Many IQ advocates argue that a general index of cognitive ability is the single best predictor of virtually all criteria considered necessary for success in life in the Western part of the developed world (Jensen, 1998; Schmidt, Ones & Hunter, 1992), and maintain that the average undergraduate, “those who graduate from college or university”, must possess an IQ that is no lower than 115 (Ostrowsky, 1999; Gottfredson, 1998), while individuals who are able to obtain a graduate level degree must on average, possess an IQ in the range of 125 (Gottfredson, 1998). This often serves the implied purpose of suggesting that blacks and other minorities can not go on to, or graduate from institutions of higher learning - and ultimately move on to professional careers and economic success – and that this is not because of matters relating to personal interest, financial ability, or the quality of schooling received in the past, but instead because of factors relating to IQ (e.g. Jensen, 1969; Gottfredson, 1998). These arguments also tend to base themselves within the tiresome framework of nature vs. nurture; in this case, does more school develop high IQ, or does a high IQ equal more school and greater opportunity (Jensen, 1998)? To put it another way, these researchers believe that a student’s level of academic attainment is predestined by their genes.

AFRICAN BLACKS SIGNIFICANTLY EXCEED WHITES IN EDUCATIONAL ATTAINMENT AND PROFESSIONAL EMPLOYMENT:

African-born blacks comprise 16 percent of the U.S. foreign-born black population and are considerably more educated than other immigrants (U.S. Bureau of the Census, 2000). The vast majority of these immigrants come from minority white countries in East and West Africa (e.g. Kenya and Nigeria), and less than 2 percent originate from North or South Africa (World Factbook, 2004; Yearbook of immigration Statistics, 2003). In an analysis of Census Bureau data by the Journal of Blacks in higher education, African immigrants to the United States were found more likely to be college educated than any other immigrant group, which included those from Europe, North America and Asia (also see Nisbett, 2002; U.S. Bureau of the Census, 2000). African immigrants have also been shown to be more highly educated than any native-born ethnic group including white and Asian Americans (Logan & Deane, 2003; Williams, 2005; The Economist, 1996; Arthur, 2000; Selassie, 1998; Nisbett, 2002).

Most data suggest that between 43.8 and 49.3 percent of “all” African immigrants in the United States hold a college diploma (Nisbett, 2002; Charles, 2007; U.S. Census, 2000). This is slightly more than the percentage of Asian immigrants to the U.S., substantially greater than the percentage of European immigrants, nearly “double” that of native-born white Americans, nearly four times the rate of native-born African Americans, and more than “8 times” that of some Hispanic groups (Williams, 2005; Nisbett, 2002; The Journal of Blacks in Higher Education, 1999-2000; U.S. Census, 2000).

Black immigrants from Africa have also been shown to have rates of college graduation that are “more” than double that of the U.S.-born population, in general (Williams, 2005). For example, in 1997, 19.4 percent of all adult African immigrants in the United States held a “graduate degree”, compared to 8.1 percent of adult whites (a difference of “more than” double) and 3.8 percent of adult blacks in the United States, respectively (The Journal of Blacks in Higher Education, 1999-2000). This shows that America has an equally large achievement gap between white Americans and African born immigrants as between native born white and black Americans.

In the UK, 1988, the Commission for Racial Equality conducted an investigation on the admissions practices of St. George's, and other medical colleges, who set aside a certain number of places for minority students. This informal quota system reflected the percentage of minorities in the general population. However, minority students with Chinese, Indian, or black African heritage had higher academic qualifications for university admission than did whites (Blacks in Britain from the West Indies had lower academic credentials than did whites). In fact, blacks with African origins over the age of 30 had the highest educational qualifications of any ethnic group in the British Isles. Thus, the evidence pointed to the fact that minority quotas for University admissions were actually working against students from these ethnic groups who were on average more qualified for higher education than their white peers (Cross, 1994; Also see, Dustmann, Theodoropoulos, 2006).

Dustmann and Theodoropoulos (2006) provide a first thorough investigation of educational attainment and economic behavior of ethnic minority immigrants and their children in Britain. They studied how British born minorities perform in terms of education, employment and wages, when compared to their parent generation as well as to comparable groups of white natives, using 27 years of LFS data (Labour Force Survey). In terms of educational attainment their results showed a strong educational background for Britain’s ethnic minority immigrant population. In addition, they showed that second generation ethnic minorities do better than their parents, and substantially better than their white peers! For both generations Black Africans topped the list in both years of schooling/educational qualifications and wages/employment (ibid).

Again, when comparing immigrants in the United States one quickly finds that the racialist models adopted by many Psychologists do not always predict outcomes in the way one might expect. For example, it has been shown that black immigrants born from Zimbabwe (96.7 percent), Botswana (95.5 percent) have high school graduation rates that far exceed all white immigrant and native born groups. While the average Nigerian immigrant (58.6 percent) living in the United States is “eight times” more likely to have obtained a bachelors degree than the average Portuguese born (7.3 percent) (Dixon D, 2006; Dixon D, 2005)!

The African born in the United States are concentrated in management or professional and sales or office-related occupations. Of the employed population age 16 and older in the civilian labor force, the African born are much more likely than the foreign born in general to work in management and professional occupations as well as sales and office occupations (i.e. clerical/administrative). Additionally, the African born are less likely to work in service, production, transportation, material moving, construction, and maintenance occupations than the foreign born in general (Dixon D, 2006). In the UK a study by Dr Yaojun Li, from Birmingham University, and Professor Anthony Heath, from Oxford University, found that Africans are more likely to be in professional and managerial jobs than white British men, with a large proportion, about 40%, holding these positions (Li and Heath, 2006).

BLACK AFRICAN EDUCATIONAL ATTAINMENT AND THEIR IMPLICATIONS FOR IQ:

The presented information above suggests that African born blacks residing in western countries as a group possess IQs that are between 5 points and a full standard deviation (15 IQ points) above that of whites living in these countries (see, Gottfredson, 1998; Ostrowsky, 1999; Richardson, 2002; Cross, 1994; Williams, 2005; Nisbett, 2002) - This is especially true for those in the United States and in the UK. One may also expect to find, according to much of the corroborative literature that relates IQ with education, approximately twice the number of African born immigrants with IQs in the 115 range, than among the general white American population (Gottfredson, 1998; Ostrowsky, 1999; Williams, 2005; Nisbett, 2002), and “more” than twice the number of African immigrants in the 125 IQ range (see Gottfredson, 1998; Nisbett, 2002; The Journal of Blacks in Higher Education, 1999-2000).

For example, in the United States, African born blacks and their offspring have been reported to exceed American born whites in several socio-economic indicators - particularly in the areas of educational attainment and occupational status - in ways that resemble the gaps observed between native born white and black Americans, in the same indicators (Nisbett, 2002; Charles, 2007; Le, 2007; Le, 2007; US Census Bureau, Census 2000. "5% Public Use Microdata Sample.").

Some advantages to using academic attainment comparisons for the analysis of major group differences in IQ in Western industrialized nations are that they provide very big numbers, with sample sizes often in the hundreds of thousands, that are genuinely random; and consequently specific ethnicities can be compared with statistical confidence. The differences in overall educational attainment observed between African born blacks in the United States and native born white Americans are quite spectacular! Indeed, if one chooses to adopt the hereditarian thinking of Jensen (1998), Herrnstein and Murray (1994) or Gottfredson (1998), these disparities become suggestive of underlying intelligence differences between the two populations; with these differences in strong “favor” of African born blacks. Though higher cognitive indices are said by some to be predictive of more educational achievements and more education predictive of higher intellectual outcomes (e.g., Brody, 1997; Ceci & Williams, 1997), so that there are reciprocal relationships. Most who study African immigrants attribute their inclination toward academic attainment to be the result of positive cultural factors (Arthur, 2000; Selassie, 1998).

In the United States today, most claims regarding intelligence differences between ethnic populations in relationship to IQ are based on statistically derived data relating to scholastic aptitude tests and academic achievement (e.g. Flynn, 2002). Keeping this in mind, and acknowledging the superior educational attainment of most African blacks in the united states (and elsewhere), it can thus be argued, because of their higher educational levels, that they must also be expected to pass far more (in number), and more difficult scholastic aptitude tests, which would require higher level IQs (see Gottfredson, 1998; Ostrowsky, 1999). Moreover, as whites on average do not, or are unable to attain the same levels of academic achievement within these (their own!) institutional frameworks they must also, by racialist thinking, possess significantly lower cogitative indices on the group level (e.g. Jensen, 1998; Gottfredson, 1986). In fact, attainment differences of these magnitudes would suggest that (American) whites are at an intellectual handicap when matched against black African immigrants.

African born blacks residing in Western countries tend also to be concentrated in higher level professional occupations, which are considered by many to be more cognitively demanding, requiring more intellectual ability (Jensen, 1998; Gottfredson, 1986; Herrnstein and Murray, 1994), than the average occupations of either American or British born whites (Dixon, 2006; Li and Heath, 2006). According to IQ advocates and social Darwinists, alike, these occupational differences should also indicate higher levels of intelligence among black African immigrants than among whites (e.g. Gottfredson, 1986; Jensen 1998). In fact, as virtually all IQ tests in popular use today are designed specifically for the purposes of predicting academic success and occupational status, it could thus be argued that the west’s hereditarian “Cognitive Elite” (discussed in “The Bell Curve”) are best described as black men and women from Africa. That is, if we assume the outcome measure of IQ tests to be a truly independent measure, and that a positive correlation between IQ tests and the criterion establishes predictive validity.

Something else to note, according to the New York Times (Roberts, 2005), for the first time in history more blacks are coming to the United States from Africa than during the entire span of the transatlantic slave trade. Immigration figures show that since 1990 more Africans have arrived voluntarily than the total who disembarked in chains before the United States outlawed international slave trafficking in 1807. For example, research shows that around 15% of Ghana’s 20million citizens live aboard (Owusu-Ankomah 2006). Similar trends can be observed among other African states. In other words: black African achievement can not simply be dismissed as that of a “small group” of elites entirely unrepresentative of the greater continent. Moreover, the academic attainment and occupational achievements of black Africans are not only documented in the United States, but also the UK (Li and Heath, 2006; Dustmann, Theodoropoulos, 2006) and Canada (Guppy and Davies, 1998; Boyd, 2002).

CULTURE, RACE AND INTELLIGENCE TESTING:

It is taken for granted by many in the United States and much of the developed world, that children who do well on standardized tests are intelligent. However, different cultures have their on views of what intelligence is (Sternberg, 2007; Cole, 1990; Cole et al. 1971; Greenfield). In this respect children that are considered intelligent may vary from one culture to another, along with the acts that constitute intelligent behavior (Sternberg, 2007). It has been said, for example, that the comparison of IQ scores of different nationalities or cultural groups is, at best, a hazardous enterprise, to be undertaken with caution and humility, and at worst, a nonsensical and mischievous waste of time (Mackintosh, 1998). Cronbach (1949/1970, p. 182) states that IQ tests require experience common to the (mainstream) US culture and is of dubious value for comparing cultural groups. In addition, there are countless empirical and theoretical studies that thoroughly debunk the suspicious racial thinking involved in IQ testing; with good examples being Schonemann (1997a; 1997c) and Guttman (1992).

