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The gene-environment hypothesis

When it comes to the B-W IQ gap there are three possible types of non-hereditarian explanations: the gap is due to different frequencies of IQ affecting environmental factors (VE-factors) which vary within both populations (e.g. SES or average savings or bad schools), the gap is due to some gene-environment factors which are as yet undetected by heritability estimates, or that gap is due to IQ affecting environmental factors (X-factors) which are unique to one or the other population and are more or less equally distributed across that population.

X-factor explanations were always theoretically implausible. For one, Blacks and Whites more or less live in the same environment unlike, for example, Americans and North Koreans or Americans now and Americans 50 years from now; given this, it’s rather hard to think of factors which could uniquely affect one or the other population and affect that population more or less equally. Additionally, X-factor explanations require a rather unparsimonious dual hypothesis for intellectual differences within the US; accordingly, the causes of differences within populations are completely distinct from the causes of differences between populations.

Given this situation, and given that high within group heritability of intelligence precludes any one VE factor from accounting for the Gap, environmentalists are left with either arguing that numerous VE factors sneak through the cracks of heritability and cause the gap (let’s call this the many causes hypothesis) or maintaining that gene-environment correlations confound heritability estimates (let’s call this the gene-environment hypothesis). Unlike Nisbett (2010), Flynn (2010) concedes that Jensen’s within-group/between group heritability argument makes implausible the many causes hypothesis. Instead, he tries to escape Jensen’s “steal chain of ideas,” as he calls it, by proposing a COVGE model of heritabiltiy. This is a seductive proposition because it offers a single unified explanation for within, between, and across cohort variations in intelligence. Jensen long argued that a between group genetic explanation should be treated as the default explanation as it offers the most parsimonious account of differences within and between groups (X-factors need not apply). With the gene-environment model, Flynn one ups the genetic explanation and offers a single account which can incorporate individual, group and cross cohort differences in IQ.

Let’s look at what Flynn (2010) has to say about intelligence and within group heritability:

Originally, Jensen argued: (1) the heritability of IQ within whites and probably within blacks was 0.80 and between family factors accounted for only 0.12 of IQ variance — with only the latter relevant to group differences; (2) the square root of the percentage of variance explained gives the correlation between between-family environment and IQ, a correlation of about 0.33 (square root of 0.12=0.34); (3) if there is no genetic difference, blacks can be treated as a sample of the white population selected out by environmental inferiority; (4) enter regression to themean — for blacks to be one SD below whites for IQ, they would have to be 3 Sds (3×.33=1) below the white mean for quality of environment; (5) no sane person can believe that — it means the average black cognitive environment is below the bottom 0.2% of white environments; (6) evading this dilemma entails positing a fantastic “factor X”, something that blights the environment of every black to the same degree (and thus does not reduce within-black heritability estimates), while being totally absent among whites (thus having no effect on within-white heritability estimates). [comment: When it comes to X-factors. Flynn is being disingenuous — years before developing his 2001 model with Dickens, he considered the Flynn effect and X-factors, in general, to be theoretically plausible and, presumably, not “fantastic” accounts for the said racial group differences]

I used the Flynn Effect to break this steel chain of ideas: (1) the heritability of IQ both within the present and the last generations may well be 0.80 with factors relevant to group differences at 0.12; (2) the correlation between IQ and relevant environment is 0.33; (3) the present generation is analogous to a sample of the last selected out by a more enriched environment (a proposition I defend by denying a significant role to genetic enhancement); (4) enter regression to the mean — since the Dutch of 1982 scored 1.33 SDs higher than the Dutch of 1952 on Raven’s Progressive Matrices, the latter would have had to have a cognitive environment 4 SDs (4×0.33=1.33) below the average environment of the former; (5) either there was a factor X that separated the generations (which I too dismiss as fantastic) or something was wrong with Jensen’s case. When Dickens and Flynn developed their model, I knew what was wrong: it shows how heritability estimates can be as high as you please without robbing environment of its potency to create huge IQ gains over time.

