of correlated vectors" (Jensen, 1998). Because it has also been well established that general intelligence has a substantial genetic component, results from the method of correlated vectors have been offered as putative evidence that the "default hypothesis" ought to be that about 50% of the variance in the African American versus White difference reflects genetic differences in a potential for intelligence (Jensen, 1998; Rushton and Jensen, 2005a).

They further summarize criticisms of this position:

Technical objections have been made to the method of correlated vectors and to a somewhat stronger condition: that if the within-group correlations between measures are identical across groups, the between-group differences must arise from the same cause as the within-group correlations (Widaman, 2005). The essence of these objections is that the method of correlated vectors does not consider alternative hypotheses concerning the latent traits that might give rise to the observed difference in test scores. When a more appropriate method of analysis, multigroup confirmatory factor analysis, is applied, it has been found that Spearman's hypothesis (i.e., that the difference is due to differences in general intelligence) is only one of several models that could give rise to the observed distributions in test scores (Dolan, 2000). These findings render the method of correlated vectors ambiguous—which is not the same as saying that the Jensen-Rushton position is incorrect. Our point is that the argument for the default hypothesis is an indirect one. It would be far better if a direct causal argument could be made linking racial/ethnic genetic differences to studies of the development of the brain.

Variables potentially affecting intelligence in groups

The following factors have been suggested as explaining a portion of the differences in average IQ between races. These factors are not mutually exclusive with one another, and some may in fact directly contribute to others. For example, some or all of the differences in average brain size between races could be the result of nutritional factors, and different geographic ancestry could also result in genetic differences.

Socioeconomic environment

File:TBC-BW-IQ-SES-withDiff.png

Socioeconomic status (SES) varies both between and within populations, but Black-White differences in IQ persist among the children of parents matched for SES, and the gap is largest among the children of wealthiest and best educated parents.

According to the report of a 1996 APA task force, socioeconomic factors (SES) cannot account for all of the observed racial-ethnic group differences in IQ. Their first reason for this conclusion is that that the black-white test score gap is not eliminated when individuals and groups are matched on SES. Second, attempts to exclude extreme conditions, nutritional and biological factors that may vary with SES have shown little effect on IQ. Third, the relationship between IQ and SES is not simply one in which SES determines IQ, but differences in intelligence, particularly parental intelligence, also cause differences in SES, making separating the two factors nearly impossible. Lastly, they argue that parameters of income and education alone fail to capture important categories of cultural experience that differ between racial and ethnic groups.

Health and nutrition

Environmental factors including lead exposure, breast feeding, and nutrition can significantly affect cognitive development and functioning. For example, iodine deficiency causes a fall, in average, of 12 IQ points . Such impairments may sometimes be permanent, sometimes be partially or wholly compensated for by later growth. Comprehensive policy recommendations targeting reduction of cognitive impairment in children have been proposed. The African American population of the United States is statistically more likely to be exposed to all of the possible prenatal and perinatal detrimental enviromental factors.

Education

Although the test performance gaps between races persist even after adjusting for education level, several studies have proposed that a large part of the gap can be attributed to differences in quality of education. Racial discrimination in education has been proposed as one possible cause of differences in educational quality between races. According to a paper by Hala Elhoweris, Kagendo Mutua, Negmeldin Alsheikh and Pauline Holloway, teachers' referral decisions for students to participate in gifted and talented educational programs was influenced in part by the students’ ethnicity.

Ellis Cose has suggested that special education programs can have a significant effect on raising the test scores of black students. In his book Intelligence can be Taught, Cose describes a program called SOAR implemented by Xavier University, which produced gains equivalent to 120 points on an SAT test. The Abecedarian Early Intervention Project, an intensive early childhood education project, was also able to cause an average IQ gain of 5 points in black children who participated in it, narrowing the IQ gap between them and whites from 15 points to 10. Arthur Jensen has agreed that the Abecedarian project demonstrates that education can have a significant effect on IQ, but also points out that no educational program thus far has been able to reduce the B/W IQ gap by more than a third, so differences in education are unlikely to be its only cause.

Nisbett argues that hereditarians Rushton and Jensen ignore early childhood development programs aside from Head Start. He points to work by Ramey and colleagues as an example, which found that 87% of children exposed to an educational intervention had IQs in the normal range compared to 56% of controls, and none of the intervention-exposed children were mildly retarded compared to 7% of controls. Nisbett also lists five other successful intervention studies, noting that they can be effective at any age.

