[Paleopsych] Rushton and Jensen: Thirty Years of Research on Race Differences in Cognitive Ability, with responses.
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Rushton and Jensen: Thirty Years of Research on Race Differences in Cognitive
Ability, with responses.
Psychology, Public Policy, and Law, 2005 June, Vol. 11(2), a publication of the
American Psychological Association.
[First, a EurekAlert!. Second, the announcement from the American Psychological
Association, which contains summaries of the article and responses. Third, the
Rushton and Jensen article. Fourth till end, the responses.]
Black-White-East Asian IQ differences at least 50% genetic, major law review
journal concludes
http://www.eurekalert.org/pub_releases/2005-04/cdri-bai042505.php
Public release date: 25-Apr-2005
Contact: Prof. J. P. Rushton
[3]rushton at uwo.ca
519-661-3685
[4]Charles Darwin Research Institute
Black-White-East Asian IQ differences at least 50% genetic, major law review
journal concludes
A 60-page review of the scientific evidence, some based on
state-of-the-art magnetic resonance imaging (MRI) of brain size, has
concluded that race differences in average IQ are largely genetic. The
lead article in the June 2005 issue of Psychology, Public Policy and
Law, a journal of the American Psychological Association, examined 10
categories of research evidence from around the world to contrast "a
hereditarian model (50% genetic-50% cultural) and a culture-only model
(0% genetic-100% cultural)."
The paper, "Thirty Years of Research on Race Differences in Cognitive
Ability," by J. Philippe Rushton of the University of Western Ontario
and Arthur R. Jensen of the University of California at Berkeley,
appeared with a positive commentary by Linda Gottfredson of the
University of Delaware, three critical ones (by Robert Sternberg of
Yale University, Richard Nisbett of the University of Michigan, and
Lisa Suzuki & Joshua Aronson of New York University), and the authors'
reply.
"Neither the existence nor the size of race differences in IQ are a
matter of dispute, only their cause," write the authors. The
Black-White difference has been found consistently from the time of
the massive World War I Army testing of 90 years ago to a massive
study of over 6 million corporate, military, and higher-education
test-takers in 2001.
"Race differences show up by 3 years of age, even after matching on
maternal education and other variables," said Rushton. "Therefore they
cannot be due to poor education since this has not yet begun to exert
an effect. That's why Jensen and I looked at the genetic hypothesis in
detail. We examined 10 categories of evidence."
1. The Worldwide Pattern of IQ Scores. East Asians average higher on
IQ tests than Whites, both in the U. S. and in Asia, even though IQ
tests were developed for use in the Euro-American culture. Around the
world, the average IQ for East Asians centers around 106; for Whites,
about 100; and for Blacks about 85 in the U.S. and 70 in sub-Saharan
Africa.
2. Race Differences are Most Pronounced on Tests that Best Measure the
General Intelligence Factor (g). Black-White differences, for example,
are larger on the Backward Digit Span test than on the less g loaded
Forward Digit Span test.
3. The Gene-Environment Architecture of IQ is the Same in all Races,
and Race Differences are Most Pronounced on More Heritable Abilities.
Studies of Black, White, and East Asian twins, for example, show the
heritability of IQ is 50% or higher in all races.
4. Brain Size Differences. Studies using magnetic resonance imaging
(MRI) find a correlation of brain size with IQ of about 0.40. Larger
brains contain more neurons and synapses and process information
faster. Race differences in brain size are present at birth. By
adulthood, East Asians average 1 cubic inch more cranial capacity than
Whites who average 5 cubic inches more than Blacks.
5. Trans-Racial Adoption Studies. Race differences in IQ remain
following adoption by White middle class parents. East Asians grow to
average higher IQs than Whites while Blacks score lower. The Minnesota
Trans-Racial Adoption Study followed children to age 17 and found race
differences were even greater than at age 7: White children, 106;
Mixed-Race children, 99; and Black children, 89.
6. Racial Admixture Studies. Black children with lighter skin, for
example, average higher IQ scores. In South Africa, the IQ of the
mixed-race "Colored" population averages 85, intermediate to the
African 70 and White 100.
7. IQ Scores of Blacks and Whites Regress toward the Averages of Their
Race. Parents pass on only some exceptional genes to offspring so
parents with very high IQs tend to have more average children. Black
and White children with parents of IQ 115 move to different
averages--Blacks toward 85 and Whites to 100.
8. Race Differences in Other "Life-History" Traits. East Asians and
Blacks consistently fall at two ends of a continuum with Whites
intermediate on 60 measures of maturation, personality, reproduction,
and social organization. For example, Black children sit, crawl, walk,
and put on their clothes earlier than Whites or East Asians.
9. Race Differences and the Out-of-Africa theory of Human Origins.
East Asian-White-Black differences fit the theory that modern humans
arose in Africa about 100,000 years ago and expanded northward. During
prolonged winters there was evolutionary selection for higher IQ
created by problems of raising children, gathering and storing food,
gaining shelter, and making clothes.
10. Do Culture-Only Theories Explain the Data? Culture-only theories
do not explain the highly consistent pattern of race differences in
IQ, especially the East Asian data. No interventions such as ending
segregation, introducing school busing, or "Head Start" programs have
reduced the gaps as culture-only theory would predict.
In their article, Rushton and Jensen also address some of the policy
issues that stem from their conclusions. Their main recommendation is
that people be treated as individuals, not as members of groups. They
emphasized that their paper pertains only to average differences. They
also called for the need to accurately inform the public about the
true nature of individual and group differences, genetics and
evolutionary biology.
Rushton and Jensen are well-known for research on racial differences
in intelligence. Jensen hypothesized a genetic basis for Black-White
IQ differences in his 1969 Harvard Educational Review article. His
later books Bias in Mental Tests (1980) and The g Factor (1998), as
well as Rushton's (1995) Race, Evolution, and Behavior, show that
tests are not biased against English speaking minorities and that
Black-White-East Asian differences in brain size and IQ belong in an
evolutionary framework.
J. Philippe Rushton, Department of Psychology, University of Western
Ontario, London, Ontario N6A 5C2, Canada. Tel: 519-661-3685; Email:
[5]rushton at uwo.ca
Arthur R. Jensen, School of Education, University of California at
Berkeley, Berkeley, California 94305. Email: [6]nesnejanda at aol.com
References
3. mailto:rushton at uwo.ca
4. http://www.charlesdarwinresearch.org/
5. mailto:rushton at uwo.ca
6. mailto:nesnejanda at aol.com
----------------------
PsycARTICLES - Browse Psychology, Public Policy, and Law
http://content.apa.org/journals/law
Editor: Jane Goodman-Delahunty, JD, PhD
Volume 11, Issue 2
[63]Thirty years of research on race differences in cognitive ability.
Rushton, J. Philippe; Jensen, Arthur R.
_________________________________________________________________
The culture-only (0% genetic-100% environmental) and the hereditarian
(50% genetic-50% environmental) models of the causes of mean
Black-White differences in cognitive ability are compared and
contrasted across 10 categories of evidence: the worldwide
distribution of test scores, g factor of mental ability, heritability,
brain size and cognitive ability, transracial adoption, racial
admixture, regression, related life-history traits, human origins
research, and hypothesized environmental variables. The new evidence
reviewed here points to some genetic component in Black-White
differences in mean IQ. The implication for public policy is that the
discrimination model (i.e., Black-White differences in socially valued
outcomes will be equal barring discrimination) must be tempered by a
distributional model (i.e., Black-White outcomes reflect underlying
group characteristics).
[67]There are no public-policy implicatons: A reply to Rushton and
Jensen (2005).
Sternberg, Robert J.
J. P. Rushton and A. R. Jensen (see record 2005-03637-001) purport to
show public-policy implications arising from their analysis of alleged
genetic bases for group mean differences in IQ. This article argues
that none of these implications in fact follow from any of the data
they present. The risk in work such as this is that public-policy
implications may come to be ideologically driven rather than data
driven, and to drive the research rather than be driven by the data.
[71]Heredity, environment, and race differences in IQ: A commentary on
Rushton and Jensen (2005).
Nisbett, Richard E.
J. P. Rushton and A. R. Jensen (see record 2005-03637-001) ignore or
misinterpret most of the evidence of greatest relevance to the
question of heritability of the Black-White IQ gap. A dispassionate
reading of the evidence on the association of IQ with degree of
European ancestry for members of Black populations, convergence of
Black and White IQ in recent years, alterability of Black IQ by
intervention programs, and adoption studies lend no support to a
hereditarian interpretation of the Black-White IQ gap. On the
contrary, the evidence most relevant to the question indicates that
the genetic contribution to the Black-White IQ gap is nil.
[75]What if the hereditarian hypothesis is true?
Gottfredson, Linda S.
J. P. Rushton and A. R. Jensen (see record 2005-03637-001) review 10
bodies of evidence to support their argument that the long-standing,
worldwide Black-White average differences in cognitive ability are
more plausibly explained by their hereditarian (50% genetic causation)
theory than by culture-only (0% genetic causation) theory. This
commentary evaluates the relevance of their evidence, the overall
strength of their case, the implications they draw for public policy,
and the suggestion by some scholars that the nation is best served by
telling benevolent lies about race and intelligence.
[79]The cultural malleability of intelligence and its impact on the
racial/ethnic hierarchy.
Suzuki, Lisa; Aronson, Joshua
This commentary highlights previous literature (see record
2005-03637-001) focusing on cultural and environmental explanations
for the racial/ethnic group hierarchy of intelligence. Assumptions
underlying definitions of intelligence, heritability/genetics,
culture, and race are noted. Historical, contextual, and testing
issues are clarified. Specific attention is given to studies
supporting stereotype threat, effects of mediated learning
experiences, and relative functionalism. Current test development
practices are critiqued with respect to methods of validation and item
development. Implications of the genetic vs. culture-only arguments
are discussed with respect to the malleability of IQ.
[83]Wanted: More race realism, less moralistic fallacy.
Rushton, J. Philippe; Jensen, Arthur R.
Despite repeated claims to the contrary, there has been no narrowing
of the 15- to 18-point average IQ difference between Blacks and Whites
(1.1 standard deviations); the differences are as large today as they
were when first measured nearly 100 years ago. They, and the
concomitant difference in standard of living, level of education, and
related phenomena, lie in factors that are largely heritable, not
cultural. The IQ differences are attributable to differences in brain
size more than to racism, stereotype threat, item selection on tests,
and all the other suggestions given by the commentators. It is time to
meet reality. It is time to stop committing the "moralistic fallacy"
that good science must conform to approved outcomes.
References
63. http://content.apa.org/journals/law/11/2/235.html
67. http://content.apa.org/journals/law/11/2/295.html
71. http://content.apa.org/journals/law/11/2/302.html
75. http://content.apa.org/journals/law/11/2/311.html
79. http://content.apa.org/journals/law/11/2/320.html
83. http://content.apa.org/journals/law/11/2/328.html
---------------
Rushton and Jensen: Thirty Years of Research on Race Differences in
Coagnitive Ability, with responses.
Psychology, Public Policy, and Law
by the American Psychological Association
Volume 11(2)
June 2005
p 235-294
THIRTY YEARS OF RESEARCH ON RACE DIFFERENCES IN COGNITIVE ABILITY
Rushton, J Philippe1,3; Jensen, Arthur R.2
1Department of Psychology, The University of Western Ontario, London,
Ontario, Canada
2School of Education, University of California, Berkeley
3 Correspondence concerning this article should be addressed to J.
Philippe Rushton, Department of Psychology, The University of Western
Ontario, London, Ontario N6A 5C2, Canada. E-mail: rushton at uwo.ca
Outline
* Abstract
* Section 1: Background
* Section 2: The Two Conflicting Research Programs
* Section 3: Mean Race-IQ Differences: A Global Perspective
* Section 4: The g Factor and Mean Race-IQ Differences
* Section 5: Gene-Environment Architecture and Mean Black-White IQ
Differences
* Section 6: Race, Brain Size, and Cognitive Ability
* Section 7: Mean Race-IQ Differences and Transracial Adoption
Studies
* Section 8: Mean Race-IQ Differences and Racial Admixture
* Section 9: Mean Race-IQ Differences and Regression to the Mean
* Section 10: The Race-Behavior Matrix
* Section 11: Mean Race-IQ Differences and Human Origins
* Section 12: How Well Have Culture-Only Theories of Mean Race-IQ
Differences Held Up?
* Section 13: Evaluating the Culture-Only and the Hereditarian
Research Programs
* Mean Race-IQ Differences Are Found Worldwide (Section 3)
* Race-IQ Differences Are Most Pronounced on the More g-Loaded
Components of Tests and Least So on the Most Culturally Loaded Items
(Section 4)
* Race-IQ Differences Are Most Pronounced on the More
Heritable Components of Tests With Little or No Evidence of
Race-Specific Developmental Processes (Section 5)
* Mean Race-IQ Differences Are Associated With Mean Brain Size
Differences (Section 6)
* Mean Race Differences in IQ Remain Following Transracial
Adoption (Section 7)
* Studies of Racial Admixture Reflect Mean Black-White IQ
Differences (Section 8)
* IQs Show Regression Toward Predicted Racial Means (Section
9)
* Mean Race-IQ Differences Are Paralleled by a Matrix of Other
Traits and Behaviors (Section 10)
* Mean Race-IQ Differences and Human Evolution (Section 11)
* Culture-Only Hypotheses Fail to Account for Mean Race-IQ
Differences (Section 12)
* Section 14: Progressive Research Leads to Provisional Truth
* Section 15: Implications for Public Policy
* Discrimination or Distribution?
* Race Relations
* Educational, Vocational, and Psychological Testing
* Health, Medical Genetics, and Pharmaco-Anthropology
* Conflicting Worldviews
* References
Graphics
* Figure 1
* Table 1
* Figure 2
* Figure 3
* Table 2
* Table 3
* Table 4
* Table 5
* Table 5
The culture-only (0% genetic-100% environmental) and the hereditarian
(50% genetic-50% environmental) models of the causes of mean Black-White
differences in cognitive ability are compared and contrasted across 10
categories of evidence: the worldwide distribution of test scores, g
factor of mental ability, heritability, brain size and cognitive
ability, transracial adoption, racial admixture, regression, related
life-history traits, human origins research, and hypothesized
environmental variables. The new evidence reviewed here points to some
genetic component in Black-White differences in mean IQ. The implication
for public policy is that the discrimination model (i.e., Black-White
differences in socially valued outcomes will be equal barring
discrimination) must be tempered by a distributional model (i.e.,
Black-White outcomes reflect underlying group characteristics).
Section 1: Background
Throughout the history of psychology, no question has been so persistent
or so resistant to resolution as that of the relative roles of nature
and nurture in causing individual and group differences in cognitive
ability (Degler, 1991; Loehlin, Lindzey, & Spuhler, 1975). The
scientific debate goes back to the mid-19th century (e.g., Galton, 1869;
Nott & Glidden, 1854 ). Starting with the widespread use of standardized
mental tests in World War I, average ethnic and racial group differences
were found. Especially vexing has been the cause(s) of the 15-point
Black-White IQ difference in the United States.
In 1969, the Harvard Educational Review published Arthur Jensen's
lengthy article, "How Much Can We Boost IQ and School Achievement?"
Jensen concluded that (a) IQ tests measure socially relevant general
ability; (b) individual differences in IQ have a high heritability, at
least for the White populations of the United States and Europe; (c)
compensatory educational programs have proved generally ineffective in
raising the IQs or school achievement of individuals or groups; (d)
because social mobility is linked to ability, social class differences
in IQ probably have an appreciable genetic component; and tentatively,
but most controversially, (e) the mean Black-White group difference in
IQ probably has some genetic component.
Jensen's (1969) article was covered in Time, Newsweek, Life, U.S. News &
World Report, and New York Times Magazine . His conclusions, the
theoretical issues they raised, and the public policy recommendations
that many saw as stemming directly from them were dubbed "Jensenism," a
term which entered the dictionary. Since 1969, Jensen has continued to
publish prolifically on all of these issues, and increasing numbers of
psychometricians and behavioral geneticists have come to agree with one
or more of the tenets of Jensenism (Snyderman & Rothman, 1987, 1988).
The Bell Curve (Herrnstein & Murray, 1994 ) presented general readers an
update of the evidence for the hereditarian position along with several
policy recommendations and an original analysis of 11,878 youths
(including 3,022 Blacks) from the 12-year National Longitudinal Survey
of Youth. It found that most 17-year-olds with high scores on the Armed
Forces Qualification Test, regardless of ethnic background, went on to
occupational success by their late 20s and early 30s, whereas those with
low scores were more inclined to welfare dependency. The study also
found that the average IQ for African Americans was lower than those for
Latino, White, Asian, and Jewish Americans (85, 89, 103, 106, and 113,
respectively; Herrnstein & Murray, 1994, pp. 273-278).
Currently, the 1.1 standard deviation difference in average IQ between
Blacks and Whites in the United States is not in itself a matter of
empirical dispute. A meta-analytic review by Roth, Bevier, Bobko,
Switzer, and Tyler (2001) showed it also holds for college and
university application tests such as the Scholastic Aptitude Test (SAT;
N = 2.4 million) and the Graduate Record Examination (GRE; N = 2.3
million), as well as for tests for job applicants in corporate settings
(N = 0.5 million) and in the military (N = 0.4 million). Because test
scores are the best predictor of economic success in Western society
(Schmidt & Hunter, 1998), these group differences have important
societal outcomes (R. A. Gordon, 1997; Gottfredson, 1997).
The question that still remains is whether the cause of group
differences in average IQ is purely social, economic, and cultural or
whether genetic factors are also involved. Following publication of The
Bell Curve, the American Psychological Association (APA) established an
11-person Task Force (Neisser et al., 1996 ) to evaluate the book's
conclusions. Based on their review of twin and other kinship studies,
the Task Force for the most part agreed with Jensen's (1969) Harvard
Educational Review article and The Bell Curve , that within the White
population the heritability of IQ is "around .75" (p. 85). As to the
cause of the mean Black-White group difference, however, the Task Force
concluded: "There is certainly no support for a genetic interpretation"
(p. 97).
Among the factors contributing to the longstanding lack of resolution of
this important and controversial issue are the difficulty of the subject
matter, the political issues associated with it and the emotions they
arouse, and the different meta-theoretical perspectives of the
experimental and correlational methodologies. Cronbach (1957) referred
to these conflicting approaches as the two "halves" of psychology
because researchers are predisposed to draw different conclusions
depending on whether they adopt a "manipulations-lead-to-change" or a
"correlations-find-stability" paradigm.
Here we review in detail the research that has accumulated since
Jensen's (1969) article and compare our findings with earlier reviews
and evaluations such as those by Loehlin et al. (1975), P. E. Vernon
(1979), Herrnstein and Murray (1994), the APA Task Force (Neisser et
al., 1996), and Nisbett (1998) . Facts in themselves typically do not
answer scientific questions. For a question so complex as the cause of
the average Black-White group difference in IQ, no one fact, one study,
nor indeed any single line of evidence, can hope to be determinative.
Rather, resolving the issue requires examining several independent lines
of evidence to determine if, when taken together, they confirm or refute
rival hypotheses and research programs.
The philosophy of science methodology used here is guided by the view
that, just as in individual studies the principal of aggregation holds
that a set of measurements provides a more reliable indicator than any
single measure taken from the set (Rushton, Brainerd, & Pressley, 1983
), so in reviewing multiple lines of evidence, making strong inferences
from a number of contending hypotheses is more efficacious than
considering only one hypothesis at a time (Platt, 1964). Although strong
inference is the method of science, it has, more often than not, been
eschewed in this controversial debate.
The final section of this article addresses the question of what these
conclusions imply for policy, specifically for the issues of educational
and psychological testing, health, race relations, and conflicting
worldviews about the essence of human nature. It suggests that the
distributional model that takes genetic factors into account must temper
the discrimination model that explains Black-White differences in
socially valued outcomes.
Section 2: The Two Conflicting Research Programs
Here, we review the research on Black-White difference in average IQ
published since Jensen's (1969) now 36-year-old article. We then apply
the philosophy of science methodologies of Platt (1964), Lakatos (1970,
1978), and Urbach (1974a, 1974b) to determine if the preponderance of
this new evidence strengthens or weakens Jensen's (1969) tentative
assertion that it is more likely than not that some part of the cause of
the mean Black-White difference is genetic. The data reviewed have been
collated from articles in specialist journals and a number of scholarly
monographs on the nature of intelligence, behavioral genetics, and
social policy issues, as well as recent book-length reviews (Devlin,
Feinberg, Resnick, & Roeder, 1997; Herrnstein & Murray, 1994; Jencks &
Phillips, 1998; Jensen, 1998b; Lynn & Vanhanen, 2002; Rushton, 2000;
Sternberg, 2000 ). While we focus on the mean Black-White difference in
IQ because it is the topic on which most of the research to date has
been conducted, studies of other traits (e.g., reaction times) and other
groups (e.g., East Asians) are included when those data are sufficient
and informative.
Some have argued that the cause of Black-White differences in IQ is a
pseudo question because "race" and "IQ" are arbitrary social
constructions (Tate & Audette, 2001 ). However, we believe these
constructs are meaningful because the empirical findings documented in
this article have been confirmed across cultures and methodologies for
decades. The fuzziness of racial definitions does not negate their
utility. To define terms, based on genetic analysis, roughly speaking,
Blacks (Africans, Negroids) are those who have most of their ancestors
from sub-Saharan Africa; Whites (Europeans, Caucasoids) have most of
their ancestors from Europe; and East Asians (Orientals, Mongoloids)
have most of their ancestors from Pacific Rim countries (Cavalli-Sforza,
2000; Cavalli-Sforza, Menozzi, & Piazza, 1994; Nei & Roychoudhury, 1993;
Risch, Burchard, Ziv, & Tang, 2002). Although he eschewed the term race,
Cavalli-Sforza's (2000 , p. 70) maximum likelihood tree made on the
basis of molecular genetic markers substantially supports the
traditional racial groups classification. Of course, in referring to
population or racial group differences we are discussing averages.
Individuals are individuals, and the three groups overlap substantially
on almost all traits and measures.
The hereditarian position originated in the work of Charles Darwin
(1859, 1871) and then was elaborated by his cousin Sir Francis Galton
(1869, 1883) . Based on research models used in behavioral genetics,
this view contends that a substantial part (say 50%) of both individual
and group differences in human behavioral traits is genetic. It
therefore follows that even if all individuals in both groups were
treated identically, average group differences would not disappear,
though they might diminish.
The opposing culture-only position finds no need to posit any genetic
causation, stating that if the environments for all individuals could be
equalized, the observed group differences in average IQ would
effectively disappear, though this might be difficult to achieve. This
position has been predominant in the social sciences since the 1930s.
It is essential to keep in mind precisely what the two rival positions
do and do not say-about a 50% genetic-50% environmental etiology for the
hereditarian view versus an effectively 0% genetic-100% environmental
etiology for the culture-only theory. The defining difference is whether
any significant part of the mean Black-White IQ difference is genetic
rather than purely cultural or environmental in origin. Hereditarians
use the methods of quantitative genetics, and they can and do seek to
identify the environmental components of observed group differences.
Culture-only theorists are skeptical that genetic factors play any
independently effective role in explaining group differences.
Most of those who have taken a strong position in the scientific debate
about race and IQ have done so as either hereditarians or culture-only
theorists. Intermediate positions (e.g., gene-environment interaction)
can be operationally assigned to one or the other of the two positions
depending on whether they predict any significant heritable component to
the average group difference in IQ. For example, if gene-environment
interactions make it impossible to disentangle causality and apportion
variance, for pragmatic purposes that view is indistinguishable from the
100% culture-only program because it denies any potency to the genetic
component proposed by hereditarians.
It is also important to define and interpret heritability correctly.
Heritability refers to the genetic contribution to the individual
differences (variance) in a particular group, not to the phenotype of a
single individual. Heritability is not a constant that holds for all
groups or in all environments. A heritability of 1.00 means all the
observed differences in that group are due to genetic differences and
not at all to their differences in the environment. A heritability of
zero (0.00) means the converse. A heritability of 0.50 means the
observed variation is equally the result of genetic and of environmental
differences. The heritability of height in modern industrial
populations, for example, is about 90%, which means that most of the
differences in height among the individuals are due to their genetic
differences.
Behavioral Genetics by Plomin, DeFries, McClearn, and McGuffin (2001)
provides a detailed explanation of heritability (see also Jensen, 1973;
Miele, 2002 , for general readers). Heritability estimates are true only
for particular populations at particular times. They can vary in
different populations or at different times. Equalizing environments,
for example, produces the counterintuitive result of increasing
heritability because any individual differences that remain must be due
to genetic differences.
The cause of individual differences within groups has no necessary
implication for the cause of the average difference between groups. A
high heritability within one group does not mean that the average
difference between it and another group is due to genetic differences,
even if the heritability is high in both groups. However, within-groups
evidence does imply the plausibility of the between-groups differences
being due to the same factors, genetic or environmental. If variations
in level of education or nutrition or genes reliably predict individual
variation within Black and within White groups, then it would be
reasonable to consider these variables to explain the differences
between Blacks and Whites. Of course, independent evidence would then be
needed to establish any relationship.
Heritability describes what is the genetic contribution to individual
differences in a particular population at a particular time, not what
could be . If either the genetic or the environmental influences change
(e.g., due to migration, greater educational opportunity, better
nutrition), then the relative impact of genes and environment will
change. Heritability has nothing to say about what should be. If a trait
has a high heritability it does not mean that it cannot be changed.
Environmental change is possible. For example, phenylketunuria (PKU) is
a single-gene disorder that causes mental retardation but that can be
prevented by beginning a diet low in phenylaline early in life. (Note
that the only effective treatment for PKU is aimed directly at the
specific chemical factor that causes it.) The fact that the heritability
of IQ is between 0.50 and 0.80 does not mean that individual differences
are fixed and permanent. It does tell us that some individuals are
genetically predisposed to be more teachable, more trainable, and more
capable of changing than others, under current conditions (Jensen, 1973;
Miele, 2002).
Having defined the terms of the debate, we now discuss approaches for
resolving it. Lakatos's (1970, 1978) analytical methodology classifies
research programs as being either progressive or degenerating. A
progressive program not only explains existing phenomena and theoretical
anomalies but also offers novel predictions, some of which can be tested
and then either confirmed or rejected. A degenerating program merely
accommodates existing anomalies by a series of new, unrelated, ad hoc
hypotheses, ignores them, or denies their existence.
The philosopher Peter Urbach (1974a, 1974b) applied this methodology and
concluded that the hereditarian/culture-only IQ debate is really a
conflict of research programs that goes back to their classic
proponents-Francis Galton (1869) for the hereditarians and J. B. Watson
(1924) for the environmentalists. Each has an underlying set of
assumptions, termed its hard core, and a heuristic machinery that
generates hypotheses. The hard core of the hereditarian program is that
(a) all individuals possess some level of general mental capacity called
general intelligence that, to some degree, influences all cognitive
activity, and (b) the differences between individuals and between groups
in general intelligence are largely the result of genetic differences.
The hard core of the culture-only program is that (a) there are a number
of different learned mental skills or intelligences, and (b) any
observed differences in cognitive performance are the result of
environmental factors.
Hereditarian heuristics include constructing better tests, developing
better techniques for measuring mental abilities, and discovering
biological correlates (e.g., heritability, inbreeding depression and
heterosis, brain size, brain metabolic rate, brain evoked potentials,
brain imaging) of these tests. The process then involves examining the
similarities of the scores among people whose varying degrees of genetic
resemblance can be predicted from Mendelian theory (Fisher, 1918 ).
