The Scientific Study of General Intelligence

This recent book looks at the current debate on general intelligence, including the various adversarial opponents who deny that intelligence is highly genetic, and that there are differences in average intelligence in different races. Arthur R. Jensen's 1998 book The g Factor: The Science of Mental Ability, remains the most thorough treatment of general intelligence. This book builds on Jensen's work, and expands into some areas not covered by Jensen.

Table of Contents
General Introduction: Arthur Jensen - The Man, His Friends and This Book by Helmuth Nyborg--pg. xiii

Part I: The g Factor
Introduction--pg. 3
1. The Higher-stratum Structure of Cognitive Abilities: Current Evidence Supports g and About Ten Broad Factors by John B. Carroll--pg. 5

Part II: The Biology of g--pg. 23
Introduction--pg. 25
2. Brain Imaging and g  by Britt Anderson--pg. 29
3. Positron Emission Tomography Studies of Intelligence: From Psychometrics to Neurobiology by Richard J. Haier--pg. 41
4. Reaction Time and Psychometric Intelligence: Jensen's Contributions by Ian J. Deary--pg. 53
5. Inspection Time and g by Ted Nettelbeck--pg. 77
6. Factors Influencing the Relationship Between Brain Size and Intelligence by Gilles Gignac, Philip A. Vernon and John C. Wickett--pg. 93
7. Molecular Genetics and g by Robert Plomin--107

Part III: The Demography of g--pg. 123
Introduction--pg. 125
8. The Geography of Intelligence by Richard Lynn--pg. 127
9. Race Differences in g and the "Jensen Effect" by J. Philippe Rushton--pg. 147
10. Sex Differences in g by Helmuth Nyborg--pg. 187

Part IV: The g Nexus--pg. 223
Introduction--pg. 225
11.  Genius and g: Intelligence and Exceptional Achievement by Dean Keith Simonton--pg. 229
12.  Mental Retardation and g by Herman H. Spitz--pg. 247
13.  The Ubiquitous Role of g in Training by Malcolm James Ree, Thomas R. Carretta and Mark T Green--pg. 261
14.  Education and g by Phillip L. Ackerman and David F Lohman--pg. 275
15.  g, Jobs and Life by Linda S. Gottfredson--pg. 293
16.  Crime, Delinquency and Intelligence: A Review of the Worldwide Literature by Lee Ellis and Anthony Walsh--pg. 343

Part V: Reservations About g--pg. 367
Introduction--pg. 369
17.  "My House is a Very Very Very Fine House" - But it is Not the Only House by Robert J. Sternberg--pg. 373
18.  Jensen's Genetic Interpretation of Racial Differences in Intelligence: Critical Evaluation by Nathan Brody--397
19.  New Concepts of Intelligence: Their Practical and Legal Implications for Employee Selection by Gerald V Barrett, Alissa J. Kramen and Sarah B. Lueke--411
20.  The Sociology of Psychometric and Bio-behavioral Sciences: A Case Study of Destructive Social Reductionism and Collective Fraud in 20th Century Academia by Helmuth Nyborg--pg. 441
21.  Why Ignore the g Factor? - Historical Considerations by Christopher R. Brand, Denis Constales and Harrison Kane--pg. 503

Part VI: Epilogues --pg. 531
22.  An Arthurian Romance by Rosalind Arden--pg. 533
23.  Jensen as a Teacher and Mentor by Philip Anthony Vernon and Other Former Students--pg. 555
Bibliography           573
Author Index           599
Subject Index         619

Nyborg, in the interest of fairness, invited not only admirers of Jensen's work but detractors as well to contribute chapters to the book. As he explains:

"I, in fact, also asked a number of outspoken opponents of g-theory to write a chapter, and reserved a full part of the book for them, with the explicit purpose of seeking a balanced presentation of g theory. Unfortunately, I did not have much success in reaching this goal. One opponent said he had over the years had so many occasions to criticize g that he would consider it inappropriate to once more present his critical points in a book of this kind. He nobly added that his respect for Arthur Jensen was so great that he would rather see the book appear as laudatory as could be. Other opponents were rather brisk: 'I do not want to contribute to such a book'. Still others, such as Howard Gardner and Daniel Goleman, could neither find the time nor the motive to write a chapter. From the balance point of view, this is regrettable because science progresses best by first presenting all the pros and cons and then making an informed decision. But then again, it is a free country. Perhaps Robert Sternberg from Yale University is not directly opposing g theory, but he has his reservations, so I asked him to write a chapter for this honorary volume for Arthur Jensen. Surely he did. He paid back by comparing Arthur Jensen to a naive little boy living in his little house of g, too afraid to leave his narrow site and find out that the world outside has many more houses, that are much more interesting and, not to forget, also Sternberg's own tower! As an editor I welcomed the scientific aspects of Bob's chapter, but I must admit that it caused me personal grief to see the undeserving ad hominem remarks about Art's immaturity, in particular in a tribute such as the present. I decided, nevertheless, to include Bob's chapter, and will invite the reader to form his/her own judgment in the matter."

What is noteworthy with the above is that opponents of the concept of g and its implications for differences between races, has virtually run out of opponents. Sternberg seems to be the only serious alternative to g, and yet his approach is not that different from Jensen's. It seems that Sternberg is driven either by ego or by political motives in trying to derail Jensenism - but only he knows - unless like so many others he is self-deceiving. 

Nyborg states that:

"In Chapter 2, Britt Anderson takes a closer look at the brain size-g relationship. He first discusses the low and variable relationships found in earlier studies using such rough measures as external head circumference, and then presents the outcome of studies using more exacting in vivo neuro-imaging techniques. The overall conclusion is that anatomical and metabolic imaging techniques using magnetic resonance technology suggest a correlation in the order of 0.35 between brain size and IQ, a finding that is consistent across multiple experimental groups. Another important conclusion is that the majority of individual variation in intelligence is not explained by variation in brain volume. A third conclusion is, that we still do not know whether specific brain regions or compartments are the principal basis for the size-IQ correlation, and this sets the stage for further experiments exploiting the many new capabilities of magnetic resonance imaging and other brain image techniques."

He also notes that others have concluded that, "between 80~90 percent of brain volume is heritable, and that the genetic correlation between brain volume and IQ is 0.48."

Haier demolishes the "some people just try harder" argument, showing that those with more mental ability also exert less effort in processing data, "The higher the RAPM [Raven's Advanced Progressive Matrices test] score, the lower the GMR (glucose metabolic rate). Thus, it would appear that the harder the brain was working, the less well a subject solved the non-verbal, g-loaded problems of the RAPM. We interpreted this as evidence for a brain efficiency model of intelligence. Remarkably, in the same subjects, we found inverse correlations between degree of GMR decreases after practice and scores on the RAPM, suggesting that the brightest subjects become the most brain efficient with learning."

Haier then brings up a fascinating aspect of consciousness, one that could have a huge impact on eugenics:

"These studies did not include a focus on intelligence but pilot data suggest that the IQ of the subjects in these studies may interact with main effects of drug or cognitive condition. We are now pursuing this possibility. For example, we are designing functional imaging studies to address questions such as, are intelligent people more conscious than others and does the neuro-circuitry of consciousness, as revealed by studies of anesthetic drugs, overlap with the neurocircuitry of intelligence? We can address these questions with new image analysis software, PET hardware, MRI co-registration (for anatomical localization), and fMRI techniques that were not available for our first series of studies."

The reason the above is so important to eugenics is that it allows us to define humanness as the uniqueness of intelligence and/or consciousness. Note that very young children may have potentials for mental ability and/or consciousness, but they are neither fully functional data processing machines nor fully conscious. That is, to be more human means to be more conscious which depends on higher intelligence. Understanding this, we can then place varying levels of human value on varying levels of humanness. This refocuses the abortion issue, human rights issues, and numerous other value laden decisions on a definition of human life that is contingent on intelligence. It also allows eugenic communities to at least make moral decisions (if not legal decisions) to terminate those lives that are for any number of reasons, lacking in consciousness - therefore lacking humanness. I will let others argue that it is not acceptable to make arbitrary decisions when to terminate a life lacking in consciousness.

Lewontin, Gould and others in the past have criticized intelligence as a unitary concept, one that is highly genetic, on grounds that without looking at the actual mechanisms, modeling and testingwas too indeterminate (even with predictive validity). That is no longer the case, because psychometrics now uses many tools that triangulate on the validity of g as a unitary, highly genetic, factor. Haier explains:

"Individual differences as a mainstream discipline within psychology may be about to reassert itself after near banishment in the wake of the controversies of the last 30 years. This has already happened in cognitive psychology where new fMRI studies abound. Correlating cognitive task performance with functional brain data has yielded some spectacular results. Such correlations are fast becoming the norm in a branch of psychology where effects of individual differences were typically regarded as noise and error variance. Even more dramatic is the growing attention to the profound individual differences in drug response."

Plomin discusses additional research showing the importance of genes and the non-shared environment versus the shared environmental influence that is assumed by social scientists to reign supreme in importance:

"In his chapter on heritability in The g Factor, Jensen also notes one of the most surprising findings from behavioral genetics research: the heritability of g increases throughout development and the importance of shared environmental factors that make family members similar decreases. His hypothesis to explain this fascinating finding involves genotype-environment correlation: 'From early childhood to late adolescence the predominant component of the GE covariance gradually shifts from passive to reactive to active, which makes for increasing phenotypic expression of individuals' genotypically conditioned characteristics. In other words, as people approach maturity they seek out and even create their own experiential environment. With respect to mental abilities, a 'good' environment, in general, is one that affords the greatest freedom and the widest variety of opportunities for reactive and active GE covariance, thereby allowing genotypic propensities their fullest phenotypic expression.'"

"What are the non-shared environmental factors that are responsible for environmental influence on g after adolescence? Jensen summarizes his important view of this perplexing problem in The g Factor: 'The causes of the nonshared environmental variance are still somewhat obscure. I have presented analyses of MZ twin data elsewhere which suggest that the nonshared environmental variance is mainly the result of a great many small random effects that are largely of a biological nature. Such effects as childhood diseases, traumas, and the like, as well as prenatal effects such as mother-fetus incompatibility of blood antigens, maternal health, and perinatal effects of anoxia and other complications in the birth process, could each have a small adverse effect on mental development. Such environmental effects could differ randomly among twins or ordinary siblings. Some individuals would have the good luck of being 'hit' by very few such adverse random effects, compared to the average, and others would have the bad luck of being 'hit' by many more than the average.'"

"Concerning assortative mating, Jensen noted that the correlation between spouses for g is above 0.40, which is much higher than for other traits. In The g Factor, he uses his important 'method of correlated vectors' to show that assortative mating is largely a matter of g. That is, the degree to which cognitive tests show assortative mating is highly correlated with the tests' loadings on the g factor. Similar results for the method of correlated vectors are found for kinship correlations and for heritabilities tests with greater g loadings show greater heritability. All of these findings suggest that the g is the central plot in the story of cognitive abilities."

"Jensen also describes the results of multivariate genetic analysis that suggest that what the genetics of cognitive abilities is about is g. Although it is surprising that g accounts for about 40% of the phenotypic variance of diverse cognitive tests, it is truly amazing that about 80% of the genetic variance of such tests is explained by g. That is, multivariate genetic analyses have consistently found that genetic correlations among cognitive abilities exceed 0.80. In other words, if a gene associated with a particular cognitive ability were identified, the same gene would be expected to be associated with other cognitive abilities as well. This finding suggests that, despite its complexity, g is the best target for molecular genetic research aimed at identifying specific genes for cognitive abilities. The finding is also important for cognitive neuroscience, a field in which g has hardly entered the lexicon. The genetic nexus responsible for g provides clues for understanding how the brain works from an individual differences perspective. It suggests that there must be genetically-driven mechanisms that affect performance across diverse cognitive tasks. Although genetic g does not imply that g is due to genes that affect a single process, the multivariate genetic results indicate that the same genes affect different cognitive processes. The genetic links among cognitive processes may have been forged by evolution to coordinate effective problem solving across the modules of mind."
 
