Race and intelligence

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The existence of a link between race and intelligence has been repeatedly observed by scientists, but remains extremely controversial. Research suggests that the average IQ score of East Asians is higher than that of Europeans, and the average IQ score of Europeans is higher than that of Africans and African-Americans. Additional research has indicated that environmental factors such as socio-economic status and education can explain some, but not all, of these observed differences in IQ.

Research into the Size of Racial IQ Differences

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

1910s

In 1917, tests developed by Robert Yerkes were used to evaluate American draftees. Researchers found that: Southern and Eastern European immigrants scored lower than Americans (who at the time were largely Western and Northern Europeans); Americans from northern states had higher scores than Americans from southern states; and Black Americans scored lower than White Americans.[1] However, some scientists argued that immigrants performed poorly on these tests because English was not their first language.[2]

1930s

Psychologist Carl Brigham and anthropologists Franz Boas, and Ruth Benedict and Gene Weltfish argued that environmental factors, not genetic ones, explained differences in IQ scores.

Desegregation

In 1958, Audrey Shuey published The Testing of Negro Intelligence, in which she attempted to demonstrate that the difference between the average IQ scores of blacks and whites had not changed since IQ was first measured. In the 1960s, Nobel laureate William Shockley, argued that black children were innately unable to learn as well as white children.[3] Arthur Jensen, in a Harvard Education Review article entitled "How Much Can We Boost IQ and Scholastic Achievement?"[4][5][6][7] questioned the value of remedial education for African-American children. Jensen argued that their poor educational performance was genetic.[8] He continued research into the question until his death in 2012.

1990s

The Bell Curve (1994), written by Richard Herrnstein and Charles Murray, emphasized the societal effects of low IQ.[9]. Fifty-two researchers (mostly psychologists) signed an editorial statement "Mainstream Science on Intelligence" which was generally supportive of the claims of The Bell Curve.

In 1995 report from the American Psychological Association, "Intelligence: Knowns and Unknowns", noted that racial differences in IQ scores existed, and concluded that no current theories adequately explained it.

Several books were written in criticism of The Bell Curve, including: The Bell Curve Debate (1995), Inequality by Design: Cracking the Bell Curve Myth (1996) and a second edition of The Mismeasure of Man (1996) by Stephen Jay Gould.[10]

2000s

A review article "Thirty Years of Research on Race Differences in Cognitive Ability" by J. Philippe Rushton and Arthur Jensen was published in 2005.[11] The article was followed by a series of responses, some in support, some critical.[12][13] Richard Nisbett, another psychologist who had also commented at the time, later included an amplified version of his critique as part of the book Intelligence and How to Get It: Why Schools and Cultures Count (2009).[14] Rushton and Jensen in 2010 made a point-by-point reply to this thereafter.[15] A comprehensive review article on the issue was published in the journal American Psychologist in 2012.[16]

Rushton & Jensen (2005) wrote that, in the United States, self-identified blacks and whites have been the subjects of the greatest number of studies. They stated that the black-white IQ difference is about 15 to 18 points or 1 to 1.1 standard deviations (SDs), which implies that between 11 and 16 percent of the black population have an IQ above 100 (the general population median). According to Arthur Jensen and J. Philippe Rushton the black-white IQ difference is largest on those components of IQ tests that best measure the general intelligence factor g.[17] The 1996 APA report "Intelligence: Knowns and Unknowns" and the 1994 editorial statement "Mainstream Science on Intelligence" gave more or less similar estimates.[18][19]

Roth et al. (2001), in a review of the results of a total of 6,246,729 participants on other tests of cognitive ability or aptitude, found a difference in mean IQ scores between blacks and whites of 1.1 SD. Consistent results were found for college and university application tests such as the Scholastic Aptitude Test (N = 2.4 million) and Graduate Record Examination (N = 2.3 million), as well as for tests of job applicants in corporate sections (N = 0.5 million) and in the military (N = 0.4 million).[20] North East Asians have tended to score relatively higher on visuospatial subtests with lower scores in verbal subtests while Ashkenazi Jews score higher in verbal and reasoning subtests with lower scores in visuospatial subtests. The few Amerindian populations who have been systematically tested, including Arctic Natives, tend to score worse on average than white populations but better on average than black populations.[20]

