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Race and intelligence research investigates differences in the distributions of cognitive skills among human races. Debates in popular science and academic research over the possible connection of race and intelligence, originally as a comparison of African Americans and Caucasians in the United States, but later extended to other races and regions of the world. In the US, intelligence quotient (IQ) tests have consistently demonstrated statistical differences: the scores of the African American population are on average lower than that of the White American population; the Asian American population on average scores higher; Amerinds scores on average fall between Caucasian and African American scores. Similar findings have been reported for 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. The distribution of IQ scores has considerable range - individuals in every racial group may have IQ's that lie anywhere on the spectrum of scores. These difference show primarily in aggregate studies.

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. This claim 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 American Psychological Association has concluded that the racial IQ gap is not the result of bias in the content or administration of tests, but that no adequate explanation of it has so far been given.[1]

History

Main article: History of the race and intelligence controversy

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 educational psychologist Arthur Jensen published a long article reviving the older hereditarian point of view, with the suggestion that eugenics was more likely to increase the average intelligence in the US than remedial education for blacks. His 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 the publication in 1994 of The Bell Curve, a book by Richard Herrnstein and Charles Murray reviving the hereditarian viewpoint once more. It provoked not only the publication of several interdisciplinary books on the environmental point of view, some in popular science, but also 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 psychologists, some of whom are supported by the Pioneer Fund. [2] [3] [4] [5] [6] [7] [8] [9]

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:[1][10][11][12]

  • 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. Such self-reports are surprisingly accurate.[13] 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.[14]

Gaps are seen in other tests of cognitive ability or aptitude, including university admission exams, military aptitude tests and employment tests in corporate settings.[15]

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,[16][17] tend to score worse on average than White populations but better on average than Black populations.[15] East Asian populations score higher on average than White populations in the United States as they do elsewhere.[13]

Racial differences in IQ scores are observed around the world.[18][19][20] Richard Lynn has estimated East Asians (105), Whites (102), Amerindians (87), Non-Bushmen sub-Saharan Africans (67).[21][20][22][19] International achievement test scores, including TIMSS and PISA, have also been used to estimate average IQ worldwide with similar results where data is available.[23][24][25]

Debate assumptions

Race and intelligence involves debate over the links, if any, between race and intelligence. This research is grounded in two controversial assumptions:

Both assumptions are disputed.[26][27][28][29]

This complex context sets the background for the controversies of research in race and intelligence and has created a generally hostile research environment with scientists on both sides accusing the others of being politically motivated. Scientists in favor of the hereditarian view may accuse their opponents of being motivated by a liberal ideology and of willfully ignoring facts, whereas the proponents of an environmental explanation of the racial gap accuse their opponents of consciously or unconsciously perpetuating racist ideologies and for being poor and unethical scientists.[30]

Methodology

A host of factors, both genetic and environmental, influence the intelligence of individuals. This means that the difficulties of constructing a research model that isolates the factors of race and intelligence from other possible factors of influence are great. Often failures to exclude relevant outside factors in experimental designs has been the driving force in the development of new research methods. Development of research designs is often a cyclical process in which a study shows an intelligence difference between two racial groups and subsequently critics suggest non-genetic factors that may account for the gap and a new research design must be developed to remove the possible influence of that factor.

The research strategy for demonstrating that a factor explains the gap is relatively simple: (1) Identify and reliably measure a factor that co-varies with race. (2) Control for the factor. (3) See if the gap diminishes (in which case the factor explains the gap) or remains (in which case the factor does not explain the gap).

At least two methods exist for controlling factors that co-vary with race. The first constrains participant selection so that members of all races are equal on the factor in question. For example, if a researcher thinks education is the explanation for the gap, then he or she could compare the IQs of only similarly-educated members of each group. Showing that the gap is zero for blacks and whites (e.g.) matched on education levels would be compelling evidence that education is the cause of the gap. Showing that the gap still remains here would make it unlikely (but not impossible) that education differences across race explain the gap.

The second method is similar to the first, but uses statistics (rather than participant selection) to control the factor. For example, suppose a researcher hypothesizes that income differences which co-vary with race explain the IQ gap. A simple study could be designed where the incomes for blacks and whites are measured, together with their IQs. Via statistics like multiple and partial regression, income can then be statistically equated across members of both groups. If the black/white difference on IQ test scores diminishes (or reduces to zero), income would be a parsimonious explanation for the gap. Conversely, if the gap remains, it is unlikely (but not impossible) that income explains the race difference on IQ test scores.

Debate overview

Richard Nisbett,[31][32] in replying to hereditarian arguments,[33][34][35][36][37] structures the debate into several major areas.

Heritability

Main article: Heritability of IQ
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.