Culture-only heuristics include searching for the environmental factors
that cause differences in intellectual performance and discovering the
bias in existing tests. If two groups differ in mean IQ, culture-only
theorists conjecture either that the lower scoring group has been
exposed to one or more deleterious experience or been deprived of some
beneficial environmental stimuli or that the tests are not valid
measures of their true ability. Compensatory training might be initiated
and the hypothesis confirmed if the groups then obtain more nearly equal
scores, or if less biased tests are developed on which the group
differences are reduced but still predict outside criteria. Of course,
these two programs overlap to some degree, and a given experiment might
well combine elements of the heuristics of each.
Reviewed here are new data sets for 10 categories of evidence that have
become available since Jensen's (1969) article. They include the
international pattern of IQ test scores, more and less g -loaded
components of tests, heritability, brain-size and cognitive-ability
relations, transracial adoption, racial admixture, regression to the
mean, the race-behavior matrix, human origins research, and hypothesized
environmental variables. These findings are then used to evaluate the
culture-only and hereditarian models in terms of the methodology
proposed by Lakatos (1970, 1978).
Section 3: Mean Race-IQ Differences: A Global Perspective
The IQ debate became worldwide in scope when it was shown that East
Asians scored higher on IQ tests than did Whites, both within the United
States and in Asia, even though IQ tests were developed for use in the
Euro American culture (Lynn, 1977, 1978, 1982; P. E. Vernon, 1979, 1982
). Around the world, the average IQ for East Asians centers around 106;
that for Whites, about 100; and that for Blacks, about 85 in the United
States and 70 in sub-Saharan Africa. Most of the early research was
conducted in the United States, but some was also performed in Canada
and the Caribbean (Eysenck, 1971, 1984; Jensen, 1969, 1973; Osborne &
McGurk, 1982; Shuey, 1958, 1966; cf. Flynn, 1980; Kamin, 1974; Lewontin,
Rose, & Kamin, 1984 ). In the United States, 15% to 20% of the Black IQ
distribution exceeds the White median IQ, so many Blacks obtain scores
above the White average. This same order of mean group differences is
also found on "culture-fair" tests and on reaction time tasks. Hundreds
of studies on millions of people have confirmed the three-way racial
pattern (Jensen, 1998b; Lynn & Vanhanen, 2002; Rushton, 2000).
Racial-group differences in IQ appear early. For example, the Black and
the White 3-year-old children in the standardization sample of the
Stanford-Binet IV show a 1 standard deviation mean difference after
being matched on gender, birth order, and maternal education (Peoples,
Fagan, & Drotar, 1995 ). Similarly, the Black and the White 2½- to
6-year-old children in the U.S. standardization sample of the
Differential Aptitude Scale have a 1 standard deviation mean difference.
No data are available for East Asian children at the youngest ages. On
the Differential Aptitude Battery, by age 6, however, the average IQ of
East Asian children is 107, compared with 103 for White children and 89
for Black children (Lynn, 1996 ). The size of the average Black-White
difference does not change significantly over the developmental period
from 3 years of age and beyond (see Jensen, 1974, 1998b).
Serious questions have been raised about the validity of using tests for
racial comparisons. However, because the tests show similar patterns of
internal item consistency and predictive validity for all groups, and
because the same differences are found on relatively culture-free tests,
many psychometricians have concluded that the tests are valid measures
of racial differences, at least among people sharing the culture of the
authors of the test (Jensen, 1980; Wigdor & Garner, 1982 ). This
conclusion was endorsed by the APA Task Force's statement: "Considered
as predictors of future performance, the tests do not seem to be biased
against African Americans" (Neisser et al., 1996, p. 93).
Most disputed is the validity of the low mean IQ scores reported for
sub-Saharan Africans. Lynn's (1991) review of 11 studies found a mean IQ
of 70. A subsequent review of over two dozen studies by Lynn and
Vanhanen (2002) found an average IQ of 70 for West, Central, East, and
Southern Africa. For example, in Nigeria, Fahrmeier (1975) collected
data on 375 children ages 6 to 13 years in a study of the effects of
schooling on cognitive development. The children's mean score on the
Colored Progressive Matrices was 12 out of 36, which is at the 4th
percentile for 9½-year-olds on U.S. norms, or an IQ equivalent of about
75 (Raven et al., 1990, pp. 97-98). In Ghana, Glewwe and Jacoby (1992)
reported a World Bank study that tested a representative sample of 1,736
individuals ranging in age from 11 to 20 years old from the entire
country. All had completed primary school; half were attending middle
school. Their mean score on the Colored Progressive Matrices was 19 out
of 36, which is below the 1st percentile for 15½-year-olds on U.S.
norms, an IQ equivalent of less than 70. In Kenya, Sternberg et al.
(2001) administered the Colored Progressive Matrices to 85 children ages
12 to 15 years old who scored 23.5 out of 36, which is about the 2nd
percentile for 13½-year-olds, an IQ equivalent of 70. In Zimbabwe, Zindi
(1994) reported mean IQs for 204 African 12- to 14-year-olds of 67 on
the Wechsler Intelligence Scale for Children-Revised (WISC-R) and of 72
on the Standard Progressive Matrices. In South Africa, Owen (1992) found
that 1,093 African 12- to 14-year-old high school students solved 28 out
of 60 problems on the Standard Progressive Matrices, which is around the
10th percentile, or an IQ equivalent of about 80 (Raven, Raven, & Court,
1998, p. 77). Again in South Africa, Skuy, Schutte, Fridjhon, and
O'Carroll (2001) found mean scores 1 to 2 standard deviations below U.S.
norms on a wide variety of individually administered tests given to 154
African high school students under optimized conditions.
Black university students in South Africa also show relatively low mean
test scores. Sixty-three undergraduates at the all-Black universities of
Fort Hare, Zululand, the North, and the Medical University of South
Africa had a full-scale IQ of 77 on the Wechsler Adult Intelligence
Scale-Revised (Avenant, 1988, cited in Nell, 2000, pp. 26-28). In a
study at the University of Venda in South Africa's Northern Province by
Grieve and Viljoen (2000) , 30 students in 4th-year law and commerce
averaged a score of 37 out of 60 on the Standard Progressive Matrices,
equivalent to an IQ of 78 on U.S. norms. A study at South Africa's
University of the North by Zaaiman, van der Flier, and Thijs (2001)
found the highest scoring African sample to that date-147 first-year
mathematics and science students who scored 52 out of 60 on the Standard
Progressive Matrices, which is equivalent to an IQ of 100. This higher
score may reflect the fact that they were mathematics and science
students, specially selected for admission to the university from a pool
of 700 applicants on the basis of a math-science selection test.
At the University of the Witwatersrand in Johannesburg, South Africa,
Rushton, Skuy, and colleagues gave the Raven's Progressive Matrices in
four separate studies under optimal testing conditions. Rushton and Skuy
(2000) found 173 African 1st-year psychology students averaged an IQ
equivalent of 84. Skuy et al. (2002) tested another 70 psychology
students who averaged an IQ equivalent of 83. After receiving training
on how to solve Matrices-type items, their mean score rose to an IQ
equivalent of 96. Rushton, Skuy, and Fridjhon (2002, 2003) gave nearly
200 African 1st-year engineering students both the Standard and the
Advanced version of the Raven's test and found they averaged an IQ of 97
on the Standard and 103 on the Advanced, making them the highest scoring
African sample on record. (The White university students in these four
studies had IQs from 105 to 117; East Indian students had intermediate
IQs, from 102 to 106.)
Many critics claim that Western-developed IQ tests are not valid for
groups as culturally different as sub-Saharan Africans (e.g., Nell,
2000). The main evidence to support a claim of external bias would be if
the test failed to predict performance for Africans. Even if tests only
underpredicted performance for Africans compared with non-Africans, it
would suggest that their test scores underestimated their "true" IQ
scores. However, a review by Kendall, Verster, and von Mollendorf (1988)
showed that test scores for Africans have about equal predictive
validity as those for non-Africans (e.g., 0.20 to 0.50 for students'
school grades and for employees' job performance). The review also
showed that many of the factors that influence scores in Africans are
the same as those for Whites (e.g., coming from an urban vs. a rural
environment; being a science rather than an arts student; having had
practice on the tests; and the well-documented curvilinear relationship
with age). Similarly, Sternberg et al.'s (2001) study of Kenyan 12- to
15-year-olds found that IQ scores predicted school grades, with a mean r
= .40 (p <.001; after controlling for age and socioeconomic status
[SES], r = .28, p <.01). In Rushton et al.'s (2003) study of African and
non-African engineering students at the University of the Witwatersrand,
scores on the Advanced Progressive Matrices correlated with scores on
the Standard Progressive Matrices measured 3 months earlier (.60 for
Africans;.70 for non-Africans) and with end-of-year exam marks measured
3 months later (.34 for Africans;.28 for non-Africans).Figure 1 shows
the regression of exam marks on test scores for these university
students.
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Figure 1. Regression of Raven's scores on university grades for Africans
and non-Africans. From "Performance on Raven's Advanced Progressive
Matrices by African, East Indian, and White Engineering Students," by J.
P. Rushton, M. Skuy, and P. Fridjhon, 2003, Intelligence, 31, p. 133.
Copyright 2003 by Elsevier Science. Reprinted with permission.
Although predictive validity is the ultimate pragmatic criterion for
absence of bias, critics also suggest that the items have different
meanings for Africans than they do for Whites or East Indians (Nell,
2000). This hypothesis of internal bias has been tested. The
psychometric studies by Owen (1992) on thousands of high school
students, and by Rushton and Skuy (2000; Rushton et al., 2002, 2003 ) on
hundreds of university students, found almost identical item structures
in Africans, Whites, and East Indians on the Progressive Matrices. Items
found difficult by one group were difficult for the others; items found
easy by one group were easy for the others (mean rs = .90, p <.001). The
item-total score correlations for Africans, Whites, and East Indians
were also similar, indicating that the items measured similar
psychometric constructs in all three groups. (Section 4 reviews evidence
of the similarity of the g factor in Africans and non-Africans.) The
only reliable example of bias so far discovered in this extensive
literature is the rather obvious internal bias on the Vocabulary
components of tests such as the Wechsler for groups that do not have
English as their first language (e.g., Skuy et al., 2001 ). Even here,
the language factor only accounts for about 0.5 of a standard deviation,
out of the overall 2.0 standard deviation difference, between Africans
and Whites.
Could it make a difference that Africans have less experience in solving
problems such as those on the Raven's, are less testwise, and have less
access to coaching than non-Africans? Raven (2000) showed that students
who were encouraged to engage in complex cognitive tasks increased in
self-direction, understanding, and competence. In South Africa, Skuy and
Shmukler (1987) applied Feuerstein's (1980) Mediated Learning Experience
and raised the Raven scores of Black high school students. Skuy,
Hoffenberg, Visser, and Fridjhon (1990) found generalized improvements
for Africans with what they termed a facilitative temperament. In an
intervention study with 1st-year psychology students at the University
of the Witwatersrand, Skuy et al. (2002) increased Raven's test scores
in both Africans and non-Africans after intervention training. Both
experimental groups improved over the baseline compared with their
respective control groups, with significantly greater improvement for
the African group (IQ score gains of 83 to 97 in Africans; 103 to 107 in
non-Africans). The question remains, however, whether such intervention
procedures only increase performance through mastery of subject-specific
knowledge or whether they increase g-like problem-solving ability that
generalizes to other tests as well (te Nijenhuis, Voskuijl, & Schijve,
2001).
Some argue that African students are less interested, more anxious, work
less efficiently, or give up sooner on items they find difficult,
perhaps because the problems have less meaning for them (e.g., Nell,
2000). Four findings argue against these hypotheses. First, Rushton and
Skuy (2000) closely observed the test-taking behavior of Africans and
noted that they worked very diligently, typically staying longer than
Whites to recheck their answers. Second and third, there are the similar
predictive validities and internal consistencies previously discussed.
Finally, there is supporting evidence from reaction-time research.
Reaction time is one of the simplest culture-free cognitive measures.
Most reaction time tasks are so easy that 9- to 12-year-old children can
perform them in less than 1 s. But even on these very simple tests,
children with higher IQ scores perform faster than do children with
lower scores, perhaps because reaction time measures the
neurophysiological efficiency of the brain's capacity to process
information accurately-the same ability measured by intelligence tests
(Deary, 2000; Jensen, 1998b ). Children are not trained to perform well
on reaction time tasks (as they are on certain paper-and-pencil tests),
so the advantage of those with higher IQ scores on these tasks cannot
arise from practice, familiarity, education, or training.
For three reaction time tasks (the simple, choice, and odd-man-out
tasks), individuals with higher IQ scores average faster and less
variable reaction times. For any one task, the correlation between
reaction time and IQ normally lies between .20 and .40. A review of
several studies concluded that the six measures combined (i.e., the
average time and the variability for the three reaction time tasks)
produce a multiple correlation of .67 (Deary, 2000 ). This is about the
same magnitude as the correlation between two conventional intelligence
tests of, say, reasoning ability and vocabulary.
Lynn and his colleagues carried out a series of reaction time studies on
over 1,000 nine-year-old East Asian children in Japan and Hong Kong,
White children in Britain and Ireland, and Black children in South
Africa (summarized by Lynn & Vanhannen, 2002 , pp. 66-67). The
Progressive Matrices were given as a nonverbal test of intelligence,
along with the simple, choice, and odd-man-out tasks. Reaction times and
variabilities were measured by computer and hence were not subject to
any human error in recording. For details, see Shigehisa and Lynn (1991)
for Japan; Chan and Lynn (1989) for Hong Kong and Britain; Lynn (1991)
for Ireland; and Lynn and Holmshaw (1990) for South Africa.
The correlations between IQ and reaction times for the five countries
are summarized in Table 1 . The East Asian children in Hong Kong and
Japan obtained the highest IQs, followed in descending order by the
White children in Britain and Ireland, and then the Black children in
South Africa. The medians for simple reaction time, choice reaction
time, and odd-man-out reaction time follow the same descending order as
the IQs. Because all the tasks take less than 1 s, all children found
them easy. The variabilities in the three reaction time measures for the
three groups follow the same general descending trend.
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Table 1 Sample Size, Mean IQ Score, and Reaction Time Measures (in
Milliseconds) From Five Countries, and the Reaction Time Correlations
with IQ
The same pattern of average scores on these and other reaction time
tasks (i.e., East Asians faster than Whites faster than Blacks) is found
within the United States. Jensen (1993) and Jensen and Whang (1994)
examined the time taken by over 400 schoolchildren ages 9 to 12 years
old in California to retrieve overlearned addition, subtraction, or
multiplication of single digit numbers (from 1 to 9) from long-term
memory. All of the children had perfect scores on paper-and-pencil tests
of this knowledge, which was then reassessed using the Math Verification
Test. The response times significantly correlated (negatively) with
Raven Matrices scores, whereas movement times have a near-zero
correlation. The average reaction times for the three racial groups
differ significantly (see Figure 2). They cannot be explained by the
groups' differences in motivation because the East Asian children
averaged a shorter response time but a longer movement time than did the
Black children.
Figure 2. Mean response times of 10-year-old Black, White, and East
Asian children on the Math Verification Test for Multiplication,
Subtraction, and Addition. Redrawn by A. R. Jensen from data in Jensen
(1993; Jensen & Whang, 1994). Copyright 2002 by A. R. Jensen. Reprinted
with permission.
Section 4: The g Factor and Mean Race-IQ Differences
Jensen (1998b) showed that a test's g loading (g being the general
factor of intelligence) is the best predictor, not just of that test's
correlation with scholastic and workplace performance, but of
heritability coefficients determined from twin studies, inbreeding
depression scores calculated in children of cousin-marriages, brain
evoked potentials, brain pH levels, brain glucose metabolism, as well as
nerve conduction velocity, reaction time, and other physiological
factors. These correlations argue strongly for the heritable and
biological, as opposed to the mere statistical reality of g. Because the
mean Black-White group difference in IQ is more pronounced on
high-g-loaded tests than it is on low-g-loaded tests, it suggests that
it is not the result of any idiosyncratic cultural peculiarities of this
or that test.
Spearman (1927 , p. 379) first proposed the hypothesis that the mean
Black-White group difference in IQ would be "most marked in just those
[tests] which are known to be saturated with g." Jensen (1980, p. 535)
designated it as "Spearman's hypothesis" and developed the method of
correlated vectors to test it. This method correlates the standardized
Black-White mean differences on a set of cognitive tests with their
respective g loadings, a significant positive correlation supporting the
hypothesis. The rationale is straightforward. If g is the main source of
between- and within-group differences, then there should be a positive
relationship between a given test's g loading and the mean Black-White
group difference on that test: The more g -loaded the test, the greater
the Black-White group difference on that test. A corollary is the
prediction that when race (scored as Blacks = 1, Whites = 2) is factor
analyzed along with scores from a number of diverse cognitive tests, its
highest loading on the resulting correlation matrix will be with the g
factor.
Jensen (1998b , pp. 369-379) summarized 17 independent data sets of
nearly 45,000 Blacks and 245,000 Whites derived from 149 psychometric
tests and found that the g loadings consistently predicted the magnitude
of the mean Black-White group difference (r = .62, p <.05). This was
borne out even among 3-year-olds administered eight subtests of the
Stanford-Binet in which the rank correlation between g loadings and the
mean Black-White group differences was .71 (p <.05; Peoples et al.,
1995). Subsequently, Nyborg and Jensen (2000) analyzed a unique battery
of 19 highly diverse cognitive tests from an archival data set of 4,462
males who had served in the U.S. Armed Forces. The g factor was
extracted using different methods. Spearman's hypothesis was confirmed,
with an average correlation of .81 between the race difference on a test
and its g loading. Nyborg and Jensen concluded that Spearman's original
conjecture about the mean Black-White difference on the g factor "should
no longer be regarded as just an hypothesis but as an empirically
established fact" (p. 599). Only one study to date has examined East
Asian-White difference on psychometric tests as a function of their g
loadings; it confirmed the hypothesis for 15 cognitive tests
administered to two generations of Americans of Japanese, Chinese, and
European ancestry. In this case, the more g-loaded the test, the greater
the mean East Asian-White group difference favoring East Asians
(Nagoshi, Johnson, DeFries, Wilson, & Vandenberg, 1984).
Studies in Southern Africa have also found the mean Black-White IQ
difference is mainly on g. Lynn and Owen (1994) were the first to test
explicitly Spearman's hypothesis in sub-Saharan Africa, administering
the Junior Aptitude Test to 1,056 White, 1,063 Indian, and 1,093 Black
16-year-old high school students in South Africa. They found a 2
standard deviation difference between the Africans and Whites (yielding
an average African IQ of about 70) and a 1 standard deviation difference
between the Whites and Indians (yielding an average Indian IQ of 85).
They then tested Spearman's hypothesis and found the African-White
differences correlated .62 (p <.05) with the g factor extracted from the
African sample, but only .23 with g extracted from the White sample.
They did not find any White-Indian differences on g.
Jensen (1998b, p. 388) noted some problems with Lynn and Owen's (1994)
South African study, but their results on Black-White differences have
been well corroborated since then and extended to include East Indians
and "Coloreds" (the term used to refer to the mixed-race population of
South Africa). Thus, Rushton (2001) reanalyzed data on 10 subtests of
the WISC-R published on 154 high school students in South Africa by Skuy
et al. (2001) and found African-White differences were mainly on g.
Rushton and Jensen (2003) compared data on the WISC-R from 204 African
12- to 14-year-olds from Zimbabwe published by Zindi (1994) with the
U.S. normative sample for Whites and found 77% of the between-groups
race variance was attributable to a single source, namely g.
Spearman's hypothesis has been confirmed in South Africa using test item
analyses as well. Rushton and Skuy (2000) studied 309 university
students at the University of the Witwatersrand and found that the more
an individual item from the Raven's Standard Progressive Matrices
measured g (estimated by its item-total correlation), the more it
correlated with the standardized African-White difference on that item.
Rushton (2002) analyzed the item data from 4,000 high school students in
South Africa on Raven's Standard Progressive Matrices published by Owen
(1992) and found the four-way African-Colored-East Indian-White
differences were all on g. In two studies of engineering students,
Rushton et al. (2002, 2003) found that the more the items from both the
Standard and the Advanced Progressive Matrices loaded on g, the better
they predicted the magnitude of African-East Indian-White differences.
The g loadings showed cross-cultural generality; those calculated on the
East Indian students predicted the magnitude of the African-White
differences.
Spearman's hypothesis was also confirmed when the g factor was extracted
from 12 reaction time variables given to the 820 nine- to
twelve-year-olds. While all of the children could do the tasks in less
than 1 s, the correlations between the g loadings and the mean
Black-White differences on the reaction time tasks range from .70 to .81
(Jensen, 1993 ). These results bear out Spearman's hypothesis even more
strongly than do those from conventional psychometric tests. The
hypothesis that the mean Black-White group difference on these tests
reflects a difference in motivation is again disconfirmed by the fact
that although Whites averaged faster reaction times than Blacks, Blacks
averaged faster movement times than Whites. And again, East Asians
typically averaged higher than Whites on the g factor extracted from
their (faster) reaction time measures (Jensen & Whang, 1994).
Spearman's hypothesis, as demonstrated by the method of correlated
vectors, cannot be a chimera or a methodological artifact, as a few
critics have claimed (e.g., Gould, 1996, p. 350; Schönemann, 1992 ). In
the method of correlated vectors, the means and standard deviations of
the variables cannot have any mathematical relationship with the factor
structure of the correlation matrix because the means and the variances
of all the tests in the factor-analyzed correlation matrix are totally
removed by the Pearson correlations, which convert all variables to z
scores. Therefore, any systematic relationship between factor loadings
and standardized group means (or group mean differences) must be an
empirical fact, not an artifact (Jensen, 1992).
Other claims of artifact are contradicted by Dolan's (1997) technical
commentaries on the method of correlated vectors (Dolan, 1997, 2000).
Dolan argued that the method of correlated vectors is not incorrect but
that it lacks specificity ; that is, it does not incorporate tests of
alternative models of the factor structure of group differences or
incorporate statistical tests to compare them for goodness-of-fit. In
its place, he advocated use of the multigroup confirmatory factor model
for testing Spearman's hypothesis. Statistical tests of significance are
a built-in feature of this procedure. Dolan and Hamaker (2001) have
applied it to two large published data sets (Jensen & Reynolds, 1982;
Naglieri & Jensen, 1987 ). The results statistically confirmed the
conclusion derived from the method of correlated vectors regarding a
"weak form" of Spearman's hypothesis: Black-White group differences were
predominantly on the g factor, although the groups also showed
differences on some lower order factors (e.g., short-term memory and
spatial ability) independent of g.
Section 5: Gene-Environment Architecture and Mean Black-White IQ
Dozens of twin, adoption, and family studies have confirmed the high
heritability of intellectual and behavioral traits, and even reaction
time tasks, within a race (Bouchard, 1996; Bouchard & Loehlin, 2001;
Deary, 2000; Plomin et al., 2001 ). Most of these estimates have been
calculated on White samples. One study of 543 pairs of identical and 134
pairs of nonidentical 12-year-old Japanese twins in Japan reported a
substantial heritability of 0.58 for IQ (Lynn & Hattori, 1990). The
hereditarian model views race differences simply as aggregated
individual differences of this sort.
The culture-only model, however, predicts that special factors such as
poverty, the history of slavery, and White racism have operated on the
Black population and suppressed natural levels of intelligence and so
made heritabilities in Blacks substantially lower than they are in
Whites. In arguing against Galton's (1869) hereditarian position,
Charles H. Cooley (1897) , a founder and first president of the American
Sociological Association, was the first to introduce the powerful
analogy that corn seeds given a normal environment grow plants of full
height whereas seeds given a deprived environment grow plants of stunted
height. According to this view, cultural deprivation, not heredity, is
the cause of any Black-White IQ differences.
It is an empirical question whether heritabilities are the same for
Blacks as for Whites. Loehlin et al. (1975 , pp. 114-116) reviewed the
literature to that date and found that while there was some evidence
suggesting a lower heritability of intelligence for Blacks than for
Whites (e.g., Scarr-Salapatek, 1971), a larger body of evidence
suggested equal heritabilities in the two groups. Subsequently,
Osborne's (1980) Georgia Twin Study compared 123 Black and 304 White
pairs of 12- to 18-year-old twins drawn from schools in Georgia,
Kentucky, and Indiana, given the Basic Test Battery, along with smaller
subsets of twins given the Primary Mental Abilities test and the Cattell
Culture Fair Intelligence test. Osborne found heritabilities of about
50% for both Blacks and Whites, all significantly different from zero
but not from each other. (The heritabilities of the Basic, Primary, and
Cattell tests were, respectively, for Whites, 0.61, 0.37, and 0.71, and
for Blacks, 0.75, 0.42, and 0.19; Osborne, 1980, pp. 68-69, 89, 98.)
Another way of answering the question is to compare their psychometric
factor structures of kinship patterns, background variables, and subtest
correlations. If there are minority-specific developmental processes
arising from cultural background differences between the races at work,
they should be reflected in the correlations between the background
variables and the outcome measures. Rowe (1994; Rowe, Vazsonyi, &
Flannery, 1994, 1995 ) examined this hypothesis in a series of studies
using structural equation models. One study of six data sources compared
cross-sectional correlational matrices (about 10 × 10) for a total of
8,528 Whites, 3,392 Blacks, 1,766 Hispanics, and 906 Asians (Rowe et
al., 1994 ). These matrices contained both independent variables (e.g.,
home environment, peer characteristics) and developmental outcomes
(e.g., achievement, delinquency). A LISREL goodness-of-fit test found
each ethnic group's covariance matrix equal to the matrix of the other
groups. Not only were the Black and White matrices nearly identical, but
they were as alike as the covariance matrices computed from random
halves within either group. There were no distortions in the
correlations between the background variables and the outcome measures
that suggested any minority-specific developmental factor.
Another study examined longitudinal data on academic achievement (Rowe
et al., 1995 ). Again, any minority-specific cultural processes
affecting achievement should have produced different covariance
structures among ethnic and racial groups. Correlations were computed
between academic achievement and family environment measures in 565
full-sibling pairs from the National Longitudinal Survey of Youth, each
tested at ages 6.6 and 9.0 years (White N = 296 pairs; Black N = 149
pairs; Hispanic N = 120 pairs). Each racial group was treated
separately, yielding three 8 × 8 correlation matrices, which included
age as a variable. Because LISREL analysis showed the matrices were
equal across the three groups, there was no evidence of any special
minority-specific developmental process affecting either base rates in
academic achievement or any changes therein over time.
A nearly identical statistical structure on intellectual variables
across ethnic and racial groups has been reported in large-scale studies
of military samples. Ree and Carretta (1995) examined a nationally
representative sample of young Black, White, and Hispanic men and women
who took the Armed Services Vocational Aptitude Battery (ASVAB; N =
9,173). The ASVAB, which is used to select applicants for all military
enlistments and assign them to first jobs, consists of 10 separately
scored subtests (General Science, Arithmetic Reasoning, Word Knowledge,
Paragraph Comprehension, Numerical Operations, Coding Speed, Auto and
Shop Information, Mathematics Knowledge, Mechanical Comprehension, and
Electronics Information). Despite the especially wide variety of
subtests, Ree and Carretta found the hierarchical factor structure of
ASVAB subtest scores was virtually identical across the three groups.