"Another interesting finding from the Human Genome Project is that only 5% of the 3 billion letters in our DNA code involves genes in the traditional sense, that is, genes that code for amino acid sequences. This 5% figure is similar in other mammals. Mutations are quickly weeded out from these bits of DNA which are so crucial for development. When mutations are not weeded out, they can cause one of the thousands of severe but rare single-gene disorders. However, it seems increasingly unlikely that the other 95% of DNA is just along for the ride. For example, variations in this other 95% of the DNA are known to regulate the activity of the classical genes. For this reason, the other 95% of DNA might be the place to look for genes associated with quantitative rather than qualitative effects on behavioral traits."

Plomin is one of the leading researchers looking for the numerous genes that influence intelligence, or as stated above, the DNA that regulates the output of genes that determine intelligence. Just like the Human Genome Project, that started slow, then accelerated as new computer programs, mathematical models and diagnostic tools became available, the search for genes that influence intelligence will accelerate as the science develops new tools and methodologies. Plomin explains:

"From a QTL [quantitative trait loci] perspective, common disorders are just the extremes of quantitative traits caused by the same genetic and environmental factors responsible for variation throughout the dimension. In other words, the QTL perspective predicts that genes found to be associated with complex disorders will also be associated with normal variation on the same dimension and vice versa. Although the QTL perspective has some specific implications for the design and analysis of molecular genetic studies, the general importance of a QTL perspective is conceptual. At the most general conceptual level, a common mistake is to think that we are all basically the same genetically except for a few rogue mutations that lead to disorders. In contrast, the QTL perspective suggests that genetic variation is normal. Many genes affect most complex traits and, together with environmental variation, these QTLs are responsible for normal variation as well as for the abnormal extremes of these quantitative traits. This QTL perspective has some implications for thinking about mental illness because it blurs the etiological boundaries between the normal and the abnormal. That is, we all have many alleles that contribute to mental illness but some of us are unluckier in the hand that we draw at conception from our parents' genetic decks of cards. A more subtle conceptual advantage of a QTL perspective is that it frees us to think about both ends of the normal distribution the positive end as well as the problem end, abilities as well as disabilities, and resilience as well as vulnerability. It has been proposed that we move away from an exclusive focus on pathology towards considering positive traits that improve the quality of life and perhaps prevent pathology."
 
Lynn discusses results from his work on race and intelligence:

"In this chapter it is shown that the intelligence levels of peoples throughout the world varies consistently with their geographical location and with their race. There is a considerable overlap between geography and race. The most recent and thorough classification of the world's peoples by geography and race has been produced by Cavalli-Sforza et al. From an analysis of genetic differences between populations they distinguish eight major geographical-racial groups. Although they prefer to avoid the classical descriptive terms of Caucasoids, Mongoloids and so forth, their categories are so similar to these that it is convenient to use them. In terms of the classical taxonomy, their geographical-racial groups are:

European Caucasoids;
South Asian and North African Caucasoids;
Northeast Asian Mongoloids;
Southeast Asians extending from Thailand to Indonesia and the Philippines;
Pacific Islanders;
Australian Aborigines;
Negroids;
American Indians.

A number of useful conclusions can be drawn from the survey of the geographical distribution of intelligence and racial IQs presented in this chapter. First, these IQs should be regarded as differences in g as this construct is used by Jensen. Most of the results are obtained from the Progressive Matrices which is a pure measure of g and the remainder come from tests like the Wechslers which are good measures of g. The differences in g among all these populations should be regarded as arising from a mix of genetic and environmental factors. These populations differ genetically in numerous respects including the color of skin, eyes and hair, body build, blood groups and susceptibility to diseases. It is from the analysis of these genetic differences that Cavalli-Sforza et al. have constructed their world map of genetic differences between peoples. These genetic differences are so pervasive that it is impossible that all these peoples could be genetically identical for intelligence. The studies surveyed in this chapter show that the IQs of the world's populations vary consistently with their race. There is no environmental theory that can explain this. The only conclusion that can be drawn from this association is that race is the most important determinant of the IQs of populations."

"With regard to the intelligence difference between blacks and whites in the United States, the consistency of the black-white differences worldwide corroborates the thesis that genetic factors are largely responsible for the difference in the United States. We have seen that whites from North West Europe, which is where the ancestors of most American whites came from, almost invariably have IQs close to 100, whether they are in Europe, Canada, Australia, New Zealand or South Africa, while blacks in sub-Saharan Africa invariably obtain IQs in the range of 62-78. 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 are a hybrid population with about 25% of white ancestry. According to genetic theory this would raise their IQs above the level of blacks in Africa. The second is that American blacks live in a society run by whites and enjoy much higher standards of living, nutrition, education and health care than they have in societies run by blacks. This enriched environment can be expected to have some advantageous impact on their IQ. When we look at the IQs of blacks in Africa we have to conclude that living in a white society has raised rather than lowered the IQs of American blacks."

"This conclusion is the opposite to that of a number of environmentalists who contend that the low IQ of American blacks is due to 'white racism'. For instance, Mackintosh writes: '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.' The IQs of blacks in Africa is compelling evidence against this theory. African countries gained independence from white rule in the 1960s and African children born from 1970 onwards no longer experienced white racism. The theory that white racism has been responsible for the low IQ of American blacks leads to the prediction that recent generations of young African blacks would show significant IQ gains. Studies carried out in the 1990s show that this has not happened. African blacks have continued to obtain the same low IQs of 62 (Ghana), 75 (Kenya), 62-68 (Zaire) and 61-70 (Zimbabwe) as they have obtained from the 1920s onwards. The theory that white racism has been responsible for the low IQ of American blacks was never plausible because its proponents have not identified the mechanism by which racism could lower intelligence and because racism has had no adverse impact on the intelligence of Asians and Jews. The evidence from Africa finally discredits it."

"This association between intelligence and race is sufficiently close for it to be possible to predict the approximate IQs of nations and of sub-populations within nations from their racial identity. For instance, the population of Jamaica is 90% black, 7% mixed and 3% Indian. It would be predicted that the population's IQ should be a little above the median IQ of 68 of blacks in sub-Saharan Africa. The mean IQ is 72. In neighboring Cuba the population is 37% white, 11 % black and 51 % Afro-European. Assigning IQs of 98 for whites, 69 for blacks and 83 for Afro-Europeans, the IQ of the population should be 87. The actual IQ derived from the standardization of the Progressive Matrices by Alonso is 84. Numerous other predictions can be made and tested from the genetic theory of race differences in intelligence. The theory has crossed the threshold from descriptive to predictive science."

"The causes of genetically based racial differences in intelligence should be sought in their evolutionary history. Differences in IQ must have developed together with differences in skin color, morphology and resistance to diseases as adaptations to the environments in which the races evolved. We can reconstruct the broad outline of how this occurred. Modern humans evolved in Central East Africa about a quarter of a million years ago. Their brain size was the same as that of living blacks and it can be assumed that their intelligence was the same, represented by an IQ of 69. About 100,000 years ago some of these migrated into South West Asia. Here they encountered cold winters and a lack of plant foods during winter and spring. These conditions exerted selection pressure for an increase of intelligence to enable them to make clothing and shelters to protect themselves from the cold winters and to hunt large animals to obtain meat when plant foods were not available. By around 50,000 years ago these selection pressures raised the IQ of these peoples to about 75, represented by the present day Australian Aborigines, who migrated to Australia at about this time and whose IQ stabilized at around this figure."

"During the next 25,000 years some of the peoples of South Asia migrated into North East Asia and others migrated into Europe. Some of those who migrated into North East Asia evolved into the Mongoloids. Others crossed into America and evolved into the Native Americans. Those who migrated into Europe evolved into the European Caucasoids. About 25,000 years ago the climate in the northern hemisphere began to grow colder with the onset of the last ice age. Winter temperatures fell by around 10 degrees centigrade. This made survival more difficult and exerted further selection pressure for enhanced intelligence. This selection pressure was weakest on the peoples of South Asia but it was sufficient to raise their IQs to the present day level of about 83; it was about the same on the Native Americans because these had migrated into America before the onset of the ice age and their IQs were raised to about the same level as that of South Asians. Climatic conditions were more severe in Europe and North East Asia, where the environment resembled that of present day Alaska and Siberia. This increased the selection pressure for enhanced intelligence and drove the IQs of the European Caucasoids up to its present day figure of around 98. In North East Asia the climate was even more severe than in Europe and drove the IQs of the Mongoloids up to the present day figure of around 104. The morphological basis of the increase in intelligence in the Caucasoids and Mongoloids was an enlargement of brain size the evidence for which is set out by Rushton."

"The ice age came to an end about 10,000 years ago. In the more benign climate that followed the South Asian Caucasoids and the Mongoloids were able to use their enhanced intelligence to develop the early civilizations along the river valleys of the Tigris, Euphrates, Indus, Nile and Yangtze, where the flood plains and the favorable climate made it possible to produce the agricultural surpluses required to feed urban populations and sustain an intellectual class. The Native Americans had also evolved sufficiently high intelligence to develop the quasi-civilizations of the Aztecs, Mayas and Incas. Europe, Northern China and Japan did not have the flood plains or the favorable climate necessary for the development of these early civilizations but in the last two millennia these peoples have used their high IQs to overcome these problems and produce the advanced civilizations of today."

Rushton summarizes what Jensen has accomplished:

"Jensen formally designated the view that Black-White differences were largely a matter of g as 'Spearman's hypothesis', because Spearman was the first to suggest it. Subsequently, Osborne dubbed it the 'Spearman-Jensen hypothesis' because it was Jensen who brought Spearman's hypothesis to widespread attention, and it was Jensen who did all the empirical work confirming it. More recently, to honor one of the great psychologists of our time, Rushton proposed that the term 'Jensen Effect' be used whenever a significant correlation occurs between g-factor loadings and any variable, X; otherwise there is no name for it, only a long explanation of how the effect was calculated. Jensen Effects are not omnipresent and their absence can be as informative as their presence. For example, the 'Flynn Effect' (the secular rise in IQ) is probably not a Jensen Effect because it does not appear to be on g."

"The Black-White difference on the g-factor is the best known of all the Jensen Effects. The reason Jensen pursued Spearman's hypothesis was because it so exquisitely solved a problem that had long perplexed him. The average 15 to 18 IQ point difference between Blacks and Whites in the U.S. had not changed since IQ testing began almost 100 years ago. But Jensen noted that the race differences were markedly smaller on tests of rote learning and short-term memory than they were on tests of abstract reasoning and transforming information. Moreover, culture-fair tests tended to give Blacks slightly lower scores than did conventional tests, as typically did non-verbal tests compared with verbal tests. Furthermore, contrary to purely cultural explanations, race differences could be observed as early as three years of age, and controlling for socioeconomic level only reduced the race differences by 4 IQ points."

"Jensen initially formalized these observations in his so-called Level I-Level II theory. Level I tasks were those that required little or no mental manipulation of the input in order to arrive at the correct response whereas Level II tasks required mental manipulation. A classic example of Level I ability is Forward Digit Span in which people recall a series of digits in the same order as that in which they are presented. A clear example of a Level II task is Backward Digit Span in which people recall a series of digits in the reverse order to that in which they were presented. Jensen found that Black-White differences were twice as large for Backward as for Forward Digit Span."