Genetics

The decoding of the human genome has enabled scientists to search for sections of the genome that contribute to cognitive abilities. Current studies using Quantitative trait loci have yielded little success in the search for genes influencing intelligence. Robert Plomin is confident that QTLs responsible for the variation in IQ scores exist, but that more powerful tools of analysis will be required to detect them. Others assert that no useful answers can be reasonably expected from such research before an understanding of the relation between DNA and human phenotypes emerges. Some researchers have expressed reluctance to investigate possible links between genes and intelligence, due to the controversy it can produce.

A 2005 literature review article on the links between race and intelligence in American Psychologist stated that no gene has been shown to be linked to intelligence, "so attempts to provide a compelling genetic link of race to intelligence are not feasible at this time". Two 2007 studies found that DTNBP1 and CHRM2 appear to influence intelligence depending on which allele of it a person carries. However, a study published in 2009 by Deary et al. failed to find evidence of an association between these genes and general intelligence, stating "there is still almost no replicated evidence concerning the individual genes, which have variants that contribute to intelligence differences".

The theory that genetic differences contribute to the difference in average IQ between races has been criticized for this lack of direct evidence, and the fact that it must therefore rely on indirect evidence instead. Supporters of a partially genetic basis for the IQ gap have asserted that despite this, such a model is able to provide a more parsimonious explanation for the IQ gap than one which does not involve genetic factors, because it does not rely on the existence of undiscovered environmental X-factors that affect IQ variance between races but not within them. In The g Factor, Arthur Jensen also asserts that this theory is able to make specific predictions about future results, while explanations for the IQ gap that rely on unknown environmental factors are not empirically testable or falsifiable.

Geographic ancestry

African Americans typically have ancestors from both Africa and Europe, with, on average, 20% of their genome inherited from European ancestors. Several studies performed without the use of DNA-based ancestry estimation attempted to correlate estimates of African or European ancestry with IQ. These studies have found that mixed-race individuals tended to have IQs intermediate between those of unmixed blacks and whites, with a correlation of 0.17 between the estimated degree of difference in ancestry and the size of the difference in average IQ. These studies have been criticized for their imprecise method of estimating ancestry, which was based primarily on skin tone, as well as for their small sample sizes. Charges of data manipulation have also appeared .

Rowe (2005) and others have suggested using DNA-based methods to reproduce these studies with reliable estimates of ancestry. Such experiments have never been published, although the requirements for such a study have been discussed in the academic literature.

Stereotype threat

Main article: Stereotype threat

Stereotype threat is the fear that one's behavior will confirm an existing stereotype of a group with which one identifies; this fear may in turn lead to an impairment of performance. Testing situations that highlight the fact that intelligence is being measured tend to lower the scores of individuals from racial-ethnic groups that already score lower on average. Stereotype threat conditions cause larger than expected IQ differences among groups but do not explain the gaps found in non-threatening test conditions.

A 2009 meta-analysis by Jelte Wicherts found evidence of significant publication bias in 55 studies of stereotype threat and its effect on IQ, in which those that found a strong effect were more likely to be published than those that did not. Reviewing both published and unpublished studies, Wicherts found that stereotype threat did not have an effect on all test-taking settings in which a difference in average scores is observed between races, and therefore was not an adequate explanation for the racial IQ gap.

Brain size

Main article: Neuroscience and intelligence

In a study of the head growth of 633 term-born children from the Avon Longitudinal Study of Parents and Children cohort, it was shown that prenatal growth and growth during infancy were associated with subsequent IQ. The study’s conclusion was that the brain volume a child achieves by the age of 1 year helps determine later intelligence. Within human populations, studies conducted to determine whether there is a relationship between brain size and a number of cognitive measures have "yielded inconsistent findings with correlations from 0 to 0.6, with most correlations 0.3 or 0.4." A study on twins showed that frontal gray matter volume also was correlated with g and highly heritable. A related study has reported that the correlation between brain size (reported to have a heritability of 0.85) and g is 0.4, and that correlation is mediated entirely by genetic factors.