A 2006 study by Dickens and Flynn estimated that the difference between mean scores of blacks and whites closed by about 5 or 6 IQ points between 1972 and 2002,[21] which would be a reduction of about one-third. In the same period the educational achievement disparity also diminished.[22] However, this was challenged by Rushton & Jensen who said the difference had remained stable.[23] In a 2006 study, Murray agreed with Dickens and Flynn that there has been a narrowing of the difference, but stated that the difference was not continuing to decrease.[24]

Some studies reviewed by Hunt (2010), p. 418 found that rise in the average achievement of African Americans was caused by a reduction in the number of African American students in the lowest range of scores without a corresponding increase in the number of students in the highest ranges. A 2012 review of the literature found that the IQ gap had diminished by 0.33 standard deviations since first reported.[16]{{sfn|Nisbett|Aronson|Blair|Dickens|2012b}

National IQ scores

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In IQ and the Wealth of Nations (2002), and IQ and Global Inequality (2006), Richard Lynn and Tatu Vanhanen created estimates of average IQs for 113 nations. They estimated IQs of 79 other nations based on neighboring nations or other via other manners. They found a consistent correlation between national development and national IQ averages. The highest national IQs were in Western and Asian developed nations and the lowest national IQs were in the world's least developed nations in Sub-Saharan Africa and Latin America.

Lynn and Vanhanen's studies have been criticized for selecting data biased toward underestimating the national IQ scores of Third World countries. Specifically, their estimate of the average IQ of sub-Saharan Africans is 67, but they excluded several studies with higher estimates without providing a reason for doing so. Including them would have put the estimate at 82.

However, a 2007 meta-analysis by Rindermann found many of the same groupings and correlations found by Lynn and Vanhanen, with the lowest scores in sub-Saharan Africa, and a correlation of .60 between cognitive skill and GDP per capita. Hunt (2010, pp. 437–439) considers Rindermann's analysis to be much more reliable than Lynn and Vanhanen's.

In a meta-analysis of studies of IQ estimates in Africa, Wicherts, Dolan & van der Maas (2009), p. 10 argue that this difference is due to sub-Saharan Africa having limited access to modern advances in education, nutrition and health care.[25]

The Flynn Effect

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Over the past century, raw scores on IQ tests have been rising; this score increase is known as the "Flynn effect," after Jim Flynn. In the United States, the increase was approximately linear until 1998, at which point the scores leveled off. Some tests even began to show decreasing scores.

Flynn has stated that, because these changes take place between one generation and the next, it is highly unlikely that genetic factors could account for the increasing scores. That is, the increase must be caused by environmental factors. This has been used to argue that racial differences in IQ scores must also be environmental. However, Te Nijenhuis and van der Flier (2013) concluded that the Flynn effect and group differences in intelligence were likely to have different causes. They stated that the Flynn effect is caused primarily by environmental factors, but it is unlikely those same environmental factors could explain group differences in IQ.[26]

Research into environmental causes of racial differences in IQ

Test bias

The validity and reliability of IQ scores obtained from outside the United States and Europe have been questioned.[27][28] Several researchers have argued that cultural differences limit the appropriateness of standard IQ tests in non-industrialized communities.[29][30]

However, a 1996 report by the American Psychological Association states that controlled studies show that differences in mean IQ scores were not substantially due to bias in the content or administration of the IQ tests. Furthermore, the tests are equally valid predictors of future achievement for black and white Americans.[18] This is reinforced by Nicholas Mackintosh in his 1998 book IQ and Human Intelligence,[31] and by a 1999 literature review by Brown, Reynolds & Whitaker (1999). That is, there are no questions on IQ tests which are easier for whites to answer than for non-whites.