Heritability is a basic concept in population genetics that measures the degree to which variation among individuals is due to inherited factors. Heritability applies to variation within a population, that is, a group sharing the same environment. This is because environment must be kept constant for heritability to be measured. For example, imagine that the height of "ordinary genetically varied corn" is 100% heritable when grown in a uniform environment. Further imagine that two populations of corn are grown: one in a normal nutrient environment and the other in a deficient nutrient environment. Consequently, the average height of the corn grown in the deficient nutrient environment is less than the average height of the corn grown in the normal environment. In such a scenario, the within-group heritability of height is 100% in both populations, but the substantial difference between groups are due entirely to environmental factors. With respect to the Black-White IQ gap, Jensen suggests that effects associated with racism (both overt and institutionalized racism) might be X-factors. Flynn believes that attributing the B-W gap to the effects of racism is incorrect, because the most plausible ways in which discrimination could affect IQ are themselves common environmental factors. These may include psychological effects such as stereotype threat; biological effects such as poor nutrition, health care and living close to toxic environments; and educational effects such as a lack of good schools. Instead, Flynn and his colleague William Dickens have developed more complicated models to explain the black-white gap in terms of environmental factors. One initial motivation of the Dickens-Flynn theory was Flynn's observation that IQ test scores have been rising over time in countries around the world – termed the Flynn effect. Flynn and others believe an explanation for the Flynn effect may elucidate the cause of the B-W gap. Jensen and others disagree.

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.[38]

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?[39]

The alternative to common environmental factors is the hypothesis that the racial IQ gap can be accounted for by X-factors: factors which vary between groups but not within groups. 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.[40]


Environmental factors including lead exposure[41], breast feeding[42], and nutrition[43][44] can significantly affect cognitive development and functioning. For example, iodine deficiency causes a fall, in average, of 12 IQ points [45]. 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.[46]

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.[47] 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. However, these improvements may have stalled for people born after the early 1970s.[48]

Flynn effect

Main article: Flynn effect

Although modern IQ tests are unbiased[49], 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)[50] 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."[51]

African IQ

The very low IQ scores reported for sub-Saharan African populations (average of 70) are controversial.[52][53][54]

g loading

Main article: general intelligence factor
An illustration of Spearman's two-factor intelligence theory. Each small oval is a hypothetical mental test. The blue areas show the variance attributed to s, and the purple areas the variance attributed to g.

The general intelligence factor (abbreviated g) is a controversial construct used in the field of psychology (see also psychometrics) to quantify what is common to the scores of all intelligence tests. It was discovered in 1904 by Charles Spearman and subsequently developed in a theory in 1923.

Spearman, who was an early psychometrician, found that schoolchildren's grades across seemingly unrelated subjects were positively correlated, and proposed that these correlations reflected the influence of a dominant factor, which he termed g for "general" intelligence. He developed a model where all variation in intelligence test scores can be explained by two factors. The first is the factor specific to an individual mental task: the individual abilities that would make a person more skilled at one cognitive task than another. The second is g, a general factor that governs performance on all cognitive tasks.

Across a battery of tests, the size of the Black-White gap is correlated with the extent to which the tests measure g.[55]

Nisbett[31] writes:

Herrnstein and Murray (1994) and Rushton and Jensen (2005) argue that because blacks and whites differ more in their performance on items and subtests that have higher g loadings (correlations with the g factor), this is evidence of the biological, genetic nature of the black white difference in IQ.

Nisbett finds this argument unpersuasive, noting that

The g loadings of subtests do not differ that much, the g loading of a particular subtest cannot be construed as evidence about the degree to which the subtest measures strictly biological or hereditary differences as opposed to environmentally produced differences, and the scores for blacks have improved almost as much on a g-weighted IQ test as on a non-g-weighted test.

Brain size

Main article: Neuroscience and intelligence

On average, the brains of African-Americans are 5% smaller than the brains of Whites and 6% smaller than Asians, according to studies of brain weight at autopsy, endocranial volume of empty skulls, head size measurments by the U.S. military and NASA, and two dozen MRI volumetric studies[56][57][58][59][60]. 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.[61] Rushton and Jensen disagree, citing several studies of malnourished 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. [62] [63]

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”.[64]

Much of the research into the neuroscience of intelligence has involved indirect approaches, such as searching for correlations between psychometric test scores and variables associated with the anatomy and physiology of the brain. Historically, research was conducted on non-human animals or on postmortem brains. More recent studies have involved non-invasive techniques such as MRI scans as they can be conducted on living subjects. MRI scans can be used to measure the size of various structures within the brain, or they can be used to detect areas of the brain that are active when subjects perform certain mental tasks.