In spite of this, few researchers attempt to provide examples where the disadvantaged or culturally distinct groups actually do better on standardized measures than do members of the more culturally dominant group, who impose these kinds of measures. In addition, few researchers will apply standardized measures that are either preferred or devised in favor of those who must operate within more informal sectors and/or economically disadvantaged circles to members of the more dominant or mainstream group and/or formal sectors, in order to provide balance. It has been shown, for example, that tests which are highly novel in one culture or subculture may be quite familiar in the next (Valsiner, 2000). For example, unschooled subjects will fail at classification tasks characteristic of school learning contexts and succeed with classification relevant to their everyday practical experience (Cole, 1990; Cole et al. 1971). That is, even if components of information processing are the same, the experiential novelty to which they are applied may be different (Valsiner, 2000). People will be good at doing the things that are important to them and that they have opportunities to do often.

An example of this phenomenon can be seen in a study by Serpell R. (1979), in which Zambian and English children were asked to reproduce patterns in three media: wire models, clay models, or pencil and paper. The Zambian children excelled in the wire medium with which they were familiar, while the English children were best with pencil and paper. Both groups performed equally well with clay. Thus, children performed better with materials that were more familiar to them, from their own environments. Carraher, Carraher, and Schliemann (1985) studied a group of Brazilian children and found that the same children who were able to do the mathematics needed to run their street businesses were little able to do the same mathematics when presented in a more formal (grade schooling) context.

Cole et al (1971) studied a tribe in Africa: The Kpelle tribe. In this study adults were asked to sort items into categories; however, rather than producing taxonomic categories (e.g. "fruit" for apple), Kpelle participants sorted items into functional groups (e.g. "eat" for apple). After trying and failing to teach them to categorize items taxonomically they were asked as a last resort how a “stupid” person would do the task. At that point, according to the researchers, without any hesitation, the Kpelle sorted the items into taxonomic categories (Cole et al., 1971)! Demonstrating that not only where these participants able to do the presented tasks, but in their own culture, what was considered intelligent by western standards was believed to be “stupid.”

Crawford-Nutt (1976) found that African black students enrolled in westernized schools scored higher on progressive matrix tests than did American white students. The study was meant to examine perceptual/cultural differences between groups, and demonstrated that one’s performance on western standardized tests correspond more closely with the quality and style of schooling that one receives more so than other factors. Buj (1981) also showed Ghanaian adults in one study to score higher on a supposedly ‘culture fair’ intelligence test than did Irish adults; scores were 80 (Ghanaian) and 78 (Irish), respectively. Shuttleworth-Edwards et al (2004) conducted a study with black South Africans between the ages of 19–30, where highly significant effects for both level and quality of education within groups whose first language was an indigenous black African language, was revealed. Black African first language groups (as well as white English speaking groups) with advantaged education were comparable with the US standardization in IQ test scores (e.g. WAIS-III).

In another study, Serpell et al (2006) took 162 low-income African American and white fourth graders and randomly assigned them to ethnically homogeneous, communally structured groups of three to work on a motion acceleration task using either computer simulation or physical tools; or to a control group that did not participate in the learning activities. The results of this study showed African American and White students to perform equally well on the test of initial learning, with both groups scoring significantly higher than the control group. However, African Americans’ transfer outcomes were superior to those of their White counterparts (Serpell et al., 2006). This study demonstrated empirically that not only do African American children learn as well as white children, but that they also exceeded white children in their ability to transfer learned abilities to real tasks.

In the United States, when matched for IQ with Whites, American Blacks show superior “Working Memory” (Nijenhuis et al., 2004); an interesting finding, as African Americans are typically taught by less qualified teachers than their white counterparts and are provided with less challenging school work (Hallinan 1994; Diamond et al., 2004). In Chicago, for example, the vast majority of schools placed on academic probation as part of the district accountability efforts were majority African-American and low-income (Diamond and Spillane 2004). Educational inequality is primarily a consequence of housing. Since the majority of states determine school funding based on property taxes, schools in wealthier neighborhoods receive more funding per student. As home values in white neighborhoods are higher than minority neighborhoods, local schools receive more funding via property taxes (Kelly, 1995).

Studies have also shown that up to 99% of group IQ score differences between black and white Americans are eliminated after controlling simply for cultural factors. For example, Manly et al (1998) found in an empirical research study, that after cultural factors such as linguistic behavior (e.g. black vs. standard English) are taken into consideration between healthy black and white Americans that IQ score differences, particularly on the Wais-R (Wechsler Adult Intelligence Scale--Revised), become statistically insignificant in all but one area (a reading section)! Other studies also show similar results after controlling for cultural factors. Fagan and Holland (2002) found that where exposure to specific information was required; whites knew more about the meanings of different sayings than did Blacks (due to exposure). But, when comprehension was based on generally available information, Whites and Blacks did not differ (Fagan and Holland, 2002). This study also found that when Blacks and Whites are matched as to comprehension of sayings requiring specific knowledge that Blacks were superior to Whites on intelligence tests (ibid).

Williams and Rivers (1972b) showed that test instructions in Standard English penalized the black child and that if the language of the test is put in familiar labels, without training or coaching, the black child’s performances on the tests increase significantly. It has also been pointed out that ideally a child’s language development should be evaluated in terms of his progress toward the norms for his particular speech community (Cadzen, 1966). This kind of evaluation is rarely, if ever, done with respect to African Americans. For example, studies using sentence repetition tasks have found that, at both third and fifth grades, white subjects repeat Standard English sentences significantly more accurately than black subjects, while black subjects repeated nonstandard English sentences significantly more accurately than white subjects (Marwit et al, 1977), however, students in American school are only tested in Standard English, which puts African Americans at a disadvantage.

Teng and Manly (2005) argue that tests developed for members of the majority culture are often inappropriate for ethnic minorities, especially those who speak a different language, have little or no formal education, and grow up in vastly different circumstances (see also, Williams, 1972). These researchers argue further that variables that directly affect test performance, such as education and acculturation instead of race or ethnicity, should be considered as explanatory variables for test performance (Teng and Manly, 2005). One research team, for example, found that discrepancy in reading and education level was associated with worse psychological test performance, while racial/ethnic minority status was not (Ryan et al 2005)! That is, after reading and education levels are accounted for, there is no difference in IQ and other tests scores between blacks and whites (ibid).

Barnes (1972) noted that the Stanford-Binet, and the Wisc IQ tests are examples of “Culture specific tests”, and that the culture in this instance is what is frequently referred to as “white middle class.” Lyman (1970) designed a cross cultural test called the “American Cross Culture Ethnic Nomenclature Test”, or “ACCENT.” The instrument contained 20 black biased and 20 white biased items. In one experiment this test was administered to 110 undergraduates (91 whites and 19 blacks). It was found that the black participants out performed the white participants, with blacks obtaining a mean of 15.3 on the black items and 11.1 on the white items, while white subjects obtained a mean of 12.7 on the white items and 8.3 on the black items. The results indicate that when blacks and whites are tested cross-culturally, blacks may outperform whites.

There is also evidence showing that traditional psychological assessment is based on skills that are considered important within white, western, middle-class culture, but which may not be salient or valued within African-American culture (Helms, 1992; Helms, 1997; Hilliard, 1995). When test stimuli are more culturally pertinent to the experiences of African Americans, performance improves (Hayles, 1991; Williams and Rivers, 1972b). Research shows, for example, that “Black Culture” depicts problem solving as an integrative hemispheric endeavor rather than a linear, analytical process (Bell, 1994), and that in this culture "psychological closeness" is necessary for one’s involvement in the phenomena which he seeks to understand. It has also been shown that culturally diverse learners are often excluded in educational programs through misidentification, misassessment, miscategorization, misplacement, and misinstruction-misintervention (Obiakor and Utley, 2004). Kwate (2001) provides evidence that IQ tests are antagonistic and incompatible with an African centered conception of intelligence and mental health.

There are undoubtedly very strong cultural biases built into IQ tests (Helms 1992, 1997; Richardson, 2002, 2000; Kwate, 2001). IQ tests were originally created to simply identify individuals who had already been deemed ‘intelligent’ by other more subjective criteria (Richarson, 2002; Richardson, 2000). These criteria often involved “norm-referencing”, as well as the personal opinions and biases of the test designers. In norm-referenced tests, items which do not discriminate between preselected groups are rejected or simply thrown out (Williams, 1972). In this respect, not only will one find examples of cultural bias built into IQ tests, but also, “observer bias.”

Psychometric theory states that differences in raw test scores (eg, IQ-scores) of different groups cannot be used to infer group differences in theoretical attributes (e.g. intelligence) unless the test scores accord with a particular set restrictions (Borsboom, 2006). Namely, the same attribute must relate to the same set of observations in the same way in each group (Borsboom, 2006; Mellenbergh, 1989). Weschler (1944) “himself” warned that his Weschler Bellevue test norms were to be used exclusively for the white population, stating: “Our norms cannot be used for the colored population of the United states. Though we have tested a large number of colored persons, our standardization is based upon white subjects only (pg. 107).” This not only renders most psychometric restrictions violated, but also calls into serious question the WISC’s usefulness, cross-culturally. In fact, virtually all IQ tests in common use today were designed for the purpose of evaluating people from only one cultural setting, and do not include materials that consider the culture, values or dialectal differences of those from communities outside of the reference group: which is usually what is referred to as “white middle class,” (see also, Richarson, 2002; Greenfield, 1997; Sternberg, 2004; Valsiner, 2000; Kwate, 2001; Helms, 1992; Helms, 1997), and thus group differences in test scores can in many instances be irrelevant.

DO IQ TESTS REALLY MEASURE... STUPIDITY?

Research has shown that IQ test scores tend to correlate negatively with scores of practical intelligence (Sternberg, 2001, 2004). Practical intelligence can be described as a person’s ability to apply learned skills and knowledge to everyday, real life tasks; or how to handle challenging situations. There is currently a lot of evidence demonstrating IQ tests to be unable to gauge a person’s overall potential or aptitude for learning (see Bradshaw, 2001; Siegel, 1989; Sternberg & Grigorenko, 2002a). What this means essentially is that a person who scores unusually high on an IQ test may not be a great learner (Sternberg, 2001). In fact, high scoring individuals may actually be demonstrating deficits in other areas; particularly in areas involving adaptive behavior or “practical intelligence” (See Sternberg, 2001).

It may also be argued based on the negative correlations observed between Practical Intelligence and IQ scores that those who score moderately or even very poorly on IQ tests may possess important strengths elsewhere. These strengths would relate more closely with adaptive kinds of behaviors and the application of learned skills and knowledge to real life tasks. These practical skills in addition to their full learning capabilities would place people of high Practical intelligence at a distinct advantage over high IQ individuals with respect to most important real life everyday tasks. This is because high IQ individuals demonstrate strengths in relationship to the acquisition and retention of knowledge, but are usually weak when it comes to putting this knowledge to use in real life practical ways; this is essentially the difference between knowing and doing. Co-incidentally, practical kinds of skills are of the kind that most Anthropologists and paleoanthropologists credit with helping to make the human species so evolutionarily formidable (Tattersall and Scwartz 2000; Kuhn and Stiner 1998).

