The information presented 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. So that the median IQ for African blacks residing in the west should be about 110, if one accepts that research suggesting direct casual relationships between academic attainment levels and IQ (e.g. Gottfredson, 1998; Ostrowsky, 1999)!
Research also shows that when African Americans are matched as to linguistic behavior (e.g. black vs. standard English), literacy levels and to the comprehension of sayings requiring specific knowledge, that African Americans perform as well or better than do Whites on IQ tests.
By Bernie Douglas (April 10, 2008), Revised February 17, 2009
What are IQ Tests?
IQ is a culturally and ideologically rooted construct; an index intended to predict success or outcomes that are valued as success by some people, in western societies. The items on these tests are largely measures of achievement at various levels of competency (Sternberg et al, 1998a, 1999, 2003a) and are devised impressionistically by psychologists to simply mimic the psycholinguistic structures of schooling and middle class clerical/administrative occupations (Richardson, 2000, 2002). Alfred Binet, the inventor of the first intelligence test devised this instrument more than 100 years ago to screen “children” for educational difficulties, and made clear its conceptual foundations (See Richardson, 2002). His interest was in the educational development of children, and argued that his test could not be used for children over the age of seventeen. He also believed that scores on his test could be radically improved through learning and instruction. Stern (1914) would devise what is known today as the concept of “I.Q.,” which stands simply for “Intelligence Quotient.” Stern’s quotient system was, too, like Binet’s test, devised for use exclusively with children, and was not intended for use with adults.
IQ tests were originally intended to be little more than devices for
generating numbers that are useful in assessing academic aptitude with in a
given culture, and for use mainly with children. IQ tests sample some elements
of intelligent behavior and these elements are associated with academic
performance (Capron et al, 1999). Traditional IQ tests do not measure the many
forms of intelligence that are beyond more academically specific skills, such
as music, creativity, art, interpersonal and intrapersonal abilities (Braaten
and Norman, 2006; Gardner, 2000; Armstrong, 1993). The processes associated
with schooling influence performance on IQ tests through a combination of
direct instruction and indirect inculcation of modes of thinking, and the
values associated with standardized testing (Ceci and Williams 1997; Ceci,
1991; Richardson, 2000, 2002). Tests have a narrow focus on skills and tasks
which are acquired and rehearsed through the processes of formal or informal
schooling (Ceci and Williams, 1997; Ceci, 1991: Kamin, 1974).
IQ and similar tests are also unable to measure one' s potential, are not
independent from what is measured by achievement tests and are not powerful
predictors of low reading performance (Siegel, 1989, 1992; Bradshaw, 2001;
Naglieri and Reardon, 1993; Rispens et al 1991). Test results in one child can
vary according to mood, motivation, and fatigue, while the tests themselves
show prominent rehearsal/learning effects, generally assume a degree of
literacy, and are largely framed to suit mainstream Western cultural
requirements (Ceci & Williams, 1997; Ceci, 1991; O' Brien, 2001;
Richardson 2000, 2002; Sternberg, 2004). For these reasons and others many
believe that the use of IQ tests should be abandoned (Siegel, 1989, 1992;
Vellutino et al, 2000, Bradshaw, 2001; Schonemann, 1997c). In addition, no
tests except dynamic tests (see Sternberg & Grigorenko, 2002a) that
require learning at the time of the test directly measure ability to learn.
Traditional IQ tests focus on measuring past learning, typical of the kind
acquired through the processes of formal schooling and cultural exchange.
While these things are known to be heavily influenced by accessibility,
motivation and available opportunities to learn (see Fagan and Holland, 2002,
2007).
Heritability and IQ:
Despite what some have argued in the past, there is no serious evidence
which has demonstrated IQ tests to measure either an inborn property or what
is commonly understood to mean intelligence (see Hirsch 1970, 1997,
2004; Schonemann, 1997c, 2005; Schonemann and Schonemann, 1994; Kempthorne
1978, 1997; Capron et al, 1999; Vetta, 2002; Wahlsten, 1981, 1990; Capron and
Vetta, 2001). Intelligence is a highly subjective and culturally
confound concept which remains largely undefined (Schonemann, 1997c;
Sternberg, 2007; Cole et al, 1971; Guttman, 1992). The twin and adoption
studies commonly used to report heritability estimates in relationship to IQ
tests have also been shown to be suspicious in nature. The biometrical school
of scientists who fit models to IQ data traces their history to R. Fisher
(1918), but their genetic models have been shown to have virtually no
predictive value (Vetta, 2002; Vetta, 1976; Capron and Vetta, 2001; Capron et
al, 1999; Schonemann, 1997c). For example, statistical models used in twin
studies and inferences from them relating to IQ tests lack statistical
validity, and are thus of dubious value (Capron et al., 1999; Kempthorne,
1997; Schonemann, 1997c; Schonemann and Schonemann, 1994).