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.[65] 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."[66]

A study on twins showed that frontal gray matter volume was correlated with g and highly heritable.[67] 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.[68]

Reaction time

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 2 seconds typically allow for strategic differences among people which 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.

Regression toward the mean

Galton’s Law of Ancestral Heredity is a principle of genetics which describes the degree to which the offspring, parents, or siblings of an individual will regress towards the mean of its population for any quantifiable genetic trait.

Arthur Jensen has tested this theory as it applies to the racial IQ gap, by matching black and white children for IQ and comparing the IQs of their siblings. This study found that black children regress towards their population mean IQ of 85, while white children regress to the mean of 100; i.e. black children with an IQ of 120 would tend to have siblings with an average IQ of around 100, while white children with a 120 IQ would have siblings averaging close to 110.[69] According to Jensen, this result is consistent with the theory that genetic factors contribute to the difference in average IQ between races, while it is difficult to explain why environmental factors would cause IQ variance within families to differ in this way between races.[70] Richard Nisbett recognizes the existence of this effect, but believes that it could be produced by environmental factors alone, such as parenting practices and subculture pressures.[71]

Structural equation modeling provides a more rigorous way to analyze regression patterns among siblings, as well as other aspects of gene-environment architecture. These studies have concluded that the model which best fit their results were those in which the genetic and environmental contributions to the IQ gap were approximately equal, with the difference in average IQ scores being due 50% to environmental and 50% to genetic factors.[72]

Adoption studies

The Minnesota Transracial Adoption Study examined the IQ test scores of 130 black/interracial children adopted by advantaged White families.[73][74][75] 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.[76][77][78]

Children's background Age 7 Corrected IQ Age 17 Corrected IQ
Non adopted, with two white biological parents 110.5 105.5
Adopted, with two white biological parents 111.5 101.5
Adopted, with one white and one black biological parent 105.4 93.2
Adopted, with two black biological parents 91.4 83.7
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
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

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 which are the result of 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.[35]