Empirical research has shown Practical intelligence to be a better predictor of numerous real life outcomes. For example, Chawarski (2002), found that among scientists immigrating to Israel from the USSR those who were rated highest on levels of practical intelligence tended to adapt better than those who were not. Moreover, higher practical intelligence tended to predict overall success in research and development jobs; with correlations at times reaching as high as .60 (Chawarski, 2002). Correlations this high are rarely if ever obtained with IQ tests with respect to any criteria, be they academic or real life (Schonemann, 1997c; Bradshaw, 2001). Another study found that teachers of high practical intelligence were rated more effective by their school principals and were better able to handle problematic situations (Grigorenko et al, 2006). While Sternberg (2001) reported that among academics, measures of practical intelligence predict productivity, citation rates, and quality ratings of the institution at which one is teaching over and above those obtained from IQ tests (2001).

A study by Bilali? et al (2007) found when an elite subsample of 23 children was tested for IQ that their scores were not a significant factor in chess skill, and that, if anything, IQ tended to correlate negatively with chess skill. The study demonstrated the dangers of focusing on a single factor in complex real-world situations where a number of closely interconnected factors operate. It has been argued, for example, that IQ test scores are little more than examples of developed competencies (Sternberg, 2001); much like this particular chess study has shown of chess skill.

FORMAL STUDIES OF COGNITIVE ABILITY IN ATHLETES:

Literature on covert orienting in various athlete groups points to four general findings. First, effects of voluntary covert orienting are usually smaller in magnitude for highly skilled athletes than for less skilled athletes or nonathletes, and this has been given a variety of interpretations, including that athletes are able to distribute their attention more effectively over multiple locations (Nougier et al., 1991; Nougier et al., 1989). Eric et al (2006) preformed two experiments investigating the perceptual processes employed during same/different judgment tasks in professional athletes and novice athletes. It was found that the eye movements of experts (i.e., number of fixations and fixation duration) were “consistent” across discrepant source and target conditions where the number of displaced elements was manipulated. In contrast, novices “decreased” the number of fixations employed as the number of elements displaced increased. Manipulation of target presentation confirmed that recognition was viewpoint dependent for both expert and novice players. The degradation in performance was accompanied by a change in the visual search behaviors employed by experts, which confirmed the strength of the search–cognition–performance links (Ibid).

Kioumourtzoglou et al (1998) conducted a laboratory study with a group of 13 men on an elite male national team of basketball players, between the ages of 22 and 23 years; and a control group of 15 men of equal age (physical education class) to assess differences in their scores on cognitive skills (memory-retention, memory-grouping analytic ability), perceptual skills (speed of perception, prediction, selective attention, response selection), and motor skills (dynamic balance, whole body coordination, wrist-finger dexterity, rhythmic ability). Their analysis showed that elite male basketball players scored higher on hand coordination and lower on dynamic balance given their anthropometric measurements (mainly height). Elite players were better on memory-retention, selective attention, and on prediction measures than the control group. The above skills are important in basketball performance (ibid).

In 1973 while 11.1 per cent of the United States population was black, about a quarter of all major league baseball players, a third of all pro football players and two thirds of all pro basketball players were black (Scully, 1973). Black players also appeared to earn more than white players in these sports (ibid), which would suggest a superior athlete. In more recent years it has been shown that while African Americans make up approximately 12.5% of the American population, they comprise nearly 79 per cent of pro Basketball players, close 67 per cent of pro football players and are dramatically overrepresented among professional boxing champions and other professional athletes.

Studies of reaction time in athletes and non athletes generally find athletes to out perform non athletes in these tasks. Reaction time is believed to be a good indicator of performance in sports (Kaur et al, 2006). This may explain why Blacks athletes can be found overrepresented in many of the world’s most highly selective high performance sports (e.g. Football and Basketball). Kaur et al (2006), found quicker reaction times in athletes as compared to control groups, and attributed this to improved concentration, alertness, better muscular co-ordination and improved performance in speed and accuracy tasks among athletes (Kaur et al, 2006). Kamin (1995) reported that in tasks of choice reaction time, blacks in 2 out of three studies out performed white individuals.

Studies also find that black infants demonstrate superior psychomotor development when compared with white infants (Super, 1976; Wilson 1978). This may be interpreted as being indicative of superior neurological development, as delayed psychomotor development is often associated with developmental defects. For example, Walter et al (1989) found that infants with Iron Deficiency Anemia tended to do poorly on body balance-coordination skills when compared with controls. While Autti-Rämö and Granström (1991) found that infants exposed to intrauterine alcohol experienced delayed psychomotor development. Psychomotor vigilance performance is said to be important to athletic performance. Studies investigating motor development have also found black boys to be superior to white children in overall motor abilities (Wilson 1978; DiNucci, 1975).

Molecular genetic studies also show that people of African descent generally possess higher levels of genetic variation and heterozygosity than do people of other backgrounds (Vigilant et al. 1991; Nei et al. 1993; Cavalli-Sforza et al. 1991; Deka et al. 1995b; Jorde et al. 1997; Lohmueller et al, 2008). Heterozygosity is thought to enhance resistance of hosts to infectious diseases, offers a greater degree of fitness for one or the other allele, and improves overall health (Gangestad & Buss 1993, Thornhill & Gangestad 1993). This may explain some of the difference observed in motor development between blacks and whites in younger ages. Africans have also been shown to possess the largest total number of alleles, as well as the largest number of unique alleles for most systems (Jorde et al, 2000). Surveys of 2000 databaseascertained insertion/deletion polymorphisms also show a pattern of higher ancestral allele frequencies in African populations (Weber et al. 2002). These genetic advantages, along with long hours of practice and dedication, may contribute to some of the observed superior performance among black athletes in a number of the world’s most highly selective athletic arenas.

Researchers continue to examine the distinctiveness of motor performance by dark- versus light-eyed individuals. For example, it has been shown that Dark-eyed individuals generally perform better at reactive type tasks, while light-eyed individuals perform better at ‘some’ self-paced tasks (Miller et al, 1992; Beer and Fleming, 1988; Rowe and Evans, 1994; Beer and Beer, 1989). Strange as this research may seem, Beer and Fleming (1988) using multiple regression analysis, found that dark-eyed students hit a target with a frisbee more times than did light-eyed students. While Rowe and Evans (1994) had College students (61 men, 64 women) perform a forehand rally with different colored racquetballs. Eye color, sex, and total hits were recorded for each subject. Men scored significantly better with balls of each color than did women. Dark-eyed men performed better than other subjects and performance was better with blue balls than yellow or green balls. Other research shows that children with blues eyes tend also to be more timid and socially un savvy in preschool than children with darker eyes (Moehler et al, 2006; Coplan et al, 1998), and are more susceptible to alcohol abuse at later ages (Bassett and Dabbs, 2001).

Bredin et al (2005), in an experiment of cognitive ability in athletes and non athletes, examined subjects’ ability to walk when blindfolded to a previously seen target. In the two groups of healthy volunteers: 21 athletes and 20 non-athletes. Subjects were asked to walk at three different velocities (slow, normal, and fast) to a target (10 m in front of them) that they had seen before being blindfolded. Increase in velocity was associated with a decrease in the distance walked for both groups. Both groups were accurate at normal velocities; however, athletes were also accurate at fast velocities whereas non-athletes undershot the target.

Other cognitive studies argue the following: athletes possess superior visual abilities to nonathletes; elite athletes possess visual abilities superior to those of ordinary athletes; and, athletes, in particular those participating in fast paced sports involving resolution of detail at high speed, might have innately superior DVA (dynamic visual acuity) or might have developed superiority through repeated practice (Blundel, 1985; Ishigaki and Miyao; Long and Riggs, 1991; Bahill and La Ritz, 1984).

Referenced literature:

Alan H. Goodman , Deborah Heath , M. Susan Lindee et al (2003).Genetic Nature/Culture Anthropology
and Science beyond the Two-Culture Divide (see Chapter 13 p 268). UNIVERSITY OF CALIFORNIA PRESS

Arthur, John (2000). Invisible Sojourners: African Immigrant Diaspora in the United States. Prager Westport, CT.

Bahill AT, La Ritz T. (1984). Why can't batters keep their eyes on the ball? American Scientist 1984 72 249-253.

Baldwin J.A., Bell Y.R. (1985). The African Self-Consciousness Scale: An Africentric Personality Questionnaire. Western Journal of Black Studies, v9 n2 p61-68 Sum 1985

Barnes, E. (1972). I.Q. Testing and Minority Children: Imperatives for Change, 1972. National Leadership Institute Teacher Education/Early Childhood. The University of Connecticut, Technical paper, pp. 1-8.

Bassett J.F. and Dabbs Jr J.M. (2001). Eye color predicts alcohol use in two archival samples. Personality and Individual Differences Volume 31, Issue 4, 5 September 2001, Pages 535-539

Beer J, Beer J. (1989). Relationship of eye color to winning horseshoe pitching contests. Percept Mot Skills. 1989 Feb;68(1):136-8.

Beer J, Fleming P. (1988). Effects of eye color on frisbee toss. Percept Mot Skills. 1988 Apr;66(2):675-6.

Bernstein L, Ross RK, Judd H, et al (1986). Serum testosterone levels in young black and white men. J Natl Cancer Inst 76:45—48, 1986

Bilali? M., McLeod P., and Gobet F. (2007). Does chess need intelligence? - A study with young chess players. Intelligence Volume 35, Issue 5, September-October 2007, Pages 457-470

Bloch GJ & Gorski RA. (1988) Estrogen/progesterone treatment in adulthood affects the size of several components of the medial preoptic area in the male rat. Journal of Comparative Neurology 1988 275 613–622.

Blundell NL. (1985). The contribution of vision to the learning and performance of sports skills: Part 1: The role of selected visual parameters. The Australian Journal of Science and Medicine in Sport September 1985 249-253.

Borsboom D. (2006). When Does Measurement Invariance Matter? Medical Care • Volume 44, Number 11 Suppl 3, November 2006

Boyd, M. (2002). Educational Attainments of Immigrant Offspring: Success or Segmented Assimilation? International Migration Review 36 (Winter): 1037-1060.

Buj, V. (1981). "Average IQ values in various European countries." Personality and Individual Differences, 2:168-169.

Braaten E.B., Norman D. (2006). Intelligence (IQ) Testing. Pediatrics in Review. 2006;27:403-408

Brace C.L, Nelson A.R., Seguchi N, Oe H., Sering L., Qifeng P., Yongyi L., and Tumen D (2001). Old World sources of the first New World human inhabitants: A comparative craniofacial view. PNAS August 14, 2001 u vol. 98 u no. 17 u 10017–10022

Bradshaw, J. (2001). Developmental Disorders of the Fronto-Striatal System. Philadelphia: Psychiatric Press.

Branda, R. F. and J. W. Eaton (1978) Skin color and nutrient photolysis: an evolutionary hypothesis. Science 201, 625-626.

Bredin J., Kerlirzin Y., Israël I. (2005) . Path integration: is there a difference between athletes and non-athletes? Experimental Brain Research Volume 167, Number 4 / December, 2005

Brody, N. (1997). Intelligence, schooling, and society. American Psychologist, 52, 1046–1050.
Capron C., Adrian R. Vetta, Michel Duyme, and Atam Vetta (1999). Misconceptions of biometrical IQists. Current Psychology of Cognition 1999, 18 (2), 115-160

Capron C, & Vetta A (2001) Familial studies: genetic inferences. International Encyclopedia of the Social and Behavioral Sciences, 8, 5259-5265

Carraher, T. N., Carraher, D., & Schliemann, A. D. (1985). Mathematics in the streets and in schools. British Journal of Developmental Psychology, 3, 21–29.