"Five of the tests were administered at the time of induction into the armed forces while the others were given approximately 17 years later. The battery included the Grooved Pegboard Test, the Paced Auditory Serial Addition Test, the Rey-Osterrieth Complex Figure Drawing Test, the Wisconsin Card Sorting Test, the Wide Range Achievement Test, the California Verbal Learning Test, the General Information Test, and various sub-tests from the Wechsler Adult Intelligence Scale-Revised, and the Army Classification Battery. The g factor was extracted using different methods. Spearman's hypothesis was confirmed regardless of procedure, with an average correlation between the race differences on a test and its g loading across the extraction procedures of 0.81. This value is higher than the average correlation of 0.62 for all previous studies. Nyborg & Jensen concluded that Spearman's original conjecture about the Black-White difference on the g factor 'should no longer be regarded as just an hypothesis but as an empirically established fact.'"

"Another apparent absence of the Jensen Effect is that shown for the secular increase in test scores. The Flynn Effect (sometimes also known as the Lynn-Flynn Effect) refers to the repeated demonstration by Flynn that the average IQ in several countries has increased by about 3 points a decade over the last 50 years. The Flynn Effect seems to imply the 1 SD difference in the mean IQ between Blacks and Whites in the U.S. will simply disappear over time. However, analysis shows that the Flynn Effect is not on the g factor."

"Table 9.3 shows the results of a principal components analysis of the secular gains in IQ from the U.S., Germany, Austria and Scotland, along with Black-White IQ difference scores from the U.S., inbreeding depression scores from cousin marriages in Japan, and g-loadings from the standardization samples of the Wechsler Intelligence Scale for Children (WISC-R and WISC-III). The important findings are: (1) the IQ gains on the WISC-R and WISC-III form a cluster, showing that the secular trend is a reliable phenomenon; but (2) 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). This analysis shows that the secular increase in IQ behaves in a different way than the mean Black-White IQ difference. The secular increase is unrelated to g and other heritable measures, while the magnitude of the Black-White difference is related to heritable g and inbreeding depression."

"Flynn's hypothesis that the 'massive IQ gains over time' imply an environmental origin of race 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 show that effect is unrelated to the g-factor. Instead, g is associated with inbreeding depression, for which there is no non-genetic explanation, which implies strongly that g is less amenable to environmental manipulation."

"Chapter 12 of The g Factor presents Jensen's technical arguments for why he believes that Black-White IQ differences are about 50% genetic in origin. These include that: (1) the Black-White IQ differences are most pronounced on the more g-loaded components of IQ tests; (2) the Black-White IQ differences are most pronounced on the more heritable components of IQ tests; (3) IQ differences are associated with brain size within each race and there are significant Black-White (and East Asian) differences in average brain size; (4) Black-White (and East Asian) differences show up in myopia which has been linked to brain size; (5) the Black-White (and East Asian) IQ differences remain following transracial adoption; (6) the Black-White IQ differences are reflected in studies of racial admixture; (7) the Black-White IQ differences are predicted by 'regression to the mean'; (8) Black-White-East Asian differences in neonate behavior, rate of maturation, and a suite of life-history traits parallel the IQ differences; (9) the Black-White-East Asian IQ differences cannot be explained by any culture-only theory; and (10) the Black-White-East Asian IQ differences dovetail with what is known about human evolution. What follows is a summary of some of the evidence from Jensen's The g Factor and Rushton's Race, Evolution, and Behavior."

"As reviewed early in this chapter, Black-White differences are Jensen Effects, being most pronounced on the more g-loaded subtests. Spearman's hypothesis thus constitutes a special case of the Jensen Effect. It applies even to the g factor extracted from reaction time measures taken from 9- to 12-year-old Black and White children. Jensen has shown that a test's g loading is the best predictor not just of that test's correlation with scholastic and work-place performance, but of heritability coefficients determined from twin studies, inbreeding depression scores calculated in children born from cousin-marriages, and many other variables including brain evoked potentials, brain pH levels, brain glucose metabolism, as well as nerve conduction velocity, reaction time and other physiological factors. These correlations establish the heritable and biological, as opposed to the mere statistical, reality of g. The general factor g is a product of human evolution. Indeed, massive evidence indicates that g is related to the size and functioning of the brain. As reviewed above, race differences in brain size occur at birth and continue through life."

"Myopia (near-sightedness) is positively correlated with IQ. The relationship appears to be pleiotropic, that is, a gene affecting one of the traits also has some effect on the other. Further, there are significant racial and ethnic differences in the frequency of myopia, with the highest rates found in East Asians, the lowest rates among Africans and Europeans intermediate. Among Europeans, Jews have the highest rate of myopia, about twice that of gentiles and about on a par with that of Asians. Miller suggested that myopia is caused by extra myelinization in the eye and is similarly linked to brain size."

"The g Factor also cites the evidence of transracial adoption studies. Three studies have been carried out on Korean and Vietnamese children adopted into White American and White Belgian homes. Though many had been hospitalized for malnutrition prior to adoption, they went on to develop IQs ten 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 perform at a lower level than similarly adopted White children. The largest and best known such study, the Minnesota Transracial Adoption Study, was designed specifically by Sandra Scarr and Richard Weinberg to separate genetic factors from rearing conditions as causal influences on the poor cognitive performance of Black children. It is also the only transracial adoption study that includes a longitudinal follow-up, with testing at ages 7 and 17 years."

"Scarr and her colleagues compared the IQ and academic achievement scores of Black, White, and mixed-race Black/White children adopted into privileged White families in Minnesota by adopting parents whose mean IQ was more than 1 SD above the population mean of 100 (see Table 9.5). The biological children of these parents were also tested. 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 (non-adopted) children had an average IQ of 117 (Table 9.5, 2nd column), similar to that found for other children of 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 & Weinberg interpreted the results of their testing at age 7 as strong support for the culture-only interpretation of racial differences in intelligence. They drew special attention to the fact that the mean IQ of 107 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 (two points lower in adoptive parents IQ). They found no evidence for 'the expectancy effects' hypothesis that adoptive parent' 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 for 56 children correctly classified by their adoptive parents as having one Black and one White biological parent."

"Table 9.5 also presents the results for the 196 children retested at 17 years old. There were four independent assessments of the children's cognitive performance at this later age: (1) an individually administered IQ test; (2) an overall grade point average; (3) a class rank based on school performance; and (4) four special aptitude tests in school subjects administered by the educational authority, which Rushton averaged. The results are strikingly concordant with the earlier testing. The non-adopted 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 and 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 were used in the follow-up, the overall average difference of about eight IQ points (evident for all groups, including the non-adopted group) between the two test periods is of no theoretical importance for the hypothesis of interest. The relevant comparisons are those between the adopted groups 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."

"In the Minnesota Transracial Adoption Study, the Mixed-Race (Black/White) adoptees had a mean IQ between those of the 'non-mixed' White and 'non-mixed' Black adoptees, as predicted from a genetic hypothesis (see Table 9.5). Although Jensen himself is equivocal on this topic, in fact many other studies report similar results. For example, with respect to IQ scores, Shuey found that in 16 of 18 studies, Blacks with lighter skin color averaged higher IQ scores than did those with darker skin. Shockley estimated that for low IQ Black populations there is a one-point increase in average 'genetic' IQ for each 1 % of Caucasian ancestry, with diminishing returns as an IQ of 100 is reached. The genetic hypothesis is also consistent with the African American mean IQ of 85 being 15 points above the African average of 70 (reviewed earlier), given the approximately 20% White admixture in this group. Corroborating data come from the mixed-race 'Colored' population of South Africa showing they too have an average IQ of 85, intermediate to the 'pure' Africans and 'pure' Whites. What brain weight data are available also fit with the genetic hypothesis. Both Bean and Pearl found that the greater the amount of White admixture (judged independently from skin color), the higher the average brain weight at autopsy in Blacks."

"Most recently, Lynn and Rowe have 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 r=0.17 (p<0.01)."

"Regression toward the mean provides still another way to test if race differences are genetic. Regression toward the mean is seen, on average, when high IQ people mate and their children are less intelligent than their parents. This is because the parents pass on some, but not all, of their exceptional genes to their offspring. The converse happens for very low IQ parents; they have children with 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. It's like rolling a pair of dice and having them come up two sixes or two ones. The odds are that on the next roll, you'll 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 lesser the closer the degree of kinship (e.g. identical twin > full-sibling > half-sibling). Culture-only theory makes no systematic or quantitative predictions based on genetic kinship per se."

"For any trait, regression predicts that scores will move towards the average for that race. 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, while children of White parents of IQ 115 will regress toward the White IQ average of 100. There are similar predictions for the low end of the scale. Children of Black parents of IQ 70 should move up toward the Black IQ average of 85, while children of White parents of IQ 70 should move up toward the White IQ average of 100. Regression to the mean has been tested and the predictions proved to be true many times over. But more importantly, both the White and Black groups show the same degree of regression throughout the entire range of IQs between plus or minus 3 SDs from the group mean. The Law of Regression also explains why Black children born to high IQ, wealthy Black parents have test scores two to four points lower than do White children born to low IQ poor White parents. The high IQ Black parents were unable to pass on their advantage to their children. even though they gave them a good upbringing and good schools. (The same phenomenon, of course, is also found for high IQ White parents.) Again, no culture-only theory predicts these results."
 
"When deciding whether genes are involved in the Black-White average IQ difference, or whether culture-only theory is correct, the following results should be considered. First, the mean difference in IQ scores has scarcely changed over the past 100 years (despite repeated claims that the gap is narrowing) and it can be observed as early as three years of age . Controlling for overall socioeconomic level only reduces the mean difference by 4 IQ points. Culture-fair tests tend to give Blacks slightly lower scores, on the average, than do more conventional tests, as do non-verbal tests compared with verbal tests, and abstract reasoning tests compared with tests of acquired knowledge. Also, the Black-White differences show up on the g-factor extracted from culture-fair reaction time tests. The pattern of race differences shown in Table 9.4 is consistent across time and nation. Environmental explanations must account for all these differences in IQ, brain size, myopia, speed of dental development, age of sexual maturity, testosterone level and number of multiple births. Genetic theory provides a single parsimonious explanation for all of them."

"Most pieces of the scientific puzzle for why Blacks average lower IQ scores than do Whites are now falling into place. For example, the conclusion that intelligence is related to brain size and that there are racial differences in brain size, is becoming accepted. Ulric Neisser, Chair of the recent American Psychological Association's Task Force Report on The Bell Curve, acknowledged 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.' Moreover, the average Black-White differences are now established using independent data sets and different test instruments around the world, in southern Africa and in the Netherlands, as in the United States. All are Jensen Effects. As Spearman predicted, those sub-tests that show the most pronounced Black-White differences are typically the ones with the highest g-loadings."

"It is important to know that the Spearman-Jensen hypothesis is robust and that g is the same in southern Africa and the Netherlands as it is in the U.S. This tells us that the largest single source of Black-White differences around the world is essentially the same as the source of differences between individuals within each racial group namely, g. This implies that a scientific understanding of Black-White, indeed of many individual, group and developmental differences, depends on understanding the nature of g. Race differences are not due to idiosyncratic cultural peculiarities in this or that test but to a general factor that all the ability tests measure in common."

"Jensen's default hypothesis views mean population differences in g simply as aggregated individual differences and they are explainable by the same principles, thereby not violating Occam's razor by invoking unnecessary ad hoc hypotheses. Jensen's hypothesis is consistent with a preponderance of psychometric, behavior-genetic and evolutionary lines of evidence. And like true scientific hypotheses generally, it continually invites empirical refutation."

"Jensen's methodological and theoretical analyses have distilled the deep essence of intelligence. Jensen has gone beyond proving the statistical reality and predictive validity of the general factor. He has shown Spearman's g to be a keystone of the behavioral sciences. If future psychometricians 'see further', it will only be by standing on the shoulders of these two giants: Spearman and Jensen."

