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Jewish IQ is one of the most-talked-about things in the hereditarian sphere. Jews have higher IQs, Cochran, Hardy, and Harpending (2006: 2) argue due to “the unique demography and sociology of Ashkenazim in medieval Europe selected for intelligence.” To IQ-ists, IQ is influenced/caused by genetic factors—while environment accounts for only a small portion.
“Fourth, other environmentalists such as Majoribanks (1972) have argued that the high intelligence of the Ashkenazi Jews is attributable to the typical “pushy Jewish mother”. In a study carried out in Canada he compared 100 Jewish boys aged 11 years with 100 Protestant white gentile boys and 100 white French Canadians and assessed their mothers for “Press for Achievement”, i.e. the extent to which mothers put pressure on their sons to achieve. He found that the Jewish mothers scored higher on “Press for Achievement” than Protestant mothers by 5 SD units and higher than French Canadian mothers by 8 SD units and argued that this explains the high IQ of the children. But this inference does not follow. There is no general acceptance of the thesis that pushy mothers can raise the IQs of their children. Indeed, the contemporary consensus is that family environmental factors have no long term effect on the intelligence of children (Rowe, 1994).
The inference is a modus ponens:
P1 If p, then q.
C Therefore q.
Let p be “Jewish mothers scored higher on “Press for Achievement” by X SDs” and let q be “then this explains the high IQ of the children.”
So now we have:
Premise 1: If “Jewish mothers scored higher on “Press for Achievement” by X SDs”, then “this explains the high IQ of the children.”
Premise 2: “Jewish mothers scores higher on “Press for Achievement” by X SDs.”
Conclusion: Therefore, “Jewish mothers scoring higher on “Press for Achievement” by X SDs” so “this explains the high IQ of the children.”
Vaughn (2008: 12) notes that an inference is “reasoning from a premise or premises to … conclusions based on those premises.” The conclusion follows from the two premises, so how does the inference not follow?
IQ tests are tests of specific knowledge and skills. It, therefore, follows that, for example, if a “mother is pushy” and being pushy leads to studying more then the IQ of the child can be raised.
Looking at Lynn’s claim that “family environmental factors have no long term effect on the intelligence of children” is puzzling. Rowe relies heavily on twin and adoption studies which have false assumptions underlying them, as noted by Richardson and Norgate (2005), Moore (2006), Joseph (2014), Fosse, Joseph, and Richardson (2015), Joseph et al (2015). The EEA is false so we, therefore, cannot accept the genetic conclusions from twin studies.
Lynn and Kanazawa (2008: 807) argue that their “results clearly support the high intelligence theory of Jewish achievement while at the same time provide no support for the cultural values theory as an explanation for Jewish success.” They are positing “intelligence” as an explanatory concept, though Howe (1988) notes that “intelligence” is “a descriptive measure, not an explanatory concept.” “Intelligence, says Howe (1997: ix) “is … an outcome … not a cause.” More specifically, it is an outcome of development from infancy all the way up to adulthood and being exposed to the items on the test. Lynn has claimed for decades that high intelligence explains Jewish achievement. But whence came intelligence? Intelligence develops throughout the life cycle—from infancy to adolescence to adulthood (Moore, 2014).
Ogbu and Simon (1998: 164) notes that Jews are “autonomous minorities”—groups with a small number. They note that “Although [Jews, the Amish, and Mormons] may suffer discrimination, they are not totally dominated and oppressed, and their school achievement is no different from the dominant group (Ogbu 1978)” (Ogbu and Simon, 1998: 164). Jews are voluntary minorities, and voluntary minorities, according to Ogbu (2002: 250-251; in Race and Intelligence: Separating Science from Myth) suggests five reasons for good test performance from these types of minorities:
- Their preimmigration experience: Some do well since they were exposed to the items and structure of the tests in their native countries.
- They are cognitively acculturated: They acquired the cognitive skills of the white middle-class when they began to participate in their culture, schools, and economy.
- The history and incentive of motivation: They are motivated to score well on the tests as they have this “preimmigration expectation” in which high test scores are necessary to achieve their goals for why they emigrated along with a “positive frame of reference” in which becoming successful in America is better than becoming successful at home, and the “folk theory of getting ahead in the United States”, that their chance of success is better in the US and the key to success is a good education—which they then equate with high test scores.
So if ‘intelligence’ is a test of specific culturally-specific knowledge and skills, and if certain groups are exposed more to this knowledge, it then follows that certain groups of people are better-prepared for test-taking—specifically IQ tests.