Cavalli-Sforza LL, Bowcock AM, Kidd JR, Mountain JL, Hebert JM, Carotenuto L, Kidd KK, (1991) Drift, admixture, and selection in human evolution: a study with DNA polymorphisms. Proc Natl Acad Sci USA 88:839–843

Ceci, S. J., & Williams, W. M. (1997). Schooling, intelligence, and income. American Psychologist, 52, 1051–1058.

Charles C.Z, Massey, D.S., Mooney, M. and Kimberly C. Torres, (2007). Black Immigrants and Black Natives Attending Selective Colleges and universities in the United States. American Journal of Education 113 (Feb. 2007)

Chawarski M.C. (2002). Individual differences in practical intelligence and success in immigration. Intelligence Volume 25, Issue 2, 1997, Pages 83-92

Cole, M. (1990). Cognitive development and formal schooling: The evidence from cross-cultural research. In L. C. Moll (ed.), Vygotsky and Education (pp. 89-110). Cambridge: Cambridge University Press.

Cole, M., Gay, J. Glick, J.A., & Sharp, D.W. (1971). The Cultural context of learning and thinking. New York: Basic Books

Coplan RJ, Coleman B, Rubin KH (1998). Shyness and little boy blue: iris pigmentation, gender, and social wariness in preschoolers. Dev Psychobiol. 1998 Jan;32(1):37-44.

Crawford-Nutt. D. (1976). Are black scores on Raven’s Standard Progressive Matrixes an artifact of method of test presentation? Psychologia Africana, 16, 201-206.

Cronbach, L. J. (1949). Essentials of psychological testing (3rd ed., 1970). New York: Harper International Editions.

Cross, T. (1994). Black Africans Now the Most Educated Group in British Society. The Journal of Blacks in Higher Education, No. 3 (spring, 1994), pp.92-93

Deka R, Jin L, Shriver MD, Yu LM, DeCroo S, Hundrieser J, Bunker CH, et al (1995a). Population genetics of dinucleotide (dC-dA)n.(dG-dT)n polymorphisms in world populations. Am J Hum Genet 56:461–474

Diamond, John B., Antonia Randolph, & James P. Spillane. (2004) "Teachers’ Expectations and Sense of Responsibility for Student Learning: The Implications of School Race, Class, and Organizational Habitus." Anthropology and Education Quarterly, 35(1) 75-98

Diamond, John B. & James P. Spillane. (2004) "High Stakes Accountability in Urban Elementary Schools: Challenging or Reproducing Inequality?" Teachers College Record, Special Issue on Testing, Teaching, and Learning. 106(6): 1140-1171.

DiNucci, James M. (1975). Motor Performance Age and Race Differences between Black and Caucasian Boys Six to Nine Years of Age. The ERIC database, an initiative of the U.S. Department of Education. 1975-02-00

Dixon, D. (2006). Characteristics of the African Born in the United States. Migration Policy Institute. January, 20, 2006

Dixon, D. (2005). Characteristics of the European Born in the United States. Migration Policy Institute. February, 2005

Dustmann, C, Theodoropoulos, N (2006): Ethnic Minority Immigrants and their Children in Britain. Centre for Research and Analysis of Migration, Department of Economics, University College London

Eric L., Paul W., Mark W., Hubert R. (2006). Expertise in basketball modifies perceptual discrimination abilities, underlying cognitive processes, and visual behaviours. Visual Cognition, Volume 13, Number 2, Number 2/January 2006, pp. 247-271(25).

Evans JR. (2003). Risk factors for age-related macular degeneration. Prog Retin Eye Res 2001;20:227–53.

Frank, G., (1983). The Wechsler Enterprise. Pergamum Press, Oxford.

Frayer, D.W. (1984). In The Origins of Modern Humans: A world survey of the Fossil Evidence (eds Smith, F.H. & Spencer, f.) 211-250 (Liss, New York, 1984)

Gangestad SW, Buss DM. 1993. Pathogen prevalence and human mate preferences. Ethol. Sociobiol. 14:89–96

Gardner H. (2000). Intelligence Reframed: Multiple Intelligences for the 21st Century. Basic Books (September 20, 2000)

Guppy, Neil and Scott Davies (1998). Education in Canada: Recent Trends and Future Challenges. Ottawa: Statistics Canada and the Minister of Industry.

Gottfredson, L. S. (1998). The general intelligence factor. Scientific American Presents, 9(4), 24-29.
Gottfredson, L. S. (1986). Societal consequences of the g factor in employment. Journal of Vocational Behavior, 29, 379-410.

Guttman, L.L. (1955). The Determinacy of factor scores matrices with implication for five other basic problems of common factor theory. Br. J. Statistical Psychol. 8, 65-81

Guttman, L. (1992). The irrelevance of factor analysis for the study of group differences. Multivariate Behavioral Research, 27, 175-204

Greenfield, P. M. (1997). You can’t take it with you: Why abilities assessments don’t cross cultures. American Psychologist, 52, 1115– 1124.

Grigorenko E.L., Sternberg R.J and Strauss, S. (2006). Practical intelligence and elementary-school teacher effectiveness in the United States and Israel: Measuring the predictive power of tacit knowledge. Thinking Skills and Creativity Volume 1, Issue 1, April 2006, Pages 14-33

Grigorenko E.L., Jarvin J., and Sternberg R.J. (2002). School-Based Tests of the Triarchic Theory of Intelligence: Three Settings, Three Samples, Three Syllabi. Contemporary Educational Psychology Volume 27, Issue 2, April 2002, Pages 167-208

Hallinan, Maureen T. 1994. “Tracking From Theory to Practice”. Sociology of Education 67:79-84.

Harrison GA. 1992. Human genetics and variation. In: Harrison GA, Tanner JM, Pilbeam DR, Baker PT, editors. Human biology. Oxford: Oxford University Press. p 145–336.

Hayles, V.R. (1991). African American Strengths: a survey of empirical findings. In R.L. Jones (Ed.), Black Psychology (3rd ed., pp. 379-400). Berkeley, CA: Cobb & Henry Publishers.

Helms, J.E. (1997). The triple quandary of race, culture, and social class in standardized cognitive ability testing. In D.P. Flanagan, J.L. Genshaft, & P.L. Harrison (Eds.), contemporary intellectual assessment: theories, tests, and issues (pp.517-532). New York: Guilford Press.

Helms, J.E. (1992). Why is there no study of cultural equivalence in standardized cognitive ability testing? American Psychologist, 47, 1083-1101.

Herlin S.J. (2003). Ancient African Civilizations to ca. 1500. Text Supplement and Study Guide for History/PAS 393

Herrnstein, R., & Murray, C. (1994). The bell curve. New York: Free Press.

Hilliard, Asa G., III (1995), ed. Testing African American students: special reissue of the Negro Educational Review. Chicago: Third World Press.

Hirsch, J. (1970). Behavior-genetic analysis and its biosocial consequences. Seminar in Psychiatry. 89-105

Hirsch J. (2004). Uniqueness, Diversity, Similarity, Repeatability, and Heritability. International Journal of Comparative Psychology, 2004. 17. 304-314.

Horan R.D., Bulte E., Shogren J.F. (2005). How trade saved humanity from biological exclusion: an economic theory of Neanderthal extinction. Journal of Economic Behavior & Organization Volume 58, Issue 1, September 2005, Pages 1-29

Hulshoff Pol H.E., Cohen-Kettenis P.T., Peper J.S., Cahn W. (2006). Changing your sex changes your brain: influences of testosterone and estrogen on adult human brain structure. European Journal of Endocrinology (2006) 155 S107–S114

Ishigaki H, Miyao M. (1994). Implications for dynamic visual acuity with changes in age and sex. Perceptual and Motor Skills 1994. 78 363-369
Jensen, A. R. (1998). The g factor. Westport, CT: Praeger-Greenwood

Joseph, J. (2004). The Gene Illusion: Genetic Research in Psychiatry and Psychology under the Microscope.

Joseph, J. (2006).The Missing Gene: Psychiatry, Heredity, And the Fruitless Search for Genes

Jorde LB, Rogers AR, Bamshad M, Watkins WS, Krakowiak P, Sung S, Kere J, et al (1997). Microsatellite diversity and the demographic history of modern humans. Proc Natl Acad Sci USA 94:3100–3103

Jorde, L.B., Watkins, W.S., Bamshad, M.J., Dixon, M.E., Ricker, C.E., Seielstad, M.T., and Batzer, M.A. (2000). The distribution of human genetic diversity: Acomparison of mitochondrial, autosomal, and Y-chromosome data. Am. J. Hum. Genet. 66: 979–988

Kamin L.J. (1995). Lies, Damn lies and Statistics. The Bell Curve Wars.

Kelly E.E. (1995). All Students Are Not Created Equal: The Inequitable Combination of Property-Tax-Based School Finance Systems and Local Control. Duke Law Journal, Vol. 45, No. 2 (Nov., 1995), pp. 397-435

Kempthorne, O. (1978). Logical, epistomological and Statistical aspects of nature-nurture, Biometrics, 34, 1-23

Kioumourtzoglou E, Derri V, Tzetzis G, Theodorakis Y. (1998). Cognitive, perceptual, and motor abilities in skilled basketball performance. Percept Mot Skills. 1998 Jun; 86 (3 Pt 1):771-86.

Kleinstein R.N,; Jones L.A, Hullett S., Kwon S, Lee R.J., Friedman N.E., Manny R.E., Mutti D.O, et al (2003). Refractive Error and Ethnicity in Children. ARCH OPHTHALMOL/VOL 121, AUG 2003

Kuar P. Paul M., Sandhu J.S. (2006) Auditory and visual reaction time in athletes, healthy controls, and patients of type 1 diabetes mellitus: A comparative study. Int J Diab Dev Ctries, Sept 2006, Vol 26, issue 3

Kuhn, S.L. and M.C. Stiner, (1998). Middle Palaeolithic ’Creativity’: Reflections on an Oxymoron, Chap. 9 in: S. Mithen (ed), Creativity in Human Evolution and Prehistory, London: Routledge, pp. 143-164.

Kwate, N (2001). Intelligence or Misorientation? Eurocentrism in the WISC-III. Journal of Black Psychology, Vol. 27, No. 2, 221-238 (2001)

Lapunzina P (2006) Ultraviolet light-related neural tube defects? Am J Med Genet 1996, 67:106

Lamason RL, Mohideen M, Mest JR, Wong AC, Norton HL, et al. (2005) SLC24A5, a putative cation exchanger, affects pigmentation in zebrafish and humans. Science 310:1782–1786

Lawrence VA (1983). Demographic analysis of serum folate and folate-binding capacity in hospitalised patients. Acta Haematol 1983, 69:289-293

Le, C.N. (2007). "Demographic Characteristics of Immigrants" Asian-Nation: The Landscape of Asian America.

Le, C.N. (2007). "Socioeconomic Statistics & Demographics" Asian-Nation: The Landscape of Asian America.

Lee ST, Nicholls RD, Schnur RE, Guida LC, Lu-Kuo J, Spinner NB, Zackai EH, Spritz RA. Diverse mutations of the P gene among African-Americans with type II (tyrosinase-positive) oculocutaneous albinism (OCA2). Hum Mol Genet. 1994 Nov;3(11):2047-51.