Nyborg introduces Part IV on "The g Nexus":

"Arthur Jensen wrote in 1998 in his major opus The g factor: 'The g factor derives its broad significance from the fact that it is causally related to many real-life conditions, both personal and social. These relationships form a complex correlational network, or nexus, in which g is a major node. The totality of real-world variables composing the g nexus is not yet known, but a number of educationally, socially, and economically critical elements in the nexus have already been identified and are the subject of ongoing research'. He further wrote that it seems likely that '... g acts only as a threshold variable that specifies the essential minimum level required for different kinds of achievement. Other, non-g special abilities and talents, along with certain personality factors, such as zeal, conscientiousness and persistence of effort, are also critical determinants of educational and vocational success        . Future g research will extend our knowledge in two directions. In the horizontal direction, it will identify new nodes in the g nexus, by studying the implications for future demographic trends, employment demands and strategies for aiding economically developing countries. Research in the vertical direction will seek to discover the origins of g in terms of evolutionary biology and the causes of individual differences in terms of the neurophysiology of the brain.'"

Marxists continue to deny the existence of g, general intelligence or mental ability, trying to claim that since we can't define the genes responsible, then it just does not exist. And yet they accept that gravity exists, even though physicists still do not know what it is. All they have left to refute Jensenism is to claim that science is inadequate to know anything for certain primarily where they do not like the results. Yet they accept all kinds of other predictive validities, like being able to fly in an airplane long before the exact nature of fluid mechanics were understood. And yet, these same people would be very upset if they flew in an airplane with a pilot that was randomly selected from the population, given X number of hours of instruction, and then told to go fly a jumbo jet without any testing or proof of ability. These positions of denial are no different from the Christian creationists' denial of evolution. They also claim, that evolution is just a theory and cannot be proven. True, but science is not about perfect proofs but building upon the existing best theories or hypothesis; and it has taken us to the moon, cured disease, and given us an endless number of technological marvels.

The left has also tried to use the "Flynn effect" as proof that intelligence is malleable because intelligence test scores have been rising over the last few decades. Unfortunately, few believe that real intelligence is rising, and some disheartening results of research do not bode well for the less intelligent. As Spitz explains:

"There is an interesting sidelight to results of repeated testing on the different intelligence scales. The low intelligence groups do not perform better on the later tests, contrary to expectations based on the 'Flynn effect'. Flynn had found that with individuals of average intelligence, the standardization group scored higher on the second, later test, thereby making it more difficult to get a high score on the second test than on the first and also indicating a rising intelligence. But, surprisingly, just the opposite happens when low IQ groups take both the WAIS and, many years later, the WAIS-R, which was normed 27 years after the WAIS.Other findings supported this finding of a negative Flynn effect at the lower end of the intelligence curve. (The typical Flynn effect disappears but apparently does not reverse at the higher end of the curve.) The WAIS-R minus WAIS curve across the intelligence spectrum is so orderly (bow shaped) that a regression equation nicely describes the data. Are most people getting smarter while people with low intelligence are getting less intelligent? Not likely. Flynn attributed the contradictory findings in part to inadequate sample sizes in the standardization group at the lower intelligence levels. He had wisely recognized that allowances for massive gains in IQ might apply only for scores ranging from 90 to 110, but he did not predict that a lawful, gradually increasing reverse effect might be found below that range. This is another example of how, for whatever reason, the use of groups with low intelligence can occasionally produce surprises for unwary investigators."

Christopher R. Brand, Denis Constales & Harrison Kane comment on the Flynn effect: "When an appeal to 'interactionism' is thought too risky or over-used, the second refuge is in the work of James Flynn (e.g. 1984) telling of the secular rise in IQ-test scoring that was first noticed in 1948. Unfortunately for this notion, these test-score gains are greatest on sub-tests of copying skill [Coding or Digit Symbol] that are relatively poor measures of g (Rushton 1999); and no-one has ever explained them or been able to speed them up. Flynn himself had hoped that Black test scores might be rising as fast as those of Whites once did; and Hunt (1999) still thought the Black-White gap was 'clearly decreasing' and had already declined to 0.8 SD units (i.e. 12 IQ points). However, Murray (1999) reported National Longitudinal Survey of Youth data from the previous generation showing no closing of the racial gap in fluid g; Nyborg & Jensen (2000) found a highly significant (p<0.00001) Black-White difference of 1.174 in psychometric g in a sample with an N of 4,037; and in 2000 the U.S. federal Department of Education said the Black-White gap in reading had actually been increasing through the 1990s leaving the average Black 17-year-old of 2000 reading only about as well as the average White 13-year-old. Statewide achievement testing in New York State in 2002 found large race differences persisting that could not readily be attributed to the socio-economic backgrounds of pupils (Hartocollis 2002)."

Ackerman and Lohman shed additional light on g and the Flynn effect: "From Gustafsson's analysis of extant literature, g is essentially equivalent to Cattell's conceptualization of fluid intelligence (Gf) which in turn is best identified by measures of reasoning and working memory.[The Flynn effect] increases in the average raw scores of successive generations of samples during the 20th Century in several countries, might be at least partly attributable to the increase in average number of years of schooling in these populations."

"Ceci argued that even if one or more of these sources of evidence are not necessarily decisive in showing that schooling positively affects intelligence level, in the aggregate, these data are concordant with such a proposition. It is important to note, though, that Ceci also argued that it is the amount of formal schooling that influences the growth of intelligence, rather than the quality of formal schooling. That is, studies of the quality of the educational experience have been far more inconsistent in supporting a linkage with increasing levels of intelligence."

With regards to the Flynn effect, education, and malleability, we can draw several observations. Those population groups that have large numbers of people with low intelligence (low average IQ) will not benefit from better schooling, and may not be able to access "catch up" by any environmental intervention aside from perhaps prenatal care, vaccinations, vitamin supplements, etc. That is, the IQ will not be closed easily, with or without the Flynn effect or educational enhancements. A person needs a minimum level of g or mental ability to be able to benefit from increased schooling. The others will just become frustrated and give up, unable to grasp ever increasing complexities in both school and in life. And it only gets worse as people age:

"After a number of early studies on the constancy of the IQ indicated that change in IQ levels for infant and child subjects were not correlated with initial status, Anderson suggested the 'overlap hypothesis' as an explanatory mechanism. In Anderson's formulation, 100% of intelligence is present in an individual at 'terminal status' (presumed by Anderson to be around age 16). At earlier ages, progressively smaller portions of intelligence are present in the individual, such that for the child entering school, perhaps only 40-50% of the child's intelligence is actually developed. While Anderson's proposition was based on a relatively small set of longitudinal studies, the general sense of the overlap hypothesis suggests an important limitation on the role of schooling on intelligence. That is, as a larger proportion of intelligence is obtained (e.g. as the individual grows in age close to 'terminal status') the malleability of intelligence decreases. Identical educational interventions could thus be expected to have the greatest impact on younger children than older children. Today, there are differing views on this perspective indeed some researchers suggest that failures in attempts to raise IQ (such as Head Start) falsify both the overlap hypothesis and any general notions that intelligence is malleable. However, such arguments are consistent with Ceci's proposition that the quality of education is generally unrelated to improvements in intelligence, while the quantity of schooling is indeed related to intelligence change."

Gottfredson then explains why g is so important:

"Like the individual items on an IQ test, no single life task is likely to be very highly g loaded. g's impact in life may therefore stem largely from the consistency of its influence in long streams of behavior that is, from virtually all life activities being g loaded to at least some small degree. Other factors are often more important than g in correctly answering any one particular IQ test item, but none has such a consistent influence throughout the test as does g. That is the secret of why IQ tests measure g so well the 'specificities' in the items cancel each other out when enough items are administered, but the effects of g accumulate. Perhaps so in life too. Might the many weakly g-loaded actions in life cumulate in the same manner to account for g's often strong and always robust correlations with the various overall outcomes in life, good and bad (good education, jobs, and income vs. unemployment, out-of-wedlock births, and incarceration)?"

"What evidence is there that life is like a mental test battery, in particular, a highly g-loaded one? Some have claimed, for instance, that the general mental ability factor, g, is only 'a tiny and not very important part' of the mental spectrum and that it 'applies largely, although not exclusively, to academic kinds of tasks.' If that were so, then pursuing the foregoing questions would yield useless answers. The considerable evidence about occupations, employment and career development shows, however, that differences in g play a powerful role in the world of work."

"Next to educational achievement, job performance has probably been the most exhaustively studied correlate of general intelligence. Personnel selection psychologists and job analysts have performed many thousands of studies to determine which aptitudes and abilities different jobs require for good performance. The large status attainment literature in sociology has correlated academic ability (it eschews the term intelligence) with life outcomes such as occupational level and income at different ages. These psychological and sociological literatures are not only vast but also provide a valuable contrast: namely, whereas on-the-job performance is a proximal, short-term correlate of g, occupation and income level are more distal, cumulative outcomes because they represent the culmination of a long process of developing and exercising job-related skills as well as negotiating an elaborate social system. This distinction between proximal and distal, discrete and cumulative outcomes becomes very important, as we will see, in understanding g's role in other domains of life, from daily health self-care to ending up with illegitimate children or a prison record."

"Personnel researchers have collected extensive data on the aptitude and task demands of different jobs in order to improve hiring and training procedures, rationalize pay scales, and the like. Sociologists have collected parallel data on the socioeconomic requirements and rewards of occupations in order to better understand the nature and origins of social inequality. When factor analyzed, both sets of data reveal a task complexity factor among job demands that coincides with the occupational prestige hierarchy. What Figure 15.1 only suggested, the job analysis data prove: there is a g-demands factor dominating the occupational structure that parallels the g-skills factor dominating the structure of human mental abilities."

"Table 15.4 summarizes the pattern of findings from the job performance literature. It is based on a review of several large military studies as well as the major meta-analyses for civilian jobs. Its first general point, on the 'utility of g', is that g (i.e. possessing a higher level of g) has value across all kinds of work and levels of job-specific experience, but that its value rises with: (a) the complexity of work; (b) the more 'core' the performance criterion being considered (good performance of technical duties rather than 'citizenship'); and (c) the more objectively performance is measured (e.g. job samples rather than supervisor ratings). Predictive validities, when corrected for various statistical artifacts, range from about 0.2 to 0.8 in civilian jobs, with an average near 0.5. In mid-level military jobs, uncorrected validities tend to range between 0.3 and 0.6. These are substantial. To illustrate, tests with these levels of predictive validity would provide 30% to 60% of the gain in aggregate levels of worker performance that would be realized from using tests with perfect validity (there is no such thing) rather than hiring randomly."

"The next point of Table 15.4, on g's utility relative to other 'can do' components of performance, is that g carries the freight of prediction in any mental test battery. Specific aptitudes, such as spatial or mechanical aptitude, seldom add much to the prediction of job performance, and they provide such increments only in narrow domains of jobs. General psychomotor ability can rival g in predictive validity, but its value rises as job complexity falls, which pattern is opposite that for g."
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Table 15.4: Major findings on g's impact on job performance'.
Utility of g
(1) Higher levels of g lead to higher levels of performance in all jobs and along all dimensions of performance. The average correlation of mental tests with overall rated job performance is around 0.5 (corrected for statistical artifacts).

(2) There is no ability threshold above which more g does not enhance performance. The effects of g are linear: successive increments in g lead to successive increments in job performance.

(3) (a) The value of higher levels of g does not fade with longer experience on the job. Criterion validities remain high even among highly experienced workers. (b) That they sometimes even appear to rise with experience may be due to the confounding effect of the least experienced groups tending to be more variable in relative level of experience, which obscures the advantages of higher g.

(4) g predicts job performance better in more complex jobs. Its (corrected) criterion validities range from about 0.2 in the simplest jobs to 0.8 in the most complex.

(5) g predicts the core technical dimensions of performance better than it does the non-core "citizenship" dimension of performance.

(6) Perhaps as a consequence, g predicts objectively measured performance (either job knowledge or job sample performance) better than it does subjectively measured performance (such as supervisor ratings).