Stereotype threat and minority status

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Psychometrician Nicholas Mackintosh considers that there is little doubt that the effects of stereotype threat contribute to the IQ gap between blacks and whites.[32]

A large number of studies have shown that the African-Americans generally perform worse in school and on intelligence tests than whites and immigrants.[18] They may even deliberately reject certain behaviors that are seen as "acting white."[33][34][35]

Socioeconomic Status

Generally the difference between mean test scores of blacks and whites is not eliminated when individuals and groups are matched on SES, suggesting that the relationship between IQ and SES is not simply one in which SES determines IQ. Rather it may be the case that differences in intelligence, particularly parental intelligence, may also cause differences in SES, making separating the two factors difficult.[18] Hunt (2010), p. 428 summarizes data showing that, jointly, SES and parental IQ account for the full gap (in populations of young children, after controlling parental IQ and parental SES, the gap is not statistically different from zero). He argues the SES-linked components reflect parental occupation status, mother's verbal comprehension score and parent-child interaction quality. Hunt also reviews data showing that the correlation between home environment and IQ becomes weaker with age.

Other research has focussed on different causes of variation within low SES and high SES groups.[36] [37] [38] In the US, among low-SES groups, genetic differences account for a smaller proportion variance in IQ than among higher SES populations.[39] Such effects are predicted by the bioecological hypothesis – that genotypes are transformed into phenotypes through nonadditive synergistic effects of the environment.[40] Nisbett et al. (2012) suggest that high SES individuals are more likely to be able to develop their full biological potential, whereas low SES individuals are likely to be hindered in their development by adverse environmental conditions. The same review also points out that adoption studies generally are biased towards including only high and high middle SES adoptive families, meaning that they will tend to overestimate average genetic effects. They also note that studies of adoption from lower-class homes to middle-class homes have shown that such children experience a 12 - 18 pt gain in IQ relative to children who remain in low SES homes.[16]

Health and Nutrition

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Percentage of children aged 1-5 with blood lead levels at least 10 µg/dL. Black and Hispanic children have much higher levels than white children. A 10 µg/dL increase in blood lead at 24 months is associated with a 5.8-point decline in IQ.[41] Although the Geometric Mean Blood Lead Levels (GM BLL) are declining, a CDC report (2002) states that: "However, the GM BLL for non-Hispanic black children remains higher than that for Mexican-American and non-Hispanic white children, indicating that differences in risk for exposure still persist."[42]

Environmental factors including lead exposure,[41] breast feeding,[43] and nutrition[44][45] can significantly affect cognitive development and functioning. For example, iodine deficiency causes a fall, on average, of 12 IQ points.[46] Such impairments may sometimes be permanent, sometimes be partially or wholly compensated for by later growth. The first two years of life is the critical time for malnutrition, the consequences of which are often irreversible and include poor cognitive development, educability, and future economic productivity.[47] The African American population of the United States is statistically more likely to be exposed to many detrimental environmental factors such as poorer neighborhoods, schools, nutrition, and prenatal and postnatal health care.[48][49] Mackintosh points out that for American Blacks infant mortality is about twice as high as for whites, and low birthweight is twice as prevalent. Also, white mothers are twice as likely to breastfeed their infants as black mothers are. Breastfeeding is highly correlated with IQ for low birthweight infants.[50]

The Copenhagen consensus in 2004 stated that lack of both iodine and iron has been implicated in impaired brain development, and this can affect enormous numbers of people: it is estimated that one-third of the total global population are affected by iodine deficiency. In developing countries, it is estimated that 40% of children aged four and under suffer from anaemia because of insufficient iron in their diets.[51]

Other scholars have argued that the standard of nutrition has a significant effect on population intelligence, and that the Flynn effect may be caused by increasing nutrition standards across the world.[52] James Flynn has himself has written against this idea.[53]

Some recent research has argued that the retardation of brain development by infectious diseases, many of which are more prevalent in non-White populations, may be an important factor in explaining the differences in IQ between different regions of the world.[54] This research, showing the correlation between IQ, race and infectious diseases, was also applied to the "IQ gap" in the US, which suggests that this may be an important environmental factor.[55]