Similarly, Carretta and Ree (1995) examined the more specialized and
diverse Air Force Officer Qualifying Test, a multiple-aptitude battery
that had been given to 269,968 applicants (212,238 Whites, 32,798
Blacks, 12,647 Hispanics, 9,460 Asian Americans, and 2,551 Native
Americans). The g factor accounted for the greatest amount of variance
in all groups, and its loadings differed little by ethnicity. Thus, the
factor structure of cognitive ability is nearly identical for Blacks and
for Whites, as was found in the studies by Owen (1992) and Rushton and
Skuy (2000; Rushton et al., 2002, 2003 ) comparing Africans, East
Indians, and Whites on the item structures of tests described in Section
3. There was no "Factor X" specific to race.
Within-race heritabilities have also been calculated using structural
equation modeling. Rowe and Cleveland (1996) estimated the genetic
architecture for Black and White full- and half-siblings from the
National Longitudinal Survey of Youth (106 pairs of Black half-sibs, 53
pairs of White half-sibs; 161 pairs of Black full-sibs, 314 pairs of
White full-sibs). Three Peabody Individual Achievement Tests were used
(Mathematics, Reading Comprehension, and Reading Recognition). The
best-fitting model was one in which the sources of the differences
between individuals within race and of the differences between racial
means was the same-about 50% genetic and 50% environmental. Similarly,
Jensen (1998b , p. 465) used structural equation modeling to reanalyze a
subset of the Georgia Twin Study (comprising 123 Black and 304 White
pairs of 12- to 18-year-old twins). He broke down the phenotypic mean
differences into their genetic and environmental contributions and
tested four alternative models: only genetic factors, only environmental
factors, neither genes nor environment, and genes plus environment. The
model of both genetic and environmental factors best explained the
observed Black-White group differences in IQ, whereas both the
genetic-only and the environmental-only explanations were inadequate.
Heritability data are especially informative when the hereditarian and
the culture-only models make opposite predictions. For example, the
hereditarian model predicts race differences will be greater on those
subtests that are more heritable within races, whereas culture-only
theory predicts they will be greater on subtests that are more
culturally malleable (i.e., those with lower heritabilities) on which
races should grow apart as a result of dissimilar experiences. Analyses
of several independent data sets support the genetic hypothesis.
Nichols (1972, cited in Jensen, 1973 , pp. 116-117) was the first to
apply differential heritabilities in the study of racial-group
differences. He estimated the heritability of 13 tests from 543 pairs of
7-year-old siblings, including an equal number of Blacks and Whites, and
found a .67 correlation between the heritability of a test and the
magnitude of the Black-White group difference on that test.
Subsequently, Jensen (1973, pp. 103-119) calculated the environmentality
of a test (defined as the degree to which sibling correlations departed
from the pure genetic expectation of 0.50) in Black and in White
children and found it was inversely related to the magnitude of the
Black-White group difference (r = -.70); that is, the more
environmentally influenced a test, the less pronounced its Black-White
group difference.
Prompted by Jensen's approach, Rushton (1989) estimated genetic
influence from the amount of inbreeding depression found on the 11 tests
of the WISC. Inbreeding depression occurs in offspring who receive the
same harmful recessive genes from each of their closely related parents.
Rushton found a positive correlation between inbreeding depression
scores calculated from 1,854 cousin-marriages in Japan and the magnitude
of the mean Black-White group difference in the United States on the
same 11 Wechsler tests (.48). This contradicts culture-only theory,
which predicts that mean differences between Blacks and Whites should be
greater on those subtests most affected by the environment (i.e., those
showing the lowest amount of inbreeding depression). We know of no
nongenetic explanation for the relation between inbreeding depression
scores from Japan and mean Black-White group differences in the United
States.
Other aspects of the gene-environment architectural matrix also pertain
to the question of mean Black-White group differences. First, it is
possible to distinguish between two different types of environmental
effects. Shared (also called common or between-family ) environmental
effects are due to variables all children reared in the same family
(whether genetically related or adopted) have in common but that differ
between families (e.g., father's occupation, family cultural practice,
parents' child-rearing style). Nonshared (also called unique or
within-family ) effects are specific to each child in the same family
and therefore differ within families (e.g., an accident, illness, or
chance friendship that happens to one sibling and not to the other).
Twin and adoption studies can be used to measure the two types of
environmental effect (Plomin, DeFries, & Loehlin, 1977; see also Plomin
& Daniels, 1987; Plomin et al., 2001).
Based on within-race data, Figure 3 summarizes the changes with age in
the proportions of the total IQ variance attributable to genetic factors
and to the effects of the shared and the nonshared environment. It is
based on an analysis of 6,370 monozygotic and 7,212 dizygotic twin pairs
reared together (McGue, Bouchard, Iacona, & Lykken, 1993 ). As can be
seen, the estimated proportion of IQ variance associated with shared
environmental factors is relatively constant at approximately 30% for
ages up to 20 years but then drops to 0% in adulthood. The estimated
proportion of IQ variance associated with genetic factors increases
throughout development, but especially after 20 years of age.
Figure 3. Estimated proportions of the total IQ variance attributable to
genetic and environmental (shared and nonshared) effects. Note that only
the nonshared (or within-family) environmental variance remains
relatively constant across the entire age range. From "Behavioral
Genetics of Cognitive Ability: A Life-Span Perspective," by M. McGue, T.
J. Bouchard, Jr., W. G. Iacono, and D. T. Lykken, in R. Plomin and G. E.
McClearn (Eds.), Nature, Nurture, and Psychology (p. 64), edited by R.
Plomin and G. E. McClearn, 1993, Washington, DC: American Psychological
Association. Copyright 1993 by the American Psychological Association.
Reprinted with permission.
These results are corroborated by studies of monozygotic twins reared
apart and of other kinships groups (Plomin et al., 2001 ). Because the
variables usually proposed to explain mean racial-group differences are
part of the shared family environment (such as social class, religious
beliefs, cultural practices, father absence, and parenting styles), and
these account for little variance within a race, they are unlikely to
account for the differences between races. Rather, mean differences
between races are primarily due to nonshared family effects, which
include not only genetics but also a range of idiosyncratic
environmental events that, within-families, affect one sibling and not
the other (Jensen, 1997).
Hereditarians have also examined the question of whether group
differences occur in shared and in nonshared environmental effects as
well as in genetic effects. For example, Rushton and Osborne (1995)
reanalyzed 125 Black and 111 White pairs of 12- to 18-year-old twins
from the Georgia Twin Study and estimated their cranial capacities from
head size measures. They found a lower range of heritabilities for
Blacks than for Whites (12% to 31% against 47% to 56%) and a higher
range of common environmental (i.e., shared family) effects for Blacks
than for Whites (42% to 46% against 28% to 32%). However, these
percentage differences between Blacks and Whites were not significant,
although all heritabilities within each race were significantly above
zero.
Also relevant to the question of the mean Black-White group differences
are the changes in heritability that occur with increases in age (see
Plomin et al., 2001 ). The average correlation of IQ between full
siblings reared together reaches .49 in adulthood. The correlation in IQ
for siblings reared apart as children is .24, which increases to .49 in
adulthood. This shows that siblings grow more similar to each other as
they age. In genetically unrelated people reared together, such as
adopted children, the correlation for IQ is .25 in childhood but
decreases to .01 in adulthood (McGue et al., 1993 ). This shows,
conversely, that unrelated people reared together grow less similar over
time. Between childhood and adulthood the influence of the shared home
environment on IQ decreases, whereas the effect of genetic similarity
increases.
The diminishing or even vanishing effect of differences due to the
shared home environment can best be understood in terms of three
components of gene-environment correlation and the change in their
relative importance during development (Plomin et al., 1977; Plomin et
al., 2001). The passive component of the gene-environment correlation
reflects all those things that happen to the phenotype, independent of
its own characteristics. For example, children of academically oriented
parents may inherit genes for academic ability and also be exposed
(through no effort of their own) to stimulating intellectual
environments. The reactive component of gene-environment correlation
results from the reaction of others to the expression of genetically
based abilities, as when children with an unusual curiosity about
science are given chemistry sets. The active component of the
gene-environment correlation results from children actively seeking
experiences compatible with their genotypes, for example, going to
science fairs rather than sports events or music concerts. From early
childhood to late adolescence the predominant component of the
gene-environment covariance gradually shifts from passive to reactive to
active. The child's enlarging world is like a cafeteria in which choices
become increasingly biased by genetic factors (Scarr, 1996; Scarr &
McCartney, 1983). As individuals mature they seek out and even create
their own experiential environment.
Section 6: Race, Brain Size, and Cognitive Ability
Studies on over 700 participants show that individuals with larger brain
volumes have higher IQ scores. About two dozen studies using magnetic
resonance imaging (MRI) to measure the volume of the human brain have
found an overall correlation with IQ of greater than .40 (Rushton &
Ankney, 1996; P. A. Vernon, Wickett, Bazana, & Stelmack, 2000 ). The
correlation of .40 using MRI is much higher than the .20 correlation
found in earlier research using simple head size measures, although the
.20 correlation is also reliable and significant. Rushton and Ankney
(1996) reviewed 32 studies correlating measures of external head size
with IQ scores or with measures of educational and occupational
achievement, and they found a mean r = .20 for people of all ages, both
sexes, and various ethnic backgrounds, including African Americans.
The most likely reason why larger brains are, on average, more
intelligent than smaller brains is that they contain more neurons and
synapses, which make them more efficient. Haier et al. (1995) tested the
brain efficiency hypothesis by using MRI to measure brain volume and
glucose metabolic rate to measure glucose uptake (an indicator of energy
use). They found a correlation of -.58 between glucose metabolic rate
and IQ, suggesting that more intelligent individuals have more efficient
brains because they use less energy in performing a given cognitive
task. Several other studies supporting the brain-size/efficiency model
were reviewed in Gignac, Vernon, and Wickett (2003). In any individual,
however, energy use increases with the increasing complexity of the
cognitive task.
Estimates from twin studies indicate that genes contribute from 50% to
90% of the variance to both cranial capacities based on external head
size measures and to brain volume measured by MRI (Bartley, Jones, &
Weinberger, 1997; Pennington et al., 2000; Posthuma et al., 2002;
Rushton & Osborne, 1995; Thompson et al., 2001). Common genetic effects
mediate from 50% to 100% of the brain-size/IQ correlation (Pennington et
al., 2000; Posthuma et al., 2002). Studies have also shown that
correlations between brain size and IQ also hold true within families as
well as between families (Gignac et al., 2003; Jensen, 1994; Jensen &
Johnson, 1994 ), which also implies shared genetic effects. However, one
study that examined only sisters failed to find the within-family
relation (Schoenemann, Budinger, Sarich, & Wang, 2000 ). Families with
larger brains overall tend to have higher IQs and, within a family, the
siblings with the larger brains tend to have higher IQ scores. The
within-family finding is of special interest because it controls for
most of the sources of variance that distinguish families, such as
social class, styles of child rearing, and general nutrition, that
differ between families.
Race differences in average brain size are observable at birth. A study
by Rushton (1997) analyzed recorded head circumference measurements and
IQ scores from 50,000 children in the Collaborative Perinatal Project
followed from birth to age 7 (Broman, Nichols, Shaugnessy, & Kennedy,
1987 ). Using the head circumference measures to calculate cranial
capacity at birth, 4 months, 1 year, and 7 years, at each of these ages,
the Asian American children averaged larger cranial volumes than did the
White children, who averaged larger cranial volumes than did the Black
children. Within each race, cranial capacity correlated with IQ scores.
By age 7, the Asian American children averaged an IQ of 110; the White
children, 102; and the Black children 90. Because the Asian American
children were the shortest in stature and the lightest in weight while
the Black children were the tallest in stature and the heaviest in
weight, these average race differences in brain-size/IQ relations were
not due to body size.
External head size measurements (length, width, height) also have been
used to estimate cranial capacities in adults. Rushton carried out five
studies of large archival data sets. The first (Rushton, 1991 ) examined
head size measures in 24 international military samples collated by the
U.S. National Aeronautics and Space Administration. After adjusting for
the effects of body height, weight, and surface area, the mean cranial
capacity for East Asians was 1,460 cm3 and for Europeans 1,446 cm3. The
second (Rushton, 1992 ) demonstrated that even after adjusting for the
effects of body size, sex, and military rank in a stratified random
sample of over 6,000 U.S. Army personnel, the average cranial capacity
of East Asians, Whites, and Blacks were 1,416, 1,380, and 1,359 cm3,
respectively. The third study (Rushton, 1993 ) reanalyzed a set of
anthropometric data originally published by Melville Herskovits (who
concluded there were not race differences in cranial capacity) and found
Whites averaged a cranial capacity of 1,421 and Blacks, 1,295 cm3. The
fourth study (Rushton, 1994 ) analyzed data obtained on tens of
thousands of people from around the world collated by the International
Labor Office in Geneva, Switzerland. It found that after adjusting for
the effects of body size and sex, samples from the Pacific Rim, Europe,
and Africa had average cranial capacities, of 1,308, 1,297, and 1,241
cm3 respectively. Finally, Rushton and Osborne (1995) analyzed the
Georgia Twin Study of adolescents and found that after correcting for
body size and sex, Whites had an average cranial capacity of 1,269 cm3,
Blacks 1,251 cm3.
Rushton's results, based on calculating average cranial capacity from
external head size measures, join those from dozens of other studies
from the 1840s to the present on different samples using three different
methods (endocranial volume from empty skulls, wet brain weight at
autopsy, and high-tech MRI). All show the same strong pattern of East
Asians averaging larger and heavier brains than Whites who average
larger and heavier brains than Blacks. For example, using MRI
technology, Harvey, Persaud, Ron, Baker, and Murray (1994) found that 41
Blacks in Britain averaged a smaller brain volume than did 67 British
Whites.
The American anthropologist Samuel George Morton (1849) filled over
1,000 skulls with packing material to measure endocranial volume and
found that Blacks averaged about 5 cubic inches less cranial capacity
than Whites. His results were confirmed by Todd (1923), H. L. Gordon
(1934), and Simmons (1942) . The most extensive study of race
differences in endocranial volume to date measured 20,000 skulls from
around the world and reported East Asians, Europeans, and Africans had
average cranial volumes of 1,415, 1,362, and 1,268 cm3, respectively
(Beals, Smith, & Dodd, 1984).
Using the method of weighing brains at autopsy, Paul Broca (1873)
reported that Whites averaged heavier brains than did Blacks, with
larger frontal lobes and more complex convolutions. (Broca also used
endocranial volume and found East Asians averaged larger cranial
capacities than Europeans, who averaged larger than Blacks.) Other early
autopsy studies found a mean Black-White group difference in brain
weight of about 100 g (Bean, 1906; Mall, 1909; Pearl, 1934; Vint, 1934
). A more recent autopsy study of 1,261 American adults found that the
brains of 811 White Americans in their sample averaged 1,323 g and the
brains of 450 Black Americans averaged 1,223 g-a difference of 100 g
(Ho, Roessmann, Straumfjord, & Monroe, 1980 ). Because the Blacks and
Whites in the study were similar in body size, this was not responsible
for the differences in brain weight.
Rushton (2000; Rushton & Ankney, 1996 ) summarized the world database
using the three methods on which there are a sufficient number of
studies (autopsies, endocranial volume, and head measurements), as well
as head measurements corrected for body size (see Rushton, 2000, pp.
126-132, Table 6.6). The results in cm3 or equivalents were as follows:
East Asians = 1,351, 1,415, 1,335, and 1,356 (M = 1,364); Whites =
1,356, 1,362, 1,341, and 1,329 (M = 1,347); and Blacks = 1,223, 1,268,
1,284, and 1,294 (M = 1,267). The overall mean for East Asians is 17 cm3
more than that for Whites and 97 cm3 more than that for Blacks.
Within-race differences due to differences in method of estimation
averaged 31 cm3 . Because 1 cubic inch of brain matter contains millions
of brain cells and hundreds of millions of synapses or neural
connections, these group differences in average brain size may explain
group differences in average IQ.
Jensen and Johnson (1994) showed that for both Blacks and Whites, the
head size by IQ correlation is true within families as well as between
families, indicating the intrinsic or functional relationship mentioned
earlier. Further, within each sex, Blacks and Whites fit the same
regression line of head size on IQ. When Blacks and Whites are perfectly
matched for true-score IQ (i.e., IQ corrected for measurement error) at
either the Black mean or the White mean, the overall average Black-White
group difference in head circumference is virtually nil. (Matching
Blacks and Whites for IQ eliminates the average difference in head size,
but matching the groups on head size does not equalize their IQs. This
is what one would expect if brain size is only one of a number of brain
factors involved in IQ.)
In another analysis of the Georgia Twin Study, Jensen (1994) showed that
the mean Black-White group difference in head/brain size is also related
to the magnitude of the mean Black-White group difference in g. The
correlation coefficient of each test with the head measurements was
correlated with the magnitude of the Black-White group difference on
that test, thus forming two vectors. The column vector of IQ test and
head size correlations indicated a correlation of .51 (p <.05) with the
vector of standardized Black-White group differences on each of the
tests.
Section 7: Mean Race-IQ Differences and Transracial Adoption Studies
"Transracial adoption is the human analog of the cross-fostering design,
commonly used in animal behavior genetics research.... There is no
question that adoption constitutes a massive intervention" (Scarr &
Weinberg, 1976 , p. 726). Studies of Korean and Vietnamese children
adopted into White homes show that although as babies many had been
hospitalized for malnutrition, they nonetheless grew to have IQs 10 or
more points higher than their adoptive national norms. By contrast,
Black and mixed-race (Black-White) children adopted into White
middle-class families typically have lower average scores than the White
siblings with whom they had been reared or than White children adopted
into similar homes.
The Minnesota Transracial Adoption Study, the largest and best-known
transracial study, was designed specifically by Sandra Scarr and Richard
Weinberg to separate genetic factors from rearing conditions as causal
influences on the cognitive performance of Black children (Scarr &
Weinberg, 1976; Weinberg, Scarr, & Waldman, 1992 ). It is also the only
transracial adoption study that includes a longitudinal follow-up, with
testing at ages 7 and 17 years. Scarr and Weinberg compared the IQ and
academic achievement scores of Black, White, and mixed-race Black/White
children adopted into upper-middle-class White families in Minnesota by
adopting parents whose mean IQ was more than 1 standard deviation above
the population mean of 100 (see Table 2). The biological children of
these parents were also tested.
Table 2 Comparison of Cognitive Performance Measures at Ages 7 and 17 in
Biological and Adopted (White, Mixed-Race, and Black) Children, All
Reared in Middle-Class White Families
The first testing of 265 children was carried out in 1975 when they were
7 years old and the second in 1986 when the 196 remaining in the study
were 17 years old. The 7-year-old White biological (i.e., nonadopted)
children had an average IQ of 117 (see Table 2 , 2nd column), similar to
that found for children of White upper-middle-class parents. The adopted
children with two White biological parents had a mean IQ of 112. The
adopted children with one Black and one White biological parent averaged
109. The adopted children with two Black biological parents had an
average IQ of 97. (A mixed group of 21 Asian, North American Indian, and
Latin American Indian adopted children averaged an IQ of 100 but were
not included in the main statistical analyses.)
Scarr and Weinberg (1976) interpreted the results of the testing at age
7 as support for the culture-only position. They drew special attention
to the fact that the mean IQ of 105 for all "socially classified" Black
children (i.e., those with either one or two Black parents) was
significantly above the U.S. White mean. The poorer performance of
children with two Black biological parents was attributed to their more
difficult and later placement. Scarr and Weinberg also pointed out that
this latter group had both natural and adoptive parents with somewhat
lower educational levels and abilities (2 points lower in adoptive
parents' IQ). They found no evidence for the expectancy effects
hypothesis that adoptive parents' beliefs about the child's racial
background influence the child's intellectual development. The mean
score for 12 children wrongly believed by their adoptive parents to have
two Black biological parents was virtually the same as that of the 56
children correctly classified by their adoptive parents as having one
Black and one White biological parent.
Table 2 also presents the results for the 196 children retested at age
17 (Weinberg et al., 1992 ). There were four independent assessments of
the children's cognitive performance at this later age: (a) an
individually administered IQ test, (b) an overall grade point average,
(c) a class rank based on school performance, and (d) four special
aptitude tests in school subjects administered by the educational
authority, which we averaged. The results are concordant with the
earlier testing. The nonadopted White children had a mean IQ of 109, a
grade point average of 3.0, a class rank at the 64th percentile, and an
aptitude score at the 69th percentile. The adopted children with two
White biological parents had a mean IQ of 106, a grade point average of
2.8, a class rank at the 54th percentile, and an aptitude score at the
59th percentile. The adopted children with one Black and one White
biological parent had a mean IQ of 99, a grade point average of 2.2, a
class rank at the 40th percentile, and an aptitude score at the 53rd
percentile. The adopted children with two Black biological parents had a
mean IQ of 89, a grade point average of 2.1, a class rank at the 36th
percentile, and an aptitude score at the 42nd percentile. (The 12
remaining mixed group of Amerindian/Asian children had an IQ of 96 with
no data provided on school achievement.)
Because different tests based on different standardization groups were
used in the first testing than in the follow-up, the overall average
difference of about 8 IQ points (evident for all groups, including the
nonadopted group) between the two test periods does not bear on the
hypothesis of interest. The relevant comparisons are those between the
adopted groups of different races within each age level. The mean of 89
for adopted children with two Black parents was slightly above the
national Black mean of 85 but not above the Black mean for Minnesota.
Weinberg et al. (1992) interpreted their follow-up results as further
support for the culture-only theory. Emphasizing the beneficial effects
of the rearing environment, they pointed out that at both age 7 and 17
all groups of adopted children averaged above their expected population
means. Their analyses frequently combined the two "socially classified
Black" groups with "other" mixed-race children who had one parent of
unknown, Asian, Amerindian, or other racial background. In their age 17
breakdowns, Weinberg et al. (1992 , p. 132) stated that "[b]iological
mothers' race remained the best single predictor of adopted child's IQ
when other variables were controlled," which they then attributed to
"unmeasured social characteristics." Their overall conclusion was that
"the social environment maintains a dominant role in determining the
average IQ level of Black and interracial children and that both social
and genetic variables contribute to individual variations among them"
(p. 133).
Levin (1994) and Lynn (1994) disputed Weinberg et al.'s (1992)
culture-only interpretation. They each proposed a straightforward,
hereditarian alternative: The mean IQ and school achievement scores of
Black children reflected their degree of African ancestry. At both age 7
and 17, the adopted children with two Black biological parents had lower
average IQs and school achievement scores than did those with one Black
and one White biological parent, and these children, in turn, averaged
lower scores than did those with two White biological parents. Waldman,
Weinberg, and Scarr (1994) responded to Levin (1994) and Lynn (1994)
with further regression analyses that indicated the children's
preadoptive experience was confounded with racial ancestry, and so an
unambiguous interpretation of the results was not possible.
Subsequently, Jensen (1998b) discussed these studies at length and
reviewed the evidence showing that age of adoption does not influence
children's IQ scores after age 7 (e.g., Fisch, Bilek, Deinard, & Chang,
1976 ). Studies of severely malnourished, late-adopted, East Asian
children (see below) provide substantial evidence that age of adoption
does not adversely influence IQ in transracial adoptions. More
generally, as reviewed in Section 5, dozens of adoption, twin, and
family studies of Whites show that although the shared-family
environmental component of true-score IQ variance can be quite large at
age 7, by late adolescence it is the smallest component. After that age,
genetic and within-family (nonshared) environmental effects account for
the largest components of variance (see Figure 3).
Small sample studies of very young children reared in enriched
environments sometimes find an absence of the usual race differences in
IQ. In two studies of 2- to 5-year-olds raised in English residential
nurseries, Tizard (1974) compared Black (African and West Indian),
White, and mixed-parentage children and found no significant differences
among the three groups on several language comprehension tests and on
the Wechsler Preschool and Primary Scale of Intelligence (WPPSI); the
single significant difference was in favor of the non-White children.
Moore (1986) found that at age 7, 23 Black children adopted by
middle-class White families had a mean IQ of 117, whereas a similar
group of children adopted by middle-class Black families had a mean IQ
of 104, both significantly above the national Black mean of 85. To be
more informative, future studies need to be supplemented by follow-up
testing, as in the Minnesota Study. Behavior genetic studies
consistently show that, as people age, their genes exert ever more
influence, whereas family socialization effects decrease (see Figure 3).
Trait differences not apparent early in life begin to appear at puberty
and are completely apparent by age 17.
Three studies of East Asian children adopted by White families support
the hereditarian hypothesis. In the first, 25 four-year-olds from
Vietnam, Korea, Cambodia, and Thailand, all adopted into White American
homes prior to 3 years of age, excelled in academic ability with a mean
IQ score of 120, compared with the U.S. norm of 100 (Clark & Hanisee,
1982). Prior to placement, half of the babies had required
hospitalization for malnutrition.
In the second study, Winick, Meyer, and Harris (1975) found 141 Korean
children adopted as infants by American families exceeded the national
average in both IQ and achievement scores when they reached 10 years of
age. The principal interest of the investigators was on the possible
effects of severe malnutrition on later intelligence, and many of these
Korean children had been malnourished in infancy. When tested, those who
had been severely malnourished as infants obtained a mean IQ of 102; a
moderately well-nourished group obtained a mean IQ of 106; and an
adequately nourished group obtained a mean IQ of 112.
A study by Frydman and Lynn (1989) examined 19 Korean infants adopted by
families in Belgium. At about 10 years of age, their mean IQ was 119,
the verbal IQ was 111, and the performance IQ was 124. Even correcting
the Belgian norms upward to 109 to account for the increase in IQ scores
over time (about 3 IQ points a decade; see Section 13), the Korean
children still had a statistically significant 10-point advantage in
mean IQ over indigenous Belgian children. Neither the social class of
the adopting parents nor the number of years the child spent in the
adopted family had any effect on the child's IQ.
Section 8: Mean Race-IQ Differences and Racial Admixture
In the Minnesota Transracial Adoption Study, the IQs of the mixed-race
(Black/White) adoptees averaged between those of the "nonmixed" White
and the "nonmixed" Black adoptees, as expected under a genetic
hypothesis (see Table 2). Results from some other types of studies are
also consistent with that hypothesis. In her review, Shuey (1966) found
that in 16 of 18 studies in which skin color could be used as a proxy
for amount of admixture, Blacks with lighter skin color averaged higher
scores than those with darker skin, although the magnitude of the
association was quite low (r = .10). The Black American average IQ of 85
(15 points higher than the sub-Saharan African average of 70; see
Section 3) is also consistent with the genetic hypothesis, given the
approximately 20% White admixture of Black Americans (Chakraborty,
Kamboh, Nwankwo, & Ferrell, 1992; Parra et al., 1998 ). The mixed-race
"Colored" population of South Africa also has an average IQ of 85,
intermediate to the respective African and White means of 70 and 100
(Owen, 1992). Early studies of brain weight data also fit with the
genetic hypothesis. Bean (1906) found, as did Pearl (1934) , that the
greater the amount of White admixture (judged independently from skin
color), the higher the mean brain weight at autopsy in Black groups.
More recent data of this nature are not available.
The average IQ scores of around 70 for Black Americans in certain areas
of the Deep South of the United States where the degree of White
admixture is significantly below the general average (Chakraborty et
al., 1992; Parra et al., 1998 ) are also consistent with the
hereditarian interpretation of the effects of hybridization. An average
IQ of 71 was found for all of the Black children in an entire school
district from a rural county in Georgia; the average White IQ in the
same county was 101 (Jensen, 1977). Similarly, Stanley and Porter (1967)
found the scores on the SAT of all-Black college students in Georgia
were too low to be predictive of college grades, thereby raising the
question of whether test scores on Black Americans are as valid as those
for White Americans. However, when Hills and Stanley (1970) gave the
School and College Ability Test (a much easier test to pass) to similar
students, they found that their scores were normally distributed and did
predict college grades, though the average for the Black college
students was at about the 50th percentile on eighth-grade national
norms.