Utility of g relative to other "can do" components of performance
(7) Specific mental abilities (such as spatial, mechanical or verbal ability) add very little, beyond g, to the prediction of job performance. g generally accounts for at least 85-95% of a full mental test battery's (cross-validated) ability to predict performance in training or on the job.

(8) Specific mental abilities (such as clerical ability) sometimes add usefully to prediction, net of g, but only in certain classes of jobs. They do not have general utility.

(9) General psychomotor ability is often useful, but primarily in less complex work. Their predictive validities fall with complexity while those for g rise.

Utility of g relative to the "will do" component of job performance
(10) g predicts core performance much better than do "non-cognitive" (less g-loaded) traits, such as vocational interests and different personality traits. The latter add virtually nothing to the prediction of core performance, net of g.

(11) g predicts most dimensions of non-core performance (such as personal discipline and soldier bearing) much less well than do "non-cognitive" traits of personality and temperament. When a performance dimension reflects both core and non-core performance (effort and leadership), g predicts to about the same modest degree as do non-cognitive (less g-loaded) traits.

(12) Different non-cognitive traits appear to usefully supplement g in different jobs. just as specific abilities sometimes add to the prediction of performance in certain classes of jobs. Only one such non-cognitive trait appears to be as generalizable as g: the personality trait of conscientiousness/integrity. Its effect sizes for core performance are substantially smaller than g's, however.

Utility of g relative to the job knowledge
(13) g affects job performance primarily indirectly through its effect on job-specific knowledge.

(14) g's direct effects on job performance increase when jobs are less routinized, training is less complete, and workers retain more discretion.

(15) Job-specific knowledge generally predicts job performance as well as does g among experienced workers. However, job knowledge is not generalizable (net of its g component), even among experienced workers. The value of job knowledge is highly job specific; g's value is unrestricted.

Utility of g relative to the "have done " (experience) component of job performance
(16) Like job knowledge, the effect sizes of job-specific experience are sometimes high but they are not generalizable.

(17) In fact, experience predicts performance less well as all workers become more experienced. In contrast, higher levels of g remain an asset regardless of length of experience.

(18) Experience predicts job performance less well as job complexity rises, which is opposite the trend for g. Like general psychomotor ability, experience matters least where g matters most to individuals and their organizations.
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Some of Gottfredson's other interesting findings include:

"As we saw, g is more important than personality traits in predicting performance of core technical duties (decontaminating equipment, repairing an engine, determining grid coordinates on a map, and so on), but it is less predictive in activities of a more interpersonal or characterological nature (being a reliable worker or helpful team-mate, showing leadership, impressing superiors and the like). For purposes of understanding the social consequences of g, we might therefore distinguish tasks not only along a complexity dimension, but also along a continuum from instrumental to socioemotional, as shown in Figure 15.2. We might expect the g loadings of tasks to be highest in the upper left corner (complex instrumental tasks), and to drop steadily for tasks located nearer the lower right corner of Figure 15.2 (simple and socioemotional)."

"Differences in g are clearly a major predictor of differences in career success, but why? The answer is not as obvious as it is for proximal outcomes such as on-the-job performance. Sociologists and economists have put much effort into modeling the interrelated processes of how people "get ahead" on the educational, occupational and income hierarchies. Their statistical modeling suggests that "academic ability" (whether measured as IQ or standardized academic achievement) has both direct and indirect effects on each successive outcome in the education-occupation-income chain of development. Cognitive ability is by far the strongest predictor of education level relative to others studied (0.5-0.6 for IQ vs. 0.3-0.4 for parents' socioeconomic status), and therefore seems to have large direct effects on how far people go in school. Educational level is, in turn, the major predictor of occupational levels attained. After controlling for educational attainment, mental ability's direct effect is much smaller on occupational than educational level, but still larger than the influence of family background. Jencks et al. summarize mental ability as having a "modest influence" through age 25 in boosting young adults up the occupational ladder. Much the same pattern is found for earnings, after controlling for both education and occupation the impact of IQ is mostly indirect. However, the direct effects of cognitive ability on earnings grow with age, leading Jencks et al. to comment that IQ's direct effects are "substantively important" for raising earnings through at least middle age."

"The causal question is still a major one, however, when the job outcomes at issue are broader, more personally consequential ones such as occupational prestige and income level attained. Although many social scientists still assume that intelligence is a result rather than a cause of social class differences, research continues to show the opposite. Sibling studies, for instance, provide evidence that g does, in fact, have a big causal influence and that social class has a comparatively weak one on children's adult socioeconomic outcomes. Biological siblings differ two-thirds as much in IQ, on the average, as do random strangers (12 vs. 17 IQ points). Despite growing up in the very same households, their differences in IQ portend differences in life outcomes that are almost as large as those observed in the general population. Even in intact, non-poor families, siblings of below average intelligence are much less likely to have a college degree, work in a professional job, and have high earnings than are their average-IQ siblings, who in turn do much less well than their high-IQ siblings."

"Specifically, about 40%, 25% and 20% of the total (phenotypic) variation in education, occupation and income, respectively, can be traced to genetic influences that each shares with g. These overlapping heritabilities provide additional evidence that much variation in socioeconomic outcomes can be traced back to variation in g, in this case, to its strictly genetic component. In fact, behavioral genetic research has shown that most social environments and events are themselves somewhat genetic in origin."

"Jobs collectively represent a vast array of tasks, both in content and complexity. While not reflecting the full range of tasks we face in daily life, many of them are substantially the same, from driving to financial planning. There is no reason to believe that g and other personal traits play a markedly different role in performing these same tasks in non-job settings, because g is a content- and context-free capability. To take just one example, the likelihood of dying in a motor vehicle accident doubles and then triples from IQ 115 to IQ 80."

"To the extent that there is overlap between the task domains of work and daily life, the research on jobs and job performance forecasts what to expect from research on daily life. Namely, we will find that the many "subtests" of life range widely in their g loadings; that people "take" somewhat different sets of subtests in their lives; that their own g levels affect which sets they take, voluntarily or not; that life tests are even less standardized than jobs, which further camouflages g's impact when taking any single life test; that life's full test battery is large and long, giving g more room to express itself in more cumulative life outcomes; and that social life (marriage, neighborhoods, etc.) will frequently be structured substantially along g lines."

"More specifically, the research on job duties and job performance describes the topography of g's impact that we can expect to find in social life: higher g has greater utility in more complex tasks and in instrumental rather than socioemotional ones; g's utility can sometimes swamp the value of all other traits, but many other traits can also enhance performance and compensate somewhat for low g; and the practical advantages of higher g over a lifetime probably rest as much on the steady tail wind it provides in all life's venues as on its big gusts in a few."

"In a separate study of patients with chronic illnesses such as diabetes and hypertension, generally only about half of those with inadequate literacy knew even the most basic facts about their disease or how to cope with it, despite presumably having received instruction. Table 15.8 shows, for instance, that among diabetic patients with inadequate literacy, 62% did not know that they need to eat some form of sugar if they suddenly get sweaty, nervous or shaky (a signal that their blood sugar has dropped too low also a fact that only about half knew)."

"Few functional literacy tasks may be discretionary if individuals want to protect their health and welfare over the long-run. It may matter little whether one occasionally fails to adequately describe the problems with an appliance needing repair, select the best values in a supermarket, capitalize on opportunities for cheaper goods and services, identify available social services, understand public issues affecting one's welfare, take medication properly, or recognize the symptoms of one's chronic illness that require immediate action, such as an imminent asthma attack or insulin reaction. Repeated such failure, however, especially across multiple arenas of life, can threaten one's health, disposable income and overall quality of life. Research on health literacy indicates, for example, that low-literacy individuals experience much higher health costs, poorer health and more frequent hospitalization (National Work Group on Literacy and Health 1998)."

"The heated debate over The Bell Curve revealed, once again, that many if not most policy researchers assume that differences in intelligence do not play much role in who exhibits the behaviors that policy makers seek to reduce. They nonetheless seem willing to attribute causal importance to what are actually good surrogates for g for instance, literacy and "basic skills" if they attribute them to socioeconomic disadvantage rather than to g. To illustrate, a well-received 1988 report for the Ford Foundation "explores the basic-skills crisis, presenting evidence that inadequate skills are an underlying cause of poverty and economic dependency." What was their measure of "basic skills?" The highly g-loaded AFQT. The report's authors concluded from their data that poverty is rooted substantially in skills deficits, but they minimize the implications of this by mistakenly conceiving "basic skills" as a collection of highly specific, discrete, remediable skills rather than a suite of relatively stable, highly general ones. In fact, as the bottom panel of Table 15.9 shows, risk gradients for siblings growing up in the same household parallel those in the general population for similar outcomes. This provides additional evidence that g plays a strong role independent of one's family circumstances."

"There are many other areas of life yet to be plumbed with the psychometric tools to which Jensen has pointed us. At the individual level, they include interpersonal relations, parenting and family life, health and safety, good citizenship, civic engagement and aging. As g-based gradients of risk play out at the individual level, they yield higher-order effects that are also ripe for study: g-based residential and social segregation; patterns of cooperation and competition, envy and respect, compassion and contempt; political tensions between populations that differ noticeably in g; evolution of social policy, law and mores in response to g-based social inequalities; the special difficulties of stemming preventable epidemics in some populations; and much more."

Ellis and Walsh provide additional data on crime, delinquency and intelligence, confirming what  J. Philippe Rushton has stated in his seminal book Race, Evolution, and Behavior: a life history perspective, 1995:

"The conclusion reached by Hirschi and Hindelang was sharply criticized by a number of social scientists, while others defended the conclusion. Since the Hirschi and Hindelang article appeared, at least three selective reviews of the IQ-crime relationship have been published, all of which have characterized the relationship as ubiquitous and robust."

"Despite a reawakening of interest in the intelligence-criminality in the 1970s, today's criminologists continue to play down the role of intelligence in explaining delinquent and criminal behavior. Evidence in this regard comes from a recent survey of criminologists, which found low intelligence ranked 19th among factors that were considered important causes of serious and persistent offending. Furthermore, it is ironical to note that even though Hirschi has played an important role in drawing attention to the substantial relationship between intelligence and offending, the theory of delinquency and crime to which he subscribes control theory itself offers no specific explanation for why such a relationship should exist."

"Given that nearly a quarter of a century has passed since the last exhaustive review of the intelligence-criminality relationship was published, an updated review is in order. To make the review as condensed as possible, we have organized the relevant references into two tables. One table deals with intelligence in general, and the other has to do with a phenomenon known as intellectual imbalance. As will be explained more later, intellectual imbalance refers to significant inconsistencies in scores between the two main components of standardized tests: the linguistic and the non-linguistic component."

"Besides investigating the relationship between overall intelligence and offending behavior, numerous researchers have decomposed intelligence tests into their two main factorial components and compare each component to offending behavior. The result of this research has led to the identification of what is termed intellectual imbalance. Basically, if an individual scores significantly higher on one component of an IQ test than on another, he or she is said to be intellectually imbalanced. One can be intellectually imbalanced in either of two directions: the VIQ score can significantly exceed the PIQ, or vice versa."

"Studies undertaken to determine if offenders are more likely to be imbalanced than persons in general are cited in Table 16.2. As one can see, the research indicates that offenders are more often imbalanced, and that the direction of the imbalance is in a specific direction: PIQ scores tend to exceed VIQ scores. This suggests that it is primarily the linguistic portion of standardized IQ tests that are unusually low among delinquents, criminals and persons with antisocial personalities. In other words, on average, offenders are nearer to the mean (or even above it) with regard to PIQ than regarding VIQ. Most of the studies that have documented this imbalance have found the deficit to be in the range of 3 to 5 IQ points."

"By way of qualifications, two points are worth making. First, Table 16.2 shows that about 20% of the studies have not found a significant VIQ-PIQ difference. This is to be expected given the relatively small sample size in several of these studies. Second, one study actually found a significant difference in the opposite direction. Interestingly, this study is the only one pertaining to self-reported drug use. Given that Table 16.1 also revealed an excess of incongruous findings in regarding to self-reported drug use, we suspect that people whose offenses are confined to drug use are cognitively distinct from offenders who primarily engage in what we have termed victimful offending."