To sum up: Jensen used the high heritability of IQ to argue that, in absence of X-factors, differences between populations were not likely due to variable environmental factors and therefore most probably had a partial genetic basis. Flynn turns this logic around, using it to construct the IQ paradox and argue that the conventional understanding of heritability must be wrong. Accordingly, given the high heritability of IQ, the rapid secular increase in IQ can not be due to variable environmental factors and so must be due to genetics or X-factors; as the latter two explanations are supposedly implausible, there must be something incorrect about the conventional ( g + e) understanding of heritability.

Flynn concludes that high heritability doesn’t constrict vE explanations for differences (both between cohorts and between populations) because there must be some variable environmental factors which go undetected by heritability studies (i.e. variable environmental factors that are recursively correlated with genotype). That is, heritablility estimates must miss gene x environment correlations (rGE).

From Dickens and Flynn (2001):

“Thanks to industrialization, it is likely that the cognitive complexity of the average person’s job has increased over the last century. There is no doubt that more-demanding educational credentials control access to a wide range of jobs. There are far more people in scientific, managerial, and technical positions than ever before.6 Increased leisure time is another possible trigger for IQ gains, as some activities undertaken during extended“

“Between generations, the mask slips. For it to do its work, the worse environment of the earlier generation would have to be matched by worse genes for IQ; and the better environment of the later generation would have to be matched by better genes for IQ. However, because the two generations are equivalent for genes, there is no matching and therefore no masking. The potency of environmental factors stands out in bold relief.”

Initially, the COV GE model seems reasonable; when it comes to individual differences, it doesn’t seem outlandish to suppose that naturally born intellectuals might increase their verbal IQ through bookish behavior. On the subpopulation level, likewise, it’s doesn’t seem implausible that a propensity for studiousness might lead to cognitive enhancement. Yet, there are a few bumps which preclude a simple GE model for the US subpopultion differences.

When it comes to subpopultion differences in the US, the differences are general intelligence-loaded. As such, a COVGE explanation for these differences would entail a GE explanation for the high heritability of g. Arguing for the necessity of a GE explanation for g by way of the Flynn effect doesn’t work because the cause of g differences are qualitatively different from the cause of the Flynn effect (See: Wicherts, Dolan, Hessen, et al. 2004) and g has shown no secular rise. Flynn’s argument is reduced to a plead for the possibility of a g GE explanation. This is problematic.

When it comes to rGE explanations (the more a posteriori plausible of the two GE possibilities), GE theorists are forced to maintain that g is created from the outside in. (See theoretical diagram). Since g is structurally the same across individuals, cultures, sexes, and subpopulations, not only would the patterns of one’s environment have to construct g, the patterns of everyone’s environment would have to construct the same g.

Additionally, IQ g has numerous endophenotypic correlates, such as the volume of white and grey matter, the mass of the prefrontal lobe, and total brain size [1, 11, 13] and the overlap between IQ (g) and many of these endophenotypes is entirely due to genetic influences [1, 13]. To explain this genetic covariation, rGE theorists must maintain that genetics sets the parameters for environmental selection, which leads to the development of different cognitive phenotypes, which, in turn, molds the endophenotypic differences, thus creating the three way correlation.

Since the Phenotypic/endophenotypic correlations have been found to be a function of differential rates of change during the development process [ 9] and correspondingly since IQ differences are stable after adulthood, rGE theorists must maintain that this environmentally induced endophenotypic molding occurs primarily during the developmental process and starts early on. If we kept in mind what we said above, that the genes that lead to slight genetic IQ differences in infancy are the same genes that lead to large genetic based differences in adulthood, and note that the heritability of many dispositions also increases with age [4], we can readily identify the problem with this conception. Somehow, dispositional differences, which are under heavy environmental influence early on, must set the phenotypic/endophenotypic molding (environmental) parameters in a way that happens to correspond to the genetic driven phenotype that the individual will later express.

None of the above logically precludes a rGE explanation for g; the explanation would just have to be exceedingly complex. That said, there is a growing body of evidence against the active GE model. Since according to the active rGE model, environmentally conditioned phenotypic differences cause endophenotypic differences, the active rGE model predicts that environments will correlate with endophenotyes [13]. This was found to not be the case by Posthuma et al. (2003), De Moor et al. (2008), van Leeuwen et al (2009), and Betjeman (2009), disconfirming the model.