The IQ-ists attempt to argue that differences in IQ are due, largely, to differences in ‘genes for’ IQ, and this explanation is supposed to explain Jewish IQ, and, along with it, Jewish achievement. (See also Gilman, 2008 and Ferguson, 2008 for responses to the just-so storytelling from Cochran, Hardy, and Harpending, 2006.) Lynn, purportedly, is invoking ‘genetic confounding’—he is presupposing that Jews have ‘high IQ genes’ and this is what explains the “pushiness” of Jewish mothers. The Jewish mothers then pass on their “genes for” high IQ—according to Lynn. But the evolutionary accounts (just-so stories) explaining Jewish IQ fail. Ferguson (2008) shows how “there is no good reason to believe that the argument of [Cochran, Hardy, and Harpending, 2006] is likely, or even reasonably possible.” The tall-tale explanations for Jewish IQ, too, fail.
Prinz (2014: 68) notes that Cochran et al have “a seductive story” (aren’t all just-so stories seductive since they are selected to comport with the observation? Smith, 2016), while continuing (pg 71):
The very fact that the Utah researchers use to argue for a genetic difference actually points to a cultural difference between Ashkenazim and other groups. Ashkenazi Jews may have encouraged their children to study maths because it was the only way to get ahead. The emphasis remains widespread today, and it may be the major source of performance on IQ tests. In arguing that Ashkenazim are genetically different, the Utah researchers identify a major cultural difference, and that cultural difference is sufficient to explain the pattern of academic achievement. There is no solid evidence for thinking that the Ashkenazim advantage in IQ tests is genetically, as opposed to culturally, caused.
Nisbett (2008: 146) notes other problems with the theory—most notably Sephardic over-achievement under Islam:
It is also important to the Cochran theory that Sephardic Jews not be terribly accomplished, since they did not pass through the genetic filter of occupations that demanded high intelligence. Contemporary Sephardic Jews in fact do not seem to haave unusally high IQs. But Sephardic Jews under Islam achieved at very high levels. Fifteen percent of all scientists in the period AD 1150-1300 were Jewish—far out of proportion to their presence in the world population, or even the population of the Islamic world—and these scientists were overwhelmingly Sephardic. Cochran and company are left with only a cultural explanation of this Sephardic efflorescence, and it is not congenial to their genetic theory of Jewish intelligence.
Finally, Berg and Belmont (1990: 106) note that “The purpose of the present study was to clarify a possible misinterpretation of the results of Lesser et al’s (1965) influential study that suggested that existence of a “Jewish” pattern of mental abilities. In establishing that Jewish children of different socio-cultural backgrounds display different patterns of mental abilities, which tend to cluster by socio-cultural group, this study confirms Lesser et al’s position that intellectual patterns are, in large part, culturally derived.” Cultural differences exist; cultural differences have an effect on psychological traits; if cultural differences exist and cultural differences have an effect on psychological traits (with culture influencing a population’s beliefs and values) and IQ tests are culturally-/class-specific knowledge tests, then it necessarily follows that IQ differences are cultural/social in nature, not ‘genetic.’
In sum, Lynn’s claim that the inference does not follow is ridiculous. The argument provided is a modus ponens, so the inference does follow. Similarly, Lynn’s claim that “pushy Jewish mothers” don’t explain the high IQs of Jews doesn’t follow. If IQ tests are tests of middle-class knowledge and skills and they are exposed to the structure and items on them, then it follows that being “pushy” with children—that is, getting them to study and whatnot—would explain higher IQs. Lynn’s and Kanazawa’s assertion that “high intelligence is the most promising explanation of Jewish achievement” also fails since intelligence is not an explanatory concept—a cause—it is a descriptive measure that develops across the lifespan.
… what IQ tests actually assess is not some universal scale of cognitive strength but the presence of skills and knowledge structures more likely to be acquired in some groups than in others. (Richardson, 2017: 98)
For the past 100 years, the black-white IQ gap has puzzled psychometricians. There are two camps—hereditarians (those who believe that individual and group differences in IQ are due largely to genetics) and environmentalists/interactionists (those who believe that individual and group differences in IQ are largely due to differences in learning, exposure to knowledge, culture and immediate environment).
However, one of the most forceful arguments for the environmentalist (i.e., that the cause for differences in IQ are due to the cultural and social environment; note that an interactionist framework can be used here, too) side is one from Fagan and Holland (2007). They show that half of the questions on IQ tests had no racial bias, whereas other problems on the test were solvable with only a specific type of knowledge – knowledge that is found specifically in the middle class. So if blacks are more likely to be lower class than whites, then what explains lower test scores for blacks is differential exposure to knowledge – specifically, the knowledge to complete the items on the test.