"Some have interpreted the inverse relationship between IQ and crime as simply reflecting the tendency for low IQ offenders to be arrested and convicted at higher rates than high IQ offenders. There are three problems with this the 'dumb-ones-get-caught' argument."

"First, it is not just in official data that an inverse correlation has been found, but as shown in Table 16.1, most self-report data show the same pattern, except in the case of illegal drug use. Second, the dumb-ones-get-caught argument does not explain why below average IQ scores are also found among children with conduct disorders, a diagnosis that nearly always precedes the onset of official delinquency. Third, as was noted above, intelligence does not appear to predict recidivism among incarcerated offenders. If the dumb-ones-get-caught argument had merit for explaining major variations in the offending-IQ relationship, one would expect the relationship to be true for recidivism as well. Nevertheless, it should be conceded that the IQ range in prison populations is substantially restricted to a below normal range, which places mathematical constraints on uncovering any small residual relationship that may exist."
 
"Others have suggested that the relationship between intelligence and offending may just reflect the link that both of these variables have with parental social status. In other words, because persons with high IQs tend to be reared by parents of high social status, and because offenders tend to be of low social strata (see below), the link between intelligence and criminality may be spurious. This possibility has been directly investigated, and found to be wanting based on three lines of evidence. First, studies have found that even after controlling for parental SES, a significant relationship continued to exist between low IQ scores and criminality. Second, a review of the SES-offending relationship concluded that this relationship was much better established in the case of individual (achieved) social status than in the case of parental (background) social status. The opposite would be expected if it is parental status per se that is responsible for the IQ-criminality relationship. Third, even among siblings, one finds a negative correlation between IQ and criminality/delinquency. In other words, the IQ scores of criminal and delinquent siblings is 8 to 10 points lower than the scores for same-sex siblings with no offending history. All three of these lines of evidence argue against the view that the IQ-criminality link can be dismissed as an artifact of parental social status."

"In light of the evidence that the relationship between intelligence and offending is real, it is somewhat surprising to find how few theoretical attempts have been made to explain the relationship, either singularly or in conjunction with the PIQ > VIQ relationship. None of the leading theories in criminology today offer an explicit explanation, particularly for the PIQ > VIQ relationship."

"For those of us who teach criminology, it is disappointing to note how many texts in the field leave students with the impression that the jury is still out with respect to there being an IQ-offending relationship. Our suspicion is that there are two main reasons for lingering ambiguity in the face of strong evidence: First, criminologists may not be aware of the vast number of studies that have been conducted, and the consistency of their findings. Hopefully, the present review will help to inform them in this regard."

"Second, most criminologists (and other social scientists) still seem to be uncomfortable with the IQ-offending relationship, since most of them still strongly favor the nurture side of the nature-nurture controversy."

"The third theory actually consists of varying proposals regarding the role of evolutionary forces in setting the stage for criminal behavior. These proposals converge on the following idea: that some individuals approach reproduction by emphasizing mating effort (i.e. having sex often, especially with numerous partners). while others emphasize a parenting approach (i.e. investing heavily in caring for a few offspring). Other theorists refer to essentially the same idea by distinguishing an r-approach to reproduction and a K-approach. According to these theoretical proposals, individuals who focus on mating effort (an r-strategy) should exhibit a variety of behavior patterns that facilitate having numerous children in a brief amount of time. These interconnected behavior patterns often entail obtaining resources rapidly by whatever means, using the resources to attract sex partners, and employing other relatively inconsiderate methods of securing and controlling sex partners. In short, they are highly antisocial."

"Because the methods used to succeed at a mating effort approach to reproduction tend to be crude and short term, those who use these methods have not been enfavored for developing high intelligence or long term planning abilities. For individuals who emphasize parenting effort, on the other hand, intelligence and long term planning become premium commodities. To reproductively succeed using parental effort usually requires establishing a lasting relationship with a sex partner, and then cooperating to rear and nurture a few children to do likewise in the next generation."

"If evolutionary thinking along these lines is correct, genes should be making a substantial contribution to criminal behavior as well as to traits such as intelligence and the ability to plan ahead. We have recently shown that the evidence now strongly supports the 'genetic influence hypothesis' regarding criminal/antisocial behavior. Others in the present volume will build the case for genetic influences on intelligence. This leads us to predict that several of the same genes that increase intelligence will serve to inhibit involvement in criminal/antisocial behavior."

Barrett, Kramen and Lueke discuss the legal implications of using intelligence for employee selection and how many of the new folk-psychology approaches have zero validity:
 
"In the 1920s and 1930s basic theories of intellectual ability were developed along with operational tests which proved effective in predicting job performance. In a series of studies and meta-analyses throughout the 1970s and 1980s, Schmidt and Hunter showed that cognitive ability was the best overall predictor of job performance. Partially in reaction to the meta-analytic findings, research to expand on the definitions of competencies continued. The development of competencies by McClelland was followed by a discussion of tacit knowledge, practical intelligence, and multiple intelligence. In the 1990s, emotional intelligence became the intelligence of interest."

"All these new theories and proposed measurement instruments pose a challenge to traditional cognitive ability tests since it is claimed that these tests are more valid and have lower adverse impact. It is our contention that many of these tests are nothing more than pop psychology. It is distressing to see such books quoted as if they had some merit. We will review the themes present throughout all of these "creative" concepts and examine whether they have practical implications and can withhold legal scrutiny in the public and private sector."

"It is our opinion that despite all these theorists' claims of validity, if challenged in court, they would fail. The Daubert Standards for scientific tests are a set of guidelines for admissibility of scientific evidence into court (see Table 19.1)."
----
Table 19.1: Daubert criteria.
1)   The theory must have been tested, or is at least able to be tested.
2)   The theory (& expert) must have (been) published in peer reviewed publications.
3)   There must be a known or potential error rate.
4)   The theory must be generally accepted in the relevant scientific community.
5)   The methods for testing the theory must meet scientific standards.
----
"The criteria were set forth in Daubert v. Merrell Dow Pharmaceuticals (1993) and clarified through subsequent supreme court cases (General Electric Company v. Joiner 1997; Kumho Tire Company Ltd. v. Carmichael 1999) and federal district and appeals court cases (e.g. Black v. Rhone-Poulenc 1998; Butler v. Home Depot, Inc. 1997; Camp v. Lockheed Martin Corporation 1998; Clark v. Takata Corp. 1999; Gerlib v. R. R. Donnelley & Sons Co. 2001; Smith v. Ford Motor Co. 2000). (See American College of Trial Lawyers 1994, and Barrett 2000, for a discussion). In the U.S., the Daubert standards pertain to any selection instrument used or advocated by a plaintiff. This is part of American case law, but the basic principles of scientific standards are relevant to everyone considering a particular measure or construct's use for personnel selection."

"If a practitioner were to attempt to defend this study as evidence of the validity of tacit knowledge for predicting job performance, the study would certainly not meet the Daubert criteria. The theory was not tested and the methods used to test the theory would not meet scientific standards for test validation (APA 1999; EEOC 1978, 1980; SLOP 1987)."

"There have been studies that have attempted to empirically demonstrate a relationship between tacit knowledge and job performance. Wagner & Sternberg conducted a study at the Center for Creative Leadership using tacit knowledge to predict performance on two managerial simulations: Earth II and Energy International. Tacit Knowledge (or street smarts) was defined as the "work-related practical know-how that is learned informally on the job" and was measured by the Tacit Knowledge Inventory for Managers (TKIM), which consists of a series of work related situations. Wagner and Sternberg concluded that "scores on research measures of street smarts are quite predictive of ability to learn to solve practical problems in the office" (see Table 19.4)."

"The first of the Daubert criteria states that the theory must have been tested, or is at least able to be tested. Gardner [multiple intelligence] admits that he is not going to develop tests and attempt to empirically prove his theory. This admission would automatically rule out his expert testimony and preclude his concept of multiple intelligences from having any value for personnel selection in a real context. The concept of Emotional Intelligence also would fail to meet the Daubert standards, since there are no instruments which have demonstrated validity in predicting job performance. Goleman's  theory is so diffuse it can never be tested, while Mayer et al. have a theory but negative results. Competencies as developed by McClelland, Boyatzis, and Spencer & Spencer is not actually a theory that can be tested, but a process of obtaining scores based on expert responses. Many competencies rely on past performance, but there is no definition of the construct of past performance. This has not been done with the measures of specific intelligence described here. Tacit knowledge, has been criticized due to its lack of a coherent definition. Without a definable construct/latent trait, there is no way a coherent measure can be developed. Constructs need to be defined, measures need to be developed, tested and then cross-validated."

"The second of the Daubert criteria, that the theory (& expert) must have (been) published in peer reviewed publications, has also not been met by these new concepts. One of the outstanding features of all new concepts of intelligence is that they are primarily published in trade books and book chapters without adequate peer review. The number of actual publications in peer reviewed journals by these mentioned authors is very few, despite the fact that they have been around for 30 years."

"The third is that there must be a known or potential error rate. Within selection contexts, either insufficient data exists or the data show that the instruments are not valid. It is impossible to determine the number of true positives, true negatives, false positives and false negatives to be expected in using the technique."

"The fourth of the criteria says that the theory must be generally accepted in the relevant scientific community. All of the conceptualizations have been critiqued by practitioners and professionals in the area of Industrial/Organizational Psychology. It is doubtful that there is any acceptance of the concepts in the relevant field."

"The fifth of the Daubert criteria asserts that the methods for testing the theory must meet scientific standards. All of the attempts to validate the instruments discussed here use non-standard procedures. They confuse predictors and criteria, make unwarranted statistical adjustments to the data, try schemes of using experts to develop prototypes, and manipulate data to get desired results when all else fails. Finally, none of the studies have ever used a predictive validation design."

"All of the new concepts, including emotional intelligence, tacit knowledge, practical intelligence, competencies and multiple intelligence have common themes throughout their theories and research. These theorists start by claiming that cognitive ability is given too much weight and that other attributes are important in predicting job performance or life outcomes."

"Often these researchers interpret research results directly opposite to actual findings, leave out of their discussion any positive results for cognitive ability, cite unpublished research they claim supports their viewpoint, which is often unattainable, and ignore early research on the topic."

"The most egregious case of citing inaccurate evidence is Goleman, who cites hundreds of articles in professional literature to support his propositions. In examining these studies, we found that he was often factually incorrect in his reporting."

"Sternberg has also ignored evidence contradicting his theories. Colonia-Willner found that the TKIM did not predict job performance. However, this study has been completely ignored by Sternberg, as it does not support his theory that tacit knowledge should predict job performance."

"All of the 'novel' researchers claim that their new measures of competencies, emotional intelligence, practical intelligence and tacit knowledge have lower adverse impact when predicting job performance. There are three problems with this contention. First, there are very few examples, if any, demonstrating that any of these constructs actually predict job performance in real organizations. Second, we could find no evidence based on studies in any organization that these measures reduce adverse impact. Third, even when one considers personality tests, the alternative selection tests most researched as a means to reduce adverse impact, there is no conclusive evidence that a consistent reduction in adverse impact occurs. In fact, there is evidence that the use of a personality test in addition to a cognitive ability test may produce larger mean group differences than the use of a cognitive ability test alone."

Again, Rushton's work in r-K reproduction would indicate that not only are Blacks lower in intelligence, they are probably lower in conscientiousness or integrity as well. Therefore, when intelligence is combined with personality profiles, Blacks would score even lower than Whites than would be indicated by mental ability alone. There is no doubt however, that Leftist academics will continue to churn out new concepts and notions on human behavior in order to derail the massively validated research on intelligence, so that they can continue to provide hope that racial differences will some day just go away. So far they have failed miserably.