Wahlsten (1981) argues that errors are so wide spread in the heritability
literature that the critical reader has good reason to doubt every article
published on the topic in relationship to IQ. He goes further stating that it
is necessary to check the arithmetic, algebra and original references before
seriously considering any conclusions. For example, the most widely used
heritability method, now, is based on a paper by Jinks and Fulker (1970).
However, this method contains an algebraic error that renders its application
in most instances, worthless (See: Capron et al, 1999; Schonemann,
1997c, 1990). Schonemann (1997c) shows that conventional heritability
estimates often produce absurdly high values for variables that cannot
possibly be genetic. He found that if one applies the traditional heritability
arithmetic to the twin data collected by Loehlin and Nichols (1976), that the
answer to the question Did you take a bubble bath last year is 90%
genetic (Schonemann, 1997c)! Kempthorne (1978, 1997) argues that the concept
of heritability is important for plant and animal breeding because it is
possible to design and carry out experiments to estimate variance components,
but that data on humans is observational and individuals are not randomly
assigned to environments, and should, for these reasons, be ignored.
A psychologist administering an IQ test to different kinships (e.g. twins) is
not manipulating either the genetic or environmental factors, as is done in
animal experiments (Capron et al, 1999; Kempthorne, 1997), thus their
estimates tend to be speculation in absence of any definitive proof. Many well
regarded statistical and biometrical experts have argued that the true
heritability of IQ is probably closer to zero (see: Schonemann, 1997c, 1990;
Schonemann and Schonemann, 1994; Capron et al, 1999; Vetta, 2002; Wahlsten,
1981, 1990; Vetta and Coureau, 2003; Taylor, 1980; Hirsch 1970, 1997, 2004;
Kempthorne 1978, 1997)! Indeed, literacy and acculturation have
been shown to predict IQ score differences between groups and individuals
better than any other variables (Boone, 2007; Manly et al, 1998; Fagan and
Holland, 2002, 2007; Ryan et al, 2005).
Why the Racial Controversy?
While one will find many flaws and inconsistencies associated with the
concept of IQ, this has not managed to sway some hard nosed advocates from
continuing to promote the test’s practical merits for predicting academic
success and occupational status within western market based societies – This
is in spite of the test’s predictive value in these areas also having been
roundly challenged (Schonemann, 1997c, 2005; Siegel, 1989; Bradshaw, 2001;
Sternberg, 2001; Frank, 1983).
Some of the more ardent IQ advocates have even gone so far as to argue that
the possible reason many blacks and other minorities do not achieve in areas
relating to academic attainment and occupational status, particularly in the
US, is not due to historical racism or negative societal factors, but instead
because of factors that relate to low IQ scores. Ignoring historical
events (e.g. slavery and Jim Crow) economic and educational biases
(Pattillo,1999; Diamond and Spillane 2004; Roscigno, 1998), the affects of
culture and cultural differences (Valsiner, 2000; Cole et al. 1971; Serpell
R., 1979; Ogbu and Simons, 1998), the questionable methodology and theory
involved in IQ tests (Schonemann, 1997c, 2005; Guttman, 1955, 1992; Hirsch,
1970, 1997, 2004), poor test validity and predictive value (Schonemann, 1997c,
Bradshaw, 2001; Sternberg, 1997), test bias (Manly, 1998; Helms, 1992; Helms,
1997; Kwate, 2001; Baldwin and Bell, 1985; Borsboom, 2006) and overwhelming
criticism leveled against heritability estimates (Capron et al, 1999;
Schonemann, 1994, 1997c; Hirsh, 1970, 2004 ; Kempthorn; 1978, 1997; Lidz and
Blatt, 1983; Joseph, 2004, 2006; Vetta, 1976, 2002), these advocates tend to
proceed with their arguments, unaltered.