Education

Several studies have proposed that a large part of the gap can be attributed to differences in quality of education.[56] Racial discrimination in education has been proposed as one possible cause of differences in educational quality between races.[57] 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 were influenced in part by the students' ethnicity.[58]

The Abecedarian Early Intervention Project, an intensive early childhood education project, was also able to bring about an average IQ gain of 4.4 points at age 21 in the black children who participated in it compared to controls.[43] Arthur Jensen agreed that the Abecedarian project demonstrates that education can have a significant effect on IQ, but also said that no educational program thus far has been able to reduce the black-white IQ gap by more than a third, and that differences in education are thus unlikely to be its only cause.[59]

Rushton and Jensen argue that long-term follow-up of the Head Start Program found large immediate gains for blacks and whites but that these were quickly lost for the blacks although some remained for whites. They argue that also other more intensive and prolonged educational interventions have not produced lasting effects on IQ or scholastic performance.[17]

A series of studies were conducted by Fagan and Holland to determine whether prior exposure to the types of tasks required on IQ tests would improve IQ scores. Assuming that the IQ gap was the result of lower exposure to tasks using the cognitive functions usually found in IQ tests among African American test takes, they exposed a group of African Americans to these types of tasks before giving them an IQ test. The researchers found that there was no subsequent difference in performance between the African-Americans and White test takers.[60][61] Daley and Onwugbuezie conclude that Fagan and Holland demonstrate that "differences in knowledge between Blacks and Whites for intelligence test items can be erased when equal opportunity is provided for exposure to the information to be tested".[62] A similar argument is made by David Marks who argues that IQ differences correlate well with differences in literacy suggesting that developing literacy skills through education causes an increase in IQ test performance.[63][64]

Research into genetic causes of racial differences in IQ

Genetics of race and intelligence

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The decoding of the human genome has enabled scientists to search for sections of the genome that may contribute to cognitive abilities.

Intelligence is a polygenic trait. That is, several genes, possibly several thousand, affect intelligence. The effect of most individual genetic variants on intelligence is thought to be very small, well below 1% of the variance in g. 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 due to their small effect sizes, more powerful tools of analysis will be required to detect them.[65] 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.[49] Several candidate genes have been proposed to have a relationship with intelligence.[66][67] However, a review of candidate genes for intelligence published in Deary, Johnson & Houlihan (2009) 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".[68]

A 2005 literature review article by Sternberg, Grigorenko and Kidd 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".[69] Hunt (2010), p. 447 and Mackintosh (2011), p. 344 concurred, both noting that while several environmental factors have been shown to influence the IQ gap, the evidence for a genetic influence has been circumstantial, and according to Mackintosh negligible. Mackintosh, however, suggests that it may never become possible to account satisfyingly for the relative contributions of genetic and environmental factors.

Heritability within and between groups

Intelligence as tested by IQ tests is generally considered to be highly heritable. Psychometricians have found that intelligence is substantially heritable within populations, with 30–50% of variance in IQ scores in early childhood being attributable to genetic factors in analyzed US populations, increasing to 75–80% by late adolescence.[18][68] In biology heritability is defined as the ratio of variation attributable to genetic differences in an observable trait to the trait's total observable variation. The heritability of a trait describes the proportion of variation in the trait that is attributable to genetic factors within a particular population. A heritability of 1 indicates that variation correlates fully with genetic variation and a heritability of 0 indicates that there is no correlation between the trait and genes at all. In psychological testing heritability tends to be understood as the degree of correlation between the results of a test taker and those of their biological parents. However, since high heritability is simply a correlation between traits and genes, it does not describe the causes of heritability which in humans can be either genetic or environmental.

In regards to the IQ gap the question becomes whether racial groups can be shown to be influenced by different environmental factors that may account for the observed differences between them. Jensen originally argued that given the high heritability of IQ the only way that the IQ gap could be explained as caused by the environment would be if it could be shown that all blacks were subject to a single "x-factor" which affected no white populations while affecting all black populations equally.[70]

Jensen has also argued that heritability of traits rises with age as the genetic potential of individuals becomes expressed. The IQ gap between white and black test takers has been shown to appear gradually, with the gap widening as cohorts reach adulthood. This he sees as a further argument in favor of Spearman's hypothesis (see section below).