On average, the brains of African-Americans are 5% smaller than the brains of Whites and 6% smaller than East Asians, according to studies of brain weight at autopsy, endocranial volume of empty skulls, head size measurements by the U.S. military and NASA, and two dozen MRI volumetric studies. Proponents of both the environmental and hereditarian perspective believe that this variation is relevant to the racial IQ gap, although they disagree as to its cause. Ulric Neisser, The Chair of the APA’s Task Force on intelligence, acknowledges the brain size difference, but points out that brain size is known to be influenced by environmental factors such as nutrition, and that this fact has been demonstrated experimentally in rats. He thus believes that data on brain size cannot be considered strong evidence for a genetic component to the IQ difference. Rushton and Jensen disagree, citing several studies of malnourished East Asians showing that they have larger brains than Whites, and studies demonstrating the brain size difference at birth and prenatally just a few weeks after conception. A third perspective is offered by Leonard Lieberman, who believes that human variation in brain size is primarily genetic and an adaptation to climate, but that this variation should be viewed as being based on biogeographic ancestry and independently of “race”.

Processing efficiency

Main article: Reaction time

Reaction time (RT) is the elapsed time between the presentation of a sensory stimulus and the subsequent behavioral response by the participant. RT is often used in experimental psychology to measure the duration of mental operations, an area of research known as mental chronometry. In psychometric psychology, RT is considered to be an index of speed of processing. That is, RT indicates how fast the thinker can execute the mental operations needed by the task at hand. In turn, speed of processing is considered an index of processing efficiency. The behavioral response is typically a button press but can also be an eye movement, a vocal response, or some other observable behavior.

Scores on many but not all RT tasks tend to correlate with scores on paper and pencil IQ tests. This is especially true for so-called elementary cognitive tasks (ECTs). These require participants to perform trivially simple cognitive tasks, like deciding which of two briefly-presented lines is longer (the inspection time task), or which of three lighted buttons is farthest away from the other two (the odd man out task).

Most people can perform ECTs with near 100% accuracy, but individual differences in RT on these tasks are large and correlate well with IQ scores. Jensen (2001) argues that ECTs could replace traditional IQ tests as measures of intelligence, because the former are measured on a ratio scale whereas IQ tests only rank people on an ordinal scale. Jensen has invented a Jensen box to present ECT task stimuli to participants in a precise, standardized fashion.

Not all RT tasks, however, are good measures of intelligence. In general, RT on tasks that take between 200 milliseconds and 2 seconds to perform tend to correlate well with IQ. Tasks that most people can do faster than 200 milliseconds generally measure the efficiency of sensory processes (seeing, hearing) rather than intelligence. Tasks that take longer than about two seconds typically allow for strategic differences among people that cloud any relationship between RT and IQ (for these tasks, accuracy—versus speed—is likely more related to IQ).

Reaction time best predicts IQ test scores when participants perform many trials (i.e., 100s) of the same ECT. Aggregating average reaction times across different ECTs also produces significantly larger RT/IQ correlations. In many studies, the within person variability of RT is also a strong predictor of IQ. Participants showing relatively large RT differences from trial to trial tend to score lower on IQ tests than do participants who do not deviate much in their reaction time from trial to trial. Finally, the slowest trials for any person tend to better predict that person's IQ relative to either his or her average or fastest response.

Although the literature on RT is vast, far less research has looked at race differences on RT as a potential explanation for the race/IQ gap. The general pattern, however, is that race differences exist on ECT performance, and that these differences are in line with those found on traditional IQ tests. For example, a recent study in the journal Intelligence looked at race differences on the Wonderlic Personnel Test (a traditional paper and pencil IQ test) and performance on two ECTs (an inspection time and choice reaction time task). A black/white difference was found on the Wonderlic, and both ECTs. Statistical mediation was found in that controlling for race differences on the ECTs resulted in the race difference on the Wonderlic no longer being significant.

Some studies have found that movement time, the measure of how long it takes a person to move a finger after taking the decision to do so, correlate just as well with IQ as processing time does (a weak correlation of about .20) and that Blacks generally have faster movement times than whites.

Caste-like minorities

A large number of studies have shown that systemically disavantaged minorities, such as the African American minority of the United States generally perform worse in the educational system and in intelligence tests than the majority groups or less disadvantaged minorities such as immigrant or "voluntary" minorities. The explanation of these findings may be that children of caste-like minorities, due to the systemic limitations of their prospects of social advancement, do not have "effort optimism", i.e. they do not have the confidence that aquiring the skills valued by majority society, such as those skills measured by IQ tests, is worthwhile.

