Jensen, 2011. The theory of intelligence and its measurement
At a time of increasing attention to IQ variation among subpopulations, the FE promised to absolve the onus of unfavorable social attitudes engendered by these results. The seeming benevolent promise of the FE is that if samples of entire populations in various countries showed secular gains in IQ scores, the lower-scoring subpopulations within these regions would also gain in average IQ. Since the gradual rise in test scores is assumed to approach a saturation (i.e., peak) level, the subpopulation differences in mean IQ should eventually diminish to nonsigniﬁcance. Although Flynn did not explicitly make this hopeful surmise, the popular appeal of the FE attracted the interest of experts in psychometrics and statistics. It is through their agency that the greater signiﬁcance of Flynn’s contribution will ﬁnally be realized.
The critical point about the FE, however, is the singular fact that both the whole phenomenon and the massive data relating to it are scientiﬁcally incapable of answering the essential questions it raises. 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.
See also: The Jensen Mental Chronometer in the ISIR 2010 Abstracts page 58.
To our knowledge, this is the ﬁrst study to aggregate DNA markers to a unit of analysis higher than the individual. Moreover, this is the ﬁrst study to our knowledge that has revealed that variation in aggregate IQ scores is associated with variation in aggregate DNA markers. These results are in line with Lynn and Vanhanen’s (2002, 2006) (see also Hart, 2007; Rushton, 1997) thesis that the average IQ of nations is the result of genetic differences across those nations. Of course, the current study used schools, not nations, as the unit of analysis, meaning that the results reported here may not generalize to other levels of aggregation, including the nation level. There is good reason to believe, however, that the association between DNA and IQ would be even stronger at the nation level in comparison with the school level. There is much more variation in both genetic markers and IQ scores cross-nationally than there is across schools. Schools in the current study were all drawn from the same country (i.e., the United States) creating more genetic homogeneity among schools than there is among nations. Given that nations can vary quite drastically in terms of the allelic distributions of certain genes (Cavalli-Sforza, Menozzi, & Piazza, 1994), it stands to reason that this increased genetic variation would be able to explain more of the variance in IQ scores. Future research is needed to address this issue more fully and examine whether the link between DNA markers and IQ scores would be detected at other levels of aggregation
(Kevin Beaver also coauthored: Beaver et al., 2010. Three dopaminergic polymorphisms are associated with academic achievement in middle and high school and Beaver et al., 2010. Genetic risk, parent–child relations, and antisocial phenotypes in a sample of African-American males; Beaver and Wright recently authored The association between county-level IQ and county-level crime rates (2011).)