Dickens and Flynn argued that the conventional interpretation ignores the role of feedback between factors, such as those with a small initial IQ advantage, genetic or environmental, seeking out more stimulating environments which will gradually greatly increase their advantage, which, as one consequence in their alternative model, would mean that the heritability figure is only in part due to direct effects of genotype on IQ.[71][72][73]

Spearman's hypothesis

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Spearman's hypothesis states that the magnitude of the black-white difference in tests of cognitive ability is entirely or mainly a function of the extent to which a test measures general mental ability, or g. The hypothesis was first formalized by Arthur Jensen who devised the statistical Method of Correlated Vectors to test it. Jensen holds that if Spearman's hypothesis holds true then some cognitive tasks have a higher g-load than others, and that these tasks are exactly the tasks in which the gap between Black and White test takers are greatest. Jensen, and other psychometricians such as Rushton and Lynn, take this to show that the cause of g and the cause of the gap are the same—genetic differences.[11]

Mackintosh (2011), pp. 338–39 acknowledges that Jensen and Rushton have shown a modest correlation between g-loading, heritability, and the test score gap, but he does not accept that this demonstrates a genetic origin of the gap. He points out that it is exactly in those the tests that Rushton and Jensen consider to have the highest g-loading and heritability such as the Wechsler that has seen the highest increases due to the Flynn effect. This suggests that they are also the most sensitive to environmental changes. And in turn if the highly g-loaded tests are both more liable to environmental influences and as Jensen argues the ones where the black-white gap is most pronounced, it suggests in fact contrary to Jensen's argument that the gap is most likely caused by environmental factors. Mackintosh also argues that Spearman's hypothesis, which he considers to be likely to be correct, simply shows that the test score gap is based on whatever cognitive faculty is central to intelligence - but not what this factor is. Nisbett et al. (2012), p. 146 make the same point, noting also that the increase in the IQ scores of Black test takers is necessarily also an increase in g.

James Flynn (2012), pp. 140–1 argues that there is an inherent flaw in Jensen's argument that the correlation between g-loadings, test scores and heritability support a genetic cause of the gap. He points out that as the difficulty of a task increases a low performing group will naturally fall further behind, and heritability will therefore also naturally increase. The same holds for increases in performance which will first affect the least difficult tasks, but only gradually affect the most difficult ones. Flynn thus sees the correlation between in g-loading and the test score gap to offer no clue to the cause of the gap.[74]

Hunt (2010), p. 415 states that many of conclusions of Jensen, and his colleagues rest on the validity of Spearman's hypothesis, and the method of correlated vectors used to test it. Hunt points out that other researchers have found this method of calculation to produce false positive results, and that other statistical methods should be used instead. According to Hunt, Jensen and Rushton's frequent claim that Spearman's hypothesis should be regarded as empirical fact does not hold, and that new studies based on better statistical methods are required to confirm or reject the hypothesis that the correlation between g-loading, heritability and the IQ gap is due to IQ gaps consisting mostly of g.

Adoption studies

A number of studies have been done on the effect of similar childhood conditions on children from different races. That is, studies concerning whether adopted children perform more like their biological families or their adopted ones. (The former would suggest that genetic factors are more important than environmental ones; the latter would suggest the opposite). However, given the differing heritability estimates in medium-high SES and low-SES families, Nisbett et al. (2012), pp. 134 argue that adoption studies will generally overstate the role of genetics because they represent a restricted set of environments, mostly in the medium-high SES range.

The Minnesota Transracial Adoption Study (1976) examined the IQ test scores of 122 adopted children and 143 nonadopted children reared by advantaged white families. The children were restudied ten years later.[75][76][77] The study found higher IQ for whites compared to blacks, both at age 7 and age 17.[75] Rushton & Jensen (2005) cite the Minnesota study as providing support to a genetic explanation. However, citing confounding factors, the authors of the study deny that it could support either genetic or environmental theories.[78]

Eyferth (1961) studied the out-of-wedlock children of black and white soldiers stationed in Germany after World War 2 and then raised by white German mothers and found no significant differences.