This argument is also explored in the book Inequality by Design: Cracking the Bell Curve Myth (1996) which argues that it is not lower average intelligence that leads to the lower status of racial and ethnic minorities, it is instead their lower status that leads to their lower average intelligence test scores. To substantiate this claim, the book presents a table comparing social status or caste position with test scores and measures of school success in several countries around the world. The authors note, however, that the comparisons made in the table do not represent the results of all relevant findings, nor do they reflect the fact that the tests and procedures varied greatly from study to study. The comparison of Jews and Arabs, for example, is based on a news report that, in 1992, 26% of Jewish high school students passed their matriculation exam, majority of whom were Ashkenazi Jews, as opposed to 15% of Arab students.

Rearing conditions

Several studies have been done on the effect of different rearing conditions on black children. The Minnesota Transracial Adoption Study examined the IQ test scores of 130 black/interracial children adopted by advantaged White families. The aim of the study was to determine the contribution of genetic factors to the poor performance of black children on IQ tests as compared to White children. The following table provides a summary of the results.

Biological parents	Number of children	Initial testing	10-year follow-up
Minnesota Transracial Adoption Study initially tested at age 7
Black-black	21	91.4	83.7
Black-white	55	105.4	93.2
White-white	16	111.5	101.5
Biological children	101	110.5	105.5

Studies by Moore, Eyferth, and Tizard have examined intellegence of the children of black and white parents in uniform environments. Moore examined children adopted by white parents in America, Eyferth studied the children of black and white GIs raised by white German mothers in occupied Germany, and Tizard studied West Indian children raised in British long-stay residential nurseries. None of studies found evidence of higher intellegence in white children than in black children, though none followed up the children at later ages.

Moore compared black and mixed-race children adopted by either black or white families. Unlike in the Weinberg, et al study, there was no difference in IQ between black and mixed-race children, whether raised by black or white families. Moore also observed that 23 black and interracial children raised by white parents had a significantly higher mean score than 23 age-matched children raised by black parents (117.1 vs 103.6), and argued that differences in early socialization explained these differences. Moore concluded that there is superiority of the mixed-race children over the black children and that the entire difference between the iQs of black and white at the time of the study could be accounted for by environmental factors associated with race.

The Eyferth study was criticized by Rushton and Jensen for the relatively high proportion of North Africans and the rigorous selection process of the military, but Flynn argued that the black and white soldier IQ gap was similar the general population. The data is summarised below:

Biological parents	Number of children	Initial testing	10-year follow-up
Moore (1986) initially tested at age 7–10
Black-black	9	108.7	not done
Black-white	14	107.2	not done
Eyferth (1961) initially tested at age 5–13
Black-white	171	96.5	not done
White-white	70	97.2	not done
Tizard et al (1972) initially tested at age 2-5
Black-black	31	103.1	not done
Black-white	43	104.8	not done
White-white	75	100.0	not done

Policy relevance

Main article: Intelligence and public policy

In response to criticism that their conclusions would have a negative effect on society if they were to gain wide acceptance, Jensen and Rushton have justified their research in this area as being necessary to answer the question of how much racism should be held responsible for ethnic groups' unequal performance in certain areas. They maintain that when racism is blamed for disparities that result from biological differences, the result is mutual resentment, and unjustified punishment of the more successful group. They state:

[T]he view that one segment of the population is largely to blame for the problems of another segment can be even more harmful to racial harmony, by first producing demands for compensation and thereby inviting a backlash. Equating group disparities in success with racism on the part of the more successful group guarantees mutual resentment. As overt discrimination fades, still large racial disparities in success lead Blacks to conclude that racism is not only pervasive but also insidious because it is so unobservable and "unconscious." Whites resent that nonfalsifiable accusation and the demands to compensate blacks for harm they do not believe they caused.

See also

• Health and intelligence
• Environment and intelligence
• Ashkenazi intelligence
• The Bell Curve (1994)
• Intelligence: Knowns and Unknowns (1996)
• IQ and Global Inequality (2006)
• The Mismeasure of Man (1981)
• Mainstream Science on Intelligence (1994; 1997)
• Race Differences in Intelligence (2006)
• Survey of Expert Opinion on Intelligence and Aptitude Testing (1987)

References

Main article: Race and intelligence (References)