For example, in 1994 authors Herrnstein and Murray in their controversial book
“The Bell Curve” argued that a dysgenic trend exists in western societies
that foresee the establishment of a “cognitive elite.” Although their work
was subject to wide and often scathing criticism, the authors managed to
generate a substantial amount of media attention, which helped to perpetuate
negative ethnic stereotypes in the formal literature and in public discourse
for a number of years.
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 (Schmidt, Ones
& Hunter, 1992), and maintain that the average undergraduate, “those who
graduate from college or university”, must possess an IQ that is on average
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 do not go on to, or graduate from
institutions of higher learning, and ultimately move on to professional
careers and economic success, 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 scores (e.g. Jensen, 1980;
Gottfredson, 1998). Arguments such as these tend also to base themselves
within the shaky framework that is, “nature vs. nurture.” In this case,
does more school develop high IQ, or does a high IQ equal more school and
greater socio-economic success (Jensen, 1980; Gottfredson, 1998)? Others have
pointed out, simply, that the correlation between IQ scores and school
performance is one deliberately built into tests and that processes associated
with schooling directly influence tests performance (Richardson, 2002).
Black African Immigrants Significantly Exceed Whites in Level of Education:
African-born blacks comprise about 16 percent of the U.S. foreign-born
black population (U.S. Bureau of the Census, 2000), and are “considerably”
more educated than other immigrants. The vast majority of these immigrants
come from minority white countries in East and West Africa (e.g. Kenya and
Nigeria). While less than 2 percent originate from North or South Africa (CIA
World Factbook, 2004; Yearbook of immigration Statistics, 2003). An analysis
of Census Bureau data by The Journal of Blacks in Higher Education (1999-2000)
and the “Lewis Mumford Center for Comparative Urban and Regional Research”
(2003) find that Black African immigrants to the United States are more likely
to be college educated than ‘any’ other immigrant group, which included
those from Europe, North America and Asia (see also 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 research suggests 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;
Kent, 2007; 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.
It was discovered that 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 (Cross, 1994). According to the 1991 British Census, 26.5
percent of black Britons who were born in Africa had at least some college
education. In contrast, only 13.4 percent of white Britons had gone to
college.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 and Theodoropoulos, 2006).
Dustmann and Theodoropoulos (2006) provided the first thorough investigation
of educational attainment and economic behavior of ethnic minority immigrants
and their children in Britain. This study investigated how British born
minorities performed in terms of education, employment and wages when compared
to their parent’s generation, as well as to comparable groups of white
natives using 27 years of “LFS data” (Labour Force Survey). In both
generations Black Africans topped the list in both years of
schooling/educational qualifications and wages/employment followed by Indian
and Chinese immigrants. This study generally found a strong educational
background for Britain’s ethnic minority immigrant population; with second
generation ethnic minorities, ‘on average’, doing better than their
parents, and “substantially better” than their white peers in most
socio-economic indicators and outcomes.
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 Li and Heath, from Birmingham University and Oxford
University (respectively), 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; Cassidy,
2006).
Black African Educational Attainment and their Implications for IQ:
The information presented 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). So that if one accepts the research
suggesting direct casual relationships between academic attainment and IQ (Gottfredson,
1998; Ostrowsky, 1999) the median IQ for African blacks residing in the west
should be about 110! This is especially true for those living 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 of the most cognitive socio-economic
indicators – ‘the areas of educational attainment and occupational
status’ -- in ways that are virtually identical to the gaps observed between
native born white and black Americans (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, sample sizes often in the hundreds of thousands,
that are genuinely random; and consequently specific ethnicities can be
compared with statistical confidence. Evidence shows that the differences in
overall educational attainment observed between African born blacks in the
United States and UK and native born whites are quite spectacular! Indeed, if
one chooses to adopt the racial hereditarian thinking of Jensen (1980),
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 differences between ethnic
‘populations’ in relationship to IQ test performance are based on
statistically derived data that relate to scholastic aptitude tests (e.g.
Flynn, 2006). With this in mind, and acknowledging the superior educational
attainment of African blacks in the United States (and elsewhere) it can thus
be argued, because of their superior educational attainment levels, that they
must also surmount far more in number and more difficult scholastic aptitude
tests, in general, which in turn would require higher level IQs (see
Gottfredson, 1998; Ostrowsky, 1999). As whites on average do not, or are
unable to attain the same levels of academic achievement within these (their
own!) academic institutional frameworks, they must also by the racialist
thinking employed by some, possess significantly lower cogitative indices on
the group level (e.g. Jensen, 1980; Gottfredson, 1986, 1998). In fact,
attainment differences of these ‘grand’ magnitudes would suggest that
American whites, in particular, are at a significant intellectual handicap
when matched against immigrants of black African, East Indian, and East Asian
descent. Incidentally, most American whites themselves are the children or
grandchildren of “self-selected,” voluntary immigrants from Europe (Ogbu
and Simons, 1998), and thus these trends can not be said to result from
immigrant selectivity.