Tizard et al. (1972) studied black (African and West Indian), white, and mixed-race children raised in British long-stay residential nurseries. Three out of four tests found no significant differences. One test found higher scores for non-whites.

Moore (1986) compared black and mixed-race children adopted by either black or white middle-class families in the United States. Moore 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 vs 104), and argued that differences in early socialization explained these differences.

Rushton and Jensen have argued that unlike the Minnesota Transracial Adoption Study, these studies did not retest the children post-adolescence when heritability of IQ would be higher.[15][17] Nisbett (2009, p. 226) however say that the difference in heritability between ages 7 and 17 are quite small, hence this is no reason to disregard Moore's findings.

Frydman and Lynn (1989) showed a mean IQ of 119 for Korean infants adopted by Belgian families. After correcting for the Flynn effect, the IQ of the adopted Korean children was still 10 points higher than the indigenous Belgian children.[79][11][80]

Racial admixture studies

African Americans typically have ancestors from both Africa and Europe. (On average, 20% of their genome is inherited from European ancestors.[81]) If racial IQ gaps have a partially genetic basis, one might expect blacks with a higher degree of European ancestry to score higher on IQ tests than blacks with less European ancestry, because the genes inherited from European ancestors would likely include some genes with a positive effect on IQ.[82] Geneticist Alan Templeton has argued that an experiment based on the Mendelian "common garden" design where specimens with different hybrid compositions are subjected to the same environmental influences, would be the only way to definitively show a causal relation between genes and IQ.

Studies have employed different ways of measuring or approximating relative degrees of ancestry from Africa and Europe. One set of studies have used skin color as a measure, and other studies have used blood groups. Loehlin (2000) surveys the literature and argues that the blood groups studies may be seen as providing some support to the genetic hypothesis, even though the correlation between ancestry and IQ was quite low. He finds that studies by Eyferth (1961), Willerman, Naylor & Myrianthopoulos (1970) did not find a correlation between degree of African&/European ancestry and IQ. The latter study did find a difference based on the race of the mother, with children of white mothers with black fathers scoring higher than children of black mothers and white fathers. Loehlin considers that such a finding is compatible with either a genetic or an environmental cause. All in all Loehlin finds admixture studies inconclusive and recommends more research.

Another study cited by Rushton & Jensen (2005), and by Nisbett et al. (2012), was Moore (1986), which found that adopted mixed-race children's has test scores identical to children with two black parents - receiving no apparent "benefit" from their white ancestry. Rushton and Jensen find admixture studies to have provided overall support for a genetic explanation though this view is not shared by Loehlin (2000), Nisbett (2009),Hunt (2010), Mackintosh (2011), nor by Nisbett et al. (2012). Reviewing the evidence from admixture studies Hunt (2010) considers it to be inconclusive because of too many uncontrolled variables.

Mental chronometry

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Mental chronometry measures the elapsed time between the presentation of a sensory stimulus and the subsequent behavioral response by the participant. This reaction time (RT) is considered a measure of the speed and efficiency with which the brain processes information.[83] Scores on most types of RT tasks tend to correlate with scores on standard IQ tests as well as with g, and no relationship has been found between RT and any other psychometric factors independent of g.[83] The strength of the correlation with IQ varies from one RT test to another, but Hans Eysenck gives 0.40 as a typical correlation under favorable conditions.[84] According to Jensen individual differences in RT have a substantial genetic component, and heritability is higher for performance on tests that correlate more strongly with IQ.[85] Nisbett argues that some studies have found correlations closer to 0.2, and that the correlation is not always found.[86]