Most recently, Lynn (2002) and Rowe (2002) analyzed data from large,
publicly available, archival data sets, which show that groups of
mixed-race individuals have mean scores intermediate to unmixed groups
of Blacks and of Whites. Lynn examined the 1982 National Opinion
Research Center's survey of a representative sample of the adult
population, excluding non-English speakers. The 442 Blacks in the sample
were asked whether they would describe themselves as "very dark," "dark
brown," "medium brown," "light brown," or "very light." The correlation
between these self-ratings and a 10-word vocabulary test score was .17
(p <.01). Rowe examined the 1994 National Longitudinal Study of
Adolescent Health's survey of a representative sample of youths, with
intentional oversampling of Black children of highly educated parents.
The mean age for the entire sample (9,830 Whites, 4,017 Blacks, and 119
mixed-race individuals) was 16 years. The Black adolescents averaged a
lower birth weight, a lower verbal IQ, and a higher number of sexual
partners than did the White adolescents. For each characteristic, the
mixed-race mean fell between the means of the other two groups. Rowe
found the social class explanation of the group differences
"unconvincing" because, of the three variables, only verbal IQ showed a
moderate correlation with social class and statistically adjusting for
it left the main findings unchanged. He also rejected the
"discrimination based on skin tone" hypothesis because it was eliminated
by deliberately selecting only those mixed-race adolescents who were
judged by their interviewers to be Black, based on their physical
appearance.
Three studies of racially mixed individuals at first appear to support
the culture-only hypothesis against the genetic hypothesis. Eyferth
(1961; Eyferth, Brandt, & Hawel, 1960 ) reported IQ data for
out-of-wedlock children fathered by soldiers stationed in Germany after
World War II and then reared by White German mothers. The mean IQs for
83 White children and for 98 racially mixed children were both about 97
(97.2 for the Whites, 96.5 for the racially mixed). As Loehlin et al.
(1975 , pp. 126-128) noted, however, these results are ambiguous for
three reasons. First, the children were still very young when tested.
One third of the children were between 5 and 10 years of age, and two
thirds were between 10 and 13 years. As discussed in Section 5 (see
Figure 3 ), behavior genetic studies show that while family
socialization effects on IQ are often strong before puberty, after
puberty they dwindle, sometimes to zero. Second, 20% to 25% of the
"Black" fathers were not African Americans but French North Africans
(i.e., largely Caucasian or "Whites" as we have defined the terms here).
Third, there was rigorous selection based on IQ score in the U.S. Army
at the time, with a rejection rate for Blacks on the preinduction Army
General Classification Test of about 30%, compared with 3% for Whites
(see Davenport, 1946, Tables I and III).
The second study reports a 9-point IQ advantage for the 4-year-old
offspring of couples with a White mother and a Black father (mean IQ =
102, N = 101) compared with those from the offspring of a Black mother
and a White father (mean IQ = 93, N = 28). Willerman, Naylor, and
Myrianthopoulos (1974) , assuming White mothers provide better pre- or
postnatal environments for their children than do Black mothers,
interpreted their data as more consistent with a cultural than a genetic
hypothesis (see also Nisbett, 1998). However, Loehlin et al. (1975 , p.
126) noted that the mixed-race pairs with White mothers averaged almost
a year more schooling than did the pairs with Black mothers. Thus the
White mothers may have had a higher average IQ than the Black ones. The
mid-parent IQs have to be the same for the results to be interpretable.
Also, the two sets of mixed-race children averaged an IQ of 98,
intermediate to the White and Black children in the sample from whom the
mixed-race children had been drawn (IQs = 105 and 91, respectively;
Broman, Nichols, & Kennedy, 1975, p. 43).
The third study seeming to support the culture-only hypothesis is a
subsidiary analysis by Moore (1986 ; see Section 8) of a small number of
7-year-old children adopted by middle-class White parents. Moore found
no difference in IQ between those children with only one and those with
two Black biological parents. The mean IQ for the group of 9 adopted
children with two Black biological parents was 109, and the mean IQ for
the group of 14 children with one Black and one White biological parent
was 107. Given the young age of these children, a follow-up to
adolescence would be informative.
Studies of blood groups provide no support for the hereditarian
perspective. Both Loehlin, Vandenberg, and Osborne (1973) and Scarr,
Pakstis, Katz, and Barker (1977) found that blood groups distinguishing
African from European ancestry did not predict IQ scores in Black
samples. However, these studies failed to choose genetic markers with
large allele frequency differences between Africans and Europeans
(Jensen, 1998b, pp. 480, 524 n.64).
Molecular genetic technology was unsophisticated in the 1970s. In the
future, the issue may be resolved by calculating individual admixture
through the use of DNA markers as already occurs in medicine (Risch et
al., 2002 ). On the basis of existing surveys, an individual's racial
group can be determined by testing his or her DNA at 100 random sites
along the genome, or at 30 specifically chosen ones. Even different
ethnic groups within a race can be distinguished using some 50
specifically chosen sites. A genetic hypothesis predicts that for those
Black individuals who possess more White genes, their physical,
behavioral, and other characteristics will approach those of Whites.
Although the studies of racial hybrids are generally consistent with the
genetic hypothesis, to date they are not conclusive. It may be true, for
example, that lighter skinned Cape Coloreds and African Americans have
better nutrition, have greater opportunities for learning, or are
treated better by their societies. On the other hand, the Minnesota
Transracial Adoption Study (Table 2 ) held many such factors constant
and removed the most frequently proposed causal agents such as poverty,
malnutrition, poor schools, and dysfunctional neighborhoods. Yet, here
too, the mixed-race children had a higher mean IQ than did the children
of two Black parents, and the means for each group were very similar to
those for their respective counterparts elsewhere in the United States.
The discussion in this section is particularly supportive of Loehlin's
(2000) conclusion that "Research using larger samples and better
techniques for estimating ancestry is called for and quite feasible" (p.
188).
Section 9: Mean Race-IQ Differences and Regression to the Mean
Regression toward the mean provides still another method of testing if
the group differences are genetic. Regression toward the mean is seen,
on average, when individuals with high IQ scores mate and their children
show lower scores than their parents. This is because the parents pass
on some, but not all, of their genes to their offspring. The converse
happens for low IQ parents; they have children with somewhat higher IQs.
Although parents pass on a random half of their genes to their
offspring, they cannot pass on the particular combinations of genes that
cause their own exceptionality. This is analogous to rolling a pair of
dice and having them come up two 6's or two 1's. The odds are that on
the next roll, you will get some value that is not quite as high (or as
low). Physical and psychological traits involving dominant and recessive
genes show some regression effect. Genetic theory predicts the magnitude
of the regression effect to be smaller the closer the degree of kinship
between the individuals being compared (e.g., identical twin >
full-sibling or parent-child > half-sibling). Culture-only theory makes
no systematic or quantitative predictions.
For any trait, scores should move toward the average for that
population. So in the United States, genetic theory predicts that the
children of Black parents of IQ 115 will regress toward the Black IQ
average of 85, whereas children of White parents of IQ 115 will regress
toward the White IQ average of 100. Similarly, children of Black parents
of IQ 70 should move up toward the Black IQ average of 85, whereas
children of White parents of IQ 70 should move up toward the White IQ
average of 100. This hypothesis has been tested and the predictions
confirmed. Regression would explain why Black children born to high IQ,
wealthy Black parents have test scores 2 to 4 points lower than do White
children born to low IQ, poor White parents (Jensen, 1998b , p. 358).
High IQ Black parents do not pass on the full measure of their genetic
advantage to their children, even though they gave them a good
upbringing and good schools, often better than their own. (The same, of
course, applies to high IQ White parents.) Culture-only theory cannot
predict these results but must argue that cultural factors somehow
imitate the effect theoretically predicted by genetic theory, which have
also been demonstrated in studies of physical traits and in animals.
Jensen (1973 , pp. 107-119) tested the regression predictions with data
from siblings (900 White sibling pairs and 500 Black sibling pairs).
These provide an even better test than parent-offspring comparisons
because siblings share very similar environments. Black and White
children matched for IQ had siblings who had regressed approximately
halfway to their respective population means rather than to the mean of
the combined population. For example, when Black children and White
children were matched with IQs of 120, the siblings of Black children
averaged close to 100, whereas the siblings of White children averaged
close to 110. A reverse effect was found with children matched at the
lower end of the IQ scale. When Black children and White children are
matched for IQs of 70, the siblings of the Black children averaged about
78, whereas the siblings of the White children averaged about 85. The
regression line showed no significant departure from linearity
throughout the range of IQ from 50 to 150, as predicted by genetic
theory but not by culture-only theory.
Section 10: The Race-Behavior Matrix
Around the world, the rate of dizygotic (i.e., two-egg) twinning is less
than 4 per 1,000 births among East Asians, 8 among Whites, and 16 or
greater among Blacks (Bulmer, 1970 ). Multiple birthing rates have been
shown to be heritable, based on the race of the mother, regardless of
the race of the father, as found in East Asian-White crosses in Hawaii
and White-Black crosses in Brazil (Bulmer, 1970).
On average, Black babies are born a week earlier than White babies, yet
they are more mature as measured by pulmonary function, amniotic fluid,
and bone development. In the United States, 51% of Black children have
been born by week 39 of pregnancy compared with 33% of White children.
Black African babies, even those born to mothers in the professional
classes, are also born earlier than White babies (Papiernik, Cohen,
Richard, de Oca, & Feingold, 1986). They are not born premature but
sooner, and they are biologically more mature.
After birth, Black babies continue to mature faster, on average, than
White babies, whereas East Asian babies average an even slower rate.
X-rays show a faster rate of average bone growth in Black children than
in White children, and a faster rate in White children than in East
Asian children (Eveleth & Tanner, 1990 , pp. 154-155). Black babies at a
given age also average greater muscular strength and a more accurate
reach for objects. Black children average a younger age of sitting,
crawling, walking, and putting on their own clothes than Whites or East
Asians. The average age of walking is 13 months in East Asian children,
12 months in White children, and 11 months in Black children (Bayley,
1965; Brazelton & Freedman, 1971).
Blacks average a faster rate of dental development than do Whites, who
have a faster rate than do East Asians. On average, Black children begin
the first stage of permanent tooth growth at about 5.8 years, whereas
Whites and East Asians do not begin until 6.1 years (Eveleth & Tanner,
1990 , pp. 158-161). Blacks also have an earlier age of sexual maturity
than do Whites, who in turn have an earlier average age than do East
Asians, whether measured by age of first menstruation, first sexual
experience, or first pregnancy (Rushton, 2000, pp. 147-150).
Myopia (nearsightedness) is positively correlated with IQ and may be
caused by extra myelinization in the eye and so possibly linked to brain
size (Miller, 1994). The relationship appears to be pleiotropic (Cohn,
Cohn, & Jensen, 1988 ); that is, a gene affecting one trait also has
some effect on one or more others. There are significant racial and
ethnic differences in the frequency of myopia, with the highest rates
found in East Asians, the lowest rates among Blacks, with Whites
intermediate (Post, 1982).
Not just in the United States but around the world, East Asians and
Blacks fall at the two ends of a continuum with Whites intermediate, not
only on mean cognitive test scores and brain size measures but also on
60 life-history variables that provide measures of maturation,
personality, reproduction, and social organization. It seems unlikely
that social factors alone could produce this consistent pattern on so
diverse a set of behaviors (see Table 3; Rushton, 2000 , p. 5, Table 1.1
for complete list). This evidence raises the theoretical question of
whether single traits such as intelligence are part of a broader
"life-history" perspective.
Table 3 Worldwide Average Differences Among Blacks, Whites, and East
Asians
Section 11: Mean Race-IQ Differences and Human Origins
The currently most commonly accepted view of human origins, the
"Out-of-Africa" theory, posits that Homo sapiens arose in Africa about
150,000 years ago, expanded northward beyond Africa about 100,000 years
ago, with a European-East Asian split about 41,000 years ago
(Cavalli-Sforza et al., 1994; Stringer & McKie, 1996). In
Cavalli-Sforza's (2000) maximum likelihood tree devised on the basis of
molecular genetic markers, the most distant group was the Africans, with
Europeans and Asians being closer. Cavalli-Sforza observed, "All world
trees place the earliest split between Africans and non-Africans, which
is expected given that all humans originated in Africa" (p. 72). This is
also the conclusion of other reviewers (e.g., Risch et al., 2002).
Evolutionary selection pressures were different in the hot savanna where
Africans lived than in the cold northern regions Europeans experienced,
or the even colder Arctic regions of East Asians. These ecological
differences affected not only morphology but also behavior. It has been
proposed that the farther north the populations migrated out of Africa,
the more they encountered the cognitively demanding problems of
gathering and storing food, gaining shelter, making clothes, and raising
children successfully during prolonged winters (Rushton, 2000 ). As
these populations evolved into present-day Europeans and East Asians,
the ecological pressures selected for larger brains, slower rates of
maturation, and lower levels of testosterone-with concomitant reductions
in sexual potency, aggressiveness, and impulsivity; increases in family
stability, advanced planning, self-control, rule following, and
longevity; and the other characteristics listed in Table 3 . The fact
that the three-way pattern in IQ, brain size, and other traits is not
unique to the United States but occurs internationally is consistent
with a single, general (genetic-evolutionary) theory, whereas
culture-only theory must invoke a number of highly localized, specific
explanations.
As Homo sapiens migrated further away from Africa, the random genetic
mutations that occur at a constant rate in all living species
accumulated, along with the adaptive changes. The resulting differences
in allele frequencies are sufficient for numerous and extensive genetic
investigations to yield essentially the same picture and identify the
same major racial groupings as did the morphological markers of
classical anthropology. The greatest genetic divergence within the human
species is between Africans (who have had the most time for random
mutations to accumulate) and non-Africans (Cavalli-Sforza 2000;
Cavalli-Sforza et al., 1994; Nei & Roychoudhury, 1993). Jensen (1998b,
pp. 517-520) carried out a principal-components analysis of data on
genetic markers from Nei and Roychoudhury (1993) and found the familiar
clustering of races: (a) East Asians, (b) Europeans and East Indians,
(c) South Asians and Pacific Islanders, (d) Africans, (e) North and
South Amerindians and Eskimos, and (f) Aboriginal Australians and Papuan
New Guineans. Howells's (1993) analysis of between-groups variation in
craniometric data also revealed a similar population tree. The genetic
hypothesis is consistent with the latest findings on human origins and
genetic variation, whereas culture-only theory is indifferent to them
(Crow, 2002).
Section 12: How Well Have Culture-Only Theories of Mean Race-IQ
Differences Held Up?
Culture-only hypotheses have not explained the mean Black-White group
differences in IQ. (They have especially not explained the findings on
East Asians.) One early view was that the mean Black-White group
difference in IQ was due to the then obvious differences in (segregated)
school facilities (Myrdal, 1944). However, despite the U.S. Supreme
Court Brown v. Board of Education (1954) decision striking down
segregated schooling, and the consequent nationwide program of school
busing, the mean Black-White group difference has not decreased.
Moreover, the Coleman Report (Coleman et al., 1966 ) found that the
racial composition of schools per se was not related to achievement in
either Blacks or Whites. Most of the variation in IQ scores occurred
within schools and less than 20% occurred between schools. Negligible,
and in some cases, negative correlations were found between IQ and
variables such as pupil expenditure, teachers' salaries, teachers'
qualifications, student/teacher ratios, and the availability of other
school professionals (see also Coleman, 1990-1991).
The most frequently stated culture-only hypothesis is that the mean IQ
differences are due to SES. In fact, controlling for SES only reduces
the mean Black-White group difference in IQ by about a third, around 5
IQ points. The genetic perspective does not regard this control for SES
as being entirely environmental. It holds that the parents'
socioeconomic level in part reflects their genetic differences in
intelligence. Moreover, according to the culture-only theory, as Black
groups advance up the socioeconomic ladder, their children should be
less exposed to environmental deficits and therefore should do better
and, by extension, close the distance separating the Black mean with the
White. In fact, the magnitude of the mean Black-White group difference
in IQ for higher SES levels, when measured in standard deviations, is
larger (Herrnstein & Murray, 1994, pp. 286-289).
Other nongenetic hypotheses are that standard IQ tests are culturally
biased because the test items are not equally familiar and motivating to
all groups or that they only measure familiarity with middle-class
language or culture. However, despite attempts to equate items for
familiarity and culture-fairness, no "culture-fair" test has eliminated
the mean group difference. American Blacks actually have higher average
scores on culturally loaded tests than on culturally reduced tests,
which is the opposite to what is found for some other groups such as
Mexican Indians and East Asians. (The mean Black-White group differences
are greatest on the g factor, regardless of the type of test from which
g is extracted; see Section 4.) Moreover, the three-way pattern of mean
Black-White-East Asian group differences occurs worldwide on
culture-fair reaction time measures, which all children can do in less
than 1 s (see Section 3).
Subsequent culture-only hypotheses have pointed to specific aspects of
deprivation as possible determinants of IQ. These include the following:
(a) lack of reading material in the home, (b) poor cultural amenities in
the home, (c) weak structural integrity of the home, (d) foreign
language in the home, (e) low preschool attendance, (f) no encyclopedia
in the home, (g) low level of parental education, (h) little time spent
on homework, (i) low parental educational desires for child, (j) low
parental interest in school work, (k) negative child self-concept
(self-esteem), and (l) low child interest in school and reading.
However, both within-race kinship studies and across-race adoption
studies show that these environmental variables have increasingly
smaller effects on the adoptees' IQ as they reach adolescence (see
Sections 5 and 7). Moreover, other studies found that American Indians
and East Asians averaged higher in IQ than Blacks, even though they
averaged lower on these proposed causal factors (Coleman et al., 1966 ,
p. 20). Another example comes from the Inuit, who live above the Arctic
Circle and have higher average IQs than do either American or Jamaican
Blacks (Berry, 1966; MacArthur, 1968) even though their socioeconomic
conditions are extremely poor and unemployment is high (P. E. Vernon,
1965, 1979).
In the 1960s, culture-only theory formed the basis for implementing
"Head Start"-type intervention programs as a way to eliminate the group
differences in IQ and scholastic achievement. Although federal matching
grants were given to improve the learning skills, social skills, and
health status of low-income preschool children so that they could begin
schooling on an equal footing with their more advantaged peers, the mean
Black-White group difference in IQ was not eliminated or permanently
reduced. Currie and Thomas (1995) reviewed the literature and carried
out a longitudinal study using a national sample of over 4,000 children
in which they compared siblings to control for selection bias. They
found that although Head Start led to large and significant immediate
gains in test scores for both White and Black groups, these gains were
quickly lost for Black groups, although some remained for White groups.
Even more intensive and prolonged educational interventions than Head
Start have not produced lasting effects on IQ or scholastic performance
(Jensen, 1998b, pp. 333-344) or that generalize to other measures or
criteria.
Some culture-only theorists propose that SES should not be assessed in
terms of crude material measures but must be seen as a complex of
attitudes, aspirations, self-images, and societal stereotypes (Loury,
2002; Ogbu, 2002; Sowell, 1994 ). Some of these types of cultural
factors have been tested as well. Matching Black and White children for
the geographical areas of their homes, the schools they attend, and
other finer grade socioeconomic indicators again reduces the mean group
IQ difference but does not eliminate it. Black children from the best
areas and schools (those producing the highest average scores) still
average slightly lower than do White children with the lowest
socioeconomic indicators (Herrnstein & Murray, 1994, pp. 286-289;
Jensen, 1998b , pp. 357-360). This is an anomaly for the culture-only
theory but is explained by genetic theory through regression to the mean
(see Section 10).
Other culture-only hypotheses have invoked Black role models, test
anxiety, self-esteem, and racial stress as causal agents, but none of
these have ever been consistently confirmed (Jensen, 1980, 1998b). Other
ideas, such as stereotype threat (Steele, 1997),
involuntary-minorities-are-castes (Ogbu, 2002), and race stigma (Loury,
2002 ), do not explain the low IQ of Africans south of the Sahara, where
Blacks are in the majority. Nor is there any evidence from analyses of
large archival data sets that unique minority-specific factors such as
the history of slavery, White racism, lowered expectations, or
heightened stress make cultural influences stronger for one group than
for another (see Section 5). Neither can racial stigmatization (Loury,
2002 ) explain why East Asians average higher in IQ and brain size than
Whites. A progressive theory of racial group differences must address
all the known facts.
Culture-only theory must offer some explanation why its main
variables-poverty, social class, religious beliefs, cultural practices,
father absence, and parenting styles-account for so little variance
within groups. Given these repeated findings, it is unlikely such
variables can account for differences between groups (see Section 5).
Adoption and twin studies show that the environmental variables
influencing IQ and social behavior are primarily those that occur within
families rather than between families (see Figure 3 ). Although the
causes of within-group differences are logically separate from the
causes of between-groups differences (Section 2), even when the combined
set of within- and between-families variables is examined together,
there are still no identifiable race-specific variables (Section 5).
It is always possible that new data with sharper hypotheses and better
controls could require a revision of the finding of no shared family or
minority-specific cultural effects on race-IQ differences. There were
hints (but no more than that) of a lower heritability and a greater
shared environment component in Black adolescents than in White
adolescents in Rushton and Osborne's (1995) twin study of cranial
capacity (Section 5). Similarly, an epidemiological study of
low-birth-weight and normal children, followed from 6 to 11 years of
age, reported an IQ decline in mainly Black inner-city children with no
similar IQ decline in mainly White suburban children. The authors
interpreted their results as a between-community effect and the racial
makeup of the schools the children attended, more than to individual and
family factors (Breslau et al., 2001 ). Behavioral genetic designs using
traditional modeling procedures (Section 5), along with new individual
admixture measures on mixed-race participants (Section 8), could provide
counterevidence to our conclusions. Unfortunately, behavioral
geneticists (who have the most knowledge of the best techniques) have
for the most part avoided the racial question.
One culture-only hypothesis currently enjoying much support is based on
the secular increase in test scores, known as the Flynn effect because
of the repeated demonstration by James Flynn (1984, 1987, 1999) that the
average IQ in several countries has increased by about 3 points a decade
over the last 50 years. Some have suggested that the Flynn effect
implies that the 1 standard deviation difference in the mean Black-White
IQ difference in the United States will gradually disappear over time
(Flynn, 1999). However, one statistical analysis shows that the Flynn
effect is not on the g factor, the principal source of the mean
Black-White group difference.
Table 4 (based on Rushton, 1999 ) shows the results of a
principal-components analysis of the secular gains in IQ from the United
States, Germany, Austria, and Scotland, along with Black-White IQ
difference scores from the United States, inbreeding depression scores
from cousin-marriages in Japan, and g loadings from the standardization
samples of the WISC-R and WISC-III. The relevant findings are as
follows: (a) The IQ gains on the WISC-R and WISC-III form a cluster,
showing that the secular trend in overall test scores is a reliable
phenomenon; but (b) this cluster is independent of a second cluster
formed by Black-White differences, inbreeding depression scores (a
purely genetic effect), and g factor loadings (a largely genetic
effect).
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Table 4 Principal-Components Analysis and Varimax Rotation for Pearson
Correlations of Inbreeding Depression Scores, Black-White Differences, g
Loadings, and Gains Over Time on the Wechsler Intelligence Scales for
Children (WISC) With Reliability Partialed Out
This analysis shows that the secular increase in IQ behaves differently
from the mean Black-White group difference in IQ. Flynn's (1999)
hypothesis that the IQ gains over time imply a purely environmental
origin of mean racial-group differences is not supported. Although the
Flynn effect does suggest that improving the environment, especially at
the low end of the IQ distribution, can improve test scores, the cluster
analysis shows that the g factor is independent of the Flynn effect.
Instead, g is associated with inbreeding depression, for which there is
no nongenetic explanation, which implies strongly that g is less
amenable to environmental manipulation. These findings are consistent
with an analysis of adoption data, which shows the IQ gains that result
from being adopted into high SES homes do not produce a gain in g but
only in non-g factors and in specificity of the various subtests. The
adopted children's g factor scores reflected the SES level of their
biological parents (Jensen, 1998a).
Dickens and Flynn (2001) replied to Rushton's (1999) cluster analysis
with a more general statement of having resolved the paradox of how high
heritabilities could go along with large secular increases in IQ. Their
solution rests on the role of genotype-environment correlation. Recall
from Section 5 that this occurs largely through the individual's genetic
tendency to encounter, select, or create certain aspects of the
environment in preference to alternatives. Genotype-environment
correlation is part of the mechanism by which genetic proclivities
become realized. Dickens and Flynn hypothesized that the positive
feedback effects from even small initial environmental advantages
stimulate mental development and lead to an even more favorable
environment, stimulating yet more IQ development.
Dickens and Flynn's (2001) model, however, appears inconsistent with
some empirical evidence. Gene-environment correlation cannot explain the
mean Black-White group difference in IQ because it implies that Black
groups, in comparison with White groups, become increasingly
disadvantaged during the developmental period from early childhood to
maturity. With increasing age there would be cumulative unfavorable
effects on IQ for Black groups with respect to White groups. Yet
national data (reviewed in Section 3) show that the size of the mean
Black-White group difference remains approximately constant at 1
standard deviation and shows no significant change throughout the
developmental period after about 3 years of age. The follow-up results
of the Minnesota Transracial Adoption Study (Table 2), and the fact that
the heritability for IQ generally increases from about 0.40 in early
childhood to about 0.80 in later maturity (Figure 3), both contradict
the Dickens-Flynn thesis. So too does the fact that both g estimates
calculated from East Indians in South Africa and genetic estimates
calculated from the Japanese in Japan are able to predict the magnitude
of Black-White differences in South Africa and in the United States (see
Sections 4 and 5). Such robust generalization implies that the mean
Black-White group difference in IQ is sufficiently persistent across
cultures as to be unaffected by major changes in gene-environment
correlations.
Dickens and Flynn (2001) provided no empirical evidence that
gene-environment correlation constitutes either a large component of the
phenotypic variance or that it increases with age (both of which are
required by their model). They also did not provide any other direct
empirical evidence. In addition, their models have been criticized for
not taking the stability of IQ scores over time into account and for
having too many free parameters (Loehlin, 2002; Rowe & Rodgers, 2002),
to which Dickens and Flynn (2002) have replied. Because to date Dickens
and Flynn have not given the high heritability of IQ any independent
causal effect in explaining the mean Black-White group difference, their
thesis is best placed in the culture-only camp.
Section 13: Evaluating the Culture-Only and the Hereditarian Research
Programs
Table 5 summarizes the 30-plus-years of research on Black-White IQ
differences carried out since Jensen's (1969) Harvard Educational Review
article. It compares and contrasts the predictions of the hereditarian
and the culture-only theories against the existing data reviewed in
Sections 3 through 12, to which we then assigned "scores." We assigned
the highest score (++) when, in our opinion, the results confirmed a
novel prediction first derived from theory that was then tested and
confirmed. We awarded the next highest score (+) when the results were
consistent with theory but not predicted from it. We gave a neutral
score (0) when the results could not be predicted from theory so that it
could be either confirmed or disconfirmed. We assigned a negative score
(-) when the predicted results were disconfirmed. Because some
diacritical tests have two components, the maximum possible support for
either research program would be a score of 12 × 2 = 24; maximum
disconfirmation would be a score of -24. Naturally these scores reflect
our particular evaluation of how well the two competing theories predict
and explain the evidence. We acknowledge that others might see things
differently, and we invite them to assign their scores. Our purpose is
to advance the debate.