African born blacks residing in Western countries tend also to be concentrated
in higher level professional occupations, which are considered (by some) to be
more intellectually demanding; requiring greater cognitive ability (Jensen,
1980; Gottfredson, 1986; Herrnstein and Murray, 1994), than the average
occupations of either American or British born whites (Nisbett, 2002; Dixon,
2006; Li and Heath, 2006; Dustmann and Theodoropoulos, 2006). According to IQ
advocates and social Darwinists, alike, these occupational differences should
also be indicative of higher levels of intelligence among black African
immigrants than among whites (e.g. Gottfredson, 1986; Jensen 1980). Cole
(1990), argues that the relevance of school-based skills, such as those found
on IQ and scholastic aptitude tests, will grow as the outside-of-school
contexts becomes more like that of school itself. While demand for these kinds
of school based skills are found most frequently among the
clerical/administrative occupations (Richardson, 2002) which African born
blacks residing in western countries tend to be found overrepresented (Nisbett,
2002; Dixon, 2006). In fact, as virtually all IQ tests in popular use today
were 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”) could be best
described as black men and women from Africa.
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. The U.S.
Census Bureau's 2005 American Community Survey counted 114,000 black African
immigrants in the Washington metropolitan area, alone, accounting for about 11
percent of the area’s total immigrant population. Less than 6 percent
arrived before 1980. 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; The Canadian
Encyclopedia, 2008).
Culture, Race and Intelligence Testing:
It is taken for granted by many in the West that children who do well on
standardized tests are intelligent. However, different cultures have their on
views of what intelligence is and often these views do not resemble western
notions (Sternberg, 2007; Cole, 1990; Cole et al. 1971; Greenfield, 1997). In
this respect, people 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 and at worst a nonsensical and mischievous waste of time
(Mackintosh, 1998).
In addition, few researchers ever apply standardized measures that are either
preferred by or normed in favor of those whose livelihoods or day to day lives
are more closely associated with the informal sectors and/or economically
disparaged segments of society to those from more affluent or formal society,
in order to provide some kind of 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), so that, for instance, unschooled
subjects may fail at classification tasks characteristic of school learning
contexts and succeed with classification relevant to their own everyday
practical experiences (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; Sternberg, 2004).
Thus, the structure of thought depends upon the structure of the dominant
types of activity in different cultures. In other words, people will be good
at doing those things that are important to them and that they have
opportunities to do often.
A study by Serpell (1979) highlighted this well. Zambian and English children
were asked to reproduce patterns using three media alternatives (wire, clay,
or pencil and paper). It was found that the Zambian children excelled in the
wire medium with which they were most familiar, exceeding the English children
in that task; while the English children were best with pencil and paper. Both
groups were found to perform equally well with clay. Thus, children performed
better with the materials that were more familiar to them from their own
environments. A study by Carraher et al (1985) also demonstrated examples of
this effect, this time in a group of Brazilian children. The study found that
the same children who were able to do the mathematics needed to run their
street businesses were often unable to do “the same” mathematics when
presented in a more formal (grade schooling) context.
Cole et al (1971) studied a tribe in Africa called the “Kpelle” in which
culture was shown to have a rather humorous effect on interpretations of
intelligence. In this study adult participants were asked to sort items
into categories. However, rather than producing the kind of taxonomic
categories (e.g. "fruit" for apple) typically done in the west, the
Kpelle participants sorted items into functional groups (e.g. "eat"
for apple). After trying and “failing” to teach them to categorize items
taxonomically, the Kpelle 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 items into taxonomic categories (Cole et
al., 1971)! Demonstrating that not only where these individuals able to do the
presented tasks, but in their own culture, what was considered intelligent by
western views was thought to be “stupid.”
Education, Literacy, Culture and Standardized Tests --When Blacks Exceed Whites!
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 may actually correspond more closely with the
quality and style of schooling that one receives more so than other factors.