In addition to the above, Shikishima et al. (2009) found evidence of a causal genetic g. This effectively rules out the possibility of a purely active rGE created g:

Accordingly, our findings could furnish an argument against the typical criticisms offered by those who are opposed to the concept of g; in other words, g is an “artifact” (Simon, 1969) of the statistical methods that psychologists apply to the data. Gould (1981) argued that g, as a factor extracted from the factor analysis, is neither a “thing with physical reality” nor a “causal entity”, but is a “mathematical abstraction”, maintaining that “we cannot reify g as a ‘thing’ unless we have convincing, independent information beyond the fact of correlation itself.” Although the present study also draws information from correlations, we were able to depict the structure of human intelligence beyond the fact of phenotypic and genetic correlations with an explicit comparison between the independent pathway and the common pathway model; and as a “causal entity”, as a highly genetically driven entity…

…Several recent reports have shown that g is also correlated with a variety of neural mechanisms, such as glucose metabolism (Haier, 2003), cortical development (Shaw et al., 2006), and biochemical activity (Jung et al., 2005), along with the identification of promising endophenotypes for intelligence such as working memory and processing speed (van Leeuwen, van den Berg, Hoekstra, & Boomsma, 2007). These studies allow us to assume that it is now reasonable to consider g to be a physiological or biological, genetic entity.

Given this, while some GE interactions and correlations might occur for g, they’re unlikely to be substantial causes of differences. When it comes to the Flynn effect, it’s likely that this effect is accounted for my some variation of:

a) across cohort bias (i.e apparent rises in IQ are a measurement artifact). (See: Wicherts, Dolan, Hessen, et al. 2004; Gottfredson, 2009; Kaufman, 2010; Beaujeana and Osterlind, 2008)

b) rises in IQ which do not represent rises in general intelligence. (See: Gottfredson, 2007; Gottfredson, 2009, Jensen, 2011.) When it comes to comparisons across time, Jensen (2011) makes the key point:

The central issue is that methodology by which the dependent variable (viz., secular gains in IQ scores) has been measured, fails to meet the standard of the advanced sciences on an absolutely critical point! Despite the popular inference drawn from all the IQ data collected, this research can neither confirm nor reject the existence of the FE. Doubling the amount of the already massive data (other conditions being unaltered) could not resolve the issue. But whatever the outcome of a proper investigation of the FE, the gentleman– scholar philosopher James Flynn deserves recognition as an important figure in the history of psychometrics. The term Flynn Effect, however, will go down in history as a blind alley in psychometrics, viz., trying to answer a basic, nontrivial factual question using wholly inappropriate data.

Suppose a study were performed on the secular trend in the mean height (measured in either centimeters or inches) of 10- year old school children born and reared in a given locality over the past century. The result per se is not controversial and provides a valid basis for research on its causes. Indeed, such studies are among the least controversial findings in the science of human growth and development. Why? Because ‘height’ can be defined objectively by describing the physical operations used to measure it. The problem with IQ tests and virtually all other scales of mental ability in popular use is that the scores they yield are only ordinal (i.e., rank-order) scales; they lack properties of true ratio scales, which are essential to the interpretation of the obtained measures.

1.1. Minimum requirements for the scientific study of secular changes in psychometric variables

Four conditions are essential for advancing scientific knowledge about intelligence: (a) clearly formulated coherent theory of intelligence; (b) instrumentation for the ratio-scale testing of theory-driven hypotheses; (c) a standard protocol for administering the use of this equipment; and (d) appropriate statistical analysis of the raw data so obtained.

c) heterosis (See: Mingroni, 2007)

d) plan old X-factors working across time (e.g. nutrition). These are hardly implausible since different times represent different environments.

With regards to that last point, Flynn (and Taylor) fallaciously argued that since between population X-factors were theoretically implausible and empirically found not to exist, then between generation X-factors were likewise implausible. The fallacy of this argument is readily shown by the findings of Ang et al., 2009. The authors find no significant difference in the rate of the Flynn effect between ethnic groups, sexes, urbanity, age, family interaction, household income, and income x race. In this data, the Flynn effect indeed behaves like an x-factor.

Of course, even if one did maintain that differences between groups were due to rGE correlations, one would still be left with the basic problem found in the case of X-factor explanations. The rGE factors would have to differentially hit one population living more or less in the same environment — as such they can not be population generic rGE factors like those Flynn argues are behind the secular rise (of IQ). To get around this, Flynn seems to posits average genetic difference between populations!