Table 5 Comparison Chart for Evaluating the Hereditarian (50% Genetic)
and Culture-Only (0% Genetic) Research Programs
Table 5 (continued)
Our evaluation of the evidence supports a cumulative score of 17 for the
hereditarian model and -7 for the culture-only model. We therefore
suggest that the hypothesis of some genetic component in the mean
Black-White group difference in IQ should be considered "provisionally
true." Naturally, we do not expect everyone to agree with this
assessment. Our own perspective is obviously hereditarian (Jensen,
1998b; Rushton, 2000 ). Those working from a different perspective may
arrive at alternative tallies or add new dimensions to be tallied that
we have overlooked. Before discussing our conclusion, we consider in
more detail the data on each of the categories in Table 5.
Mean Race-IQ Differences Are Found Worldwide (Section 3)
The mean Black-White IQ difference in the United States of 85 versus 100
can be, and has been, explained both by the hereditarian model (in terms
of some genetic difference) and by the culture-only model (in terms of
nutrition, poverty, SES, family structure, schooling, racism, and the
legacy of slavery). Hence, initially we were inclined to give both the
hereditarian model and the culture-only model a score of (+). The
hereditarian model, however, also predicted that the same pattern would
be found worldwide, with lower scores for sub-Saharan Africa than for
Black Americans, and that the differences would also be found on
culture-fair tests and on reaction time tasks that measure the speed and
efficiency with which the brain processes information (and which all
children can perform in less than 1 s). These predictions were
confirmed. The culture-only hypothesis is disconfirmed by the
differences on culture-fair and reaction time tests. Nor can the
culture-only model easily explain why the East Asian average IQ of 106
is higher than the average White IQ, including on these same
speed-of-processing tasks. Within the United States, the mean
Black-White group difference in IQ has not changed significantly over
the past 100 years despite significant improvements in the conditions of
Black Americans. The same magnitude of difference is observed as early
as age 2½ years. Our score for Section 3: hereditarian model (+);
culture-only model (-).
Race-IQ Differences Are Most Pronounced on the More g-Loaded Components
of Tests and Least So on the Most Culturally Loaded Items (Section 4)
The hereditarian model made the novel prediction that the mean
Black-White group difference in IQ is not the result of idiosyncratic
cultural peculiarities in this or that test but would be more pronounced
on highly g-loaded tests. Because the prediction was confirmed, it
counts as evidence for the hereditarian position while also
contradicting the prediction from the culture-only model that the
differences are due to culturally loaded tests. In South Africa, g
loadings calculated on East Indians predicted mean Black-White group
differences, showing substantial cross-cultural generalizability. A
test's g loading is the best predictor, not just of its correlation with
scholastic and workplace performance, but also of its correlation with
reaction time measures, heritability coefficients determined from twin
studies, inbreeding depression scores calculated in children of
cousin-marriages, and neurological variables such as brain size, brain
evoked potentials, brain pH levels, brain glucose metabolism, and nerve
conduction velocity. Thus, we conclude the evidence reviewed in Section
4 strongly supports the hereditarian model (++) and argues against the
culture-only model (-).
Race-IQ Differences Are Most Pronounced on the More Heritable Components
of Tests With Little or No Evidence of Race-Specific Developmental
Processes (Section 5)
Research based on this novel prediction from the hereditarian model
established that (a) the heritability of IQ among Black groups is around
0.50, not significantly different from that found in White groups; (b)
there is no evidence of the effect of any special minority-specific
developmental process resulting from the legacy of slavery or of White
racism in large sets of archival correlation matrices between background
variables and outcome measures, or on relations among subtests; (c) IQ
subtests with higher heritabilities predict mean Black-White group
differences better than do subtests with lower heritabilities; and (d)
the shared environment type of variables usually proposed to explain
group differences (e.g., differences in income, schools) decrease in
effect size with age. Cross-cultural generality was demonstrated by the
fact that the magnitude of inbreeding depression scores on various
subtests calculated on the Japanese in Japan predicted the magnitude of
Black-White differences in the United States. Because the empirical
results confirmed a novel prediction from the hereditarian model (++)
but disconfirmed several predictions from culture-only theory (-), we
scored Section 5: hereditarian model (++); culture-only model (-).
Mean Race-IQ Differences Are Associated With Mean Brain Size Differences
(Section 6)
Overall, MRI studies show that brain size is related to IQ differences
within race. Moreover, the three-way pattern of group differences in
average brain size is detectable at birth. By adulthood, East Asians
average 1 cubic inch more cranial capacity than Whites, and Whites
average 5 cubic inches more cranial capacity than Blacks. These findings
on group differences in average brain size have been replicated using
MRI, endocranial volume from empty skulls, wet brain weight at autopsy,
and external head size measures. They were acknowledged by Ulric
Neisser, Chair of the APA's Task Force on intelligence, who noted that,
with respect to "racial differences in the mean measured sizes of skulls
and brains (with East Asians having the largest, followed by Whites and
then Blacks) ... there is indeed a small overall trend" (Neisser, 1997 ,
p. 80). The hereditarian model explains these in terms of genetic
differences. The culture-only position can explain them in terms of
nutrition, SES, or early cognitive stimulation. Adding the East Asian
data, however, literally "changes the shape of the table." The
hereditarian model posits that if East Asians average higher IQs than do
Whites, then they must also average larger brains than Whites, and that
perhaps both the higher IQ and the larger brain are most parsimoniously
explained in terms of the natural selection experienced in colder
climates during human evolution (++). The culture-only position has yet
to explain both the higher IQ and the larger brain size of East Asians,
given that these groups have also been subjected to prejudice in White
societies or severe malnutrition in their homelands. We scored Section
6: hereditarian model (++); culture-only model (-).
Mean Race Differences in IQ Remain Following Transracial Adoption
(Section 7)
Transracial adoption studies provide one of the best methods for
resolving the question of group differences in mean IQ. The
above-average IQ scores of Black adoptees at age 7 confirmed the
culture-only predictions. The results of the follow-up testing at age 17
were more ambiguous. The hereditarian model predicted that when the
longitudinal study was carried out, the Black-White difference would
emerge (based on the increasing size of the genetic effect on IQ with
age), and this is one interpretation of the data, though a culture-only
interpretation is also plausible. However, support for the hereditarian
model again comes from adding the East Asian data to the mix. Korean and
Vietnamese children adopted into White homes, even though as babies many
had been hospitalized for malnutrition, nonetheless grew to have IQs 10
or more points higher than their adoptive national norms. The
culture-only model cannot explain that finding. Further, it argues
against the culture-only hypothesis that the high performance of East
Asian children is due to "trying harder" or other cultural values
emphasized by East Asian families. Our score for Section 7: hereditarian
model (++); culture-only model (-).
Studies of Racial Admixture Reflect Mean Black-White IQ Differences
(Section 8)
Both the hereditarian and the culture-only model can explain why groups
of lighter skinned African Americans and the (also lighter skinned)
mixed-race "Coloreds" of South Africa have average IQs between those of
(for the most part) unmixed groups of Blacks and Whites. Both models can
also explain the fact that the degree of White admixture is correlated
with brain weight at autopsy. The culture-only position does so in terms
of societal discrimination based on skin color as well as its possible
cascading effects on nutrition and health (+); the hereditarian model
does so in terms of the hypothesized genetic difference in average IQ
and its correlations with race and skin color (+). Some evidence against
the culture-only position comes from studying the misclassified adoptees
in the Minnesota Transracial Adoption Study (-). The expectancy effects
hypothesis, that adoptive parents' beliefs about their child's racial
background influence the child's intellectual development, is not
supported by the finding that the mean IQ score for 12 children wrongly
believed by their adoptive parents to have had two Black biological
parents was about the same as that of the 56 children correctly believed
by their adoptive parents to have had one Black and one White biological
parent. While the number of children is small, this conclusion is
supported by Rowe's study in which 119 mixed-race children were selected
as "looking African American" but their IQ scores also turned out to be
intermediate. Our score for Section 8: hereditarian model (+);
culture-only model (0).
IQs Show Regression Toward Predicted Racial Means (Section 9)
The phenomenon of regression to the mean is predicted from basic genetic
theory and has been documented for a number of physical traits in humans
and in other species. The hereditarian model applied this reasoning to
IQ studies to make a novel prediction about the amount of regression
across the whole IQ distribution and various degrees of kinship. The
results showed that the children of Black parents of IQ 115 regressed
toward the Black average IQ of 85, whereas children of White parents of
IQ 115 regressed toward the White average IQ of 100. The converse
occurred at the low end of the scale. Even stronger support for the
hereditarian position came from sibling data. The regression lines for
both Blacks and for Whites showed no significant departure from
linearity throughout the range of IQ from 50 to 150. A failure of this
prediction would have argued against the hereditarian model but would
have been neutral for the culture-only model. The predictions from the
hereditarian model were tested and confirmed. The culture-only theory
must argue that environmental effects or chance variation mimics the
predicted genetic effects. We scored Section 9: hereditarian model (++);
culture-only model (0).
Mean Race-IQ Differences Are Paralleled by a Matrix of Other Traits and
Behaviors (Section 10)
A suite of over 60 life-history variables, including rate of two-egg
twinning, speed of maturation and longevity, personality and
temperament, family stability and crime, sexual behavior and fertility,
as well as intelligence and brain size, have been identified on which
East Asian and African groups consistently average at the two ends of a
continuum, with European groups intermediate, regardless of where they
presently live. This race-behavior matrix constitutes a series of novel
predictions derived from an evolutionary theory of the origin of races
that were tested and confirmed. The culture-only model has only
partially addressed this race-behavior matrix, with (sometimes
contradictory) supplementary hypotheses. Our score for Section 10:
hereditarian model (++); culture-only model (-).
Mean Race-IQ Differences and Human Evolution (Section 11)
One theory of human evolution argues that the farther north the
ancestral human populations migrated out of Africa, about 100,000 years
ago, the more they encountered the cognitively demanding problems of
gathering and storing food, gaining shelter, making clothes, and raising
children successfully during prolonged winters. (This is not the only
theory of human evolution, nor do all who endorse it concur with our
interpretation.) Ecological pressures selected for larger brains, slower
rates of maturation, lower levels of sex hormone, and all the other
life-history characteristics. From this perspective, the data from both
human genetics and human evolution mesh with the race-behavior matrix
(++). Genetic-evolutionary theory acknowledges factors such as East
Asian family strength or African poverty, but as effects rather than
causes. The consistency of the pattern of traits in Table 3 also
supports the argument, as do genetic analyses, against the view that
race is only a social construction based on a few salient traits such as
skin color (Crow, 2002; Risch et al., 2002). Our score for Section 11:
hereditarian model (++); culture-only model (-).
Culture-Only Hypotheses Fail to Account for Mean Race-IQ Differences (
---------------------------------
Volume 11(2) June 2005 p 295-301
THERE ARE NO PUBLIC-POLICY IMPLICATIONS: A Reply to Rushton and Jensen
(2005)
Sternberg, Robert J.1,2
1Department of Psychology, Yale University
2 Correspondence concerning this article should be addressed to Robert
J. Sternberg, Department of Psychology, Yale University, P.O. Box
208358, New Haven, CT 06520-8358. E-mail: robert.sternberg at yale.edu
Outline
* Abstract
* References
J. P. Rushton and A. R. Jensen (2005) purport to show public-policy
implications arising from their analysis of alleged genetic bases for
group mean differences in IQ. This article argues that none of these
implications in fact follow from any of the data they present. The risk
in work such as this is that public-policy implications may come to be
ideologically driven rather than data driven, and to drive the research
rather than be driven by the data.
The quest to show that one socially defined racial, ethnic, or other
group is inferior to another in some important way, such that "the
public must accept the pragmatic reality that some groups will be
overrepresented and other groups underrepresented in various socially
valued outcomes" (Rushton & Jensen, 2005 , p. 283), has what I believe
to be a long, sad history. Since ancient times, cynical political,
religious, and other leaders have used such arguments to justify
discriminatory ideological positions. Does science want to provide them
the ammunition?
Scientists might argue that their work is value free and that they are
not responsible for the repugnant or even questionable values or actions
of opportunistic leaders. Rushton and Jensen (2005) seem to believe, as
have others, that they do perform a kind of value-free science and that
they merely respect the truth. However, using tests and scoring them in
itself represents a value judgment: Taking a test means different things
for diverse groups, and the backgrounds of varied groups who take these
tests are different (Greenfield, 1997 ). Studying so-called races
represents a value judgment because race is a social construction, not a
biological concept, and Rushton and Jensen's entire article is based on
the false premise of race as having meaning other than in their and
other people's imaginations (Sternberg, Grigorenko, & Kidd, 2005 ).
Deciding to study group differences represents a value judgment-that the
problem is worth studying. Deciding to show that one group is
genetically inferior on an index is a value judgment as to what is worth
showing. These decisions, among others, indicate that there is no
value-free science. Few of us can hear our own accents when we
speak-only other people have accents! In the same way, supposedly
"value-free science" reflects the values of investigators who cannot see
their own values underlying their research.
In our work in Tanzania, for example, we have found that children who do
not do well on conventional static cognitive tests do much better when
the tests are administered dynamically (Sternberg et al., 2002). Many
others have found the same results (see general review of literature in
Sternberg & Grigorenko, 2002; see also Sternberg, 2004). In some
cultures, the act of taking a test in isolation from other people is
itself an unfamiliar activity (Greenfield, 1997 ). Indeed, even outside
the Mayan cultures that Greenfield has studied, such as in the United
States, most significant projects are done collaboratively, not
individually. In general, when we use a psychological measuring
instrument in assessing people, we are imposing a set of values we often
do not realize we are imposing.
Ruston and Jensen (2005) make what I believe to be ambiguous
references-for example, speaking of biological inequality without
defining this term. I also believe they inadvertently create "straw
men." These straw men take the form of false dichotomies, such as
between the culture-only model and the hereditarian model (as though
there is nothing in between), and imaginary oppositions, such as between
people who believe in the influence of genetics and people who engage in
"denial of any genetic component in human variation." There are probably
no such people, at least among serious scientists. What scientist, for
example, believes that height or weight is entirely environmental?
What good is research of the kind done by Rushton and Jensen supposed to
achieve? Only vaguely cloaked behind their words is the purported
demonstration that certain groups are, on average, genetically inferior
to other groups, at least in that aspect of intelligence measured by IQ.
The articles and books reporting on this research inevitably have the
seemingly obligatory final public-policy section, which is somehow
supposed to justify, in part, the usefulness of the research. The
"Implications for Public Policy" section (Rushton & Jensen, Section 15)
that is included in works of this kind (see also Herrnstein & Murray,
1994; Jensen, 1969 ) seem to have the intention to provide a
public-policy rationale for work attempting to show that one group is
inferior to another and that not much, if anything, can be done about
it. It is therefore worthwhile to examine whether any of the alleged
public-policy implications follow from the data. If not, the argument
that the research is useful in formulating public policy is impugned.
I believe that, as in similar past works, none of the claims regarding
"implications for public policy" are justified. As was true of
Herrnstein and Murray (1994) and their predecessors, the science risks
being used to promote social engineering unsupported by the data. In my
response, because of space restrictions, I limit my response to their
public-policy claims.
Rushton and Jensen's (2005) article is based on the equation of IQ with
intelligence. Many psychologists question this equation (see essays in
Sternberg, 2000 ), including even those who have designed the most
widely used tests of intelligence such as Binet and Wechsler. So in this
rejoinder, I talk about IQ, which is the basis for Rushton and Jensen's
article, not intelligence in its full sense.
According to Rushton and Jensen (2005),
The research supporting the role of heredity in human behavior implies
that the distributional model is more correct than the discrimination
model. It explains some of the mean Black-White group difference in
IQ-related outcomes in terms of the differential distribution of the
genes for general mental ability. For example, IQ is a significant
predictor of such socially disadvantageous outcomes as dropping out of
high school, being unemployed, being divorced within 5 years of
marriage, having an illegitimate child, living in poverty, being on
welfare, and incarceration. (Rushton & Jensen, 2005, p. 282)
First, as Rushton and Jensen (2005) realize, these correlations, like
heritability coefficients, are all obtained under a given social system.
Heritabilities of intelligence differ widely even across social classes
(Turkheimer, Haley, Waldron, D'Onofrio, & Gottesman, 2003 ). Moreover,
in a social system that has no welfare (e.g., traditionally, Mexico), IQ
is not correlated with going on welfare. In a social system in which the
state ensures that no one lives in poverty (e.g., traditionally,
Sweden), IQ is not correlated with living in poverty. Is divorce
heritable? In a system that does not allow divorce (e.g., traditionally,
Chile), IQ is not correlated with divorce within the first 5 years of
marriage. And in a system that does not allow discrimination, who knows
what the heritability of intelligence would be?
It is very difficult to find such a truly nondiscriminatory system.
Built into any correlation is the contextual backdrop in which the two
interrelated variables occur. The correlation of IQ with other variables
may stay the same, go down, or go up. No one knows. It would be easy for
middle- and upper-middle-class majority-group individuals (presumably,
such as Rushton and Jensen) to state that, if they were born into
poverty, they or others like them would have achieved socially desirable
outcomes in life. But is this so? Many individuals-disproportionately,
members of certain minority groups and those in developing
countries-grow up in miserable circumstances from which there is no
ready exit. Their home life may be bad; their schools may be bad; their
economic situation may be bad. It is extremely difficult to escape from
these environments because they are members of a socially defined lower
caste for which the opportunities for advancement are meager. Ogbu
(1978) , for example, found that displaced members of minority groups
who are, or are descended from, forced immigrants tend to underperform
compared with members of the same group when the group is in an
environmental context in which it was not forced to immigrate. Even when
African American students live in affluence, some of their prevailing
cultural attitudes may prevent them from achieving at the levels of
which they are capable. Such attitudes may affect their ability test
scores as well as their achievement test scores, because existing
ability tests, including tests of nonverbal abilities, all measure
achievement, to a greater or lesser extent.
Not all the correlates of higher IQ are socially desirable, although
Rushton and Jensen (2005) only mention the socially desirable ones. To
be fair, we probably ought to list selected undesirable correlates of
higher IQ: for example, being able to design and fabricate sophisticated
bombs, the capacity to successfully manufacture weaponized anthrax and
other biological agents, and planning terrorists attacks without getting
caught. In these cases, higher IQ may be correlated with socially
devalued outcomes. Arguably, these outcomes do more social harm than
divorce (associated, according to Rushton and Jensen, with low IQ).
As these examples illustrate, a problem with our society is its emphasis
on intelligence and its corresponding lack of emphasis on wisdom.
Unfortunately, it is our foolishness that is likely to destroy our
society, not our lack of IQ (Sternberg, 1998, 2002).
Second, before we ask about distributions of particular attributes, we
need to ask ourselves which attributes we want to study to begin with.
IQ is one attribute that, in our society, is correlated with success. In
many other societies, IQ probably matters as well, although not to the
same extent. In a hunter-gatherer society, IQ will still be important,
but if a hunter cannot shoot straight, IQ will not bring food to the
table. In a warrior society, IQ will still matter, but physical prowess
may be equally necessary to stay alive. In a totalitarian society, a
high IQ may be the kiss of death. During the reigns of Stalin and Pol
Pot, among other such reigns, intellectuals were the first to be shot.
In a rapidly changing society, such as modern-day Russia, many high-IQ
professors have found their already low pay sinking to even lower
levels. Those who are not creatively flexible may find themselves unable
to sustain their families. IQ matters, but so do many other qualities.
Rushton and Jensen (2005) acknowledge this fact in one sentence, but
their sweeping policy generalizations suggest that the acknowledgment
does not carry much weight with them.
Third, it is not the case that the "research supporting the role of
heredity in human behavior implies that the distributional model is more
correct than the discrimination model" (Rushton & Jensen, 2005 , p.
282). Their argument incorrectly implies that IQ is the only cause of
success. Members of other socially defined racial or ethnic groups might
be superior in other attributes correlated with success but still not
attain the success of the majority because they find their success
blocked by discrimination. Perhaps Rushton and Jensen, like most of us,
are not even aware of the extent to which we ourselves discriminate, and
would prefer to think that those who do not achieve at high levels fail,
not because they are blocked, but because they are incapable of
succeeding. This has been the stand of privileged majorities throughout
history. And these majorities have routinely provided arguments of
various kinds, including so-called scientific ones, to support their
positions.
Rushton and Jensen (2005) state that "although the distributional model
does not rule out affirmative action or compensation-type initiatives,
it does reduce the impact of arguments in their favor based on an
exclusive adherence to the discrimination model" (p. 283). This argument
may not be correct. Germany, Austria, Switzerland, and other countries
have paid compensation to victims of the Holocaust. The compensation had
nothing to do with IQ. Some forms of compensation were monetary, others
were not (e.g., return of stolen works of art). They recognized a
history of discrimination and wrongs unrelated to intelligence. The
United States unquestionably has a history of wrongs toward African
Americans through slavery and many other forms of discrimination. Should
African Americans be paid compensation for slavery? That is a
public-policy issue, not a science issue. It has nothing to do with the
average IQs of various groups, or anyone else's. Conflating the issue of
past wrongs with group-average differences in IQ does not make sense.
Another supposed policy implication is that tests such as the SAT and
the General Aptitude Test Battery are about equal in predictive validity
for all groups. But Rushton and Jensen (2005) mention and then fail to
elaborate on the qualification that this is the case "for all groups who
speak the same language and have been schooled in the culture of the
test" (p. 283). This is an extremely significant qualification to only
mention in passing. First, it simply is not the case that people either
are or are not schooled in the culture of the test. People are schooled
in this culture in varying degrees. Many inner-city and remote rural
schools do not, and in some cases, cannot provide the same schooling in
the culture of the test that wealthy suburban or urban schools can
provide. Second, in many countries, children are only minimally schooled
in the culture of the test (Sternberg et al., 2002 ). In other
societies, they are schooled slightly more in the culture of the test
but, for economic or social reasons, need to devote most of their
attention to nonschool matters (Sternberg et al., 2001 ). In some
societies, people have conceptions of intelligence that do not
particularly value as intelligent what the tests measure (Grigorenko et
al., 2001 ). Yet in others, people are often ill from disease or
malnutrition much of the time and find it difficult to absorb the full
benefit of the schooling they receive.
The assumption should not be made that all children speak the same
language even in countries such as the United States. Many children
attend schools where students do not all speak the same language. Within
a given school, there may be scores of native languages, as is routine
in schools in large states such as California. The point, quite simply,
is that what appears in Rushton and Jensen's (2005) article to be a
minor qualification is actually a significant one.
If one examines studies of conventional ability tests, they generally
are not biased in a narrow statistical sense. However, the same
environmental factors that depress criterion-test scores also lower
ability-test scores, as ability tests and achievement tests all measure
achievement to some degree. Thus the correlation reflects, in part, that
school-based skills predict school-based skills. Changing the
environment might change the correlations, although of course we cannot
know for sure. Thus the tests are not biased, but they fail to reflect
what individuals might be capable of under different circumstances.
There is no reason to believe that the failure of what Rushton and
Jensen (2005) call "equal opportunity programs to enable all groups in
society to perform equally scholastically" (p. 283) is because of "the
true nature of individual and group differences, genetics, and
evolutionary biology" (p. 283). If height is heritable but modifiable,
so is intelligence. It is not clear that any program will fully equalize
performance, but programs can raise performance. We, as a society, have
not yet determined how most effectively to raise achievement. There are
some extraordinarily successful programs, such as those at the
University of Maryland, Baltimore County, that do seem to be
dramatically raising achievement. Jaime Escalante also apparently had
great success. But certainly we are less effective than the natural
environment (Mathews, 1989). The Flynn effect (Flynn, 1999 ) shows that
environmental factors can raise IQs. No one, to my knowledge, has
claimed that the effect is genetic, and it is unclear how it possibly
could be. So it can be done. Nature apparently knows how; we do not know
as well, at least, as of yet.
Rushton and Jensen (2005) argue that failure to take ethnicity into
account in epidemiological work would be a great mistake. For example,
different groups may suffer from different rates of hypertension,
prostate cancer, and so forth. This may be true, but it is irrelevant to
their arguments regarding the sources of group differences in
intelligence. The fact that African Americans have higher rates of
hypertension, for example, is not enlightening as to whether African
Americans show different IQs from Whites because of genetic factors. So
these policy recommendations, like the others, have no clear relation to
the alleged scientific argument advanced by their article.
According to Rushton and Jensen (2005) , "modern social science has
typically ... promoted the idea that all babies are born more or less
equally endowed in intelligence and learning ability. It followed
therefore that inequalities were the result of social, economic, and
political forces" (p. 284). This argument, too, is not correct. Modern
social science has not taken the view that all babies are born with
equal intelligence or learning ability. Are there any psychologists who
seriously study intelligence who believe that genetic factors play no
role in individual differences in intelligence? I doubt it. This is yet
another of the many examples of straw men created in their article to
foster belief in an untenable position by arguing the alternative. Where
there is genuine disagreement in the field is not over whether there are
individual differences of genetic origins, but rather whether there are
group differences of IQ that are genetic in origin (i.e., of what they
believe to be biologically defined racial groups).
Can one seriously believe that there are not inequalities that foster
differences in outcomes? Children growing up in the slums of India, all
of low caste, have almost no chance of ever leaving those slums,
regardless of their IQs. Children of rural Appalachia or Watts in Los
Angeles, or Harlem in New York, or Togiak in Alaska, all in the United
States, have opportunities far reduced compared with those children
living, say, in Winnetka, Illinois, Scarsdale, New York, or Palo Alto,
California. In current-day Somalia and Liberia, the opportunities are
even worse. For some of these children, getting to and from school and
through a school day safely, having food on the table to eat, and
avoiding the random gunfire or drug wars raging around them may consume
many more of their mental resources than getting good grades in school.
Were Rushton or Jensen or any of us reading this article to have grown
up or lived in these environments, what would have become of us? Would
we have the luxury of writing such articles, or would we have to spend
our time attending to basic food and safety needs?
Rushton and Jensen (2005) suggest that "organizations such as the
[American Psychological Association (APA)] could play a critical role in
changing the zeitgeist" (p. 283). The chances of APA or similar
organizations adopting any of the policy recommendations in Rushton and
Jensen's article seem remote. My experience during my presidency of the
APA is that this organization and others like it are devoted to
creating, not restricting, opportunities for growth and advancement.
The quality of science is determined not only by the quality of problem
solving but also by taste in the selection of problems to solve. Readers
will have to decide for themselves whether the problem addressed in
Rushton and Jensen's (2005) article represents good taste in the
selection of the problems. Would that Rushton and Jensen had devoted
their penetrating intellects to other more scientifically and socially
productive problems!
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intelligence: A study of implicit theories in a Kenyan village.
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---------------------------------
Psychology, Public Policy, and Law
Volume 11(2) June 2005 p 302-310
HEREDITY, ENVIRONMENT, AND RACE DIFFERENCES IN IQ: A Commentary on
Rushton and Jensen (2005)
Nisbett, Richard E.1,2
1Department of Psychology, University of Michigan
2 Correspondence concerning this article should be addressed to Richard
E. Nisbett, Department of Psychology, University of Michigan, Ann Arbor,
MI 48109. E-mail: nisbett at umich.edu
Outline
* Abstract
* The Current Difference in Intelligence Between Blacks and Whites
* The Effects of Intervention
* Direct Tests of Heritability of the Black-White IQ Difference
* Skin Color
* Self-Reports of European Ancestry
* Children in Postwar Germany Born to Black and White American
Soldiers
* Mixed-Race Children Born to Either a Black or a White Mother
* Studies Measuring European Ancestry Through Blood Group
Indicators
* Adoption Studies
* Assignment of Black Adoptees to Families of Different Races
* Assignment of Black and White Adoptees to the Same
Environment
* Assignment of Black and White Adoptees to Different White
Families
* Conclusion
* References
J. P. Rushton and A. R. Jensen (2005) ignore or misinterpret most of the
evidence of greatest relevance to the question of heritability of the
Black-White IQ gap. A dispassionate reading of the evidence on the
association of IQ with degree of European ancestry for members of Black
populations, convergence of Black and White IQ in recent years,
alterability of Black IQ by intervention programs, and adoption studies
lend no support to a hereditarian interpretation of the Black-White IQ
gap. On the contrary, the evidence most relevant to the question
indicates that the genetic contribution to the Black-White IQ gap is
nil.