See also

Notes

  1. ^ a b Neisser, U., Boodoo, G., Bouchard, T. J. Jr., Boykin, A. W., Brody, N., Ceci, S. J.; et al. (1996). "Intelligence: Knowns and unknowns" (PDF). American Psychologist. 51: 77–101. {{cite journal}}: Explicit use of et al. in: |author= (help)CS1 maint: multiple names: authors list (link) "African American IQ scores have long averaged about 15 points below those of Whites, with correspondingly lower scores on academic achievement tests. In recent years the achievement-test gap has narrowed appreciably. It is possible that the IQ-score differential is narrowing as well, but this has not been clearly established. The cause of that differential is not known; it is apparently not due to any simple form of bias in the content or administration of the tests themselves. The Flynn effect shows that environmental factors can produce differences of at least this magnitude, but that effect is mysterious in its own right. Several culturally-based explanations of the Black/White IQ differential have been proposed; some are plausible, but so far none has been conclusively supported. There is even less empirical support for a genetic interpretation. In short, no adequate explanation of the differential between the IQ means of Blacks and Whites is presently available."
  2. ^ Benjamin, Ludy T. (2006), Brief History of Modern Psychology, Wiley-Blackwell, pp. 188–191, ISBN 140513206X
  3. ^ Hothersall, David (2003), History of Psychology (4th ed.), McGraw-Hill, pp. 440–441, ISBN 0072849657
  4. ^ Lynn, Richard (2001), The science of human diversity: a history of the Pioneer Fund, University Press of America, ISBN 076182040X
  5. ^ Mackintosh, N.J. (1998), IQ and Human Intelligence, Oxford University Press, ISBN 019852367X
  6. ^ Maltby, John; Day; Macaskill, Ann (2007), Personality, Individual Differences and Intelligence, Pearson Education, ISBN 0131297600 {{citation}}: Unknown parameter |furst2= ignored (help)
  7. ^ Richards, Graham (1997), Race, racism, and psychology: towards a reflexive history, Routledge, ISBN 0415101417
  8. ^ Tucker, William H. (2002), The Funding of Scientific Racism: Wickliffe Draper and the Pioneer Fund, University of Illinois Press, ISBN 0252027620
  9. ^ Wooldridge, Adrian (1995), Measuring the Mind: Education and Psychology in England c.1860-c.1990, Cambridge University Press, ISBN 0521395151
  10. ^ David J. Bartholomew (2004). Measuring Intelligence: Facts and Fallacies. Cambridge University Press. ISBN 0521544785.
  11. ^ Ian J. Deary (2001). Intelligence: A Very Short Introduction. Oxford University Press. ISBN 0192893211.
  12. ^ N. J. Mackintosh (1998). IQ and Human Intelligence. Oxford University Press. ISBN 019852367X.
  13. ^ a b Earl Hunt and Jerry Carlson (2007). "Considerations Relating to the Study of Group Differences in Intelligence". Perspectives on Psychological Science. 2 (2): 194-213."Nevertheless, self-identification is a surprisingly reliable guide to genetic composition. Tang et al. (2005) applied mathematical clustering techniques in order to sort genomic markers for over 3,600 people in the United States and Taiwan into four groups. There was almost perfect agreement between cluster assignment and individuals’ self-reports of racial/ethnic identification as White, Black, East Asian, or Latino."
  14. ^ James R. Flynn (2007). What Is Intelligence? Beyond the Flynn Effect. Cambridge University Press. ISBN 0521880076.
  15. ^ a b Attention: This template ({{cite doi}}) is deprecated. To cite the publication identified by doi: 10.1111/j.1744-6570.2001.tb00094.x, please use {{cite journal}} (if it was published in a bona fide academic journal, otherwise {{cite report}} with |doi= 10.1111/j.1744-6570.2001.tb00094.x instead.
  16. ^ Attention: This template ({{cite doi}}) is deprecated. To cite the publication identified by doi:10.1080/00207596608247156, please use {{cite journal}} (if it was published in a bona fide academic journal, otherwise {{cite report}} with |doi=10.1080/00207596608247156 instead.
  17. ^ Attention: This template ({{cite doi}}) is deprecated. To cite the publication identified by doi:10.1080/00207596808246642, please use {{cite journal}} (if it was published in a bona fide academic journal, otherwise {{cite report}} with |doi=10.1080/00207596808246642 instead.
  18. ^ "We should accept, then, without further ado that there is a difference in average IQ between blacks and white." Mackintosh (1998), page 150.
  19. ^ a b Lynn, R. and Vanhanen, T. (2002). IQ and the wealth of nations. Westport, CT: Praeger. ISBN 0-275-97510-X
  20. ^ a b Lynn, R. (2006). Race Differences in Intelligence: An Evolutionary Analysis. Washington Summit Books. {{cite book}}: Unknown parameter |isbd= ignored (help)
  21. ^ Lynn, R. (1991). "Race Differences in Intelligence: A Global Perspective" (PDF). Mankind Quarterly. 31: 255–296. {{cite journal}}: Cite has empty unknown parameter: |month= (help)
  22. ^ Attention: This template ({{cite doi}}) is deprecated. To cite the publication identified by doi: 10.1016/j.paid.2005.10.004, please use {{cite journal}} (if it was published in a bona fide academic journal, otherwise {{cite report}} with |doi= 10.1016/j.paid.2005.10.004 instead.
  23. ^ Rindermann, H. (2006). What do international student assessments measure?. Psychologische Rundschau, 57, 69–86.
  24. ^ Attention: This template ({{cite doi}}) is deprecated. To cite the publication identified by doi:10.1016/j.intell.2007.09.003, please use {{cite journal}} (if it was published in a bona fide academic journal, otherwise {{cite report}} with |doi=10.1016/j.intell.2007.09.003 instead.
  25. ^ Attention: This template ({{cite doi}}) is deprecated. To cite the publication identified by doi: 10.1016/j.intell.2006.06.001, please use {{cite journal}} (if it was published in a bona fide academic journal, otherwise {{cite report}} with |doi= 10.1016/j.intell.2006.06.001 instead.
  26. ^ American Anthropological Association (1994), Statement on "Race" and Intelligence, retrieved March 31, 2010
  27. ^ Steven Rose (2009). "Darwin 200: Should scientists study race and IQ? NO: Science and society do not benefit". Nature. 457: 786–788. doi:10.1038/457786a.
  28. ^ Stephen Ceci and Wendy M. Williams (2009). "Darwin 200: Should scientists study race and IQ? YES: The scientific truth must be pursued". Nature. 457: 788–789. doi:10.1038/457788a.
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  30. ^ Vogel, Friedrich & Arno G. Motulsky Human genetics: problems and approaches, Springer, 1997 p. 708
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  33. ^ Jensen, Arthur (1969). "How Much Can We Boost IQ and School Achievement?". Harvard Educational Review. 39: 1–123. "So all we are left with are various lines of evidence, no one of which is definitive alone, but which, viewed all together, make it a not unreasonable hypothesis that genetic factors are strongly implicated in the average Negro-white intelligence difference. 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."
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  38. ^ Reviewed in Neisser et al. (1996). Data from the NLSY as reported in figure adapted from Herrnstein and Murray (1994), p. 288.
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  49. ^ "Despite widespread belief to the contrary, however, there is ample evidence, both in Britain and the USA, that IQ tests predict educational attaintment just about as well in ethnic minorities as in the white majority." Mackintosh (1998), page 174.
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References

Main article: Race and intelligence (References)
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