“The standard model that poses the paradox assumes that environment and genetic endowment are uncorrelated. Applied to basketball, this implies that good coaching, practicing, preoccupation with basketball, and all other environmental factors that influence performance must be unrelated to whether genes contribute to someone being tall, slim, and well coordinated. For this to be true, players must be selected at random for the varsity basketball team and get the benefits of professional coaching and intense practice, without regard to build, quickness, and degree of interest”

So, in short, at minimal Jensen’s dilemma forces Flynn et al. to accept a genetic component to the difference. (What are the cognitive equivalents to well built, quick, attuned, “tall, slim, and well coordinated”?) While this technically might not be a hereditarian account of the gap, it surely is not a 0-genetic account (2).

Notes

1. X-factors accounts for groups differences when the groups are living in approximately the same environment are not just theoretically implausible, but, in the US, they have been empirically ruled out. Both Flynn and Nisbett have conceded this. This is substantial given that an X-factor explanation was long held to be the cause of the gap. For example, refer to Sandra Scar’s . In: Race, social class, and individual differences in I.Q.

X-Factors were empirically ruled out by the following studies:

Lubke, et al. 2003. On the relationship between sources of within- and between-group differences and measurement invariance in the common factor model

Rowe, 1994. No more than skin deep. American Psychologist; Rowe and Cleveland, 1996. Academic achievement in Blacks and Whites: Are the developmental processes similar?

Rowe, et. al., Vazsonyi 1994. No more than skin deep: Ethnic and racial similarity in developmental process.

Rowe, et. al., 1995. Ethnic and racial similarity in developmental process: A study of academic achievement.

Rowe, et al. (1994) found that that Blacks, Hispanics, Asians, and Whites have the same relation between background variables and developmental outcomes; Rowe and Cleveland (1994) found that the achievement tests of Black and White siblings and half sibling had the same structure of variances and covariances and that a quantitative genetic model was the best fit explanation. Based on an analysis AFOQT scores; Ree and Carreta (1995) found that the above ethnoracial groups had approximately the same general intelligence loadings — finding effectively ruling out x-factors. X-factors accounts for cohort differences across time are both theoretically plausible and, in many cases, empirically certain (differences in nutrition, etc).

(2) A gene x environment explanation which does not allow one to parse out a specifically genetic components would be non-hereditarian.

(3) There are two types of GE interactions. The first involves non-additive genetics. When it comes to the IQ wars, environmentalists hold out for the possibility of this. With non-additive GE:

What constitutes a good environment for one genotype in terms of the development of the phenotype may constitute a bad environment for some other genotype in terms of the development of the phenotype OR Environmental advantage, through acting in some phenotypic direction for all genotypes may have unequal phenotypic effects on different phenotypes

This is the type of GE that I’m maintaining plays an insignificant role in the heritability of IQ. The second type of GE involves additive genetics. With this type of GE, environmental differences interact with the heritability of a trait, such that poor environments can depress heritability and rich environments can increase heritability. This is the type of GE that is commonly found. What one notices is that with age the h^2 if IQ for impoverished kids nonetheless increases. My guess would be that by adulthood no gene-environment interaction of this sort is found. Whatever the case, this type of GE is irrelevant to the above discussion.

Images from:

Tucker-Drob et al., 2011. Emergence of a Gene× Socioeconomic Status Interaction on Infant Mental Ability Between 10 Months and 2 Years

Harden, 2007. Genotype by environment interaction in adolescents’ cognitive aptitude

References:

Ang et al., 2009. The Flynn Effect within subgroups in the U.S.: Gender, race, income, education, and urbanization differences in the NLSY-Children data

Beaujeana and Osterlind, 2008. Using Item Response Theory to assess the Flynn Effect in the National Longitudinal Study of Youth 79 Children and Young Adults data

Borsboom and Dolan, 2006. Why g is not an adaptation: A comment on Kanazawa (2004).

Dickens, W. T., & Flynn, J. R. (2001). Heritability estimates versus large environmental effects: The IQ paradox resolved.

.