Rushton and Jensen's (2005) article is characterized by failure to cite,
in any but the most cursory way, strong evidence against their position.
Their lengthy presentation of indirectly relevant evidence which, in
light of the direct evidence against the hereditarian view they prefer,
has little probative value, and their "scorecard" tallies of evidence on
various points cannot be sustained by the evidence.
The Current Difference in Intelligence Between Blacks and Whites
One of the most serious misrepresentations in Rushton and Jensen's
(2005) article is their claim that the current difference in IQ between
Blacks and Whites is slightly more than 15 points, or 1 standard
deviation. The best evidence we have indicates that that value is out of
date and that the Black-White IQ gap has lessened considerably in recent
decades (Grissmer, 1994; Grissmer, Flanagan, & Williamson, 1998;
Grissmer, Williamson, Kirby, & Berends, 1998; Hedges & Nowell, 1998;
Nisbett, 1995, 1998 ). We do not have actual IQ scores available to
establish this point but rather various ability tests, most of which are
highly correlated with IQ-some as high as .8 to .9. Though IQ scores
would be preferable to speak directly to the question of IQ change, such
data are unavailable in the form of a national random sample. In
contrast, several probability samples of U.S. elementary and high school
students are available. These include, over the period 1965-1994, the
Equality of Educational Opportunity (EEO) survey, the National
Longitudinal Study, the High School and Beyond survey, the National
Education Longitudinal Study, and the National Assessment of Educational
Progress program (NAEP).
Hedges and Nowell (1998) found improvement on almost all tests for
African American 12th graders compared with other 12th graders over the
period 1965-1994. The best estimates in terms of the stability the
scores provide, and in terms of their correlations with IQ, are in the
form of composites, for example, reading + vocabulary + mathematics for
the EEO survey. The Black-White gap on these composites over the period
decreased on average by 0.13 standard deviation per decade, yielding an
estimate of a reduction of the gap by around 0.39 standard deviation
over the period. The largest study, conducted by the NAEP, indicated
that, if trends were to continue, the gap in reading scores would be
eliminated in approximately 25 years and the gap in science scores in
approximately 75 years.
Grissmer, Flanagan, and Williamson (1998) found comparably large gains
on the NAEP for Blacks in elementary school, junior high, and high
school. Whites gained slightly in both math and reading between 1971 and
1996, but Blacks gained much more, narrowing the gap by 0.2 to 0.6
standard deviations. This would yield estimates of obliteration of the
gap somewhere between 20 and 60 years from now, except that the gains
were concentrated among the students, at all age groups, who entered
school in the period between 1968 and 1980. Students entering prior to
that period and after that period showed no gains. It would take us far
afield to discuss why the gains occurred when they did, but the main
relevance is that the old estimate of 1 standard deviation in ability
scores no longer applies. The gap is substantially less than that at the
present time, probably more like 0.6-0.7 standard deviation or
approximately 10 IQ points.
The Effects of Intervention
A second misrepresentation by Rushton and Jensen (2005) flows from their
statement that the Head Start program leads only to immediate and not to
long-term gains. Because no other early childhood intervention programs
are mentioned, the implication is that such programs are not effective
over the long run. But in fact, more ambitious interventions produce
very significant gains that last as long as until age 15, the oldest age
tested to this point to my knowledge (S. L. Ramey & Ramey, 1999). For
example, Campbell and Ramey (1994) provided Black infants with an 8-hr
per day intervention involving exercises designed to enhance cognitive,
language, perceptual-motor, and social development. Mothers of the
children had an average IQ of 85. At age 12, 56% of control children had
IQs in the normal range (above 85), about what would be expected based
on the mothers' IQ and assuming that the fathers' IQ was in the same
vicinity. But 87% of children exposed to the intervention had IQs in the
normal range. Only 13% of intervention-exposed children were of
borderline IQ, and none were even mildly retarded. In contrast, 37% of
control children were of borderline intelligence, and 7% were at least
mildly retarded.
Other early intervention programs have shown IQ effects of intervention
programs in the range of 4-5 points, which are sustained until at least
age 8-15 (e.g., S. L. Ramey & Ramey, 1999 ). Effects on academic
achievement can also be substantial. Ramey and his colleagues found an
intervention program resulted in 12% placement in special education
classes at some point by the age of 15 as compared with 48% for control
children (C. T. Ramey et al., 2000 ). They found that 30% of children
who had participated in an intervention program had been retained in a
grade by age 15 as compared with 56% of control children. By now, there
are many studies showing significant, sometimes marked and sustained,
effects of early intervention programs. But Rushton and Jensen (2005)
choose to cite only one failure, and by implication to allow it to stand
as the only relevant finding.
It should also be noted that it is not merely early intervention that
increases IQ and school achievement. Programs at every age level from
infancy to college can be effective (Bennett, 1987; Herrnstein,
Nickerson, De Sanchez, & Swets, 1986; Selvin, 1992; Steele et al., 2004;
Treisman, 1992 ). There is thus very good reason to believe that steps
can be taken-some not terribly expensive-to improve test and academic
performance of Blacks.
Direct Tests of Heritability of the Black-White IQ Difference
Most important, Rushton and Jensen (2005) ignore or misrepresent a large
literature dealing with the most direct sort of evidence, which relates
to the influence of European ancestry on Black intelligence. U.S.
"Black" populations contain as much as 30% European genes. This means
that an individual who is identified as Black could have anywhere from
100% African ancestry to mostly European ancestry (true of as much as
15% of some U.S "Black" subpopulations; Herskovits, 1930 ). This allows
us to identify the extent to which percentage African ancestry,
variously assessed, is associated with IQ. Five different types of
studies allow for an estimation of the effect of relatively African
versus relatively European genes on IQ. I report these below in
increasing order of what I take to be their probativeness.
Skin Color
There are numerous studies of the association between skin color and IQ.
Skin color can be used as at least a weak proxy for racial admixture. We
can ask whether lighter, presumably more European, skin is associated
with higher IQ. Of course, if it were, this would constitute only modest
support for the genetic hypothesis because there would be valid grounds
for assuming that more social and economic advantages accrued to people
with relatively light skin than to people with relatively dark skin and
that these advantages would be reflected in higher IQs. In fact,
however, the correlation between lightness of skin and IQ, averaged over
a large number of studies reviewed by Shuey (1966), is in the vicinity
of .10. The average correlation between IQ and judged "Negroidness" of
features is even lower.
Self-Reports of European Ancestry
Another way to determine the genetic origins of the Black-White
difference is to examine the tails of the distribution of Black IQ. We
can ask whether Blacks having a significant degree of European heritage
are more likely to have high IQ scores. The extreme high-end tail of the
IQ distribution should be especially telling, because on the
hereditarian theory one would expect people at the tail to be
particularly likely to have substantial European ancestry. Jenkins
(1936) identified 63 children in a sample of Black Chicago
schoolchildren with IQs of 125 or above, and 28 with IQs of 140 or
above. Degree of European ancestry was assessed on the basis of
self-reports about parents and grandparents. Children with IQs of 125 or
above, as well as those with IQs of 140 or above, were slightly less
likely to have substantial European ancestry than was estimated to be
characteristic of the U.S. Black population as a whole at the time. The
results are consistent with a model of zero genetic contribution to the
Black-White gap. Rushton and Jensen do not mention this study.
Children in Postwar Germany Born to Black and White American Soldiers
Eyferth (1961) examined the IQs of several hundred German children
fathered by Black GIs during the post-1945 occupation and compared them
with the IQs of children fathered by White GIs. The children of the
Black GIs had an average IQ of 96.5. The children of the White GIs had
an average IQ of 97. Because the (phenotypic) Black-White gap in the
military was similar to that for the U.S. population, these data imply
that the Black-White gap in the U.S. population as a whole is not
genetic, even in part (Flynn, 1980 , pp. 87-88). The results seem
particularly telling because it seems highly likely that environmental
conditions were inferior for Black children.
How do Rushton and Jensen (2005) treat this study, so telling on the
face of it? They give it only two sentences of description and then
proceed to critique it on two main grounds. First, 20% to 25% of the
"Black" fathers were North African. But one would have to assume
preposterously high IQ scores on the part of the North African portion
of the Black population to make up for the substantial difference
between offspring of Blacks and Whites predicted by their hereditarian
theory. Second, Rushton and Jensen assume that Black soldiers were more
rigorously selected than Whites and so might have had IQs nearly as high
as those of the White soldiers. Blacks in the military did indeed have
higher IQs than did Blacks in the general population, but the same was
true of White soldiers compared with the general White population. Flynn
(1980) has argued that the evidence indicates that the gap in IQ between
Black and White soldiers was the same as that in the U.S. population at
large.
Mixed-Race Children Born to Either a Black or a White Mother
If the Black-White IQ gap is largely hereditary, then children having
one Black and one White parent should have the same IQ on average,
regardless of which parent is Black. But if one assumes that mothers are
particularly important to the intellectual socialization of their
children and if the socialization practices of Whites are more favorable
to IQ development than those of Black mothers, then children of White
mothers and Black fathers should have higher IQs than children of Black
mothers and White fathers. This could of course not have a plausible
genetic explanation. In fact, it emerges that children of White mothers
and Black fathers have IQs 9 points higher than children with Black
mothers and White fathers (Willerman, Naylor, & Myrianthopoulos, 1974 ).
This result in itself suggests that most of the Black-White IQ gap is
environmental in origin. But because mothers are not the only
environmental influence on the child's IQ, the 9-point difference might
be regarded as a very conservative estimate of the environmental
contribution to the gap.
What do Rushton and Jensen (2005) have to say about this study? Because
the White mother-Black father pairs averaged 1 year more of education
than the Black mother-White father pairs, they conclude the study is
uninterpretable! Of course, there can be no basis for assuming that
1-year's difference in education on the part of the parents could
possibly translate into an expected 9 IQ point difference for the
children.
Studies Measuring European Ancestry Through Blood Group Indicators
Different races have different frequencies of various blood groups. If
the hereditarian model is correct, Blacks having more blood groups
characteristic of Europeans should have higher IQs. But Sandra Scarr and
her colleagues (Scarr, Pakstis, Katz, & Barker, 1977 ) found that the
correlation between IQ and "European" heritage among Blacks as measured
by blood groups was only .05 in a sample of 144 Black adolescent twin
pairs. They found a typical correlation of .15 between skin color and
IQ, which suggests that the comparable correlations between skin color
and IQ in other studies are due not to more European genes on the part
of light-skinned Blacks but to social and economic advantages accruing
to individuals with lighter skin.
Another blood-group study, by Loehlin, Vandenberg, and Osborne (1973),
also examined the association between Europeanness and IQ in a sample of
Blacks. In this study, the estimated Europeanness of blood groups
(rather than the Europeanness of individuals, estimated from their blood
groups) was correlated with IQ in two small samples of Blacks (Loehlin
et al., 1973 ). A .01 correlation between IQ and the extent to which
blood group genes were more characteristic of European than African
populations was found. In another small sample, they found a
nonsignificant, -.38 correlation, such that blood groups associated with
Europeanness predicted lower IQ scores.
How do Rushton and Jensen (2005) deal with these data, so apparently
damning of an even partially hereditary model? They report that "these
studies failed to choose genetic markers with large allele frequency
differences between Africans and Europeans" (p. 262). Of course, on the
hereditarian hypothesis, the markers would have to have been worthless
to yield a zero difference between the populations studied.
Rushton and Jensen (2005) add only a few studies to the list above
concerned with racial admixture, and those have extremely weak findings,
poor methodology, tangential relevance, or a combination of the three.
For example, they cite one study by Lynn (2002) , which found a
correlation of .17 between self-report of skin color as "very dark,"
"dark brown," "light brown," or "very light" and a 10-word vocabulary
test score. Another study, by Rowe (2002) , is merely yet another
showing that Blacks have lower IQ scores than Whites. Still other
studies ask us to believe that average IQ scores of 70 (in the retarded
range) for samples of Africans and for the Black children in a
particular Georgia county could possibly be an accurate reflection of
genotypic IQ in pure African populations. This would mean that an
individual 2 standard deviations from the mean would only manage to
reach an IQ of 100, which is average for Western White populations.
Rushton and Jensen (2005) end the empirical part of their article with a
scorecard. The scorecard results: hereditarian model (+); culture-only
model (0). But any sensible reading of the directly relevant research
would have to conclude that there is no support whatever in these
studies for an even partially hereditarian model. On the contrary, the
converging methodologies provide strong evidence that the genetic
contribution to the Black-White IQ gap is close to zero and do not even
suggest a direction for any possible genetic contribution.
Adoption Studies
There are three major adoption studies that address the question of
genetic contribution to the Black-White IQ difference. The first two
reported below receive one sentence each of description from Rushton and
Jensen (2005); the third receives seven paragraphs.
Assignment of Black Adoptees to Families of Different Races
Under the hereditarian model, it should make relatively little
difference whether Black children are adopted by Black families or by
White families. Under an environmental model that assumes that White
families are especially likely to intervene in their children's
socialization in ways that result in their having high IQs, it should
make a substantial difference whether the Black child is raised with a
Black or White family. And in fact, it does. Moore (1986) found that
Black children raised by Black middle-class families had mean IQs of
104, whereas Black children raised by White middle-class families had
mean IQs of 117.
Though it is possible that self-selection of some kind might have
operated to produce this difference, it could only have happened if
genotypically less intelligent children were more likely to be assigned
to the Black families than to the White families. But there is no reason
to assume that this was the case, or at least that it could possibly
account for the results by itself. It seems extraordinarily unlikely
that adoption agencies could have engineered IQ differences in placement
on the order of 13 points.
Moore's (1986) study also provides some evidence about socialization for
intelligence. White mothers were more supportive of their children's
intellectual explorations and more forgiving of mistakes than were Black
mothers, who tended to be highly critical.
Assignment of Black and White Adoptees to the Same Environment
Tizard, Cooperman, and Tizard (1972) studied Black and White children
assigned to a highly enriched institutional environment. At age 4 or 5,
the White children had IQs of 103, the Black children IQs of 108, and
mixed-race children IQs of 106. The Black children were West Indian and
the White children were English, and though it is possible that the
Black children were born to more intelligent parents than the White
children, Flynn (1980) has argued that the difference could have been
only enough to eradicate the Black advantage in IQ score, not to turn
the advantage to the Black children.
Assignment of Black and White Adoptees to Different White Families
The study to which Rushton and Jensen (2005) allocate so much space is
the single adoption study that provides any support whatever to the
hereditarian position. This is a study by Scarr and Weinberg (1976;
Weinberg, Scarr, & Waldman, 1992 ), which examined adoptees into White
families who had two White biological parents, two Black biological
parents, or one Black and one White parent. The study is more difficult
to interpret than the other two, one of which assigns Black children,
who were probably equivalent in expected IQ, to either Black or White
middle-class families and the other of which assigns both Black and
White children to the same environment. The Scarr and Weinberg study
held neither race nor expected IQ nor adoptive setting constant. An
additional problem with the Scarr and Weinberg study is that the Black
children were adopted at a later age than the others, which would prompt
an assumption of lower initial IQ for them. In addition, the Black
children's mothers had lower educational levels than did those of the
other two groups, which also would prompt an assumption of lower initial
IQ. Finally, the "quality of placement" was higher for White children
than for other children. All of these facts combined mean that it is not
possible to know what to predict under either a hereditarian model or a
pure environmental model.
The average IQ of the White children at age 7 to 8 years was 112, that
of mixed-race children 109, and that of Black children 97. The results
are consistent with the assumption that the middle-class family
environment resulted in a substantial gain in IQ for all groups. They do
not rule out a genetic contribution to explain the gap because the Black
children had lower IQs than those of either of the other two groups.
Because of the likelihood that the Black children had lower IQs to begin
with, for both genetic and nongenetic reasons, however, the results do
not give strong support to the hereditarian model. At age 17 the White
children had IQs (as measured by another test) of 106, the mixed-race
children 99, and the Black children 89. These results are not materially
different, in terms of size of the gap, from those at age 7 to 8. The
Black children at the earlier point had IQs 15 points lower than those
of the White children and at the later point had IQs 17 points lower.
The gap was 3 points at age 7 to 8 between White children and mixed-race
children and 7 points at age 17.
Rushton and Jensen (2005) , however, wish to emphasize the relative
difference at the two ages. Because the genetic influence on IQ asserts
itself progressively over the life span, they maintain that the greater
gap at the later age is reflective of a genetic contribution to the gap.
In fact, Rushton and Jensen give as one of their main reasons for
reviewing the Scarr and Weinberg study in such depth is that it
continues out to the older ages (the other two reasons being that it is
the "largest" and "best-known"). There are several flaws with the
developmental argument. First, the relative magnitude of differences at
the two ages are slight, and second, and more important, the life span
data that Rushton and Jensen themselves cite do not support the claim
that more of the IQ variance at age 17 is genetically driven than at
earlier ages. Evidence of a greater genetic contribution to IQ occurs
only after the age of 20 (see their Figure 3). Finally, Weinberg et al.
(1992) noted that the scores of the adolescent Black and mixed-race
children have to be interpreted in light of the fact that these children
as a group had severe adjustment problems, a fact that Rushton and
Jensen do not mention.
The Scarr and Weinberg study thus provides nothing more definite than
the likelihood that middle-class environments raise the IQs of children
of all racial combinations. Many aspects of design weakness have to be
overlooked to infer any support at all for the hereditarian model.
How do Rushton and Jensen (2005) assess the adoption results across the
two studies showing unambiguous lack of support for the hereditarian
model and the one study showing at most ambiguous support for it? Their
scorecard results: hereditarian model (++); culture-only model (-)!
The rest of Rushton and Jensen's (2005) article consists of reports of
brain size and reaction time correlates and other indirect evidence. If
the direct evidence were not so strongly supportive of a purely
environmental explanation of the Black-White difference in IQ, then such
findings would have relevance to an understanding of the difference. But
when direct evidence points so clearly to the conclusion that there is
no hereditary basis for the difference, indirect correlational evidence
has little meaning.
Conclusion
In short, Rushton and Jensen (2005) ride roughshod over the evidence
concerning the question of whether the Black-White IQ gap has a
hereditary basis. The most directly relevant research concerns degree of
European ancestry in the Black population. There is not a shred of
evidence in this literature, which draws on studies having a total of
five very different designs, that the gap has a genetic basis. Adoption
studies give scarcely more support to the heritability position.
Finally, Black and White IQ scores have converged in recent decades, and
in addition, we know that intervention programs can produce substantial
and lasting effects on Black IQ. The most obvious policy relevance of
this set of findings is that at-risk children--those born to
impoverished women, especially those likely to be unable to provide a
stimulating environment, and in particular children who have low birth
weight or other factors predisposing to low IQ--should be exposed to the
most extensive intervention programs that it is practical to provide.
This group happens to include a disproportionate percentage of Black
infants, but race need not, and perhaps should not, be made a criterion
for inclusion.
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language development: A study of young children in long-stay residential
nurseries. Child Development, 43, 342-343. [Context Link]
Treisman, U. (1992). Studying students studying calculus: A look at the
lives of minority mathematics students in college. College Mathematics
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Weinberg, R. A., Scarr, S., & Waldman, I. D. (1992). The Minnesota
Transracial Adoption Study: A follow-up of IQ test performance at
adolescence. Intelligence, 16, 117-135. [Context Link]
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Performance in infancy and at 4 years. Behavior Genetics, 4, 84-88.
--------------------
Psychology, Public Policy, and Law
Volume 11(2) June 2005 p 311-319
WHAT IF THE HEREDITARIAN HYPOTHESIS IS TRUE?
Gottfredson, Linda S.1,2
1School of Education, University of Delaware
2 Correspondence concerning this article should be addressed to Linda S.
Gottfredson, School of Education, University of Delaware, Newark, DE
19716. E-mail: gottfred at udel.edu
Outline
* Abstract
* The Hereditarian Hypothesis: What Is It?
* Scientific Foundations of the Hereditarian Hypothesis: How Sound?
* Rushton and Jensen's 10 Bodies of Evidence: How Pertinent? How
Complete?
* Contrasting Predictions
* Additional Evidence
* The Totality of Available Evidence: How Compelling?
* Replication
* Consilience
* The g-based hereditarian theory
* The culture-only theory
* Rushton and Jensen's Policy Recommendations: Are They Warranted?
* Does the Hereditarian Hypothesis Leave Us Without Hope?
* References
J. P. Rushton and A. R. Jensen (2005) review 10 bodies of evidence to
support their argument that the long-standing, worldwide Black-White
average differences in cognitive ability are more plausibly explained by
their hereditarian (50% genetic causation) theory than by culture-only
(0% genetic causation) theory. This commentary evaluates the relevance
of their evidence, the overall strength of their case, the implications
they draw for public policy, and the suggestion by some scholars that
the nation is best served by telling benevolent lies about race and
intelligence.
Rushton and Jensen (2005) review the last 30 years of evidence on an
important but spurned question: Is the average Black-White difference in
phenotypic intelligence partly genetic in origin? Much relevant
scientific evidence has accumulated since Jensen first asked the
question in 1969, but openly addressing it still seems as politically
unacceptable today as it was then. Taking the question seriously raises
the possibility that the answer might be yes, which for some people is
unthinkable. It is therefore no surprise that such research and
researchers are often evaluated first against moral criteria and only
secondarily, if at all, against scientific ones. My commentary therefore
examines the Rushton-Jensen article against both the scientific and
moral criteria typically applied to such work.
The Hereditarian Hypothesis: What Is It?
Rushton and Jensen's (2005) hereditarian hypothesis is that Black-White
differences in general intelligence (IQ, or the general mental ability
factor, g ) are "substantially" genetic in origin, which they quantify
as 50% genetic and 50% environmental. They specify 50% genetic because
they hypothesize that race differences are simply aggregated individual
differences and because researchers commonly summarize within-group IQ
heritability as 50%. Rushton and Jensen do not attempt to prove
conclusively a genetic component but to show that their hypothesis is
more plausible than the culture-only hypothesis long favored by social
scientists, which entails 0% genetic and 100% environmental causation.
Scientific Foundations of the Hereditarian Hypothesis: How Sound?
The hereditarian hypothesis becomes scientifically plausible only after
five evidentiary prerequisites have been met: IQ differences among
same-race individuals represent (a) real, (b) functionally important,
and (c) substantially genetic differences in general intelligence (the g
factor), and mean IQ differences between the races likewise reflect (d)
real and (e) functionally important differences on the same g factor. A
century of research strongly supports all five. It has provided a vast,
interlocking network of evidence that g is the backbone of all broad
mental abilities in all age, race, sex, and national groups studied to
date; that higher levels of g confer practical advantages in many realms
of life; that within-group variability in phenotypic g has strong
genetic roots and many physiological correlates in the brain; and that
between-groups differences in g are large and pervasive enough to have
broad social significance (e.g., see the journal Intelligence; Brody,
1992; Deary, 2000; Gottfredson, 1997; Hartigan & Wigdor, 1989; Lubinski,
2004).
This is hardly the picture of intelligence research that the media and
many social scientists paint (e.g., Fish, 2002 ). Both often suggest
that the entire area of measurement of mental abilities, psychometrics,
is fundamentally flawed and morally suspect. As Snyderman and Rothman
(1988) demonstrated almost two decades ago, however, media portrayals of
accepted wisdom on intelligence tend to be the opposite of what experts
have actually concluded (e.g., Carroll, 1997 ). Thus, despite public
lore to the contrary, there is already a deep and vast nomological
network of evidence that can be called g theory.
Rushton and Jensen's 10 Bodies of Evidence: How Pertinent? How Complete?
The most general difference between g theory and culture-only theory is
that the former sees both individual and group differences in g as
embedded substantially in biology, whereas the latter theory looks only
to culture, at least when it involves race.
Contrasting Predictions
First, although both theories predict ubiquitous race differences in
observed abilities, g theory predicts that the gaps between any two
particular races will be similar over time and place regardless of
cultural circumstances (unless frequency of interbreeding changes
markedly). Culture-only theory predicts that the gaps will expand or
contract depending on similarity in cultural environments, regardless of
genetic heritage. The uniformity of the IQ gaps between African Blacks,
American Blacks, Whites, and East Asians over time and place (Rushton &
Jensen, 2005 , Section 3) and the parallel ordering of race differences
on simple reaction/inspection time tests in the United States and
elsewhere (Section 4) are both consistent with g theory. Contradicting
culture-only theory, the IQ gaps fail to shift in tandem with cultural
variation. Both theories can explain the Black-White IQ gaps seen in
studies of transracial adoption (Section 7) and racial admixture
(Section 8). However, the above-average mean IQ of even severely
malnourished East Asian infants adopted into White European homes is
more consistent with those infants having a genetic than a cultural
advantage over their White European peers.
Second, unlike culture-only theory, g theory predicts that IQ
differences will correlate with variation in "hardwired" aspects of
brain structure and function. Therefore, only g theory can account for
the nexus of correlations among the following outcomes: the g loadedness
of IQ and reaction time tests (their ability to measure g ); the tests'
heritability and susceptibility to inbreeding depression;
Black-White-East Asian mean differences in performance on them; and the
correlations of various physiological traits (brain size, evoked
potentials in the brain, brain pH levels, and brain glucose metabolism)
with IQ and reaction time (Sections 4 and 6).
Third, the two theories predict different degrees of change in
individuals' IQs when their socioeducational environments change
substantially: g theory predicts little or no lasting change, but
culture-only theory predicts relative responsiveness. Jensen's 1969
conclusion about the failure of socioeducational interventions to raise
low IQs substantially and permanently still stands (Section 12). Natural
variation in environments likewise fails to alter the common
developmental processes by which abilities are assembled in different
races. This commonality in cognitive architecture is indicated, for
instance, by cross-race identity of g factors and input-output
achievement covariance matrices (Section 5). This commonality also
contradicts predictions that different cultures create different
intelligences.
Additional Evidence
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Rushton and Jensen (2005) do not discuss one body of evidence that many
social scientists believe undermines the hereditarian hypothesis: a
narrowing of Black-White gaps in standardized reading achievement on the
National Assessment of Educational Progress (NAEP), which critics see as
a narrowing (if not the irrelevance) of the IQ gap (e.g., chapters in
Jencks & Phillips, 1998). Recent analyses (Gottfredson, in press) show
the critics to be mistaken.
First, nationally representative data on racial and ethnic IQ
differences during the 20th century provide no evidence that the IQ gap
has narrowed. Standardized effect sizes were 1.0 ± 0.2 for both children
and adults and for all ages and decades, averaging 1.02 across 20
samples.