Li, Y. (2006) Labour market trajectories of minority ethnic groups in Britain: 1972-2005, Presentation at the UPTAP Seminar, LGA, London, 28 November

Lidz, T., & Blatt, S. (1983). Critique of the Danish-American studies of the biological and adoptive relatives of adoptees who became schizophrenic. American Journal of Psychiatry, 140, 426-435

Logan, J.R, Deane, G (2003). “Black Diversity in Metropolitan America.” Lewis Mumford Center for Comparative Urban Regional Research University Albany

Lohmueller KE, Indap AR, Schmidt S, Boyko AR, Hernandez RD, Hubisz MJ, Sninsky JJ, White TJ, Sunyaev SR, Nielsen R, Clark AG, Bustamante CD (2008). Proportionally more deleterious genetic variation in European than in African populations. NATURE, Vol 451, 21 February 2008

Long GM, Riggs CA. (1991) Training effects on dynamic visual acuity with free-head viewing. Perception 1991 20 363-371.

Mackintosh, N.J. (1998). IQ and Human Intelligence. Oxford: Oxford University Press.

Maestroni GJ (1993). The immunoneuroendocrine role of melatonin. J Pineal Res. 1993 Jan;14(1):1-10.

Manly, J. J., Miller, S.W. Heaton, R. K., Byrd, D., Reilly J., Velasquez, R. J., Saccuzzo , D. P., Grant I., and The HIV Neurobehavioral research center (HNRC) group (1998). The effect of African-American acculturation on neuropsychological test performance in normal and HIV-positive individuals. Journal of the International Neuropsychological Society (1998), 4: 291-302 Cambridge University Press

Marwit S.J., Walker E.F., Marwit K.L. (1977). Reliability of Standard English Differences among Black and White Children at Second, Fourth, and Seventh Grades. Child Development, Vol. 48, No. 4 (Dec., 1977), pp. 1739-1742

McLachlan R. and Allan C. (2005). Testosterone Deficiency fact sheet. Andrology Australia, funded by the Australian Government Department of Health and Ageing.

Mellenbergh GJ. (1989). Item bias and item response theory. Int J Ed Res. 1989;13:127–143.

Miller LK, Rowe PJ, Lund J. (1992). Correlation of eye color on self-paced and reactive motor performance. Personality and Individual Differences Volume 31, Issue 4, 5 September 2001, Pages 535-539

Mitchell TG, Perfect JR (1995) Cryptococcus in the era of AIDS - 100 years after the discovery of Cryptococcus neoformans. Clin Microbiol Rev 8: 515-548.

Mithen, S., 1998 (Ed). Creativity in Human Evolution and Prehistory, London: Routledge
Murphy, N. B. (1968). Carotid cerebral angiography in Uganda: review of boo consecutive cases. East African M. 7.,1968,45,47-60.

Modi G, Mochan A, Modi M, Saffer D. (2001). Demyelinating disorder of the central nervous system occurring in black South Africans. J Neurol Neurosurg Psychiatry 2001;70:500–505.

Moehler E., Kagan J., Brunner R., Wiebel A., Kaufmann C. and Resch F. (2006). Association of behavioral inhibition with hair pigmentation in a European sample. Biological Psychology Volume 72, Issue 3, June 2006, Pages 344-346

Nei M, Livshits G (1990). Evolutionary relationships of Europeans, Asians, and Africans at the molecular level. In: Takahata N, Crow JF (eds) Population biology of genes and molecules. Baifukan, Tokyo, pp 251–265

Nelson L, et al. (1997). Incidence of idiopathic Parkinson's disease (PD) in a health maintenance organization (HMO): Variations by age, gender, and race/ethnicity. Neurology 1997:A334.

Nijenhuis, J.T., Resing, W., Tolboom, E., and Bleichrodt N. (2004) Short-term memory as an additional predictor of school achievement for immigrant children? Intelligence Volume 32, Issue 2, March-April 2004, Pages 203-213

Nesbitt, N.F. (2002). African Intellectuals in the Belly of the Beast: Migration, Identity and the Politics of Exile. African Issues 30: 1, 2002.

Nougier, Vincent; Ripoll, Hubert; Stein, Jean-François (1989). Orienting of attention with highly skilled athletes. International Journal of Sport Psychology. 1989 Jul-Sep Vol 20(3) 205-223

Nougier, Vincent; Stein, Jean-François; Bonnel, Anne-Marie (1991). Information processing in sport and "orienting of attention." International Journal of Sport Psychology. 1991 Jul-Dec Vol 22(3-4) 307-327

Nottebohm F. (1980). Testosterone triggers growth of brain vocal control nuclei in adult female canaries. Brain Research 1980 189 429.

Obiakor F.E., Utley C.A. (2004). Educating Culturally Diverse Learners with Exceptionalities: A Critical Analysis of the Brown Case. Peabody Journal of Education, Volume 79, Issue 2 March 2004 , pages 141 - 156

O’Brien G. (2001). Defining Learning Disabilities: What place does intelligence testing have now? Developmental Medicine & Child Neurology 2001, 43: 570–573

Ogbu, J.U., Simons, H.D. (1998). Voluntary and Involuntary Minorities: A Cultural-Ecological Theory of School Performance with Some Implications for Education. Anthropology & Education Quarterly, Vol. 29, No. 2 (Jun., 1998), pp. 155-188

Okano Y., Eisensmith R.C., Dasovich M., Wang T., Güttler F., and Woo S. L. C. (1990). A prevalent missense mutation in Northern Europe associated with hyperphenylalaninaemia. European Journal of Pediatrics Volume 150, Number 5 / March, 1991 p. 347-352

Ostrowsky L. (1999). College dropouts and standardized tests. Academic Questions, Springer New York Volume 12, Number 2 / June, 1999

Owusu-Ankomah (2006). Emigration from Ghana: A Motor or Brake for Development. Keynote Address at the 39th Session of the Commission on Population and Development, New York, USA.

Pattillo-McCoy, Mary (1999). Black Picket Fences: Privilege and Peril Among the Black Middle Class. Chicago: University of Chicago Press.

Reed D.H., Frankham R. (2003). Correlation between Fitness and Genetic Diversity. Conservation Biology, Volume 17, Number 1, February 2003, pp. 230-237(8)

Richardson, K. (2000). The Making of Intelligence. New York: Columbia University Press.

Richardson K (2002). What IQ tests test. Theory Psychol 12: 283?314.

Roberts, Sam (2005). More Africans Enter U.S. Than in Days of Slavery. New York Times. February 21, 2005

Roscigno, Vincent, J. 1998. “Race and the Production of Educational Disadvantage.” Social Forces. 76: 1033-60.

Ross, R.K., Coetzee, G. A., Reichardt, J., Skinner, E, and Henderson, B.E. (1995). Does the Racial-Ethnic Variation in Prostate Cancer Risk Have a Hormonal Basis? Cancer, Volume 75, Issue S7 (p 1778-1782)

Ross R.K., Henderson B.E. (1994). Do diet and androgens alter prostate cancer risk via a common etiologic pathway? / Natl Cancer lnst 1994; 86:252-4.

Rowe PJ, Evans P. (1994). Ball color, eye color, and a reactive motor skill. Percept Mot Skills. 1994 Aug;79(1 Pt 2):671-4.

Ryan E.L., Baird R., Mindt M.R., Byrd D. et al (2005). Neuropsychological impairment in racial/ethnic minorities with HIV infection and low literacy levels: Effects of education and reading level in participant characterization. Journal of the International Neuropsychological Society (2005), 11: 889-898 Cambridge University Press

Serpell, R. (1979). How specific are perceptual skills? A cross-cultural study of pattern reproduction. British Journal of Psychology, 70, 365– 380.

Serpell Z.N., Boykin A.W., Madhere S., Nasim A. (2006).The Significance of Contextual Factors in

African American Students’ Transfer of Learning. Journal of Black Psychology, Vol. 32, No. 4, 418-441 (2006)

Scheib J.E., Gangestad S.W., and Thornhill R. (1999). Facial attractiveness, symmetry and cues of good genes. Proc. R. Soc. Land. B (1999) 266, 1913-1917

Schonemann, P.H. (1997b). Some new results on hit-rates and base-rates in mental testing. Chinese J. Psychol, 39, 173-192

Schonemann, P.H. (1997a). The rise and fall of Spearman’s hypothesis. Cahier Psychol. Cognitive/Curr. Psychol. Cognition 16, 788-812.

Schonemann P.H., & Schönemann, R. D. (1994). Environmental versus genetic models for Osborne's personality data on identical and fraternal twins. Cahiers de Psychologie Cognitive - Current Psychology of Cognition 13, 141-167.

Schonemann P.H. (1997c). Models and muddles of Heritability. Genetica 99, 97-108

Schmidt, F.L., Ones, D.S, & Hunter J. (1992). Personnel selection. Annual Review of Psychology.

Scully G.W. (1973). Economic Discrimination in Professional Sports Law and Contemporary Problems, Vol. 38, No. 1, Athletics (Winter - Spring, 1973), pp. 67-84 This article consists of 18 page(s).

Selassie, Bereket H. (1996). Washington’s New African Immigrants. In Urban Odyssey: A Multicultural History of Washington D.C. Francine Cuno Cary, ed. Chapter 15 Smithsonian Institution Press.

Shade, B.J. (1991). African American patterns of cognition. In R.L. Jones (Ed.), Black Psychology (3rd ed., pp. 231-247). Berkeley, CA: Cobb & Henry Publishers.

Shuttleworth-Edwards A., Kemp R., Rust A., Muirhead J., Hartman N., Radloff S. (2004). Cross-cultural Effects on IQ Test Performance: A Review and Preliminary Normative Indications on WAIS-III Test Performance. Journal of Clinical and Experimental Neuropsychology (Neuropsychology, Developm, Volume 26, Number 7, October 2004 , pp. 903-920(18)

Spritz R A, Fukai K., Holmes S A, and Luande J. (1995). Frequent intragenic deletion of the P gene in Tanzanian patients with type II oculocutaneous albinism (OCA2). Am J Hum Genet. 1995 June; 56(6): 1320–1323.

Soejima M. Tachida H., Ishida T., Sano A., Koda Y., (2006). Evidence for Recent Positive Selection at the Human AIM1 Locus in a European Population. Mol. Biol. Evol. 23(1):179–188. 2006

Sternberg, R. J., & Grigorenko, E. L. (1999). A smelly 113° in the shade, or, why we do field research. APS Observer, 12, 1, 10–11, 20–21.

Sternberg, R. J., & Grigorenko, E. L. (2002a). Dynamic testing. New York: Cambridge University Press

Sternberg, R.J., and Williams, W.M. (1997). Does the Graduate Record Examination predict meaningful success in graduate training of psychologists? A case study. American Psychologist 52, 630-641

Sternberg, R. J. (2003a). What is an expert student? Educational Researcher, 32(8), 5–9.

Sternberg, R.J. (2007). Who Are the Bright Children? The Cultural Context of Being and Acting Intelligent. Educational Researcher, Vol. 36, No. 3, 148-155 (2007)

Sternberg, R. J. (1997). Successful intelligence. New York: Plume.

Sternberg, R.J., Torff, B., & Grigrenko, E,L. (1998a). Teaching for successful intelligence raises school achievement. Phi Delta Kappan, 79, 667-669.