But some hereditarians say otherwise – they claim that since knowledge is easily accessible for everyone, then therefore, everyone who wants to learn something will learn it and thus, the access to information has nothing to do with cultural/social effects.
A hereditarian can, for instance, state that anyone who wants to can learn the types of knowledge that are on IQ tests and that they are widely available everywhere. But racial gaps in IQ stay the same, even though all racial groups have the same access to the specific types of cultural knowledge on IQ tests. Therefore, differences in IQ are not due to differences in one’s immediate environment and what they are exposed to—differences in IQ are due to some innate, genetic differences between blacks and whites. Put into premise and conclusion form, the argument goes something like this:
P1 If racial gaps in IQ were due specifically to differences in knowledge, then anyone who wants to and is able to learn the stuff on the tests can do so for free on the Internet.
P2 Anyone who wants to and is able to learn stuff can do so for free on the Internet.
P3 Blacks score lower than whites on IQ tests, even though they have the same access to information if they would like to seek it out.
C Therefore, differences in IQ between races are due to innate, genetic factors, not any environmental ones.
This argument is strange. One would have to assume that blacks and whites have the same access to knowledge—we know that lower-income people have less access to knowledge in virtue of the environments they live in. For instance, they may have libraries with low funding or bad schools with teachers who do not care enough to teach the students what they need to succeed on these standardized tests (IQ tests, the SAT, etc are all different versions of the same test). (2) One would have to assume that everyone has the same type of motivation to learn what amounts to answers for questions on a test that have no real-world implications. And (3) the type of knowledge that one is exposed to dictates what one can tap into while they are attempting to solve a problem. All three of these reasons can cascade in causing the racial performance in IQ.
Familiarity with the items on the tests influences a faster processing of information, allowing one to correctly identify an answer in a shorter period of time. If we look at IQ tests as tests of middle-class knowledge of skills, and we rightly observe that blacks are lower class than whites who are more likely to be middle class, then it logically follows that the cause of differences in IQ between blacks and whites are cultural – and not genetic – in origin. This paper – and others – solves the century-old debate on racial IQ differences – what accounts for differences in IQ scores is differential exposure to knowledge. Claiming that people have the same type of access to knowledge and, thusly, won’t learn it if they won’t seek it out does not make sense.
Differing experiences lead to differing amounts of knowledge. If differing experiences lead to differing amounts of knowledge, and IQ tests are tests of knowledge—culturally-specific knowledge—then those who are not exposed to the knowledge on the test will score lower than those who are exposed to the knowledge. Therefore, Jensen’s Default Hypothesis is false (Fagan and Holland, 2002). Fagan and Holland (2002) compared blacks and whites on for their knowledge of the meaning of words, which are highly “g”-loaded and shows black-white differences. They review research showing that blacks have lower exposure to words and are therefore unfamiliar with certain words (keep this in mind for the end). They mixed in novel words with previously-known words to see if there was a difference.
Fagan and Holland (2002) picked out random words from the dictionary, then putting them into a sentence to attempt to give the testee some context. They carried out five experiments in all, and each one showed that, when equal opportunity was given to the groups, they were “equal in knowledge” (IQ). So, whites were more likely to know the items more likely to be found on IQ tests. Thus, there were no racial differences between blacks and whites when looked at from an information-processing point of view. Therefore, to expain racial differences in IQ, we must look to differences in the cultural/social environment. Fagan (2000) for instance, states that “Cultures may differ in the types of knowledge their members have but not in how well they process. Cultures may account for racial differences in IQ.”
The results of Fagan and Holland (2002) are completely at-ends with Jensen’s Default Hypothesis—that the 15-point gap in IQ is due to the same environmental and cultural factors that underlie individual differences in the group. However, as Fagan and Holland (2002: 382) show that:
Contrary to what the default hypothesis would predict, however, the within racial group analyses in our study stand in sharp contrast to our between racial group findings. Specifically, individuals within a racial group who differed in general knowledge of word meanings also differed in performance when equal exposure to the information to be tested was provided. Thus, our results suggest that the average difference of 15 IQ points between Blacks and Whites is not due to the same genetic and environmental factors, in the same ratio, that account for differences among individuals within a racial group in IQ.