In fact, the academic left has been so overwhelmingly crushed by scientific advances in psychometrics that they have turned their backs on rigorous scientific methods and turned to old Marxian dialectics in new clothing. A recent article entitled "Crossroads, Directions and a New Critical Race Theory" in the Yale Law Journal by Mitu Gulati and Devon Carbado, Volume 112, Issue 7, 2003, exemplifies rationalizations used to return to just-so stories in place of using scientific principles that can be verified by others.

Gulati and Carbado admit that Critical Race Theorists (CRT) use narrative rather than more mainstream analytical tools for scientific inquiry. They give several reasons for doing so, and it is in line with postmodernism's retrenchment in rejecting science because they have not been able to utilize the tools to advance their agendas. They have slid into a secular religion of scientific denial. It is based on the use of collective fraud, where everyone in the movement agrees to ignore the falsifiability rule for constructing theories. Narratives (which include "autobiographies, self-portraits, allegories, fables, and fictive narratives") are used to try to show how Whites are evil and people of color are subjugated and oppressed.

Gulati and Carbado state that "First, narrative performs an epistemological function. It provides knowledge about the nature of discrimination from the perspective of those who experience it. But why narrative and why not statistical analysis? After all, statistical analysis (assuming a large enough data set) has the benefits of identifying a general phenomenon that is verifiable by third parties. And certainly there is nothing about the use of narrative in CRT that precludes critical race theorists from also using statistic. So why not the epistemology of statistics rather than (or in addition to) the epistemology of narrative? The answer may be that narrative does something that statistical analysis does not: It focuses on the specific and provides detail. Statistical analyses do the reverse. When an outsider is trying to describe an experience to someone who cannot readily relate to it, an insider, narrative provides the detail that can help the insider empathize and relate to the experience. To employ the language of Clifford Geertz, 'We see the lives of others through lenses of our own grinding.' Narrative helps to situate whites in the 'grinding' of racial subordination."

If we compare the above with medical practice, where a doctor-patient narrative is used by some doctors to form opinions about medicine based on anecdotal evidence, versus using rigorous studies used to determine the efficacy of different treatments, medicine would be retreating into the dark ages. In fact, the very definition of quackery often resembles narrative or anecdotal evidence by charlatans to push invalid medical practices and potions. This is rejected by peer reviewed medical journals, and yet it is alive and well by those who are trying to find racism in society that does not exist. They have no other way to proceed!

They then state that "A second payoff from using narrative relates to the idea of truth. Narrative is a means by which one can challenge 'the perfectibility, externality, or objectivity of truth.' Through narrative, critical race theorists can demonstrate the contingency and situatedness of truth. CRT arises in the context of contestations between critical race theorists and their detractors, the question of what is trueas well as the question of how truth should be theorizedis contested (sometimes only implicitly) within CRT as well." In short, they reject scientific proof, review and refutation because they have not developed the analytical tools to prove their case: that minorities are oppressed by the dreaded White males.

"A third benefit of narrative is that it can serve as a counter-hegemonic device. Through narrative, people of color can counter the dominant representations of their identities and their experiences; they can engage in what Margaret Montoya refers to as 'discursive subversions.'" Or flat out distortions of reality.

And finally, "A fourth payoff from using narrative is that it can function as a rhetorical strategy to rearticulate the ideological content of various legal regimes to demonstrate that, as Enrique Carrasco puts it, 'law is essentially a story that reflects and legitimates the (racial) viewpoints and interests of those in power.' Consider Sherene Razack's contribution to A New Critical Race Theory. She employs narrative to uncover the national story behind Canadian immigration law: 'Canada is besieged. Every Tom, Dick, and Harry wants to get in. They will stop at nothing. They do not respect us. They will return our generosity with betrayal. We have no choice but to become strict and to monitor more closely who is coming in.'"

Translation: if the majority does not agree with CRT advocates, they will use narratives or just-so stories to deny citizens the use of democratic processes to regulate society, in favor of overruling rights for all minorities that they chose to include in their assault on Whiteness.

Gulati and Carbado then plainly state their agenda, "In other words, while CRT is committed to the concept of institutional discrimination, there is little in the literature that articulates what this meansand even less that reveals how institutional racism is manifested in the context of the workplace."

So they have nothing left to do but plead the oppressed case through narrative and to condemn Whites by the same means. They are committed to the dogma that any disparity in outcomes between racial groups must be due to discrimination, because they have denied the possibility that different races have different levels of average intelligence. They have rejected the scientific approach and have turned to quackery.

Probably the most interesting chapter in this book is "The Sociology of Psychometric and Bio-behavioral Sciences: A Case Study of Destructive Social Reductionism and Collective Fraud in 20th Century Academia"        by Helmuth Nyborg. He describes how the left tried to undermine racial studies in intelligence and how they failed miserably in terms of research, but are hanging on through media indoctrination of the uninformed.

Nyborg discusses at length the book Defenders of the truth: The battle for science in the sociobiology debate and beyond, by Ullica Segerstrale, 2000. This book is the most complete and ongoing longitudinal study of its kind, but it fails to explain the real conflict that it describes the clash between primarily Jewish Marxists and White sociobiologists with some crossovers on each side. The closest she gets to admitting what everyone else can easily observe in this ongoing academic struggle is that the sociobiologists are primarily rural in their outlooks (that is White) while the Marxists are more Urban (that is Jewish). Everyone in these battles is aware of the Jewish/White imbalance in sides taken, but they rarely mention it because they will be charged with antisemitism. I will try to use Nyborg's analysis and at least ask some questions about the differences in ideologies between Jews and Whites to see if these differences are cultural or genetic. I would highly recommend that you read Nyborg's chapter first because it is a fascinating expose of the collective fraud practiced by the academic left.

Nyborg states that "Many of Jensen's opponents came from what can somewhat loosely be called the academic left. My first tentative hypothesis was, accordingly, that the demonization of Jensen was a simple function of a predominantly academic left-wing dissatisfaction with the notion of a largely inherent human inequality in intelligence, threatening their honorable idea of basic solidarity with the poor. This quickly appeared to be much too narrow an analytic framework, even if the gusty impact of the academic left remained central in the auspices of an extended model. The second part of the analysis, to be presented later, incorporates a number of semi-dependent variables that are useful for the full appreciation of the intricate pattern of collective fraud, spun in a worrisome unison by many parts of modern academia and the public. The variables will be defined as they are used, but a brief overview of all variables in the two-part study may help grasp the larger picture. Jensen wondered why he could not hear the voices of the remaining hundreds of social science professors in this discussion? Obviously, even first year students with a rudimentary understanding of fair play and knowledge of the basic rules of science ought to have felt obliged to set the record straight? Few did. As I will argue later, we here begin to see the vague contours of a far-reaching collective fraud with the purpose of framing Jensen. They could neither frame him on his data nor on his methods, but they could exploit the frontal collision between Jensen's politically incorrect mode 2 nature decision, and their own beloved Zeitgeist mode 2 nurture conviction."

I don't believe in conspiracy theories, plots and other collective actions where people meet to discuss their plans for domination or control. But humans do seem innately inclined to form collectives around their kin, race, profession or even sports. Humans are well-adapted at looking around at others and determining what is expected of them in terms of behavior and attitudes, and this is especially so when it comes to expressed opinions that are politically charged. Few humans are very autonomous; most are followers and can be easily manipulated to conform. But still, what explains the preponderance of Jews in the academic left and the preponderance of Whites pursuing behavior genetics and psychometrics? (Jensen is half Jewish, and is quite neutral on all matters political.)

Nyborg gives us Gould's response why the Left must fight the evils of scientific knowledge wherever it leads:

"If we do not counter [sociobiology and or Jensenism] we will see: '... resurgences of biological determinism correlate with episodes of political retrenchment ... or ... fear among ruling elites, when disadvantaged groups sow serious social unrest. What argument against social change could be more chillingly effective than the claim that established orders, with some groups on top and others at the bottom, exist as an accurate reflection of the innate and unchangeable intellectual capacities of people so ranked? Resurgences of biological determinism correlate with periods of political retrenchment and destruction of social generosity.' We must therefore raise awareness, that '...calls for solidarity among demeaned groups should not be dismissed as mere political rhetoric, but rather applauded as proper reactions to common reasons for mistreatment.'"

Is Gould really concerned about demeaned groups? Yes, I think he is, but it is not altruistic but tribal. Jews have a history of feelings of persecution; there religion is based on it, and their solidarity is maintained by it. Of course, not all Jews feel the threat of imminent persecutions and threats, yet they do tend toward tribalism/persecution concerns on average and especially in comparison to less ethnocentric races such as Whites. Their particularism is what makes them amenable to collective fraud when the need arises, while many Whites take on the guilt of being less than perfect in racial tolerance and join the academic left in attacking their own kin.

Gould goes on in his second edition of The Mismeasure of Man, "Critics of biological determinism are like members of a fire brigade, constantly being called out in the middle of the night to put out the latest conflagration, always responding to immediate emergencies, but never with the leisure to draw up plans for a truly fireproof building. Now it is IQ and race, now criminal genes, now the biological inferiority of women, now the genetic fixity of humans. All these deterministic fires need to be doused with the cold water of reason before the entire neighborhood is in flames."

Of course reason is where science and fraud separate, and Gould and his Jewish fire brigade want to throw out reason in favor of personal attacks. If the Jewish fire brigade relied on reason, they would get on with providing research, rather than attacking researchers. In science, the results are attacked, not the people who are just the messengers of different studies and approaches. Knowledge resides outside of human desires for utopian worlds.

Nyborg observes that, "It pays off to ponder again whether it is nature, and not Jensen, who stunts life and denies opportunities? Just think for a moment, if the new insight from the molecular and brain sciences is combined with behavioral genetics' brand new way of defining the impact of environmental factors (within versus between family, and shared versus nonshared), would hold the best promise for optimizing the conditions for the deprived? Gould never entertains such a possibility, because he sees evil plots everywhere, and surely knows whom to blame!" Jewish paranoia or real concern for the deprived?

Nyborg continues, "Segerstrale's analysis of the logic behind the critics' reasoning suggests that it was not traditionally scientific but rather of a moral-legalistic kind, applied to science, and here we are back once again to the moral reading strategy. When critics apply moral reading to texts, they: '... imagine the worst possible political consequences of a scientific claim. In this way, maximum moral guilt might be attributed to the perpetrator of this claim.'"

Again, this points to a Jewish penchant to see conspiracies against them everywhere, along with a moralistic/messianistic attribution to human behavior. The world cannot just be it must be directed by a special elite who have the ability to see truth beyond simple scientific truth. And only an exceptionalist elite can interpret this moralistic truth for all the nations. Whether Marxism, neoconservatism, or Ultra Orthodox Jewish history is replete with a feeling of a special Jewish mission for them over all others. As the religion subsides, this mission takes on a secular moralizing that results in the same "us versus them" stance of perpetual tribal warfare. The tribe must be hyper-vigilant at all times because others "are against us." Jews are so exceptional that they have to have their own particularistic name for racismantisemitism. Everyone one else is just a racist unless it is directed against a Jew.

Nyborg quotes Gross and Levitt from their 1994 book, Higher Superstition: The Academic Left and its Quarrels with Science:

"Gross and Levitt wanted, first of all to avoid muddle-headedness in their own quarter, so they set out to '...first define what unites the AL [Academic Left] individuals.' They found that ALs do not '...have a well-defined theoretical position with respect to science ... but a noteworthy uniformity of tone, and that tone is unambiguously hostile ... [toward] some of the uses to which science is put ... toward the system of education ... toward the actual content of scientific knowledge and toward the assumption ... [that] scientific knowledge is reasonably reliable and rests on a sound methodology' to an extent that 'irrationality is courted and proclaimed with pride' (pp. 2-3; authors' emphasis). The group of ALs, furthermore, typically comprises humanists and social scientists, rarely working physical scientists. ALs can often be identified under the umbrella of post-modernism in fields like literary criticism, social history, cultural studies, cultural constructivism, postmodern philosophy, feminist theory, deep ecology, deconstruction, and so forth."