Sternberg, R. J. (2001). Intelligence tests as measures of developing expertise. In C. Chiu, F. Salili, & Y. Hong (Eds.) Multiple competencies and self-regulated learning: Implications for multicultural education (pp. 17–27). Greenwich, CT: Information Age Publishing.

Sternberg, R.J. (2001). What should we ask about Intelligence? American Scholar, 65(2), 205–217

Siegel, L. S. (1992). An evaluation of the discrepancy definition of dyslexia. Journal of Learning Disabilities, 25, 618–629

Siegel, L. S. (1989). IQ is irrelevant to the definition of learning disabilities. Journal of Learning Disabilities, 22, 469–478, 486

Super, C. M. (1976). Environmental effects on motor development: The case of African infant precocity. Developmental Medicine and Child Neurology, 18, 561–567.

Williams D.R. (2005). The Health of U.S. Racial and Ethnic Populations. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences 60:S53-S62 (2005)

Tanner C, Goldman S. (1996). Epidemiology of Parkinson's disease. Neurol Clin 1996; 14: 317-335.

Teng, E. L., Manly J.J (2005). Neuropsychological Testing: Helpful or Harmful? Alzheimer Disease & Associated Disorders. 19(4):267-271, October/December 2005.

The Journal of Blacks in Higher Education, No. 26 (Winter, 1999-2000). African Immigrants in the United States are the Nation's Most Highly Educated Group. pp. 60-61doi:10.2307/2999156

The Economist (1996). 339 (7965): 27-28

Thornhill R, Gangestad SW. 1993. Human facial beauty—averageness, symmetry, and parasite resistance. Hum. Nat. Interdiscip. Biosoc. Perspect. 4:237–69

U.S. Bureau of the Census, 2000

US Census Bureau, Census 2000. "5% Public Use Microdata Sample."

Valsiner, J. (2000). Culture and human development. Thousand Oaks, CA: Sage

Vellutino, F. R., Scanlon, D., & Lyon, G. R. (2000). Differentiating between difficult to remediate and readily remediated poor readers: More evidence against the IQ-discrepancy definition of reading disability. Journal of Learning Disabilities, 33, 223–238

Vetta, A. (1976). Correction to Fisher's correlations between relatives and environmental effects. Nature, 263, 316-317.

Vetta A. 2002. Discussion on Statistical Modelling and Analysis of Genetic Data. J. Roy. Statist. Soc. B. 64. 741-742.

Vickers J. (2007). Perception, Cognition, and Decision Training - The Quiet Eye in Action. Human Kinetics. Publishers; 1 edition (July 30, 2007)

Vigilant L, Stoneking M, Harpending H, Hawkes K,
Wilson AC (1991) African populations and the evolution of human mitochondrial DNA. Science 253:1503–1507

Voight BF, Kudaravalli S, Wen X, Pritchard JK (2006) A map of recent positive selection in the human genome. PLoS Biol 4(3): e72.

Vorobey P, Steindal AE, Off MK, Vorobey A, Moan J. (2006). Influence of human serum albumin on photodegradation of folic acid in solution. Photochem Photobiol. 2006 May-Jun;82(3):817-22

Wahlsten, D. (1981) Review of The IQ Game by Howard F. Taylor. Behaviorists for Social Action Journal, 3, 33-34.

Watkins, W.S, Pradipta K. Das, Mark A. Batzer and Lynn B. JordeE. Brassington, Marion L. Carroll, Son V. Nguyen, Jerilyn A. Walker, B.V. Ravi Prasad, P. Govinda Reddy, Alan R. Rogers, Christopher T. (2003). Genetic Variation Among World Populations: Inferences From 100 Alu Insertion Polymorphisms. Genome Res. 13:1607-1618, 2003

Weber, J.L., David, D., Heil, J., Fan, Y., Zhao, C., and Marth, G. (2002). Human diallelic insertion/deletion polymorphisms. Am. J. Hum. Genet. 71: 854–862.

Wilson A. (1978). Developmental Psychology of the Black Child. Africana Research Publications (December 1978).

Wiswell TE, Tuttle DJ, Northam RS, Simonds GR (1990). Major congenital neurologic malformations. A 17-year survey. Am J Dis Child
1990, 144:61-67
World Factbook, 2004; Yearbook of immigration Statistics, 2003

Tags: Race, Intelligence, IQ, Cognition, Psychology, Sociology

82-85 is average IQ if your IQ is 142 you should have heard about Bell Curve.
You belong to top 1-2% of African Americans IQ distribution > Congratulation.
Try to have as many kids as possible.

http://blogcritics.org/archives/2007/11/18/2142433.php

By the way, speaking of Dylan, between Al Kooper’s The Blues Project and the Highway 61 Sessions Revisited, there were so many Jewish contributions you could have easily had a minion if you had to.

Well, citing studies done before the 1980s is bad news, though even as something of a race realist I would give your essay an A; well argued, informative and somewhat convincing, again, even as I said, being a race realist. I have to call into question the argument you cited by Gould, not just because Gould is an idiot, but because Morton lived in the early 1800s. Gould likes to do that, however. It is very convenient for his arguments and agenda, to take data clearly obtained in bygone eras by scientists with insufficient controls in their experiments, instead of scientists of the modern era who have far more legitimate data, and cogent theories. In fact, Gould is largely silent, just indignant, or really just out-debated by many of these other researchers in modern times. Your section about microcephalin I think can be removed given the topic. As for your final argument about androgen levels, I think it was probably more destructive to your argument than constructive. It seems almost as if you are inadvertently insinuating that blacks have equal or perhaps higher(which you formerly argued but I seriously doubt) cranial capacities due to testosterone and not intelligence, or your just . Also, I think it is suspect the high preponderance of Jews cited in your study. Their numbers here seem vastly disproportionate and just too in line with many Jewish political and social ideals and experiments.

Race and brainsize: Do Black have Larger Brains?

The majority of empirical studies on the matter of racial differences in brain size suggest that blacks from comparable environments will have larger brains than do others. Brain sizes vary considerably within any species, but this variation is not usually related to intelligence. Instead, it correlates loosely with body size: large people tend to have larger brains (Gould, 1981). As a result, women on average will have smaller brains than men (Peters, 1991). However, this does not indicate that the level of male intelligence is higher than female intelligence; Neanderthals had on average larger brains than anatomically modern humans (Tattersall, 1995; Gould, 1981) but most would agree that they were considerably less intelligent than Homo sapiens (Tattersal, 1995, 2004; Gould, 1981; Mithen 1998). In addition, female brains are structured in a way that would more than make up for any size differences.

Tobias (1970) compared 7 racial and national groups in a study on brain size, in which he reported that the brain size of American blacks was larger than any white group, (which included American, English and French whites) except those from the Swedish sub sample (who had the largest brains of any of the groups measured), and American blacks were also estimated to have some 200 million more neurons than American whites (See Tobias 1970; Weizmann et al. 1990). Gould (1981, 1996) discovered upon recalculating Morton’s skull data that the crania of blacks in his sample were on average larger than those of whites. Morton included in his sample of black skulls more females than he included in the white sample. For example, in his analysis of Hottentotts (black tribe from South Africa) all measured crania were of females; the Englishmen were all mature men. Also, Morton did some early measurements with seed instead of shot. When he discovered that this method gave inconsistent results, he re did the Caucasian values with shot, but not the blacks (See Gould, 1981, 1996). After correcting these errors it was shown that the black sample had larger crania (and presumably, larger brains) than did whites (ibid).

Interestingly, during the time periods in which the data for the above mentioned studies were collected anthropomorphic research has shown that blacks were on average physically smaller in stature than whites and received poorer nutrition (e.g. Alan, 2006). Indicating that in spite of relatively lower anthropomorphic measurements and poorer nutritional intake, blacks still demonstrated larger brain volume.

Empirical evidence shows that there is virtually no correlation between the intensity of different selective force gradients (e.g. latitude/temperature) and cranial morphology (Harvati and Weaver, 2006; Keita, 2004; Roseman and Weaver, 2004; Roseman, 2004; Gould, 1981, 1996; Brace, 2001). Indeed, positive geographic selective force correlations relating to craniometric variables are usually only (vaguely) observed when people from extreme cold (arctic) environments, such as Inuit types and Siberians, are included in analysis (Roseman, 2004; Harvati and Weaver, 2006). For example, Harvati and Weaver (2006) found a weak association between cranial centroid sizes and climatic variables, which approached, but did not reach, significance. This effect disappeared when an Inugsuk (a group from Greenland similar to Eskimos) sample was removed from the analysis (ibid). Roseman (2004) observed similar findings with a Siberian sample – once the Serbian sample was removed from the analysis, there was no indication that environmental temperature or latitude played ‘any’ role in cranial morphology. In sum, recent studies comparing craniometric and neutral genetic affinity matrices have concluded that, on average, human cranial variation fits a model of neutral expectation.

Keita (2004) in his principal components analysis on male crania from the northeast quadrant of Africa and selected European and other African series also found no consistent ‘size differences’ between regional groups, as all samples showed marked variation in size. There were however some distinguishing differences in relationship to cranial shape between European and African samples, particularly with respect to nasal aperture and changes in the maxilla (part of the upper jaw from which the teeth grow). The primary goal of this study was to assess the anatomical basis of patterns of craniofacial variation along an African–European continuum, with special interest on North Africa. There was Interest in whether there was a sharp boundary separating any of these groups from each other (see Keita, 2004). In terms of overall cranial size, tropical African groups were found in many instances to have larger crania than European groups. For example, on close inspection of the 2 dimensional PC scatter plots, designating cranial size/shape, the Zulu sample appeared to have the largest crania of any group in the analysis, followed by Norse (Norway) and then Teita (Kenya). African crania were also found to be broader (wider) than European crania on average. Surprisingly, one European sample, Berg (Hungarian), correlated more closely with African samples in this respect than with other European samples.

Tremendous overlap between all groups was observed in this study, for most variables (see Keita, 2004). Extensive research in human genetics on ‘presumably’ neutral loci has also shown that the overwhelming majority of human diversity is found among individuals within local populations. Previous studies of craniometric diversity are similar to these genetic apportionments, implying that interregionally differing selection pressures have played a limited role in producing contemporary human cranial diversity (Roseman and Weaver, 2004; Brace, 2001).

Other physical anthropological research has also shown that the crania of Sub-Saharan Africans are generally wider than European and North African samples, verbatim. For example sub-Saharan specimens show a generalized vertical facial flattening, with consequent widening of the entire structure (Bruner and Manzi, 2004). This pattern involves interorbital and orbital enlargement, widening and flattening of the nasal bones and aperture, maxillary development and upper rotation, and a general widening and lowering of the face. The face shortens vertically and this flattening leads to a relative lateral enlargement of the whole morphology and maxillary frontward rotation (see Bruner and Manzi, 2004). The pattern toward the other extreme shows the opposite processes, with a general vertical stretching related to a lateral narrowing, as seen in European and North African samples (ibid).

Roseman and Weaver (2007) found that the amount of phenotypic variation in human cranial morphology decreases at the population level the further one travels from Sub-Saharan Africa. African populations tend to exhibit more cranial variation than do other world populations (Hanihara et al, 2003; Hiernaux, 1975; Keita, 2004; Roseman and Weaver, 2007). Relethford (1994) and Relethford and Harpending (1994) found that the amount of morphological variation among major geographic groups is relatively low, and is compatible with those based on the genetic data, where Africa shows the most variation. Manica et al (2007) note a smooth loss of genetic diversity with increasing distance from Africa, and along with this, using a large data set of skull measurements and an analytical framework equivalent to that used for genetic data, also show that the loss in genetic diversity is mirrored by a loss in phenotypic variability.