Gottfredson, 2007. Shattering logic to explain the Flynn Effect.

Gottfredson, 2009. Of what value is intelligence?

“The puzzle of the Flynn Effect remains unsolved in large part because intelligence tests lack ratio-level measurement, that is, a scale that starts at zero quantity and counts in equal-size units from there. Without that capability, we cannot know whether the observed secular rise in average IQ reflects an absolute change in the level of any of the constructs captured by IQ tests, either in g itself or some normally inconsequential source of variance in the composite IQ score. Critics often implicitly assume that IQ scores can register changes in absolute ability level when they criticize intelligence tests. A currently popular critique in this vein is that the Flynn Effect disproves what had come to seem incontrovertibly true, namely, that IQ tests measure a stable, heritable, psychometrically unitary general intelligence. Their argument is that g cannot at once be heritable, unitary, and yet some subtest scores increase dramatically over time. Flynn (2007), for example, argues that the rise has “shattered g.” It obviously has not. The problem is not with our conception or measurement of g, but with our measurement technology not yet allowing us to measure absolute rather than just relative positions along any ability continuum. This is the severest limitation of current IQ tests, yet to be overcome (Jensen, 2006), but it does nothing to invalidate the construct of g or the utility of current IQ tests for many diagnostic, selection, placement, training, and treatment purposes.”

Flynn, 2010. The spectacles through which I see the race and IQ debate

Hulshoff Pol, et al. 2004. Genetic Contributions to Human Brain Morphology and Intelligence

Jensen, 1998. Population Differences In Intelligence: Causal Hypotheses. In: The g Factor: The Science of Mental Ability

From Jensen (1998):

[Given BGH = WGH*(rg(1-rp)/rp(1-rg))] …To accept the preponderance of evidence that WGH > 0 and still insist that BGH = 0 regardless of the magnitude of the WGH, we must attribute the cause of the group difference to either of two sources: (1) the same kinds of environmental factors that influence the level of g but that do so at much greater magnitude between groups than within either group, or (2) empirically identified environmental factors that create variance between groups but do not do so within groups. The “relaxed” default hypothesis allows both of these possibilities. The dual hypothesis, on the other hand, requires either much larger environmental effects between groups than are empirically found, on average, within either group, or the existence of some additional empirically unidentified source of nongenetic variance that causes the difference between groups but does not contribute to individual differences within either group. If the two groups are hypothesized not to differ in WGH or in total phenotypic variance, this hypothesized additional source of nongenetic variance between groups must either have equal but opposite effects within each group, or it must exist only within one group but without producing any additional variance within that group. In 1973, I dubbed this hypothesized additional nongenetic effect Factor X. When groups of blacks and whites who are matched on virtually all of the environmental variables known to be correlated with IQ within either racial population still show a substantial mean difference in IQ, Factor X is the favored explanation in lieu of the hypothesis that genetic factors, though constituting the largest source of variance within groups, are at all involved in the IQ difference between groups. Thus Factor X is an ad hoc hypothesis that violates Occam’s razor, the well-known maxim in science which states that if a phenomenon can he explained without assuming some hypothetical entity, there is no ground for assuming it.

Jensen, 2011. The theory of intelligence and its measurement

Kaufman, 2010. In What Way Are Apples and Oranges Alike?” A Critique of Flynn’s Interpretation of the Flynn Effect

Lenroot, et al., 2007. Differences in genetic and environmental influences on the human cerebral cortex associated with development during childhood and adolescence

Miele, F.: 2002, Intelligence, Race, and Genetics: Conversations with Arthur Jensen.

Mingroni, 2007. Resolving the IQ Paradox: Heterosis as a Cause of the Flynn Effect and