Second, Black-White achievement gaps in the 1971-1999 NAEP Trend Series
were no larger or smaller than g theory would predict. The maximum
expected is 1.20 standard deviation (the size of the Black-White g gap
itself), and the minimum is 0.80 ± 0.04 standard deviation (1.20
multiplied by the IQ-achievement correlations in core subjects). NAEP
gaps narrowed from 1.07 standard deviation in the 1970s to 0.89 in the
1990s when averaged over all three subjects and ages. Degree of
narrowing stalled by the mid-1980s and differed by subject: 25% in
reading (1.06-0.79), 20% in math (1.07-0.87), and 15% in science
(1.22-1.04). As of 1999, all gaps for 9-, 13-, and 17-year-old students
were still near or above the minimum expected (reading--0.80, 0.73,
0.73; math--0.82, 0.93, 1.06; and science--0.97, 1.06, 1.07).
The Totality of Available Evidence: How Compelling?
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Which theory explains the totality of evidence more consistently and
coherently?
Replication <http://gateway.ut.ovid.com/rel_live/server1/gifs/ftup.gif>
The following major facts from Rushton and Jensen's (2005) Sections 3-6
and 10-12 have been replicated many times, and all with independent
sources of data. All are consistent with hereditarian theory but
contradict culture-only theory:
* Worldwide Black-White-East Asian differences in IQ (Section 3),
reaction time (Section 4), and brain size, with Whites having the
intermediate scores (Section 6);
* An inverse correlation between the foregoing race differences in brain
attributes and Black-White-East Asian differences in body maturation
(Section 6);
* Small (.2) and moderate (.4) correlations of IQ, respectively, with
skull size and in vivo brain volume (Section 6);
* A moderately high correlation (usually.6-.7) of different IQ subtests'
g loadings, not only with the magnitude of Black-White-East Asian mean
differences on those subtests (Section 6) but also with measures of
those subtests' rootedness in biological and genetic processes (e.g.,
heritability; Section 4);
* The rising heritability of IQ with age (within races) and the virtual
disappearance by adolescence of any shared environmental effects on IQ
(e.g., parental income, education, child-rearing practices; Section 5);
* Worldwide Black-White-East Asian mean differences in a large suite of
biological variables (e.g., twinning, gestation time, sex ratio at
birth) and social variables (e.g., law abidingness, marital stability),
with the three races always in the same rank order (Section 10);
* A genetic divergence (quantitative, not qualitative) of world
population (i.e., racial) groups during evolution (Section 11); and
* Evidence contradicting the culture-only theory's prediction that group
differences in cognitive ability should, in essence, track group
differences in identifiable cultural practices and socioeconomic
advantage (Section 12).
The threads of supporting evidence in Sections 5 (race-common mental
architecture) and 9 (regression to the mean) tend to be less well
replicated. The most direct individual tests of genetic versus
environmental effects on mental ability--transracial adoption (Section
7), racial admixture (Section 8), and behavior genetic modeling of mean
group differences (Section 5)--have either been uncommon or fraught with
ambiguity. They clearly need to be replicated, as Rushton and Jensen
(2005) suggest. Being the most direct tests of the hereditarian
hypothesis, however, they are also the most politically sensitive to
conduct and thus the least likely to be replicated. The more anomalous
findings either require replication (e.g., training helped narrow Black
African-White gaps on the Raven Matrices in some South African samples)
or constitute a paradox for both theories (the Flynn effect).
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The g-based hereditarian theory connects g -related phenomena at the
genetic, physiological, psychometric, and socioeconomic levels to form a
coherent pattern that yields novel predictions subsequently confirmed;
it is consilient. In contrast, culture-only theory has become
increasingly tattered over time, patched over by disconnected ad hoc
speculation.
The g-based hereditarian theory
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Beginning at the psychometric level, g theory has successfully predicted
not only when Black-White IQ differences will remain the same in
magnitude but also when they will differ markedly. First the predicted
uniformity: Black-White differences are essentially the same in the West
(about 1 standard deviation) across decade, age, and country, and they
are not substantially or permanently changed by interventions intended
to do so (the point of Jensen's 1969 article). This uniformity of gaps
extends to three-way comparisons among Blacks, Whites, and East Asians,
with East Asians outscoring Whites. Additionally, there is growing
evidence for a four-way contrast, with a 1-standard deviation IQ
difference--85 versus 70--always favoring Western Blacks (who average
around 20% White admixture) over Black Africans. Regarding differences
in gaps for a given race, g theory successfully predicts that gaps are
successively larger on more g -loaded tests and among children in higher
social classes (in which there is more regression to the mean). The gaps
thus contract and expand according to shifts in--not culture--but the
cognitive demands of the tasks and individuals' genetic relatedness.
Next, this systematic patterning of Black-White-East Asian differences
in performance can be traced downward from complex IQ tests, to quite
elementary cognitive tasks, then to biological processes. So far, the
three-way race pattern for IQ/g differences has been replicated with
reaction/inspection time and brain size, both of which are highly
heritable and correlated with g, as well as with a large collection of
purely physical attributes (e.g., twinning). The g factor is highly
heritable within races and also has replicated metabolic, electrical,
and structural correlates in the brain, most of them also known to be
heritable (these studies are mostly with Whites).
Although Rushton and Jensen (2005) do not discuss the fact, the nexus of
results for g also extends outward into the social realm. For instance,
the g factor (indeed, the entire hierarchical structure of mental
abilities; Gottfredson, in press) is the same in all races at all ages
yet studied. The most g -loaded tests predict school and job performance
best, and they predict performance equally well for Blacks and Whites in
both the United States and South Africa. These findings have been
replicated, but in fewer studies, for other racial and ethnic groups.
The g nexus goes full circle, from the social back to the genetic,
because major life outcomes such as level of earnings, occupation, and
education are also moderately heritable (respectively, about 40%-50%,
50%, and 60%-70%), with half to two thirds of their heritability being
joint with g (see Gottfredson, 2002, for a review; studies limited so
far to European Whites).
The culture-only theory
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One might be able to interpret many of the individual threads of
evidence differently, but it is not clear how culture-only theory could
coherently reinterpret the entire interconnected web of evidence. In
fact, culture-only theory is notable for retreating from its previous
failed explanations into ever-less plausible ones. For example, an early
claim, plausible at the time, was that Blacks' mental abilities are
underestimated because mental tests are biased against them. Research
disconfirmed that claim decades ago. Although some culture-only
theorists have never relinquished that belief, others began to press
more vigorously the claim that any confirmed cognitive deficits among
Blacks result from Blacks having suffered more than Whites from
deleterious, IQ-depressing cultural conditions.
However, no such factors have been identified in genetically sensitive
research. Virtually all social science claims that parental rearing and
socioeconomic resources influence IQ rest on studies that confound
genetic and nongenetic influences (Scarr, 1997 ). In fact, behavior
genetic research suggests that relatively little, if any, of the Western
Black-White difference in mature IQ could be due to the shared family
factors that the culture-only theory has long presumed important (e.g.,
poverty, parents' education). In studies that include a broad range of
family environments in Western nations, variation in such shared family
factors does not create permanent within-race differences in IQ. This
does not rule out the possibility that extraordinarily deleterious
shared family environments permanently depress IQ, but relatively few
children of any race in the West experience such extremes. As the
studies of malnourished East Asian adoptees illustrate, extreme
deprivation of the sort that humans have always had to contend with
(e.g., starvation, infectious disease) seldom permanently impairs
cognitive ability to any substantial degree once conditions are
rectified.
The failure of socioeconomic resources and parenting behavior to have
the influence long claimed for them led culture-only theorists to begin
stressing more subtle and more race-specific psychological factors as
the root cause of group differences in cognitive performance. Examples
include racism-depressed motivation, racial stress, race-based
performance anxiety ("stereotype threat"), and low self-esteem. All are
generally posited to result in some manner from White racism and to
disadvantage Blacks at all socioeconomic levels. However, there is no
evidence that any of the factors causes either short- or long-term
declines in actual cognitive ability. Not all of them (e.g.,
self-esteem) are lower for Blacks, and none can begin to explain the
large array of relevant nonpsychological facts, including why the races
also differ in brain size and speed (in milliseconds) of performing
exceedingly simple cognitive tasks, such as recognizing which of several
buttons on a console has been illuminated (a reaction time task).
Because the American Black-White IQ gap has not narrowed since it was
first measured in the early 1900s, the psychic injury must also be just
as deleterious now as it was during that earlier, more hostile era for
Blacks. This seems implausible. Thus, while the proposed psychic insults
may temporarily mend some rips in the culture-only theory, they would
seem to hold even less promise than the failed socioeconomic ones for
explaining the long-standing, worldwide pattern of racial IQ differences
and their links to the biological correlates of g. The newly popular
assertion that races "don't exist" is a straw man (no one believes that
racial groups are biologically distinct entities), which does nothing to
nullify the evidence it would have us ignore.
In summary, Rushton and Jensen (2005) have presented a compelling case
that their 50%-50% hereditarian hypothesis is more plausible than the
culture-only hypothesis. In fact, the evidence is so consistent and so
quantitatively uniform that the truth may lie closer to 70%-80% genetic,
which is the within-race heritability for adults in the West. The case
for culture-only theory is so weak by comparison--so degenerated--that
the burden of proof now shifts to its proponents to identify and
replicate even one substantial, demonstrably nongenetic influence on the
Black-White mean difference in g . Any such demonstration must be with
genetically sensitive research because most "environments" are partly
genetic in origin (different genotypes create and evoke different
environments for themselves and their children; Scarr, 1997).
Rushton and Jensen's Policy Recommendations: Are They Warranted?
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Rushton and Jensen (2005) make no recommendations for specific policies
and correctly argue that the hereditarian hypothesis implies none in
particular. For example, proof that the Black-White IQ gap is partly
genetic could, depending on one's goals, be used to justify banning all
racial preferences in employment and college admissions or, from a
Rawlsian perspective (that genetic advantages are undeserved and
unfair), require substantial and permanent racial preferences.
As Rushton and Jensen (2005) suggest, g theory can predict fairly
accurately how large the racial disparities in achievement will be in
different settings, depending on their demands for g and the IQ
distributions of the groups involved. It can also provide the menu of
tradeoffs between racial parity and aggregate levels of performance
under different scenarios for selecting individuals into those settings,
and also predict the likely pattern of effects and side effects, by
race, of different interventions in education and training (e.g.,
Sackett, Schmitt, Ellingson, & Kabin, 2001). In short, g theory can
detail the challenge before us, and the likely costs and benefits of
opting for different goals or means of achieving them.
Currently, racial parity in outcomes is often treated as the ultimate
standard for fairness and lack of parity as a measure of White racism.
For instance, disparate impact in hiring is prima facie evidence of
illegal discrimination in the United States, with employers, if sued,
then needing to prove themselves innocent. By undermining culture-only
explanations of racial inequality, the "provisional truth" of Rushton
and Jensen's (2005) hereditarian hypothesis thereby undermines the moral
legitimacy of all rationales for racial equalization that posit White
misbehavior as its cause. That it might persuade the public to temper or
abandon its efforts to close all racial gaps in success and well-being
is surely what inflames critics most.
Rushton and Jensen (2005) themselves acknowledge that open discussion of
genotypic ability differences between the races might harm race
relations. Their most vocal critics predict far worse. Widespread
acceptance of the hereditarian hypothesis would, they say, put us on the
slippery slope to racial oppression or genocide. They do not explain how
this would happen but usually imply that because the Nazis were
hereditarians, hereditarians must be Nazis at heart. But we can no more
presume this than that IQ-environmentalists are Communists because the
Communists were IQ-environmentalists. One might note, in addition, that
regimes with environmentalist ideologies (Stalin and Pol Pot)
exterminated as many of their citizens as did the Nazis, and virtually
all the victim groups of genocide in the 20th century had relatively
high average levels of achievement (e.g., German Jews, educated
Cambodians, Russian Kulaks, Armenians in Turkey, Ibos in Nigeria). The
critics' predictions of mass moral madness, like their frequent
demonization of scientists who report unwelcome racial differences, seem
mostly an attempt to stifle reasoned discussion.
But might society be better off not knowing that races differ in g,
whether genetic or not? As Glazer (1994, p. 16) asked, "For this kind of
truth, ... what good will come of it?" Summing up his argument against
candor, he stated:
Our society, our polity, our elites, according to Herrnstein and Murray,
live with an untruth: that there is no good reason for this [racial]
inequality, and therefore society is at fault and we must try harder. I
ask myself whether the untruth is not better for American society than
the truth. (Glazer, 1994, p. 16)
But we must also ask, What harm might the untruth cause? Should we
really presume that denying the existence of average racial differences
in g has only benefits and the truth only costs? Lying about the
enduring Black-White difference in phenotypic g would seem to be both
futile and harmful in the long run. It is futile because the truth--and
attempts to suppress it--will become increasingly obvious to the average
person. Phenotypic differences in cognitive ability have relentless
real-world effects that are neither ameliorated nor hidden by claims to
the contrary. They also have more obvious effects in more cognitively
demanding settings, such as high-level jobs and educational programs,
and when entry standards differ by race.
Lying about race differences in achievement is harmful because it
foments mutual recrimination. Because the untruth insists that
differences cannot be natural, they must be artificial, manmade,
manufactured. Someone must be at fault. Someone must be refusing to do
the right thing. It therefore sustains unwarranted, divisive, and
ever-escalating mutual accusations of moral culpability, such as Whites
are racist and Blacks are lazy.
Does the Hereditarian Hypothesis Leave Us Without Hope?
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Given what we know about g's nature and practical importance,
Black-White genetic differences in g render the goal of full parity in
either IQ or achievement unrealistic. This does not rule out the
possibility of reducing the disparities, especially in achievement, nor
does it provide any reason to "give up" on anyone or conclude that some
people "can't learn." In fact, rather than seeking racial parity in all
outcomes, we might do better by helping lower-IQ individuals of all
races. The weaker learning and problem-solving abilities of people in
the lower part of the IQ distribution make their daily lives much more
difficult and hazardous.
We might especially target individuals below IQ 80 for special support,
intellectual as well as material. This is the cognitive ability
("trainability") level below which federal law prohibits induction into
the American military and below which no civilian jobs in the United
States routinely recruit their workers. It includes about 10% of Whites
and a third of Blacks in the United States and the segment of both
groups most at risk for multiple health and social problems, regardless
of family background and material resources (Gottfredson, 1997, 2002 ).
Moreover, the risks that lower-IQ people face in relation to more able
individuals have been growing as the complexity of work, health care,
and daily life has increased. The g theory suggests that their relative
risk might be lowered if (a) education and training were better targeted
to their learning needs (instruction is more narrowly focused,
nontheoretical, concrete, hands-on, repetitive, personalized, and
requiring no inferences); (b) they were provided more assistance and
direct instruction in matters of daily well-being that we expect most
people acquire on their own (e.g., learning how best to avoid various
kinds of illness and injury); and (c) health care providers, social
service agencies, and other institutions removed some of the unnecessary
complexity (e.g., inadequate or overly complex labeling, instructions,
and forms) that often impedes full and effective use of services,
medical regimens, and preventive care by the less able. Less favorable
genes for g impose constraints on individuals and their helpers, but
they certainly do not prevent us from improving lives in crucial ways.
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Accession Number: 00043965-200506000-00004
----------------------------
Psychology, Public Policy, and Law
Volume 11(2) June 2005 p 320-327
THE CULTURAL MALLEABILITY OF INTELLIGENCE AND ITS IMPACT ON THE
RACIAL/ETHNIC HIERARCHY
Suzuki, Lisa1,2; Aronson, Joshua1
1Department of Applied Psychology, New York University
2 Correspondence concerning this article should be addressed to Lisa
Suzuki, Department of Applied Psychology, New York University, East
Building 239 Greene Street 409, New York, NY 10003. E-mail: las1 at nyu.edu
We would like to thank John Kugler, Leo Wilton, Jacqueline Mattis, and
Muninder Ahluwalia for their feedback on earlier versions of this
commentary.
Outline
* Abstract
* Problematic Assumptions Underlying Definitions
* Intelligence
* Psychometric definition of g
* Full scale IQ (FSIQ), g, and racial/ethnic group
differences
* Genetics and Heritability
* Culture
* Race
* Historical, Contextual, and Testing Issues
* Stereotype Threat
* Effects of Mediated Learning Experiences
* Relative Functionalism
* Test Development Practices
* Implications
* References
Abstract <http://gateway.ut.ovid.com/rel_live/server1/gifs/ftup.gif>
This commentary highlights previous literature focusing on cultural and
environmental explanations for the racial/ethnic group hierarchy of
intelligence. Assumptions underlying definitions of intelligence,
heritability/genetics, culture, and race are noted. Historical,
contextual, and testing issues are clarified. Specific attention is
given to studies supporting stereotype threat, effects of mediated
learning experiences, and relative functionalism. Current test
development practices are critiqued with respect to methods of
validation and item development. Implications of the genetic vs.
culture-only arguments are discussed with respect to the malleability of
IQ.
Rushton and Jensen (2005) review decades of literature to support a
genetic basis for the racial/ethnic group hierarchy in intelligence, a
position they have held unwaveringly for over 30 years. Their report
gives little mention to findings that point to the impact of environment
and race (i.e., race as a social construction) on intellectual
development or performance--what they term the culture-only perspective.
We are not among the culture-only adherents as characterized by Rushton
and Jensen. While acknowledging the impact of biological factors on
intelligence test performance, we have examined the impact of
cultural/environmental factors that affect performance on aptitude and
achievement measures. Our work, and that of others (e.g., Aronson, 2002;
Sternberg, 1996 ), show us that intellectual performance is much more
fragile and malleable than what is often noted in the current
literature. The goals of our commentary are to highlight, briefly,
assumptions underlying definitions (i.e., intelligence, heritability,
genetics, culture, race) and clarify historical, contextual, and testing
issues that were only briefly mentioned by Rushton and Jensen. Finally,
we comment on the heuristic value and on policy implications of the
research.
Problematic Assumptions Underlying Definitions
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Rushton and Jensen's (2005) argument rests on particular definitions of
intelligence, genetics (i.e., heritability), culture, and race. It is,
in part, differences in definitional assumptions that have allowed
researchers to claim support for distinctly different perspectives
(i.e., environment vs. genetics) based on the same data (Hayman, 1998).
Intelligence <http://gateway.ut.ovid.com/rel_live/server1/gifs/ftup.gif>
Numerous theories of intelligence have been framed and reframed over the
years as scholars have ruminated about what constitutes "intelligence."
In this section we highlight a few of the issues that complicate the
linkage between race and IQ as presented by Rushton and Jensen (2005).
As Fagan and Holland (2002) argued, IQ scores represent a composite of
how well one does in comparison with one's peers. Test performance is a
measure of a person's intellectual ability that is dependent on one's
genetic makeup and affected by environment and cultural experiences
(e.g., informal learning and schooling).
Psychometric definition of g
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Although different theories of intelligence have been noted throughout
the literature, intelligence has been defined to a large extent by the
tests designed to measure it. It should be noted that others have
challenged the emphasis on measurement and focused on the processing
component of intelligence (Fagan, 2000 ). The psychometric definition of
intelligence has led to debates about what should constitute the focus
of IQ tests. Some have argued that the measurement of intelligence is
based primarily on the concept of g (general intelligence) and related
subabilities, whereas other researchers have posed that intelligence
should be measured as numerous intelligences of more or less equal
status (e.g., Gardner, 1999). The focus on g has been predominant in the
literature and has proved to be one of the most controversial issues in
psychology with respect to race (Deary, 2000).
As Rushton and Jensen (2005) concede, researchers have challenged the
derivation of g as being a statistical artifact based on factor
analysis. Even Spearman's (1927) early work notes the limitations of g
as "a hypothetical and purely quantitative factor" (p. 5). Rushton and
Jensen cite Spearman's hypothesis indicating that racial group
differences would be largest on g-loaded measures. Though they note that
particular tasks are more "g saturated" than others, the discussion
alludes to g as a unitary construct in relation to various measures of
aptitude. This is clearly not the case, given that standardized IQ tests
measure multiple abilities and therefore have differential loadings in
relationship to g.
In response to accusations that g is a statistical "artifact" of factor
(or principal-components) analysis, others have noted that "it need not
occur. If, in fact, there were mental abilities that were independent of
others they would be uncorrelated and they would not load on g" (Hayman,
1998 , p. 9). While this is true in theory, in practice, new IQ tests
that do not correlate with popular measures currently in existence are
considered to be problematic in terms of validity. It is clear that
among the "best sellers" in the testing domain, the way to validate a
new test is by correlating it with other well-established cognitive
instruments (Valencia & Suzuki, 2001). Based on this practice, it is
unlikely that a measure unrelated to g will emerge as a winner in
current practice. Thus, it is no wonder that the intelligence hierarchy
for different racial/ethnic groups remains consistent across different
measures. The tests are highly correlated among each other and are
similar in item structure and format. In addition, many predictive
validity studies note correlations among IQ, level of education, income,
and socioeconomic status. As noted by White (2000), "these are anything
but independent variables; they are criteria for one another" (p. 40).
Full scale IQ (FSIQ), g, and racial/ethnic group differences
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The FSIQ is the score that is cited as the basis for the racial/ethnic
group hierarchy in intelligence, with a mean of 100 and standard
deviation of 15 (e.g., Wechsler, 1997). As the literature indicates, the
FSIQ is not a pure indicator of g. Subtest g loadings for different
subtests have been found to vary by racial group. Thus, the order of
magnitude for g loadings for Blacks and Whites can be "considerably
unique" (Kaufman, 1990, p. 254). Some may argue that this is
unimportant, because regardless of whether a test is a pure measure of
g, it can still measure something meaningful. Yet given that tests
measure more than just g , the psychometric definition of intelligence
may be challenged and performance on intelligence tests may be more
malleable than assumed in past theories.
Genetics and Heritability
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In support of their genetic arguments, Rushton and Jensen (2005) cite
research documenting results of twin and sibling studies, anatomical
differences (e.g., brain size, brain metabolism), processing speed
differences, as well as other factors that differentiate between racial
groups. However, their either-or method of scoring the evidence between
the genetic versus culture-only data implies a misleading dichotomy
(Deary, 2000 ). There are clear interactions among genetic factors,
anatomical structures, culture, and environment. The importance of
particular interactions may vary depending on an individual's
circumstances and not their racial group membership.
The genetic explanation for the racial/ethnic hierarchy of intelligence
is also based largely on estimates of heritability. Heritability
estimates are based on correlations of traits between biologically
related individuals (Lewontin, Rose, & Kamin, 1984 ). Most often,
correlations are derived from twin and adoption studies. These are
limited given that relatives resemble one another because they share
genetic traits and live in similar environments. In addition, research
on heritability estimates for minority populations is limited, given
small sample sizes and geographic regionalism (Suzuki & Valencia, 1997
). Thus, the complexities of the culture and genetic interactions make
teasing apart the individual contributions of each difficult, if not
impossible.
Culture <http://gateway.ut.ovid.com/rel_live/server1/gifs/ftup.gif>
Over the years, culture has been assigned various definitions. The
complexities and ambiguities of the definition of culture are extensive
and incorporate multiple levels of meaning across generations (Geertz,
1973).
According to Rushton and Jensen (2005) , there are four data sources
that are believed to remove the cultural component in support of the
genetic argument. These include neurological studies (e.g., reaction
time), physiological studies (e.g., anatomical), inheritance studies,
and adoption studies. Limitations in these research bases from a
cultural-environmental perspective have also been noted in the
literature (Hayman, 1998 ) but are not mentioned by Rushton and Jensen.
In particular, the major assumption that differences in culture do not
affect these supposedly culture-free measures is questionable.
Physiological measures in this case are being used to approximate
psychological variables (i.e., intelligence). Evidence supports that
culture affects nearly all psychological phenomena; therefore, it is
entirely possible that biological indicators of intelligence are also
affected.
Race <http://gateway.ut.ovid.com/rel_live/server1/gifs/ftup.gif>
Although Rushton and Jensen (2005) adhere to a biological definition of
race, other theorists such as Loury (2001) have emphasized the important
social underpinnings of this construct. In this view, although race
refers to physical characteristics, the emphasis is placed on the social
meanings or interpretations of these features made in society.
If race is, therefore, as much a social category as a biological one,
then it would follow that race differences in intellectual performance
are not simply mediated by genetics to the exclusion of cultural and
environmental factors. The reality is, "under the skin, there is very
little order to real human genetic variation" (Cohen, 2002, p. 211).
Cohen (2002) noted that of the 15,000 to 20,000 gene pairs that exist,
only 6, or 0.03%, are linked to skin color. In addition, it should be
noted that skin color and other phenotypic markers are only grossly
related to race (Cohen, 2002). Therefore, the associations made by
Rushton and Jensen (2005) between race and IQ are questionable.
A related issue with respect to racial group differences in intelligence
has been the consistent finding that the variance within racial groups
is much greater than that found between racial groups (Valencia &
Suzuki, 2001). "Average group differences in g are simply aggregated
individual differences in g, so the composition of racial group
differences and individual differences are of the same essential nature"
(Jensen, 2000, p. 124). This conclusion, however, has been challenged by
Fagan and Holland (2002) , whose research suggests that the "average
difference of 15 IQ points between Blacks and Whites is not due to the
same genetic and environmental factors, in the same ratio, that account
for differences among individuals within a racial group in IQ" (p. 382).
These results indicate the need to seek further explanations for
intelligence differences and to look beyond racially aggregated
intelligence test data.
Historical, Contextual, and Testing Issues
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Ruston and Jensen (2005) acknowledge in a few sentences the contribution
of other theoretical and empirical work supporting an
environmental-cultural perspective. These include stereotype threat,
mediated learning, and the impact of relative functionalism with respect
to particular marginalized groups.
Stereotype Threat
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Stereotype threat is defined as anxiety regarding one's performance in a
particular domain (e.g., intelligence) based on negative stereotypes
that exist in reference to one's group (e.g., racial/ethnic group;
Aronson, 2002; Steele & Aronson, 1995 ). This anxiety is not related to
the individual's ability but rather to the situation in which a negative
stereotype (e.g., "Blacks are unintelligent") may be confirmed by one's
performance. Evidence for stereotype threat's effects is now abundant.
Numerous studies show that it can depress the standardized test
performances on a variety of groups for whom stereotypes allege inferior
abilities in some domain (see Aronson, 2002, for a review).
Rushton and Jensen (2005) minimize the stereotype threat evidence,
arguing that it cannot account for cases in which Blacks are in the
majority, such as in the sub-Sahara, where despite outnumbering Whites,
Blacks perform less well on IQ tests. This work demonstrates that Blacks
and Whites experience testing situations differently, often in ways that
have a meaningful impact on scores. This effect does not require
numerical minority status. Studies have replicated the stereotype threat
effect even in all-Black colleges (Aronson, 2002 ), so it is certainly
conceivable that sub-Saharan Blacks could be affected. In addition,
Rushton and Jensen ignore the fact that people exist in sociopolitical
contexts that have a profound impact on their experience and worldview.
Sub-Saharan Blacks operate within a context of racism and colonialism
that, in turn, creates and shapes stereotypes. Therefore, when one
applies tests constructed by Whites within one cultural context (i.e.,
American) and then applies them to Blacks and Whites in another, the
tests do not mysteriously lose their bias. Stereotype threat may
therefore partly explain why any group alleged to be inferior may
underperform groups thought to be superior, regardless of their
numerical representation in a classroom, in a community, or in a
country.
Effects of Mediated Learning Experiences
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Studies have also indicated that performance on highly g -loaded tasks
can be affected through intervention such as exposure to information and
dynamic assessment procedures. For example, Skuy et al. (2002) indicated
that performance on a highly g -loaded task (i.e., Raven's Standard
Progressive Matrices [RSPM]) can be improved significantly through
mediated learning experiences. Skuy et al. concluded that "African
students, by virtue of their sociopolitical history, are especially
likely to have been deprived of mediated learning experience" (Skuy et
al., 2002 , p. 230). Thus, scores on the RSPM may be "more related to
schooling, literacy, and the cognitive demands imposed by the
environment, and, thus, they may vary more from culture to culture"
(Skuy et al., 2002 , pp. 230-231). Other studies also indicate that
mediated learning interventions were effective in raising the measured
indicators of cognitive ability for Black children (see Fagan & Holland,
2002; Sternberg et al., 2002).