Exposure to information is critical, in fact. For instance, Ceci (1996) shows that familiarity with words dictates speed of processing to use in identifying the correct answer to the problem. In regard to differences in IQ, Ceci (1996) does not deny the role of biology—indeed, it’s a part of his bio-ecological model of IQ, which is a theory that postulates the development of intelligence as an interaction between biological dispositions and the environment in which those dispositions manifest themselves. Ceci (1996) does note that there are biological constraints on intelligence, but that “… individual differences in biological constraints on specific cognitive abilities are not necessarily (or even probably) directly responsible for producing the individual differences that have been reported in the psychometric literature.” That such potentials, though may be “genetic” in origin, of course, does not license the claim that genetic factors contribute to variance in IQ. “Everyone may possess them to the same degree, and the variance may be due to environment and/or motivations that led to their differential crystallization.” (Ceci, 1996: 171)
Ceci (1996) also further shows that people can differ in intellectual performance due to 3 things: (1) the efficiency of underlying cognitive potentials that are relevant to the cognitive ability in question; (2) the structure of knowledge relevant to the performance; and (3) contextual/motivational factors relevant to crystallize the underlying potentials gained through one’s knowledge. Thus, if one is lacking in the knowledge of the items on the test due to what they learned in school, then the test will be biased against them since they did not learn the relevant information on the tests.
Cahan and Cohen (1989) note that nine-year-olds in fourth grade had higher IQs than nine-year-olds in third grade. This is to be expected, if we take IQ scores as indices of—cultural-specific—knowledge and skills and this is because fourth-graders have been exposed to more information than third-graders. In virtue of being exposed to more information than their same-age cohort in different grades, they then score higher on IQ tests because they are exposed to more information.
Cockroft et al (2015) studied South African and British undergrads on the WAIS-III. They conclude that “the majority of the subtests in the WAIS-III hold cross-cultural biases“, while this is “most evident in tasks which tap crystallized, long-term learning, irrespective of whether the format is verbal or non-verbal” so “This challenges the view that visuo-spatial and non-verbal tests tend to be culturally fairer than verbal ones (Rosselli and Ardila, 2003)”.
IQ tests “simply reflect the different kinds of learning by children from different (sub)cultures: in other words, a measure of learning, not learning ability, and are merely a redescription of the class structure of society, not its causes … it will always be quite impossible to measure such ability with an instrument that depends on learning in one particular culture” (Richardson, 2017: 99-100). This is the logical position to hold: for if IQ tests test class-specific type of knowledge and certain classes are not exposed to said items, then they will score lower. Therefore, since IQ tests are tests of a certain kind of knowledge, IQ tests cannot be “a measure of learning ability” and so, contra Gottfredson, ‘g’ or ‘intelligence’ (IQ test scores) cannot be called “basic learning ability” since we cannot create culture—knowledge—free tests because all human cognizing takes place in a cultural context which it cannot be divorced from.
Since all human cognition takes place through the medium of cultural/psychological tools, the very idea of a culture-free test is, as Cole (1999) notes, ‘a contradiction in terms . . . by its very nature, IQ testing is culture bound’ (p. 646). Individuals are simply more or less prepared for dealing with the cognitive and linguistic structures built in to the particular items. (Richardson, 2002: 293)
Heine (2017: 187) gives some examples of the World War I Alpha Test:
1. The Percheron is a kind of
(a) goat, (b) horse, (c) cow, (d) sheep.
2. The most prominent industry of Gloucester is
(a) fishing, (b) packing, (c) brewing, (d) automobiles.
3. “There’s a reason” is an advertisement for
(a) drink, (b) revolver, (c) flour, (d) cleanser.
4. The Knight engine is used in the
(a) drink, (b) Stearns, (c) Lozier, (d) Pierce Arrow.
5. The Stanchion is used in
(a) fishing, (b) hunting, (c) farming, (d) motoring.
Such test items are similar to what are on modern-day IQ tests. See, for example, Castles (2013: 150) who writes:
One section of the WAIS-III, for example, consists of arithmetic problems that the respondent must solve in his or her head. Others require test-takers to define a series of vocabulary words (many of which would be familiar only to skilled-readers), to answer school-related factual questions (e.g., “Who was the first president of the United States?” or “Who wrote the Canterbury Tales?”), and to recognize and endorse common cultural norms and values (e.g., “What should you do it a sale clerk accidentally gives you too much change?” or “Why does our Constitution call for division of powers?”). True, respondents are also given a few opportunities to solve novel problems (e.g., copying a series of abstract designs with colored blocks). But even these supposedly culture-fair items require an understanding of social conventions, familiarity with objects specific to American culture, and/or experience working with geometric shapes or symbols. [Since this is questions found on the WAIS-III, then go back and read Cockroft et al, 2015 since they used the British version which, of course, is similar.]