Other Trends

“First, as Dickens and Flynn (2001) pointed out, estimates of the heritability (h2) of IQ are high, at about .75 in adults (Neisser et al., 1996). Without positing genetic change, this would seem to require positing environmental factors that cause large changes over time yet do not vary enough at any single point in time to reduce heritability estimates very much. Dickens and Flynn referred to such an implausible aspect of the environment as a “factor X.” Of note, although Dickens and Flynn carried out their analysis using a value of .75 for h2, they suggest that assuming values as low as .60 would still necessitate positing implausibly large change in those factors that do create environmental variance within generations (i.e., non–factor Xs). The magnitude of IQ heritability estimates, however, is only the first part of the problem. In addition to the magnitude of IQ heritability, the fact that estimates appear to have remained stable over time (Jensen, 1998, pp. 322–323) is also a problem for environmental hypotheses. Some hypotheses, such as nutrition, suggest that IQ-depressing environmental factors kept individuals of the past far below their maximum genetic potential for IQ. However, unless these factors depressed everyone’s IQ by the same amount, their removal from the IQ environment should have also removed an environmental source of variance, thereby causing heritability estimates to rise over time. Conversely, if the trend is due to something like a practice effect that has artificially raised IQ, this should represent the introduction of a new source of environmental variance that should have caused heritability to decline over time, unless, that is, everyone today is practicing the same amount. The consistency of heritability estimates would therefore still pose a problem for environmental hypotheses, even if the estimates were lower, because t would suggest that large evironmental change has occurred, without either the addition or subtraction of any noticeable ource of environmental variance.”

Panizzon et al., 2009. Distinct Genetic Influences on Cortical Surface Area and Cortical Thickness

Ree and Carretta, 1995. Group differences in aptitude factor structure on the ASVAB

Rowe, et al., 2001. Expanding variance and the case of historical changes in IQ means: A critique of Dickens and Flynn

We find a model including a phenotype-environment correlation, like that in Dickens and Flynn’s (2001) Model 2, to be reasonable and plausible. However, features of the model raise three important questions. First, the model implies increasing IQ variance under typical parameter specifications. Yet empirical evidence suggests that IQ variance has not increased, and may even have declined.

Second, the model has not been fit to empirical data. Rather, its performance was evaluated by specifying different (nonoptimized) parameter values and observing the results. Then, they were compared with patterns in the literature. Dickens and Flynn discussed the difficulty of finding appropriate data. Although we are not as pessimistic about data availability as they are, we recognize the problem. However, we also have concern over model fixes and adjustments when those were created to match external empirical patterns, without mechanisms to evaluate their legitimacy. Further, in a related concern, we wonder whether the model can be falsified. What types of patterns would do so? Can we distinguish between incorrectness at a fundamental level, as opposed to problems in some particulars (to which mathematical fixes can be applied)?

Third, we note that more conventional processes—based on more parsimonious models—can account for some IQ gain. Rowe, Jacobson, and Van den Oord (1999) found that genetic and environmental components of IQ variance were moderated by socioeconomic status (SES). In the bottom 20% of the SES distribution, c2 =.40, whereas it was approximately zero in the remainder of the distribution (a result replicated by Thompson, Tiu, & Detterman, 1999). To further elaborate, shared environmental effects were strongest where there was greatest potential of improvement in environmental circumstances. Some part of the Flynn effect may have derived from improved environmental conditions for poor families. As Dickens and Flynn suggested, this effect size may be no more than one third of a standard deviation, too little to be viewed as a complete explanation of the historical change. However, the simplicity of this explanation (and others reviewed earlier) provides a stark contrast to the complexity of Dickens and Flynn’s Model 3.

Rowe and Cleveland, 1996. Academic achievement in Blacks and Whites: Are the developmental processes similar?

Rowe, Vazsonyi, and Flannery, 1994. No more than skin deep: ethnic and racial similarity in developmental process.