Genetic studies of human brainsize have discovered two genes that when mutated can result in a severely reduced brain volume, or ‘Autosomal recessive primary microcephaly’. The gene microcephalin (MCPH1) regulates brain size during development and has experienced positive selection in the lineage leading to Homo sapiens (Zhang, 2003; Evans et al, 2005). Within modern humans a group of closely related haplotypes, known as ‘haplogroup D’ arose from a single copy at this locus (Evans, 2006). Globally, D alleles are young and first appeared about 37,000 years ago; with high frequency haplotypes being rare in Asia, and particularly Africa. The highest frequencies are seen in Europe/Eurasia. The second microcephalin gene, ‘ASPM’ (abnormal spindle like Microcephaly associated), went an episode of positive selection that ended some time ago (between 6–7 million and 100,000 B.P.), with newer D variants showing positive selection arising about 5,800 years ago (Evans et al, 2005; Zhang, 2003), although some research calls into question whether these newer variants are being selected for (see Voight 2006; Yu et al, 2007).

Microcephaly genetic researchers believe that D alleles may have first arisen in an archaic homo species about 1.1 million years ago before introgression into modern Homo sapien sapiens about 37, 000 years ago; possibly as the result of interspecies breeding (Evans et al, 2006). In fact, microcephalin shows by far the most compelling evidence of admixture among the human loci examined thus far (Evans et al, 2006). Modern humans arose only 100,000 years ago in Africa (Horan et al, 2005), which would make D alleles more than 1million years “older” than modern humans, and certainly very primitive by any stretch.

Normal D variants of both ‘MCPH1’ and ‘ASPM’ genes have been shown to have mild affects on human brainsize with empirical evidence demonstrating the alleles to reduce brain volume, slightly (Woods et al, 2006). For example, each additional ASPM allele was associated with a non significant 10.9 cc decrease in brain volume. For MCPH1, each additional allele was associated with a non significant 19.5 cc decrease in brain volume (Woods et al, 2006).

While selective pressure in favor of smaller brain volume might seem counterintuitive, it should be noted that the fossil records suggest that brain size in humans – particularly in Europe - has decreased over the past 35,000 years, and on through the Neolithic period (Frayer, 1984; Ruff et al, 1997; Woods, et al, 2006). Interestingly, the selected variant of MCPH1 is thought to have arisen about 37,000 years ago (Evans et al, 2006) making it a candidate gene responsible for this general decline (Woods et al, 2006), while the ASPM variant is thought to have arisen only 5,800 years ago. These archaeological changes in brain size are paralleled by changes in body size (Ruff et al, 1997; Woods et al., 2006), and it is possible that decreases in brain size may have exerted selective pressure for corresponding decreases in body (Ruff et al, 1997; Frayer, 1984; see also, Woods et al., 2006).

The supposed rate of selection for these particular variant MCPH1 and ASPM alleles might also indicate that the genes are relatively unexpressed in the human brain, outside of causing ‘Autosomal recessive primary microcephaly.’ In one study it was shown that genes with maximal expression in the human brain tend to show little or no evidence for positive selection (Nielsen et al, 2006). For example, the microcephaly genes in question have also been implicated in the development of breast cancer (Xu et al, 2004), and other non brain related conditions (Trimborn et al, 2004). Implying that the mild brain volume reductions observed with each additional variant of ASPM and MCPH1 may in fact be adaptively unimportant. It should be further noted that one microcephalin gene (CDK5RAP2) has shown evidence of positive selection in West African Yoruba (Voight, 2006; bond et al, 2005), however, this gene at the MCPH3 locus has been least involved in causing a microcephalin phenotype (Hassan et al, 2007), and is not believed to have arisen in an archaic homo species.

Cernovsky (1990) reports that American blacks were superior in brain weight when compared with American whites. It is also known that the largest portions of the human brain are devoted to sensory and motor functions, which would mean that people with especially acute senses or strong motor skills can be expected to have larger brains than do others (Allen, 2002). It has been shown in several studies that blacks in general possess superior motor skills when compared to whites (Super, 1976; Wilson 1978; DiNucci, 1975); some believe that this may be the result of environmental and cultural factors (Super, 1976). The overall implications are the same, however, and suggest that blacks have larger brains.

TESTOSTERONE, BRAIN SIZE and PENIS SIZE…?

Some of the more desperate claims for racial differences in brain size are accompanied by highly unusual arguments suggesting racial differences in penis size (i.e. that they are inversely correlated). Thorough investigation of the formal neuroscience, anthropology, paleontology, anatomy, physiology, and ‘sex psychology’ literature reveal that legitimate references to this - ridiculous (?) - notion are not only remote, but in fact, “nonexistent.” The development and size of one’s penis is controlled by testosterone levels during puberty; and it is testosterone (and body size) that determine penis size. Testosterone: “Primary male hormone, causes the reproductive organs to grow and develop; responsible for secondary sexual characteristics, and promotes erections and sexual behavior” (1).

With this in mind; employing elementary logic one may safely arrive at the conclusion that because men tend to have dramatically higher levels of testosterone than do women (about 10 times the level), and on average have larger brains (due mostly to body size); that testosterone not only increases body and penis size, but also brain size! In fact, the relationship between larger brain size and testosterone is of common knowledge, and is well documented in the literature (e.g. Solms and Turnbull, 2002; Hulshoff Pol et al, 2006).

Moreover, low testosterone has been associated with smaller penis and testes size in humans (McLachlan and Allan, 2005). Low testosterone is also been associated with failure to go through full normal puberty, poor muscle development, reduced muscle strength, low interest in sex (decreased libido), osteoporosis (thinning of bones common in whites and Asians), poor concentration, difficulty getting and keeping erections, low semen volume, longer time to recover from exercise, and easy fatigue, in men (McLachlan and Allan, 2005). At the other (relative) extreme, high testosterone has been associated with improved health and longevity, superior motor abilities, increased reproductive success (in men), increased mental focus, larger brain volume and “boldness” in men (Dabbs and Dabbs, 2000; Solms and Turnbull, 2002; Hulshoff Pol et al, 2006; Fink el al, 2005).

With respect to brain size again; it is known that sex hormones (e.g. testosterone, estrogen) induce sexually-dimorphic brain development and organization. Research with cross-sex hormone administration to transsexuals has provided a unique opportunity to study the effects of sex steroids on brain morphology in young adulthood. Hulshoff Pol et al (2006) used magnetic resonance brain images prior to, and during, cross-sex hormone treatment to study the influence of anti-androgen +estrogen treatment on brain morphology in eight young adult male-to-female transsexual subjects and of androgen treatment in six female to- male transsexuals. The team found that compared with controls, anti-androgen (i.e. male sex hormones/testosterone) + estrogen treatment decreased brain volumes of male-to-female subjects towards female proportions, while androgen treatment in female-to-male subjects increased total brain and hypothalamus volumes towards male proportions (Hulshoff Pol et al, 2006 ). These findings have also been replicated in animal studies (Nottenbohm, 1980; Bloch and Gorski, 1988).

Brain size decreases after anti-androgen treatment observed in the above mentioned study where also very dramatic. Indeed, the magnitude of change signified a decrease in brain volume, which is at least ten times the average decrease observed a year in healthy adult individuals (Hulshoff Pol et al, 2006). The authors include that it was not surprising that the influences of sex hormones on the brain were not limited to the hypothalamus, but were also expressed as changes in total brain size. Estrogen and androgen receptor mRNA containing neurons are not limited to the hypothalamus, but are distributed throughout the adult human brain (Hulshoff Pol et al, 2006; Simerly et al, 1990).

Research has documented that American blacks possess androgen (e.g. Testosterone) levels that are as much as 10% higher than American whites (Ross and Henderson, 1994; Bernstein et al, 1986; Ross et al, 1995). This difference, as it is not excessive, should also offer blacks a number of genetic and health benefits. For example, testosterone level differences of this magnitude would suggest that blacks on average will have comparably larger brains than do whites. East Asians have been shown to possess much lower levels of androgens (Ross et al, 1995).

Notes:

1. Definition is from: University of Michigan comprehensive Cancer Center; Fertility & Cryopreservation Glossary.

References:

Alan S.A. (2006). African-American and White living standards in the 19th century American south; a biological comparison. CESifo Working Paper No. 1696

Allen B.P. (2006). If No “Races,” No Relevance to Brain Size, and No Consensus on Intelligence, Then No Scientific Meaning to Relationships Among These Notions: Reply to Rushton11. General Psychologist, Summer, 2003 Volume 38:2 Pages 31-32.

Bernstein L, Ross RK, Judd H, et al (1986). Serum testosterone levels in young black and white men. J Natl Cancer Inst 76:45—48, 1986

Bloch GJ & Gorski RA. (1988) Estrogen/progesterone treatment in adulthood affects the size of several components of the medial preoptic area in the male rat. Journal of Comparative Neurology 1988 275 613–622.

Bond J, Roberts E, Springell K, Lizarraga SB, Scott S, et al. (2005) A centrosomal mechanism involving CDK5RAP2 and CENPJ controls brain size. Nat Genet 37: 353–355.

Bruner E., Manzi G. (2004).Variability in facial size and shape among North and East African human populations. Ital. J. Zool., 71: 51-56 (2004)

Brace C.L, Nelson A.R., Seguchi N, Oe H., Sering L., Qifeng P., Yongyi L., and Tumen D (2001). Old World sources of the first New World human inhabitants: A comparative craniofacial view. PNAS August 14, 2001 u vol. 98 u no. 17 u 10017–10022

Cernovsky Z.Z. (1990). Race and Brain Weight: A note on Rushton’s conclusions. Psychological Reports 66:337-38

Dabbs,J.M, Dabbs M.G. (2000). Heroes, Rogues and Lovers: Testosterone and Behavior. McGraw-Hill Companies (July 25, 2000)

Douglas B. (2008). Race, Intelligence and IQ: Are People of African Decent More Intelligent? Africaresource: educational, arts and research materials.

DiNucci, James M. (1975). Motor Performance Age and Race Differences between Black and Caucasian Boys Six to Nine Years of Age. The ERIC database, an initiative of the U.S. Department of Education. 1975-02-00

Evan P., Mekel-Bobrov N., Vallender E., Hudson R., Lahn B., (2006). Evidence that the adaptive allele of the brain size gene microcephalin introgressed into Homo sapiens from an archaic Homo lineage. 18178–18183, PNAS November 28, 2006, vol. 103, no. 48

Erik Trinkaus (1984). Reply. Current anthropology. Vol. 25 . No. 3 June 1984

Fink B., Grammer K., Mitteroecker P., Gunz P., Schaefer K.,. Bookstein F.L. and Manning J.T. (2005). Second to fourth digit ratio and face shape Proc. R. Soc. B (2005) 272, 1995–2001

Frayer, D.W. (1984). In The Origins of Modern Humans: A world survey of the Fossil Evidence (eds Smith, F.H. & Spencer, f.) 211-250 (Liss, New York, 1984)

Gould, S. J. (1981). Mismeasure of Man. New York: Norton.