These findings closely support research suggesting that the forms of
recognition and reasoning found on Progressive Matrixes tests are exercised
and maintained within a western style educational setting (Ceci &
Williams, 1997; Ceci, 1991; Richardson, 2000, 2002). Buj (1981) also showed
Ghanaian adults in another study to score higher on the same supposedly
‘culture fair’ intelligence test than did Irish adults; scores were 80
(Ghanaian) and 78 (Irish), respectively. While Shuttleworth-Edwards et al
(2004) in a study with black South Africans between the ages of 19–30,
showed highly significant effects for both level and quality of education
within groups whose first language was an indigenous black African language.
For example, 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).
Other programs have shown dramatic improvement in test scores for socially
disadvantaged adolescents as a result of short-term cognitive training, so
that "…three months later their performance was indistinguishable from
that of middle class students” (Feuerstein & Kozulin, 1995, p. 74).
Studies done with Ethiopian immigrant students coming from extraordinarily
poor rural circumstances tested in Israel by different IQ tests had, in
pre-intervention tests, demonstrated lower test scores than the Israeli norm.
However, after a short but intensive teaching process the Ethiopian immigrant
children performed at about the same level as the Israeli norm (Tzuriel &
Kaufman, 1999; Kozulin, 1998).
Bond (1924) early last century pointed out that the average IQ scores of
African Americans from several northern states were higher than those for
whites from many southern states (Bond, 1924a, p. 63). He argued that African
Americans who migrated to the North must have left their "duller and less
accomplished White fellows in the South." Bond also believed that IQ test
scores reflected social and educational training. Inline with this belief,
Jenkins's (1936) reported the results of IQ tests given to Black and White
children in Illinois, and found that the proportion of students with scores
over 130 was the same among Black and White children when environmental
influences were comparable. A later study, involving Caribbean children, would
in essence replicate these findings. The results from that study showed that
when raised in the same enriched institutional environments as white children,
black children demonstrated superior IQ test scores. IQs were: Black children
108, Mixed children 106, and White children 103 (Tizard et al, 1972).
Studies also show that upward of 99% of group IQ score differences between
healthy black and white Americans are eliminated after controlling for
cultural factors. Manly et al (1998) found that after cultural factors such as
linguistic behavior (e.g. black vs. standard English) are controlled between
healthy black and white Americans that IQ score differences between these
populations virtually disappear; becoming insignificant in all but only one
area (a reading section)! Some argue that because those who construct
standardized tests come from a narrow social group that it follows that test
items will contain information and structures that match the background
knowledge of some people more than others (Richardson, 2000). This may explain
why “acculturation” is found to predict IQ score differences better than
virtually any other variable, aside from literacy levels (which is essentially
another mediator of culture). Other studies have shown 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; see also, Fagan and Holland, 2007).
This study also found that when Blacks and Whites are matched as to the
comprehension of sayings requiring specific knowledge that Blacks were
superior to Whites on intelligence tests (ibid).
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; Boone et al, 2007).
These researchers further argue 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). Boone et al (2007) obtained findings that further supported this
line, as not ethnic differences, but the effects of acculturation directly and
significantly influenced IQ test performance. The authors cautioned that
normative data derived on Caucasian samples may not be appropriate for use
with other ethnic groups (Boone et al, 2007). Ryan et al (2005) found that
discrepancy in reading and education level was associated with worse
psychological test performance (e.g. IQ and other tests), while racial/ethnic
minority status was not.
Educational Bias:
In the United States, when matched for IQ with Whites, American Blacks have
been shown to demonstrate superior “Working Memory” (Nijenhuis et al.,
2004). This is a particularly interesting finding as African Americans tend to
be taught by less qualified teachers (e.g. non-certified teachers and teachers
with limited experience) than their white counterparts, and are provided with
less challenging school work (Hallinan 1994; Diamond et al., 2004; Uhlenberg
and Brown 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). Thus, it
is somewhat of a surprise that African Americans should outperform white
Americans on any portion of a paper and pencil test designed to mimic the
structures of western style schooling and culture (Richardson, 2000, 2002).
Educational inequality in the U.S. is a pervasive part of the social system
and 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). In addition, there has been a
history of social policy which has limited African American’s access to
avenues of wealth accumulation (e.g. purchasing suburban homes); so that black
families also have far fewer assets than their white counterparts who earn the
same incomes (Oliver and Shapiro, 1995). Parents with greater assets are free
to use them for things like tutors, purchasing educational materials (e.g.
computers), and to pay for private schools and more expensive colleges.