This study investigated the similarity of developmental processes in Hispanics, blacks, and whites using correlation matrices. The matrices contained PIAT scores at two time points and a measure of environmental quality specific to each child. All measures were completed by siblings; hence, the correlational structure included all family effects through sibling psychological resemblance and all effects through the HOME measure of family environment. These correlation matrices were statistically equal across Hispanics, blacks, and whites. From this equality of correlation matrices, we concluded that developmental processes that determine variation in PIAT scores were similar across ethnic and racial groups. Statistical power, of course, limits the ability of this study to detect ethnic and racial group differences. Each ethnic or racial group, however, had more than 100 sibling pairs. Small developmental ef- fects may have gone undetected, but certainly larger ones would have appeared as differences in the correlational structures. As a second step, we proposed a specific structural equation model to explain variation in achievement. It postulated an achievement latent trait specific to each child and treated any association between achievement and family environment as noncausal. Other research on the NLSY (Rodgers et al., 1994) found that heritable effects on PIAT subtests were moderate, whereas shared environmental effects were relatively weak. Thus, our model emphasizing genetic effects but minimal family environment effects on PIAT achievement variation is consis tent with these direct behavior genetic analyses of the PIAT subtests in the NLSY. Nonetheless, the family environment (i.e., the HOME score) may also contain some environmental effects on achievement, but ones weaker than the family environment-achievement correlation parameter d (.314), which may contain genetic as well as environmental components. This study’s findings bear upon earlier studies of the construct validity of IQ across ethnic and racial groups. This previous research consisted essentially of showing the equality of 2×2 co variance matrices. In each such matrix, one variable was IQ and another was a theoretically related developmental outcome (e.g., course grades, job performance ratings). In general, such 2×2 matrices were statistically equal for blacks and whites (the groups most frequently studied; Barrett & Depinet, 1991; Cole, 1981; Jensen, 1980). By these statistical criteria, IQ was determined to be an equivalent psychological construct in different ethnic and racial groups. In this study, however, the argument goes considerably further by proposing that the determinants of achievement are identical across ethnic and racial groups. Our explanation for the similarity of developmental processes is that (a) different ethnic and racial groups possess a common gene pool, which can create behavioral similarities, and that (b) among second- generation ethnic and racial groups in the United States, cultural differences are smaller than commonly believed because of the omnipresent force of our mass-market culture, from teleision to fast-food restaurants (see Rowe et al., 1994).

Certainly, a burden of proof must shift to those scholars arguing a cultural difference position. They need to explain how matrices representing developmental processes can be so similar across ethnic and racial groups if major developmental processes exert a minority-specific influence on school achievement. Further research on this topic should consider replacing the more distal categories of ethnicity and race with more proximal cultural variables to measure and identify local cultures. Although local cultures (e.g., a ghetto or barrio culture) may moderate developmental processes, this claim, like the claim about ethnicity and race, remains one that has been widely accepted in the social sciences without strong empirical evidence.

Shaw, 2007. Intelligence and the developing human brain

Taylor, 2006. Heritability and Heterogeneity: The Irrelevance of Heritability in Explaining Differences between Means for Different Human Groups or Generations

Wicherts, Dolan, Hessen, et al. 2004. Are intelligence tests measurement invariant over time? Investigating the nature of the Flynn effect

This clearly contrasts with our current findings on the Flynn effect. It appears therefore that the nature of the Flynn effect is qualitatively different from the nature of B–W differences in the United States. Each comparison of groups should be investigated separately. IQ gaps between cohorts do not teach us anything about IQ gaps between contemporary groups, except that each IQ gap should not be confused with real (i.e., latent) differences in intelligence. Only after a proper analysis of measurement invariance of these IQ gaps is conducted can anything be concluded concerning true differences between groups.

[1] Betjemann, et al., 2009. Genetic Covariation Between Brain Volumes and IQ,

[2] Boomsma, et al., 1998. Genetic influences on childhood IQ in 5- and 7-year-old Dutch twins

[3] Bouchard, 2009. Genetic influence on human intelligence (Spearman’s g): How much?

[4] Gardner, 2007. A meta-analysis of age-related changes in heritability of behavioral phenotypes over adolescence and young adulthood.

[5] Flynn, 2007. What is intelligence? Beyond the Flynn effect.

[6] Haworth, 2009. The heritability of general cognitive ability increases linearly from childhood to young adulthood

[7] Plomin, 1987. Development, genetics, and psychology.

[8] Posthuma, et al., 2003. Brain volumes and the WAIS-III dimensions of verbal comprehension, working memory, perceptual organization, and processing speed.

[9] Shaw et al., 2006. Intellectual ability and cortical development in children and adolescent

[10] Shikishima, et al., 2009. Is g an entity? A Japanese twin study using syllogisms and intelligence tests.

[11] Smit et al., 2010. Endophenotypes in a Dynamically Connected Brain.

[10] van Leeuwen, 2008. A twin-family study of general IQ

[13] van Leeuwen et al., 2009. A genetic analysis of brain volumes and IQ in children.

[14] Jensen, 1973, Educatability and group differences.

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