These fields are highly overrepresented by Jews; the same imbalance that Jews decry for example in corporate America when it is White males that dominate (along with other Jews of course). Therefore, the question is why are Jews overrepresented in collective fraud, when they certainly have the intellect to grasp a "theoretical position with respect to science." Jewish scholars have been well represented in developing the theoretical framework of science, just as Whites have been well represented in developing new excuses to embrace religion and reject science (creationism, rapture, evangelicalism, etc.).

Gross and Levitt continue, "There is a sense of solidarity within the academic left, a solidarity of a political rather than an intellectual nature ... a preoccupation with science as power ... [a] distrust of experts ... [an] obsession with textual analysis...."

This sounds like Kevin MacDonald's (1994) research showing that Jewish eugenics came about through competition between Jewish scholar's ability to compete in textual analysis of Jewish religious writings writings which appear to be more concerned with "standing in" as a form of verbal and interpretive intelligence test than with religious matters. This selective process has produced an imbalance in Jewish intelligence that is much higher in verbal intelligence than practical intelligence. And this skill is now put to use by Jews in the academic left to attack science itself and they are superbly adept in their mission. Of course, most religious fundamentalists, cultists, etc. share a desire to supplant science with dogmatic facts, but they are not as talented at promoting their agendas in academia, politics, and government. Nor is the influence that high Jewish intelligence brings only used by the academic left. When Jews like Michael Levin, Richard Herrnstein, or David Horowitz decide to side with Whites against "people of color," they are formidable allies indeed.

Nyborg elaborates, "In fact, there are several ways to demonstrate that the IQ controversy was deeply asymmetrical. One of the parties is fairly well characterized by a series of brutal and merciless ad hominem attacks by a group of aggressive and ruthless ideologues, moved more by self-assumed moral authority than truth or, as Gross & Levitt (1994/1998) prefer to express it, by a shameless moral one-upmanship, going far beyond truth and data. The other party is better characterized as a group of hard-working scientists moved more by empirical arguments than by anything else; their endeavor involves correlations and experimentally controlled data and not at all some self-assumed moral authority."

Of course, all those decades of condemnation rather than research did not help the academic left win any real battles. Segerstrale explains, "I am arguing that moral/political concerns, far from being an obstacle to be eliminated, were in fact a driving force both in generating and criticizing scientific claims in this field, and that the field was better off because of this. We see, then, the importance of moral and metaphysical commitments in science. They motivate scientific work, they sustain it in the face of adversity, and they drive scientists to closely scrutinize the claims of opponents. It seems to me that moral/political criticism is an important and healthy phenomenon in science, particularly in fields which depend largely on plausibility arguments."

Over the last 30 years the academic left has relied almost entirely in condemning research they dislike, while scientists have been producing the data that proves them wrong with regards to nave environmentalism. Their last bastion of hope is propaganda, not science. Nyborg takes issue with Segerstrale's conclusion of the results, "it seems to me that nobody in the IQ wars in fact defended truth in any proper sense of that term. True statements about the world is heavily linked to positivism (or mathematics) but the last real positivist probably died shortly after the turn of the 19th century. What seemed to have taken place is that the academic left distorted the evidence and substituted truth with moral one-upmanship in the IQ controversy, whereas others, in particular Jensen, carefully collected and defended data along the lines of confluence and increasing precision, and talked a lot about probabilities, but never called upon truth."

So now, it is the academic left that relies on moral truth, and science that has turned away from absolutes to building upon falsifiable theoretical constructs to acquire knowledge, but never absolute truth. The Marxists have joined other religious fundamentalists in determining what truth is based on their own human needs and for Jews it seems these moral truths differ from those of other faiths. Science alone stands against truth seeking, absolutes, ethical normative systems, the fight against evil, and all the other isms that drive humans into protective enclaves against each other. Only science has a framework that excludes gods, values, ethics, and morality in search of knowledge. What we do with that knowledge is then up to us the citizens who occupy this world.

Nyborg tries to explain the attacks on science: "Most are not aware that they are betraying scientific stringency, and feel good by attacking any messengers of 'bad' information. They got their coupled-reasoning lessons from Gould, Lewontin, and modern French philosophers, and they want to feel good, socially safe and justified. Jensen asked several colleagues what intellectual reasons they could see for denying a genetic basis for behavioral differences. The most common reason was that 'such knowledge, if it is established and generally accepted by the scientific and intellectual community, might be used by some persons for evil purposes, to promote racial prejudice, discrimination, and segregations and to justify or rationalize the political suppression, and economic exploitation of racial minorities and the Nations' working class in general.'"

Again the question is, why is the academic left primarily Jewish, especially in its leadership? We know that Whites are easily persuaded into taking a moral universalistic stance, and in the milieu of Jewish moralism, they are quick to join in. Nevertheless, why would Jews and Whites differ so much in representing so-called exploited racial minorities? Jews have been persecuted, but they are certainly not an oppressed minority. So there must be group differences, and to be sustainable generation after generation, it would seem that the differences must be at least partly genetic. If the Semitic mind is highly ethnocentric, then it seems that the academic left's war against modern science is one based on a suspicion and hatred of the practitioners of Western science the dreaded Anglo/Teutonic oppressors of Jewish aspirations. I can find no other reasonable explanation for why so many Jewish led movements are vehemently anti-Western (MacDonald 1998b, 2002).

Colin Cooper notes in his book Individual Differences, Second Edition, 2002 (1st ed. 1998): "Several correlated facets are usually found when the items on these questionnaires are factor-analyzed. For example, the 37 items of the STA questionnaire generally produce three correlated factors: 'unusual perceptual experience', 'paranoid ideas' and 'magical thinking', although a recent study indicates that there may also be a factor comprising items concerned with social anxiety and sensitivity to criticism."

"Michael Eysenck (Hans Eysenck's son) has developed such a theory, and there is now good evidence that highly anxious people are hypervigilant. They explore the environment with their senses and so show more eye movements, look out for threat-related stimuli in the environment and, when they find them, process them more deeply. For example, Eysenck and Byrne (1992) gave their volunteers a switch to hold in each hand. They were shown stimuli consisting of three words. One of these words was always left or right, and the participants were simply asked to look for this word (ignoring the others) and press the appropriate button. The dependent variable was the time taken to press the button from the onset of the display. A range of distractor words were used. As well as various control conditions, various types of threatening words (failure, murder) were also shown. Highly anxious individuals (a) responded slower overall to words (indicating that they were processing them more deeply than the stable individuals) and (b) were particularly badly distracted by physically threatening words. In another experiment, Byrne and Eysenck (1.995) found that highly anxious individuals were better able to search through a screenful of faces and detect the threatening (angry) ones. There was no difference between the groups' performance when searching for happy faces. The theory has been developed further (see Eysenck (2000) for a useful review)."

From MacDonald's work then, we can surmise that the Jewish mind tends towards the more hypervigilant and magical, making them as a group more aware of racial differences and conflicts. The problem with this research however, is that no one wants to sponsor research into the differences between races in personality types, even though targeted research into showing that Whites are racists seems to be very much in vogue.
 
Nyborg observes, "The critique of Jensen is a perfect example of how 20th century academic freedom has come under siege in the West, as it was previously in the East. It suggests that the hostility of the academic left towards individualism and biological explanations plays a major role in ruining the research climate in modern academia, despite superficial declarations of adherence to open-minded research and obligatory cocktail-party proclamations of freedom for all. We need to eyeball the full social-academic-organizational-political-public horizon in order to understand in details why so many scientists, professional and international organizations, and the press at large, could so easily unite in such a surprisingly effective self-reinforcing synchrony, and act almost like a well-disciplined team to muster the brutal and direct force against apostates."

"Linda Gottfredson is even more explicit here. In an article Egalitarian fiction and collective fraud (1994) she said: 'Social science today condones and perpetuates a great falsehood ... or egalitarian fiction ... that racial-ethnic groups never differ in average ... g ... general ... ability ...' While individual scientists' intellectual dishonesty is well-known, little attention has been given to the ways in which collectives of scientists ... have perpetuated frauds on the scientific community and the public at large.' She further noted that no scientist in the collective can probably be accused of fraud in the usual sense, but '... their seemingly minor distortions, untruths, evasions, and biases collectively produce and maintain a witting falsehood.'"

Collective fraud is far easier to maintain when the members are more ethnocentric than individualistic. And it is not benign just because science has overcome the obstacles that the academic left has placed in the way. Nyborg writes, "Historically, PC is Marxism translated from economic into cultural terms, and the parallels to classical Marxism are very obvious, according to Lind. It is the child of a totalitarian ideology and it is deadly serious: 'the student or faculty member who dares to cross any of the lines set up by the gender feminist or the homosexual-rights activists, or the local black or Hispanic group, or any of the other sainted 'victims' groups that PC revolves around, quickly find themselves in judicial trouble. Within the small legal system of the college, they face formal charges ... and punishment.'" How could these oppressed minorities ascend to such power? Where did the oppressors fail to stand their ground?

Finally, Nyborg writes on the latest tactic of the academic left: to redefine science away from statistical analysis to narratives or just-so stories. What is so interesting is that the academic left attacked the early sociobiologists and evolutionary psychologists with telling just so stories. Now that the tables have turned, evolutionary psychology and behavior genetics are firmly entrenched disciplines, the academic left has resorted to just so stories to dig themselves out of their own dilemma of not being able to refute the evidence:

"While Jensen found himself mostly engaged in hard empirical work, Schiff & Lewontin (1986) felt free to speculate without a self-perceived obligation to collect the relevant data what the problem really was. They saw fit to conclude: '... the amount of knowledge about child behavior accumulated among schoolteachers is greater and of a different sort than that accumulated by academic psychologists. Even more instructive ... is the fact of trying to change [educational processes] ... scientists may not possess the most important part of the existing knowledge about human behavior, specifically about human intelligence ... those who believe that they have a monopoly on something may not be the best judges of the legitimacy of that monopoly.'"

"These hypotheses definitely deserve interest to the extent Schiff & Lewontin want to make comparisons among the predictive validity of teacher knowledge and the predictive validity of g. They did not do any of the hard work needed. However, the data are already out there. Why didn't they call upon it?"

"Lewontin & Schiff instead offer the following truly breathtaking scenario: '... the direct observation of human mental processes is potentially available to four billion observers. The scientific authority granted to a few concerning the functioning of the human mind may then be largely usurped.' They seem to suggest: skip science, and thy will see the light! This is an inverse illusion."

If the above is true then of course billions of people cannot also be wrong about Jews, and antisemitism is truly justified. If the masses are to judge, and we don't need science, then why not teach creationism? If blowing yourself up for Allah transports you directly to heaven, then truly a billion Islamists know what will bring them true peace and happiness. And if Western democracy is really better for all cultures, then surely America has the right to demand the dismantling of every form of government by force that is not democratic enough for our liking.

If human behavior is to be explained by subjective observations, if research is abandoned for story telling, if peer reviews of research is suspended, then science as we know it will cease to exist. And yet, that is what the academic left has had to fall back onthe replacement of science itself with narratives. The inmates will have truly taken over the asylum with the help of elite zealots who desire to mold human behavior according to their personal vision.

Let me restate that as an inegalitarian eugenicist, I do accept personal choices, desires, and a vision for the future that is based on an emotional commitment. However, I am also committed to a scientific paradigm that includes: openness, the reliance on peer reviewed research, the overturning of bad theories through better research rather than ad hominem attacks on individuals who are merely the messengers of the data, and the pursuit of knowledge no matter where it leads. It is up to us then to use the information wisely, rather than trying to suppress it.


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