Several studies have found differences between races in average reaction times. These studies have generally found that reaction times among black, Asian and white children follow the same pattern as IQ scores.[87][88][89] Rushton & Jensen (2005) have argued that reaction time is independent of culture and that the existence of race differences in average reaction time is evidence that the cause of racial IQ gaps is partially genetic instead of entirely cultural. Responding to this argument in Intelligence and How to Get It, Nisbett has pointed to the Jensen & Whang (1993) study in which a group of Chinese Americans had longer reaction times than a group of European Americans, despite having higher IQs. Nisbett also mentions findings in Flynn (1991) and Deary (2001) suggesting that movement time (the measure of how long it takes a person to move a finger after making the decision to do so) correlates with IQ just as strongly as reaction time, and that average movement time is faster for blacks than for whites.[90] Mackintosh (2011), p. 339 considers reaction time evidence unconvincing and points out that other cognitive tests that also correlate well with IQ show no disparity at all, for example the habituation/dishabituation test. And he points out that studies show that rhesus monkeys have shorter reaction times than American college students, suggesting that different reaction times may not tell us anything useful about intelligence.

Brain size

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A number of studies have reported a moderate statistical correlation between differences in IQ and brain size between individuals in the same group.[91] [92] And some scholars have reported differences in average brain sizes between Africans, Europeans and Asians. [93] J. P. Rushton has argued that Africans on average have smaller brain cases and brains than Europeans, and that Europeans have smaller brains than East Asians, and that this is evidence that the gap is biological in nature. Critics of Rushton have argued that Rushton's arguments rest on outdated data collected by unsound methods.[94] However, recent reviews by Nisbett et al. (2012b) and Mackintosh (2011) have concluded that current data does show an average difference in brain size and head-circumference between American Blacks and Whites, although they question whether this is related to the IQ gap. Nesbitt et al. argue that crude brain size is unlikely to be a good measure of IQ; for example, brain size also differs between men and women, but without well documented differences in IQ. Additionally, newborn black children have the same average brain size as newborn whites, which suggests that the difference in average size could be accounted for by differences in postnatal environment. Several factors that reduce brain size have been demonstrated to disproportionately affect Black children.[95]

Earl Hunt states that brain size has a correlation of about .35 with intelligence among whites and cites studies showing that genes may account for as much as 90% of individual variation in brain size. According to Hunt, racial differences in average brain size could potentially be an important argument for a genetic contribution to racial IQ gaps. However, Hunt notes, Rushton's head size data would account for a difference of .09 standard deviations between Black and White average test scores (the observed difference is 1.0 SD). [71][96]

Criticism

Some critics have questioned the methodology of the studies utilized to measure human intelligence. Other critics have argued that race does not exist. There are also critics who contend that IQ does not measure intelligence accurately, or does not measure it at all.