Gould, S. J. (1996). Mismeasure of Man (2nd edition). New York: Norton.

Hanihara T, Ishida H., and Dodo Y (2003). Characterization of Biological Diversity through Analysis of Discrete Cranial Traits. American Journal of Physical Anthropology 121:241–251 (2003)

Hassan M.J., Khurshid M, Azeem Z., John P, Ali G., Chishti M.S. and Ahmad W. Previously described sequence variant in CDK5RAP2 gene in a Pakistani family with autosomal recessive primary microcephaly. BMC Medical Genetics 2007, 8:58

Hiernaux J. (1975). The people of Africa. New York: Charles Scribner’s Sons.

Horan R.D., Bulte E., Shogren J.F. (2005). How trade saved humanity from biological exclusion: an economic theory of Neanderthal extinction. Journal of Economic Behavior & Organization Volume 58, Issue 1, September 2005, Pages 1-29

Hulshoff Pol H.E., Cohen-Kettenis P.T., Peper J.S., Cahn W. (2006). Changing your sex changes your brain: influences of testosterone and estrogen on adult human brain structure. European Journal of Endocrinology (2006) 155 S107–S114

Mithen, S., 1998 (Ed). Creativity in Human Evolution and Prehistory, London: Routledge
Murphy, N. B. (1968). Carotid cerebral angiography in Uganda: review of boo consecutive cases. East African M. 7.,1968,45,47-60.

Nielsen,R., Bustamante,C., Clark,A.G., Glanowski,S., Sackton,T.B., Hubisz,M.J., Fledel-Alon,A.,

Nottebohm F. (1980). Testosterone triggers growth of brain vocal control nuclei in adult female canaries. Brain Research 1980 189 429.

Tanenbaum,D.M., Civello,D., White,T.J., et al. (2005). A scan for positively selected genes in the genomes of humans and chimpanzees. PLoS Biol. 3,

Relethford JH. 1994. Craniometric variation among modern human populations. Am J Phys Anthropol 95:53–62.

Relethford JH, Harpending HC. 1994. Craniometric variation, genetic theory, and modern human origins. Am J Phys Anthropol 95:249–270.

Roseman C.C. (2004). Detecting interregionally diversifying natural selection on modern human cranial form by using matched molecular and morphometric data. Proc Natl Acad Sci U S A. 2004 August 31; 101(35): 12824–12829.

Roseman C.C., Weaver T.D. (2007) Molecules versus morphology? Not for the human cranium. Volume 29, Issue 12 , Pages 1185 – 1188

Roseman C.C., Weaver T.D. (2004). Multivariate apportionment of global human craniometric diversity. American Journal of Physical Anthropology. Volume 18, Issue 5 , Pages 668 - 675

Ross, R.K., Coetzee, G. A., Reichardt, J., Skinner, E, and Henderson, B.E. (1995). Does the Racial-Ethnic Variation in Prostate Cancer Risk Have a Hormonal Basis? Cancer, Volume 75, Issue S7 (p 1778-1782)

Ross R.K., Henderson B.E. (1994). Do diet and androgens alter prostate cancer risk via a common etiologic pathway? / Natl Cancer lnst 1994; 86:252-4.

Ruff C.B., Trinkaus E., and Holliday T.W. (1997). Body mass and encephalization in Pleistocene Homo. Nature Vol. 387, 8 May 1997

Simerly RB, Chang C, Muramatsu M & Swanson LW. (1990). Distribution of androgen and estrogen receptor mRNA-containing cells in the rat brain: an in situ hybridization study. Journal of Comparative Neurology 1990 294 76–95.

Solms M. and, Turnbull O. (2002). The brain and the inner world. Other Press, New York

Keita S. (2004). Exploring Northeast African Metric Craniofacial Variation at the Individual Level: A Comparative Study Using Principal Components Analysis. American Journal of Human Biology 16:679–689 (2004)

Super, C. M. (1976). Environmental effects on motor development: The case of African infant precocity. Developmental Medicine and Child Neurology, 18, 561–567.

Tattersall, I. and J.H. Schwartz (2000). Extinct Humans, New York: Westview Press.

Tattersall (1995) The Fossil Trail (Ev)

Tobias, T.V. (1970). Brain Size, Grey matter and Race – Fact or Fiction? American Journal of Physical Anthropology 32:3-26

Trimborn,M., Bell,S.M., Felix,C., Rashid,Y., Jafri,H., Griffiths,P.D., Neumann,L.M., Krebs,A., Reis,A., Sperling,K., et al. (2004). Mutations in Microcephalin cause aberrant regulation of chromosome condensation. Am. J. Hum. Genet., 75, 261-266.

Voight BF, Kudaravalli S, Wen X, Pritchard JK (2006) A map of recent positive selection in the human genome. PLoS Biol 4(3): e72

Wilson A. (1978). Developmental Psychology of the Black Child. Africana Research Publications (December 1978).

Woods R., Freimer N., Young J., Fears S, Sicotte N., Service S., Valentino D., Toga A., Mazziotta J. (2006). Normal Variants of Microcephalin and ASPM Do Not Account for Brain Size Variability. Human Molecular Genetics, Volume 15, Number 12, 15 June 2006, pp. 2025-2029(5)

Xu X., Lee J., and Stern D.F. (2004). Microcephalin Is a DNA Damage Response Protein Involved in Regulation of CHK1 and BRCA1. THE JOURNAL OF BIOLOGICAL CHEMISTRY Vol. 279, No. 33, Issue of August 13, pp. 34091–34094, 2004

Yu F, Hill R.S., Schaffner S.F., Sabeti P.C., Wang E.T. et al (2007).Comment on “Ongoing Adaptive Evolution of ASPM, a Brain Size Determinant in Homo sapiens”. Mignault A.A,1 Ferland RJ. Et al, 20 APRIL 2007 VOL 316 SCIENCE

Zhang J. (2003). Evolution of the Human ASPM Gene, a Major Determinant of Brain Size. Genetics 165: 2063–2070 (December 2003)

If this is true, why does every government, and city job HAVE to place blacks with lower test scores. Whites HAVE to place higher than a 90, blacks, anywhere above a 60. This isn't speculation, it is fact. Check it out yourself. Maybe it is because blacks can't score higher, say on a fire department test. It will be interesting (and depressing) to see what will happen in the next twenty years. Dumb people running the country.

I honestly believe genetics has a lot to do with it. My kid's are 1/2 Asian and both were in gifted programs and scored much higher then the white kids. When they were in grammar school one of the teachers commented on the mix. As far as using the influences of the community ..I read a study done between African Americans and the poorest white area of Appalachia and despite the White's having far less then the black group, they still scored much higher. My kids were not influenced entirely by the Asian community growing up here..neither do I think you or anyone else would be. You still have Western influence all around you.
It's also a general statement to think that all Asians only excel because they want to come to America for the dream. I know that most go into hock in order for their children to get educated. My Father In Law use to say that they can take everything away from you except your Education. So the emphasis is not only on monetary things in the Asian culture.

The Askenazi scores are higher because of inbreeding which only supports more the claim of genetics. It's a fact that characteristics can be bread into humans and has been done throughout the ages. The only problem is inbreeding can result in some of the diseases we see within this group. However if the rules of breeding, say no further then 4th cousins is obeserved a controlled selective healthy group can be acheived. It's not a matter of "is it right?" It's already part of the process and has been for centuries. It's just until recent racial issues came up after slavery was abolished that attentions been drawn to this issue of IQ and race. A meer blink of an eye on the evolutionary scale.
I think the question is still unresolved about Neanderthal interbreeding. As of last I heard no DNA has been found on Neander.. It would be easy to back track form our pools to see if it occured but without DNA it can't be done. I wouldn't doubt it did happen though. Listening to some of the post's by those who reject these scientific finding's make me wonder if the Neaderthal gene might be prevelant in their gene pool ?

Hey everybody listen to this guy! accept the figures? what r u hitler's desciple? low IQ means more likely to be in poverty,drop out of school,unemployed,idle or lazy,be on welfare,bad parents[ which means bad people, are caucasians the nicest individuals on this earth? i dont think so look at iraq]commit crimes and some other shit that's so degrading you dont have to finish high school to realize they are sayin you are a inferior species. and all that negative crap we supposed to inherit 50% from our parents? it's people like you that makes this earth such a messy place to live in, that survival of the fittest crap.caucasians twisted the bible to enslave black people, now they sayin we are half retards and we supposed to accept the figures cause our kids are failing school, get your facts straight. black folks are discredited for so many things, that we dont have a writen language, we didn't contribute nothing to civilazation, our history starts from slavery, shit! in school i never heard of any black inventor, only einstein this, newton that. shouting wont change nothing but like the late 2pac said f**k the world! and it's so called tests designed just to degrade black folks. i said earlier knowledge is power and when you educate yourself bout your past glories than you start seen flaws in these tests. low IQ means less gifted/tallented people, black folks are gifted/tallented naturally
am done with this topic, in fact all ni**as should get out of this site and let this loosers discuss our downfall like the ancient illuminati

Why are we arguing about racial superiority and all that crap.

A scientific study has shown that different races score differently on IQ tests.

What has that got to do with boxing or jazz?

Hiding the figures under a lot of shouting and ranting won't change them.

As the study has done, why not accept the figures and try and work out WHY this is the case. Shouting as loudly as possible at the tests, the scientists and at anything else to hand doesn't change the results.

The black kids are coming bottom of the class when it comes to IQ tests. This is a fact, and we need to figure out why and do something about it!

Do you even know the names of this russian boxers? Anyone out there heard of them? But the world over has heard of Muhhamad ali, Mike tyson, Lennox lewis. Music? Do some reserach before you make yourself look silly and don't even try to bully me around with that evolutionary ladder crap! Rock n roll, Jazz,The blues, R n b and now Hip hop guess who started all them
Caucasians are superior or IQ difference at least 50% genetically is bull, and anyone who actually beleives in it, is either to stupid to figure it out we are the authors of our destiny or really deep down they feel inferior and come up with crapy tests to make themselves feel better
If asians rank the highest than they are the superior race right?
Waste your little precious time on more productive activities, here is a suggestion: how about spending more time with your familly or kids perhaps that way they wont listen to hip hop so much...peace

My friend before you try to respond i suggest you do your research, and dont even try to bully me around with your evolutionary ladder crap.Caucasians believed we were inferior in every way possible until we surpassed them in boxing, if this is too hard for you to swallow, well too bad for you. Hip Hop is what? you dont even know what you talking about, am glad you touched on music let me educate you for a while. Rock n Roll, jazz, the blues, r n b now hip hop, dig deep and you'll be shocked to find out who started them.
I dont hate white people but am so tired of your superiority rubbish. White skin, blue green eyes,blond hair all this so called god given caucasoid features it's not so god given when you know the truth.
deepset inferiority you dont agree? fortunately you have a right to disagree, a lot of negroids had no sayin in been plucked out of africa
Just like rock n roll was a new phenomen in it's early days so too is hip hop, and people like you better waste that precious little time we all so have in raising your kids before they turn hip hop desciples...peace

Superiority in boxing?Is that why black Boxers are beaten almost every time by russian caucasians?Music?
Hip Hop is the lowest combination of "speach" and sound waves of any culture.IQ has nothing to do with Human values and there are some black specimen that out rank many white people in this category.But until you catch up on the evolutionary ladder,this is probably to high for you to understand.

if african americans have an IQ of