In a study which helped to highlight the need for better education for African
American children, Serpell et al. (2006) took 162 low-income African American
and white fourth graders and assigned them, randomly, to ethnically
homogeneous groups of three to work on a motion acceleration task, using
computer simulation or physical tools. Or to a control group that did not
participate in the learning activities. It was shown that both African
American and White students performed equally well on the test of initial
learning, with both groups scoring significantly higher than the control
group. However, it was also found that African American children’s transfer
outcomes were superior to those of their White counterparts (see Serpell et
al., 2006). The study demonstrated, empirically, that not only do African
American children learn as well as white children, but that they may actually
exceed their white counterparts in their ability to transfer learned abilities
to real tasks.
A Closer Look at Culturally Bias Testing:
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 referred to as “white middle class” culture. 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) where it was
found that the black participants out performed the white participants. Blacks
obtained 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 of this study indicated that when blacks and whites are
tested cross-culturally that blacks may outperform whites on standardized
tests.
Williams and Rivers (1972b) showed that test instructions in Standard English
penalize the black child and that if the language of the test is put in
familiar labels, without training or coaching, the black child’s performance
on the tests increase significantly. Ideally a child’s language development
should be evaluated in terms of his progress toward the norms for his own
particular speech community (Cadzen, 1966); however, this kind of evaluation
is rarely, if ever, done with respect to African Americans. Studies using
sentence repetition tasks have found that at both third and fifth grades white
subjects repeated Standard English sentences significantly more accurately
than black subjects, while black subjects repeated nonstandard English
sentences significantly more accurately than did white subjects (Marwit et al,
1977). Students in American schools are usually taught and tested only in
Standard English, which can put African American students at a disadvantage.
In fact, this issue was at the center debates concerning the use of Ebonics in
the American school system during the 1990s.
Researchers provide considerable 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; Boone et al, 2007; Teng and Manly, 2005). Kwate (2001) argues that IQ
tests are antagonistic and incompatible with an African centered conception of
intelligence and mental health, while a study by Obiakor and Utley (2004)
showed that culturally diverse learners are often excluded in educational
programs in the U.S. through misidentification, misassessment,
miscategorization, misplacement, and misinstruction-misintervention. When test
stimuli are more culturally pertinent to the experiences of African Americans,
performance improves (Hayles, 1991; Williams and Rivers, 1972b). For example,
research shows 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.
Studies using empirical methods also find that cultural differences in the
provision of information account for racial differences in IQ scores. Fagan
and Holland (2007) asked African-Americans and white Americans to solve
problems typical of those administered on standard IQ tests. Half of the
problems were solvable on the basis of information generally available to
either race, or on the basis of information newly learned; while other
problems were only solvable on the basis of specific previous knowledge. In
this study specific knowledge varied with race and was shown to be subject to
test bias (Fagan and Holland, 2007).
Test Design:
IQ tests are not constructed on the basis of any scientific model of
intelligence; they are simply created (by statistical manipulation of item
content) to identify individuals who have already been deemed to be
'intelligent' by other, more subjective, criteria (Richarson, 2002;
Richardson, 2000). These criteria involve what is called,
“norm-referencing.” In norm-referenced tests, items which do not
discriminate between preselected groups are simply rejected or thrown out
(Williams, 1972). So that test factors are no more than a product of the
arbitrary way that ability items are devised or selected for inclusion in
psychometric tests. Norm referenced measures are by far the most common method
used, trying out and discarding items based on item correlations is a major
part of the standardized test construction enterprise. In this respect, not
only can one expect to find examples of “cultural bias” built into IQ
tests, but also, “observer bias.”
Psychometric tests are intended to sample performance in some aspect of the
test taker's environment. However, popular IQ tests are hardly able to do this
outside of the “white middle class,” to whom the tests are typically
normed. They are also particularly harsh against those who are unfamiliar with
“white middle class’” cultural tools and values, or are simply unable to
receive an education that is comparable with this group (Richardson, 2000,
2002; Helms 1992, 1997; Barnes, 1972). For this and other reasons the use of
IQ tests can be unfair when comparing people outside of particular social
groups.