See also

References

  1. Jackson & Weidman 2004, p. 116.
  2. Pickren & Rutherford 2010, p. 163.
  3. Shurkin 2006.
  4. Jensen 1969, p. 82.
  5. Tucker 2002.
  6. Wooldridge 1995.
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  8. Alland 2002, pp. 79–80.
  9. Herrnstein & Murray 1994.
  10. Cite error: Invalid <ref> tag; no text was provided for refs named Maltby.2C_Day_.26_Macaskill_2007
  11. 11.0 11.1 11.2 Rushton & Jensen 2005.
  12. Cite error: Invalid <ref> tag; no text was provided for refs named Ludy_2006
  13. Rouvroy 2008, p. 86
  14. Nisbett 2009, pp. 209–36
  15. 15.0 15.1 Rushton & Jensen 2010
  16. 16.0 16.1 16.2 Nisbett et al. 2012.
  17. 17.0 17.1 17.2 Rushton & Jensen 2005
  18. 18.0 18.1 18.2 18.3 18.4 Neisser et al. 1996 "The differential between the mean intelligence test scores of Blacks and Whites (about one standard deviation, although it may be diminishing) does not result from any obvious biases in test construction and administration, nor does it simply reflect differences in socio-economic status. Explanations based on factors of caste and culture may be appropriate, but so far have little direct empirical support. There is certainly no such support for a genetic interpretation. At present, no one knows what causes this differential."
  19. Gottfredson 1997
  20. 20.0 20.1 Roth et al. 2001
  21. Dickens & Flynn 2006.
  22. Neisser, Ulric (Ed). 1998. The rising curve: Long-term gains in IQ and related measures. Washington, DC, US: American Psychological Association
  23. Rushton & Jensen 2006.
  24. Murray 2006.
  25. Wicherts, Dolan & van der Maas 2009.
  26. Lua error in package.lua at line 80: module 'strict' not found.
  27. Richardson 2004
  28. Hunt & Wittmann 2008
  29. Irvine 1983
  30. Irvine & Berry 1988 a collection of articles by several authors discussing the limits of assessment by intelligence tests in different communities in the world. In particular, Reuning (1988) describes the difficulties in devising and administering tests for Kalahari bushmen.
  31. Mackintosh 1998, p. 174: "Despite widespread belief to the contrary, however, there is ample evidence, both in Britain and the USA, that IQ tests predict educational attainment just about as well in ethnic minorities as in the white majority."
  32. Mackintosh 2011, p. 348.
  33. Neisser et al. 1996.
  34. Ogbu 1978.
  35. Ogbu 1994.
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  38. D. C. Rowe. (1994). The Limits of Family Influence: Genes, Experience and Behaviour. Guilford Press. London
  39. Lua error in package.lua at line 80: module 'strict' not found.
  40. Lua error in package.lua at line 80: module 'strict' not found.
  41. 41.0 41.1 Bellinger, Stiles & Needleman 1992
  42. MMWR 2005
  43. 43.0 43.1 Campbell et al. 2002
  44. Ivanovic et al. 2004
  45. Saloojee & Pettifor 2001
  46. Qian et al. 2005
  47. The Lancet Series on Maternal and Child Undernutrition, 2008.
  48. Nisbett 2009, p. 101
  49. 49.0 49.1 Cooper 2005
  50. Mackintosh 2011, pp. 343–44.
  51. Behrman, Alderman & Hoddinott 2004
  52. Lua error in package.lua at line 80: module 'strict' not found.
  53. Lua error in package.lua at line 80: module 'strict' not found.
  54. Eppig, Fincher & Thornhill 2010
  55. Eppig 2011
  56. Manly et al. 2002 and Manly et al. 2004
  57. Mickelson 2003
  58. Elhoweris et al. 2005
  59. Miele 2002, p. 133
  60. Lua error in package.lua at line 80: module 'strict' not found.
  61. Lua error in package.lua at line 80: module 'strict' not found.
  62. Daley & Onwuegbuzie 2011.
  63. Lua error in package.lua at line 80: module 'strict' not found.
  64. Lua error in package.lua at line 80: module 'strict' not found.
  65. Plomin, Kennedy & Craig 2005, p. 513
  66. Zinkstok et al. 2007
  67. Dick et al. 2007
  68. 68.0 68.1 Deary, Johnson & Houlihan 2009
  69. Sternberg, Grigorenko & Kidd 2005, p. 46.
  70. Lua error in package.lua at line 80: module 'strict' not found.
  71. 71.0 71.1 Hunt & Carlson 2007.
  72. Nisbett 2009, p. 212.
  73. Dickens & Flynn 2001.
  74. Flynn 2010.
  75. 75.0 75.1 Weinberg, Scarr & Waldman 1992
  76. Scarr & Weinberg 1976.
  77. Loehlin 2000, p. 185.
  78. Scarr & Weinberg 1990.
  79. Loehlin 2000, p. 187.
  80. Lua error in package.lua at line 80: module 'strict' not found.
  81. Bryc et al. 2009
  82. Loehlin 2000.
  83. 83.0 83.1 Jensen 2006
  84. Eysenck 1987
  85. Jensen 1998
  86. Nisbett 2009
  87. Lynn & Vanhanen 2002.
  88. Jensen & Whang 1993.
  89. Pesta & Poznanski 2008.
  90. Nisbett 2009, pp. 221–2.
  91. Deary, Penke & Johnson 2010.
  92. McDaniel 2005.
  93. Ho et al. 1980.
  94. Lieberman 2001.
  95. Nisbett et al. 2012b.
  96. Hunt 2010, pp. 433–434.

Bibliography

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External links