Relative Functionalism
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Rushton and Jensen (2005) also report findings indicating the relatively
high intelligence of Asians in comparison with other racial/ethnic
groups. They fail to mention explanations such as relative functionalism
that have been used to explain the high achievements of Asians in terms
of the educational achievement and the intelligence hierarchy. Relative
functionalism suggests that groups will pursue opportunities for
achievement in particular contexts (e.g., academic, social, vocational)
when it is perceived that other avenues to success are closed. Sue and
Okazaki (1990) refuted the notion that Asians are genetically superior
to other racial/ethnic groups. On the contrary, they cited relative
functionalism as accounting for the high achievement of Asian Americans
beyond their measured IQ. This theory posits that Asian Americans
experience opportunities for upward mobility in educational areas and
exclusion from other noneducational pursuits (e.g., entertainment,
politics) because of social discrimination or limited English language
skills. Though relative functionalism has been difficult to test
empirically, anecdotal evidence in terms of the experiences of Asians in
the United States seems to support this explanation. Arguments based on
relative functionalism could also be made with respect to the limited
educational achievements of African Americans due to slavery and
historically little access to educational opportunities.
Test Development Practices
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Current test development practices have served to maintain the
racial/ethnic group hierarchy of intelligence test scores. Strategies
used to address issues of cultural bias are limited to expert review
panels and various statistical formulations. However, these practices
have been criticized on the basis of their conceptual limitations
(Valencia & Suzuki, 2001).
Sternberg (2000) criticized current methods of establishing test
validity. He noted that intelligence can be represented in terms of a
person's talents and the abilities that are valued in a particular
sociocultural context. To the extent that one's behavior is discrepant
from that valued by society, these individuals will be viewed as less
successful and intelligent. Sternberg stated, "tests are validated
almost exclusively against the societally approved criteria, giving
tests an appearance of validity that they may not have within a given
sociocultural group" (Sternberg, 2000, p. 165). Issues of how one adapts
to particular environmental contexts that may differ from the status quo
are not considered.
With respect to specific tests, accusations of "cultural" and
"statistical" bias are still noted for popular tests such as the SAT
(Freedle, 2003). Freedle (2003) contended that a corrective scoring
method, the Revised-SAT (R-SAT), be used to address the "nonrandom
ethnic test bias patterns found in the SAT" (p. 1) by focusing on the
"hard" items of the SAT. These hard items are often dependent on "rare
vocabulary" (Freedle, 2003 , p. 2). Freedle cited work using
differential item functioning, which reflects a "small" but "highly
patterned nature; that is many easy items show a small but persistent
effect of African Americans' underperformance, while many hard items
show their overperformance" (Freedle, 2003, p. 3). Freedle referenced
the cultural unfamiliarity hypothesis that "many easy verbal items tap
into a more culturally specific content and therefore are hypothesized
to be perceived differently, depending on one's particular cultural and
socioeconomic background" (Freedle, 2003, p. 7). Hard items are less
ambiguous given that they are most often used in an academic setting.
The R-SAT has reduced the Black-White test gap by one third. Verbal
scores are particularly affected as Freedle noted that scores on the
Verbal R-SAT are increased by as much as 200 to 300 points for
individual minority test takers.
Further challenges to the SAT are noted by Rosner (2003) , executive
director of the Princeton Review Foundation. His research on the 1998
version of the SAT indicates that the percentage of White students
answering questions correctly was higher than the percentage of Black
students for all 138 items. Items with higher percentages of Black
students answering correctly in comparison with Whites were
"systematically" rejected during the pretesting phase of the instrument
development (Rosner, 2003).
Implications <http://gateway.ut.ovid.com/rel_live/server1/gifs/ftup.gif>
It is evident that to reach Rushton and Jensen's (2005) position on the
meaning of the race differences in test performance, one has to accept a
particular definition of intelligence and believe in the validity of IQ
tests to measure it. There is also growing documentation of the powerful
effects of context on intellectual performance (e.g., stereotype threat)
and learning (e.g., mediated learning). Even admitting the possibility
of racially based differences in intelligence, there appears to be
considerable research supporting environmental/cultural justification
for race differences--enough at least to make one question a steadfast
belief in a biological explanation.
It appears that the culture versus genetic debate will continue despite
the fact that most would adhere to an interactionist perspective
(Reynolds, 2000 ). As noted in the beginning of this article, our
concerns focus on the implications of the genetic argument. Where
society stands on the malleability of intelligence will affect the
allocation of resources (e.g., affirmation action) and the promotion of
particular methods of intervention (e.g., educational programs like Head
Start).
Our commentary has only briefly highlighted the literature with respect
to possible cultural and environmental explanations for the
racial/ethnic group hierarchy on intelligence tests. The theoretical and
empirical work appear promising in this area. In addition, questions may
be raised regarding current test development practices (from item
selection to validation). There appears to be many opportunities to
think "outside the box" in our examination of what constitutes an
intelligence measure and how we examine issues of bias (White, 2000). In
addition, given growing concerns regarding the usage of intelligence
tests for selection purposes, Jensen (2000) suggested using criteria
that go beyond standardized measures and the inclusion of indicators of
past performance (e.g., work history). The goal for all of us is to
discover "truth" in whatever form it may take. Reynolds (2000) called
for members of the profession to base interpretations of racial
differences on mental tests on empirical data and continually challenge
assumptions about the meaning of these differences.
It appears that many challenges remain in explaining fully the
racial/ethnic group hierarchy of intelligence whether one adheres to the
culture-only or genetic perspective. We believe that the answer resides
most likely in the interaction between the two and that data supporting
the malleability of IQ will prevail.
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Accession Number: 00043965-200506000-00005
----------------------
Psychology, Public Policy, and Law
Volume 11(2) June 2005 p 328-336
WANTED: MORE RACE REALISM, LESS MORALISTIC FALLACY
Rushton, J Philippe1,3; Jensen, Arthur R.2
1Department of Psychology, The University of Western Ontario, London,
Ontario, Canada
2School of Education, University of California, Berkeley
3 Correspondence concerning this article should be addressed to J.
Philippe Rushton, Department of Psychology, The University of Western
Ontario, London, Ontario N6A 5C2, Canada. E-mail: rushton at uwo.ca
Outline
* Abstract
* Are Black-White IQ Differences Narrowing?
* Racial Admixture Studies: Direct Versus Indirect Evidence of
Heritability
* African IQ Scores
* Brain-Size Differences
* The Moralistic Fallacy and Public Policy
* Conclusion
* References
Abstract <http://gateway.ut.ovid.com/rel_live/server1/gifs/ftup.gif>
Despite repeated claims to the contrary, there has been no narrowing of
the 15- to 18-point average IQ difference between Blacks and Whites (1.1
standard deviations); the differences are as large today as they were
when first measured nearly 100 years ago. They, and the concomitant
difference in standard of living, level of education, and related
phenomena, lie in factors that are largely heritable, not cultural. The
IQ differences are attributable to differences in brain size more than
to racism, stereotype threat, item selection on tests, and all the other
suggestions given by the commentators. It is time to meet reality. It is
time to stop committing the "moralistic fallacy" that good science must
conform to approved outcomes.
In our target article (Rushton & Jensen, 2005 ), we proposed a
hereditarian model--50% genetic-50% environmental--to explain the 15- to
18-point average IQ difference (1.1 standard deviations) between Blacks
and Whites. We reviewed the worldwide distribution of test scores, the g
factor of mental ability, the heritability of within- and between-groups
differences, the relation of brain size to intelligence and of race
differences in brain size, regression to the mean, cross-racial adoption
studies, racial admixture studies, and data from life-history traits and
human origins research. We were unable to identify (in Section 12 of
Rushton & Jensen, 2005) any reliable environmental contribution to the
Black-White IQ difference, including the non-g Flynn effect (i.e., the
secular rise in IQ scores). We also found that on many dimensions, East
Asian-White differences were a mirror image of Black-White differences.
In Section 14, we concluded in favor of an even stronger hereditarian
model--80% genetic-20% environmental--based on Jensen's (1998 , p. 443)
"default hypothesis" that, by adulthood, genetic and environmental
factors carry the same weight in causing group differences as they do in
causing individual differences.
Gottfredson (2005) is the only commentator who confronted head-on all
the empirical, theoretical, and moral issues. The other commentators
(Nisbett, 2005; Sternberg, 2005; Suzuki & Aronson, 2005 ) sidestepped
the totality of the three-way race-behavior matrix shown in our Table 3.
They invoked one or other of the culture-only refrains, that "race" is
only "skin deep"; if not, then any difference is too small to matter; if
not, then it is due to cultural factors such as statistical artifacts,
insensitive tests, racism, stereotype threat, and poverty; if not, then
it is poor form to talk about it. They also offered the usual
culture-only promissory notes that the Black-White IQ gap can be reduced
by economic improvements, interventionist programs, culture-friendly
assessment systems, and nonweighted models of gene-environment
interaction. Their examples only confirm what we described in Sections
2, 13, and 14: Culture-only theory is a degenerating research paradigm.
Are Black-White IQ Differences Narrowing?
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Nisbett (2005) provided the most empirically forceful of the rebuttals.
He claimed that the Black-White IQ difference had decreased to only 10
points in magnitude (<0.70 standard deviations) and that it could be
eliminated altogether within 20 to 60 years. He based this assertion on
a purported narrowing of the Black-White difference on school
achievement tests (reading, vocabulary, and mathematics), which he then
extrapolated to the IQ differences.
Reality, however, is stubborn. Jensen (1998, pp. 375-376, n. 33,
407-408, 494-495) showed that gains in scholastic achievement do not
equal gains in g, and the Black-White differences in g are as large as
ever, even for measures of reaction time. Jensen's conclusion dovetails
with a meta-analysis by Roth, Bevier, Bobko, Switzer, and Tyler (2001)
that we cited at the opening of our target article. They found a mean
effect size of 1.1 standard deviations that ranged from 0.38 to 1.46
(based on a sample of 6,246,729 from corporate, military, and higher
education samples) depending on the g loading of the test. On the
question of whether the difference was diminishing, they suggested any
reduction was "either small, potentially a function of sampling error
... or nonexistent for highly g loaded instruments [italics added]"
(Roth et al., 2001, p. 323).
In her commentary, Gottfredson (2005) underscored this message with
evidence that no narrowing had taken place in average Black-White
differences. She contrasted Black-White differences on highly g-loaded
"IQ tests" with those on less g -loaded "school achievement tests."
Gottfredson found that Black-White differences on IQ tests remained
constant at 1.0 standard deviation throughout the 20th century. She
agreed that the differences on school achievement tests did narrow
slightly from 1.07 to 0.89 standard deviations from the 1970s to the
1990s when the National Assessment of Educational Progress collected
data on 9- to 17-year-olds. However, as she then pointed out, even this
20% reduction in educational achievement (a) had occurred by the
mid-1980s and no longer continues, (b) is compatible with the group
differences in g, and (c) does not contradict the hereditarian
hypothesis.
These variable Black-White differences are explained by Spearman's
(1927) hypothesis, which states that Black-White IQ differences are
"most marked in just those [tests] which are known to be saturated with
g" (p. 379; see Section 4 of Rushton & Jensen, 2005 ). The differences
are lower on specific tests of memory, or arithmetic and spelling, than
they are on general reasoning and transforming information. One
implication is that test constructors could in principle reduce the
Black-White difference to zero (or even reverse it) by including only
non-g items (or those negatively loaded on g). However, they would then
be left with a test that had little or no predictive power. Roth et
al.'s (2001) meta-analysis concluded: "Overall, the results for both
industrial and educational samples provide support for Spearman's
hypothesis. That is, black-white differences on measures of cognitive
ability tended to increase with the saturation of g in the measure of
ability" (Roth et al., 2001, p. 317).
There is in fact no good evidence, contrary to Nisbett (2005; and Suzuki
& Aronson, 2005), that g is malleable by nonbiological variables. That
would require not just evidence that training produces higher scores but
evidence of broad transfer of training effects to other highly g-loaded
tasks. Extrapolation of the trends into the future may be like
extrapolating the non-g secular rise in IQ scores (the Flynn effect; see
Section 12). That the Flynn effect is not a Jensen effect (i.e., did not
have a loading on the g factor) was corroborated by Wicherts et al.
(2004). This is consistent with the lack of convergence of White and
Black means across decades despite the overall rise in IQs.
Two recent monographs show just how wide the achievement gap between
Blacks and Whites remains. First, Thernstrom and Thernstrom (2003)
comprehensively documented the scale of the Black deficiency: For
example, in reading, history, geography, and mathematics, 12th-grade
Black students do not do as well as eighth-grade White students. The
authors showed, moreover, that despite numerous, often well-publicized,
countywide projects (such as the $2 billion program in affluent
Montgomery County, Maryland, as well as the Kansas City, Missouri,
school district, under judicial supervision since 1985), no plan has yet
made a replicable dent in the Black-White achievement gap (despite low
student-teacher ratios and computers in every classroom). Second, Ogbu
(2003) studied the persistent underachievement of Black children in the
well-to-do suburb of Shaker Heights, Ohio, as a result of concern raised
by their (Black) parents, often highly paid professionals who had moved
to the area specifically for its schools. The Black students did better
than Black students elsewhere, but there were huge gaps between the
Blacks and their non-Black counterparts. Instead of genetic differences
in intelligence, both books offer variations on the usual culture-only
explanations: poor schools, prejudice, stereotyping, low expectations,
and alienation from White cultural domination. Nor do they consider
regression to the mean (Section 9) or other genetically influenced
traits that differentiate the races and affect attitudes to schoolwork
(Section 10).
Racial Admixture Studies: Direct Versus Indirect Evidence of
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Nisbett (2005) cited seven empirical studies on people of mixed race
(based on self-reported ancestry, skin color, and blood groups) as
"direct evidence" for the "nil" heritability of Black-White differences.
He claimed these outweighed those we had presented (in Rushton & Jensen,
2005 , Sections 7 and 8). It should be noted that Nisbett's studies are
peculiarly old, the mean year of publication being 1960 (median year
1966; range = 1930 to 1977). Most are actually very weak and
nondecisive, not having been replicated even once. Some are so old and
recycled that Jensen (1973 ; see also 1998, pp. 478-483, 612) dealt with
them 30 years ago! The blood-group studies could be repeated with better
sampling and methods of analysis, but probably never will be because a
more powerful tool, DNA analysis, is now available for this purpose. In
Section 8, we discussed the DNA methods that can ascertain degree of
White ancestry in Black populations. Many other DNA markers identify
Black-White differences regardless of how divergent the African
ancestry. They have been recommended for evaluating admixture in genetic
studies of disease (Collins-Schramm et al., 2002), and we recommend them
for genetic studies of IQ.
More generally, we do not share Nisbett's contention that "direct"
evidence is more relevant than "indirect" evidence unless, of course,
the quality, quantity, and consistency of the direct evidence are also
stronger than the indirect evidence. Much of evolutionary theory,
genetics, chemistry, and physics are essentially based on what Nisbett
would call indirect evidence. The hereditarian model of an 80%
genetic-20% environmental weighting for the Black-White IQ difference is
based on the hypothetico-deductive method (Sections 2 and 14), not a
patchwork of narrow, often inconsistent or unreplicated facts. Our
"indirect" evidence includes the fact that (a) the gene-environment
architectural matrix is the same for both races (Section 5); (b)
inbreeding scores from Japan predict mean Black-White differences in the
United States (Section 5); (c) regression to the mean operates
consistently in both races (Section 9); (d) psychometric g is one and
the same factor in both Whites and Blacks (Section 4); and (e) race
differences are greatest on the g factor extracted from both IQ tests
and reaction time tasks (Section 4).
How do the critics explain the fact that the Black-White difference is
greater on backward than on forward digit span memory, or on the more
complex rather than simple reaction time measures--exactly as predicted
by Spearman's (1927) hypothesis? How do they explain the fact that Black
students from families with incomes of $80,000 to $100,000 score
considerably lower on the SAT than White students from families with
$20,000 to $30,000 incomes? How do they explain why social class
factors, all taken together, only cut the Black-White achievement gap by
a third? Culture-only theory cannot predict these facts; often its
predictions are opposite to the empirical results.
African IQ Scores
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Sternberg's (2005) and Suzuki and Aronson's (2005) commentaries about IQ
studies from sub-Saharan Africa are written as though we are not aware
that African children suffer from parasitic illnesses and malnutrition,
speak languages other than English, grow up in cultures of violence, or
that mediated learning interventions show increases in African IQ
scores. We cited three studies on mediated learning (Section 3),
including the one by Skuy et al. (2002) that Suzuki and Aronson referred
to in detail, on which Rushton was a coauthor!
Rushton's series of studies in South Africa (see Rushton & Jensen, 2005
, Section 3) sought to examine further the well-replicated reports of an
African population mean of IQ = 70. He tested to see if IQ scores from
highly select students at the prestigious University of the
Witwatersrand in Johannesburg were consistent with the mean IQ of 70
reported for the general African population (Lynn & Vanhanen, 2002 ).
The results from seven studies conducted at universities in South
Africa, including those by other investigators, yield a median IQ of 84
(range = 77 to 103). Assuming that African university students are 1
standard deviation (15 IQ points) above the population mean, the finding
of a median IQ of 84 corroborates the general population mean of 70.
Although Rushton's mediated learning study with Skuy et al. (2002) on
first-year psychology students did raise the IQ of the African students
from 83 to 97, this is still low for students at a leading university.
Moreover, as we mentioned in Section 3, evidence shows that "coaching"
or "teaching-to-the-test" has the effect of denuding the test of its g
loading (te Nijenhuis, Voskuijl, & Schijve, 2001).
There can be little doubt about the replicability of the mean African IQ
of 70, or the impartiality of the investigators, for studies continue to
report low scores. In Kenya, Sternberg et al. (2001; see also Sternberg,
2005 ) administered the Colored Progressive Matrices to 85 children ages
12 to 15 years who scored 23.5 out of 36, an IQ equivalent of about 70.
In Tanzania, Sternberg et al. (2002; also Sternberg, 2005 ) gave the
Wisconsin Card Sorting Task to 358 children ages 11 to 13 who received a
perseverative error score of 18.53. Although procedural differences may
make the normative comparison problematic, as it stands, this score is
equivalent to the fifth percentile on American norms for 12-year-olds
(IQ = 75). After training on how to sort attributes, the children's
scores went up to 16.5 (lower scores meant fewer errors), but this was
still only at the ninth percentile on American norms (IQ < 80).
We accept as nonarguable that intervention strategies in Africa such as
the elimination of tapeworms, improved nutrition, and provision of
electricity, schools, and hospitals will raise test scores. However, we
predict they will not remove the substantial differences in average IQ
between Africans and Europeans, and that African Americans and other
mixed-race populations will continue to average between these "pure"
types because of White admixture. As regards Suzuki and Aronson's (2005)
reference to "a context of racism and colonialism that, in turn, creates
and shapes stereotypes" (p. 324), it should be noted that many of the
African countries showing a mean IQ = 70, such as Nigeria and Ghana,
have been independent for half a century (and the Caribbean Island of
Haiti for one and a half centuries), with no documented improvement in
cultural achievement or IQ scores.
Around the world, mean IQs differ much less within major population
groups than between them. Whites have IQs close to 100 whether they live
in Europe, Canada, Australia, New Zealand, or South Africa, whereas
Blacks in sub-Saharan Africa have IQs closer to 70 regardless of whether
they live in East, West, Central, or Southern Africa--or whether the
data were collected in the 1920s or the 2000s (Lynn & Vanhanen, 2002 ).
The IQ of Blacks in the United States is around 85 and hence
substantially higher than the IQs of Blacks in sub-Saharan Africa. There
are two explanations for this. The first is that American Blacks have
about 25% White ancestry. According to genetic theory this would raise
their IQs above the level of Blacks in Africa. The second is that
American Blacks enjoy much higher standards of living, nutrition,
education, and health care than they have in societies run by Blacks.
Living in a White society has raised rather than lowered the IQs of
American Blacks.
Genetic factors explain the worldwide pattern in a way that culture-only
theory has not. The worldwide pattern contradicts the hypothesis that
the low IQ of American Blacks is due to "White racism." For instance,
Mackintosh (1998) wrote, "it is precisely the experience of being black
in a society permeated by white racism that is responsible for lowering
black children's IQ scores" (p. 152). The IQs of Blacks in Africa is
compelling evidence against this theory. The theory that White racism
has been responsible for the low IQ of American Blacks always had an ad
hoc quality to it because "racism" has had no adverse impact on the
intelligence of East Asians and Jews, who average higher scores than do
Europeans (Section 1).
Brain-Size Differences
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Brain size and its relation to intelligence are crucial for an
evolutionary understanding of the origin of race differences in
behavior. Both magnetic resonance imaging (MRI) and external head size
measures show that brain size is related to IQ within race. Moreover,
the three-way pattern of East Asian-White-Black differences in brain
size that is found in adulthood (1,364 cm3, 1,356 cm3, and 1,267 cm3,
respectively; see Rushton & Jensen, 2005 , Section 6) is detectable at
birth. The findings on race and brain size have been repeatedly
replicated and found to be robust across variations in measures,
methods, and subject samples. How do our critics handle this evidence?
Rather than refuting or challenging this evidence, our critics
completely ignore it.
If two groups differ by 1 standard deviation in brain size and the
correlation between brain size and IQ is 0.40, then they will differ by
6 IQ points! Sarich and Miele (2003) estimated the Black-White
difference in brain size as 0.8 standard deviations, hence a 5-point IQ
difference is attributable to brain size alone. When purer measures of g
are used (Jensen, 1998) or a larger standard deviation for brain size
(Rushton, 2000), the regression of brain size on g comes to over half
the g difference.
The Moralistic Fallacy and Public Policy
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The naturalistic fallacy, identified by philosopher David Hume
(1711-1776), occurs when reasoning jumps from statements about what is
to prescription about what ought to be . An example of the naturalistic
fallacy would be to support warfare if scientific evidence showed that
it was to some degree part of human nature. (Warfare may or may not be
supportable; the point is only that it is not logical to derive "ought"
from "is.") The converse of the naturalistic fallacy is the moralistic
fallacy, which occurs when reasoning jumps from prescriptions about what
ought to be to statements about what is. It was coined by Harvard
University microbiologist Bernard Davis (1978) as a response to calls
for ethical guidelines for studying what could purportedly become
"dangerous knowledge," such as the genetic basis of IQ. Davis reasoned
that chilling an area of inquiry on moral grounds fixes our knowledge in
that area, so it becomes, in effect, an illogical effort to derive an
"is" from an "ought." An example of the moralistic fallacy is to claim
that because warfare is wrong, it cannot be part of human nature.
One corollary of the moralistic fallacy is the demonizing of those who
refuse to observe it. Another is that someone must be blamed whenever
Nature stubbornly refuses to conform. Because Blacks and Whites ought to
be equal in IQ and educational outcome but still are not, some who adopt
a moralistic position hold, in effect, that White people's attitudes are
largely to blame (e.g., Ogbu, 2003; Thernstrom & Thernstrom, 2003 ).
Both fallacies are conjoined when it is argued that whereas minority
dislike of Whites is "natural" (because of mistreatment, or because of
feeling "culturally dominated"), White prejudice is inherently bigoted
and "unnatural."
Sternberg (2005) questioned whether we showed "good taste" (p. 300) in
researching the hereditarian hypothesis in place of culture-only
alternatives such as poverty and racism, and he asked, "What good is
research of the kind done by Rushton and Jensen supposed to achieve?"
(p. 296). This is worth discussing if only because we will never make
progress in race relations if we operate on the belief that one segment
of society is responsible for the plight of another segment and that
belief is false (see also Gottfredson, 2005).
Ever since Gunnar Myrdal's (1944) An American Dilemma was cited in
footnote 11 of the U.S. Supreme Court's 1954 decision Brown v. Board of
Education of Topeka (which outlawed racial segregation in the schools),
it has become prevalent to attribute the underachievement of Black
people to prejudice and discrimination by White people. Myrdal's "Theory
of the Vicious Circle" stated: "White prejudice and discrimination keep
the Negro low in standards of living, health, education, manners and
morals. This, in turn, gives support to white prejudice. White prejudice
and Negro standards thus mutually 'cause' each other" (Myrdal, 1944 , p.
75). Myrdal rejected the idea that heredity had anything to do with "low
Negro standards," instead praising anthropologist Franz Boas for
subverting the up-to-then accepted hereditarian perspective.
Myrdal's (1944) tome (1,500 pages comprising 50 chapters and appendices)
identified White people's "attitudes" as the main cause of Black
people's problems. He contended, "the scientific facts of race and
racial characteristics of the Negro people are only of secondary and
indirect importance ... the beliefs held by white people ... are of
primary importance" (Myrdal, 1944 , p. 110, emphasis in original).
Although Myrdal himself acknowledged the facts that Blacks averaged a
"head slightly longer and narrower; cranial capacity slightly less; ...
pelvis narrower and smaller" (Myrdal, 1944 , p. 139), he worried that
these findings would lead Whites to conclude that Blacks had "lower
reasoning power," which would be an "incorrect interpretation" because
"no connection has been proved between cranial capacity and mental
capacity" (Myrdal, 1944, p. 140). He also alleged there had been
"exposés" of the "distorted ... measurements" (Myrdal, 1944, p. 91) of
racial differences in brain size (cf. Jensen, 1998; Rushton, 2000).
Conclusion <http://gateway.ut.ovid.com/rel_live/server1/gifs/ftup.gif>
Discussing the totality of the evidence with those who, for whatever
reason, refuse to adopt the behavioral genetic or evolutionary
perspective, at least when it comes to the nexus of race, intelligence,
and genetics, is little more than arguing past each other. There is not
space to respond in detail with the data and analyses that refute each
and every criticism raised by the commentators. For more information on
the g factor as the largest common factor in any battery of diverse
cognitive tests, see Jensen (1998, chap. 4); on the scientific
definition of race, see Sarich and Miele (2003, chap. 8); on whether the
Flynn effect is a Jensen effect, see Wicherts et al. (2004); on
transracial adoption studies, see Jensen (1998, pp. 472-478); on Ogbu's
class-as-caste hypothesis, see Jensen (1998, pp. 511-513); and on
stereotype threat, which is a type of test anxiety, see Jensen (1998,
pp. 513-515; see also Sackett, Schmitt, Kabin, & Ellingson, 2001 ). We
reviewed all of the relevant evidence on Black-White IQ differences and
concluded that hereditarian models of from 50% genetic-50% environmental
(Section 2) to 80% genetic-20% environmental (Section 14) provide a far
better fit than the culture-only model of 0% genetic-100% environment.
Expanding on the application of his "default hypothesis" that
Black-White differences are based on aggregated individual differences,
themselves based on both genetic and environmental contributions, Jensen
(2003) proposed "two laws of individual differences": (a) Individual
differences in learning and performance increase as task complexity
increases, and (b) individual differences in performance increase with
practice and experience (unless there is a low ceiling on proficiency).
Consequently, the more we remove environmental barriers and improve
everybody's intellectual performance, the greater will be the relative
influence of genetic factors (because the environmental variance is
being removed). However, this means that equal opportunity will result
in unequal outcomes, within families, between families, and between
population groups. The fact that we have learned to live with the first,
and to a lesser degree the second, offers some hope we can learn to do
so for the third.
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