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 those test scores accord with a
particular set of restrictions. The same attribute must relate to the same set
of observations in the same way in each group (Borsboom, 2006; Mellenbergh,
1989). However, Wechsler (1944) “himself” warned that his Wechsler
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).” Williams
(1972) administered an intelligence test which happened to be normed on the
African American population to group of white Americans to illustrate the
effects of cultural bias, and norm referencing. In this study it was found
that black Americans demonstrated a “clear superiority” of white Americans
(p. 11).
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 an especially 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 with respect 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 very similar to the kind of skills and abilities that most
Anthropologists and paleoanthropologists credit with helping to make the human
species so evolutionarily formidable (Tattersall and Schwartz, 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. This study found that higher practical intelligence also 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.
A study by Bilalić 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. Chess is often considered to be a game which puts heavy demands
on one’s cognitive abilities and reasoning skills; requiring forward
planning, short and long term strategic considerations and the ability to
think dynamically. Thus, negative correlations between IQ scores and chess
skills should cast some serious doubt on the value of such tests. One may be
left asking, since negative correlations have been observed, which is a better
measure of one’s intelligence, chess skill or IQ?
Referenced Literature:
Armstrong, T. (1993). Seven Kinds of Smart: Identifying and Developing
Your Many Intelligences. New York: Penguin Group.
Arthur, John (2000). Invisible Sojourners: African Immigrant Diaspora in the
United States. Prager Westport, CT.
Baldwin J.A., Bell Y.R. (1985). The African Self-Consciousness Scale: An
Africentric Personality Questionnaire. Western Journal of Black Studies 1985,
p61-68.
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.
Bilalic 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.
Boone K.B., Victor T.L., Wen J., Razani J, and Marcel Pontón M. (2007). The
association between neuropsychological scores and ethnicity, language, and
acculturation variables in a large patient population. Archives of Clinical
Neuropsychology Volume 22, Issue 3, March 2007, Pages 355-365 Special
Issue: Cultural Diversity.
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.
Bradshaw, J. (2001). Developmental Disorders of the Fronto-Striatal System.
Philadelphia: Psychiatric Press.
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.
Cadzen, C.B. (1966). Subcultural Differences in Child Language: An
Inter-Disciplinary Review. Merrill-Palmer Quarterly, 1955, 12, pp. 185-214.
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.
Cassidy S. (2006). Second generation ethnic minorities make 'remarkable
progress'. Independent, the (London), Aug 31, 2006.
Ceci S.J. (1991). How Much Does Schooling Influence General Intelligence and
Its Cognitive Components? A Reassessment of the Evidence. Developmental
Psychology. 1991, Vol. 27, No. 5, 703-722.
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.
Conley, Dalton (1999). Being Black, Living in Red: Race Wealth and Social
Policy in America. Berkeley: University of California Press.
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.
Cronbach, L. J. (1990). Essentials of psychological testing (5th ed.). New
York: Harper & Row.
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.
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.
Fagan J.F., Holland C.R. (2002). Equal Opportunity and Racial Differences in
IQ: Evidence from Tests of Comprehension. Intelligence Volume 30, Issue 4,
July-August 2002, Pages 361-387.
Fagan J.F., Holland C.R. (2007). Racial equality in intelligence: Predictions
from a theory of intelligence as processing. Intelligence Volume 35, Issue 4,
July-August 2007, Pages 319-334.
Feuerstein, R. & Kozulin, A. (1995). The Bell Curve: Getting the facts
straight. Educational Leadership, 52(7), 71-74.
Flynn J.R., Dickens W.T. (2006). Black Americans Reduce the Racial IQ Gap:
Evidence from Standardization Samples. Psychological Science, October 2006.
Frank, G., (1983). The Wechsler Enterprise. Pergamum Press, Oxford.
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.
Herrnstein, R., & Murray, C. (1994). The bell curve. New York: Free Press.
Hilliard, Asa G., III (1995): 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. (1997). The triumph of wishful thinking over genetic irrelevance.
Cahiers de Psychologie Cognitive. 16, 711-720.
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.
Jensen, A. R. (1980). Bias in mental testing. New York: Free Press.
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.
Jinks, J. L., & Fulker, D. W. (1970). Comparison of the biometrical gene-tical,
MAVA, and classical approaches to the analysis of human behavior.
Psychological Bulletin, 73, 311-349.
Kamin L.J. (1995). Lies, Damn lies and Statistics. The Bell Curve Wars.
Kamin, L.J. (1974). The Science and Politics of I.Q. John Wiley &
Sons, 1974.
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.
Kempthorne, O. (1997). Heritability: uses and abuses. Genetica 99: 109-112,
1997.
Kent, M.M.(2007): Immigration and America's Black Population. Population
Bulletin 62, no. 4 (2007).
Kozulin, A. (1998). Profiles of immigrant students' cognitive performance on
Raven' s Progressive Matrices. Perceptual and Motor Skills, 87, 1311-1314.
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).
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., Heath A. (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.
Loehlin. J.C. & Nichols, (1976). Heredity, Environment, and Personality.
University of Texas Press, Austin and London.
Logan, J.R, Deane, G (2003). Black Diversity in Metropolitan
America. Lewis Mumford Center for Comparative Urban Regional Research
University Albany.
Mackintosh, N.J. (1998). IQ and Human Intelligence. Oxford: Oxford University
Press.
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.
Mellenbergh GJ. (1989). Item bias and item response theory. Int J Ed Res.
1989;13:127-143.
Mithen, S., 1998 (Ed). Creativity in Human Evolution and Prehistory. London:
Routledge.
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.
Naglieri J.A., Reardon S.M. (1993)Traditional IQ is irrelevant to learning
disabilities--intelligence is not. J Learn Disabil. 1993 Feb;26(2):127-33.
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.
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
Oliver M. and Shapiro T. (1995). Black Wealth/White Wealth: A New Perspective
on Racial Inequality. New York: Routledge
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.
Richardson, K. (2000). The Making of Intelligence. New York: Columbia
University Press.
Richardson K (2002). What IQ tests test. Theory Psychol 12314: 283.
Rispens J, van Yperen TA, van Duijn GA. (1991). The irrelevance of IQ to the
definition of learning disabilities: some empirical evidence. J Learn Disabil.
1991 Aug-Sep;24(7):434-8.
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.
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., (1990). Environmental versus genetic variance components
models for identical twins: A critique of Jinks and Fulker’s reanalysis of
the Shield’s data. Cahuers de Psychologie cognitive/EuropeanBulletin of
Psychology 10: 451-473
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)
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
Stern, W. (1914). The psychological methods of testing intelligence.
Baltimore, MD: Warwick & York.
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
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.
Tattersall, I. and J.H. Schwartz (2000). Extinct Humans. New York: Westview
Press.
Taylor, H. F. (1980). ''The IQ Game: A Methodological Inquiry into the
Heredity-Environment Controversy''. New Brunswick, NJ: Rutgers University
Press.
Teng, E. L., Manly J.J (2005). Neuropsychological Testing: Helpful or Harmful?
Alzheimer Disease & Associated Disorders. 19(4):267-271, October/December
2005.
The Canadian Encyclopedia (2008). Ethnic Groups: Blacks. Historica Foundation
of Canada (all rights reserved)
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
Tizard, B., Cooperman, A and Tizard, J. (1972) "Enviromental effects on
langauge development a study of young children in longstay residential
nurseries." Child Development, 43: 342-3
Tzuriell, D. & Kaufman, R. (1999). Mediated learning and cognitive
modifiability: Dynamic assessment of young Ethiopian immigrant children to
Israel. Journal of Cross-cultural Psychology, 30 (3), 359-380.
Uhlenberg, Jeffery and Kathleen M. Brown (2004). “Racial Gaps in Teachers
Perceptions of the Achievement Gap.” Education and Urban Society.
34(4):494-530
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.
Vetta A. and Coureau D. (2003). Demographic Behavior and Behaviour Genetics.
Population (English Edition) p 401-428 Volume 58 2003/4-5
Voight BF, Kudaravalli S, Wen X, Pritchard JK (2006): A map of recent positive
selection in the human genome. PLoS Biol 4(3): e72.
Wahlsten, D. (1981) Review of The IQ Game by Howard F. Taylor. Behaviorists
for Social Action Journal, 3, 33-34.
Wahlsten, D. 1990. Insensitivity of the Analysis of variance to
heredity-environment interations. Behavioral and Brain Sciences 13: 109-120
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).
Williams R.L. (1972). The BITCH-100: A Culture-Specific Test. Paper
presented at the American Psychological Association Annual Convention,
Honolulu, Hawaii, September 1972.
Wilson A. (1978). Developmental Psychology of the Black Child. Africana
Research Publications (December 1978).
CIA World Factbook, 2004; Yearbook of immigration Statistics, 2003