If one is not exposed to the structure of the test along with the items and information on them, how, then, can we say that the test is ‘fair’ to other cultural groups (social classes included)? For, if all tests are culture-bound and different groups of people have different cultures, histories, etc, then they will score differently by virtue of what they know. This is why it is ridiculous to state so confidently that IQ tests—however imperfectly—test “intelligence.” They test certain skills and knowledge more likely to be found in certain groups/classes over others—specifically in the dominant group. So what dictates IQ scores is differential access to knowledge (i.e., cultural tools) and how to use such cultural tools (which then become psychological tools.)
Lastly, take an Amazonian people called The Pirah. They have a different counting system than we do in the West called the “one-two-many system, where quantities beyond two are not counted but are simply referred to as “many”” (Gordon, 2005: 496). A Pirah adult was shown an empty can. Then the investigator put six nuts into the can and took five out, one at a time. The investigator then asked the adult if there were any nuts remaining in the can—the man answered that he had no idea. Everett (2005: 622) notes that “Piraha is the only language known without number, numerals, or a concept of counting. It also lacks terms for quantification such as “all,” “each,” “every,” “most,” and “some.””
(hbdchick, quite stupidly, on Twitter wrote “remember when supermisdreavus suggested that the tsimane (who only count to s’thing like two and beyond that it’s “many”) maybe went down an evolutionary pathway in which they *lost* such numbers genes?” Riiiight. Surely the Tsimane “went down an evolutionary pathway in which they *lost* such numbers genes.” This is the idiocy of “HBDers” in action. Of course, I wouldn’t expect them to read the actual literature beyond knowing something basic (Tsimane numbers beyond “two” are known as “many”) and the positing a just-so story for why they don’t count above “two.”
Take a non-verbal test, such as the Bender-Gestalt test. There are nine index cards which have different geometrical designs on them, and the testee needs to copy what he saw before the next card is shown. The testee is then scored on how accurate his recreation of the index card is. Seems culture-fair, no? It’s just shapes and other similar things, how would that be influenced by class and culture? One would, on a cursory basis, claim that such tests have no basis in knowledge structure and exposure and so would rightly be called “culture-free.” While the shapes that come on Ravens tests are novel, the rules governing them are not.
Hoffmann (1966) studied 80 children (20 Kickapoo Indians (KIs), 20 low SES blacks (LSBs), 20 low SES whites (LSWs), and 20 middle-class whites (MCWs)) on the Bender-Gestalt test. The Kickapoo were selected from 5 urban schools; 20 blacks from majority-black elementary schools in Oklahoma City; 20 whites in low SES areas of Oklahoma; and 20 whites from middle-schools in Oklahoma from majority-white schools. All of the children were aged 8-10 years of age and in the third grade, while all had IQs in the range of 90-110. They were matched on a whole slew of different variables. Hoffman (1966: 52) states “that variations in cultural and socio-economic background affect Bender Gestalt reproduction.”
Hoffman (1966: 86) writes that:
since the four groups were shown to exhibit no significant differences in motor, or perceptual discrimination ability it follows that differences among the four groups of boys in Bender Gestalt performance are assignable to interpretative factors. Furthermore, significant differences among the four groups in Bender performance illustrates that the Bender Gestalt test is indeed not a so called “culture-free” test.
Hoffman concluded that MCWs, KIs, LSBs, and LSWs did not differ in copying ability, nor did they differ significantly in discriminating in different phases in the Bender-Gestalt; there also was no bias in figures that had two of the different sexes on them. They did differ in their reproductions of Bender-Gestalt designs, and their differing performance can be, of course, interpreted differently by different people. If we start from the assumption that all IQ tests are culture-bound (Cole, 2004), then living in a different culture from the majority culture will have one score differently by virtue of having differing—culture-specific knowledge and experience. The four groups looked at the test in different ways, too. Thus, the main conclusion is that:
The Bender Gestalt test is not a “culture-free” test. Cultural and socio-economic background appear to significantly affect Bender Gestalt reproduction. (Hoffman, 1966: 88)
Drame and Ferguson (2017) and Dutton et al (2017) also show that there is bias in the Raven’s test in Mali and Sudan. This, of course, is due to the exposure to the types of problems on the items (Richardson, 2002: 291-293). Thus, their cultures do not allow exposure to the items on the test and they will, therefore, score lower in virtue of not being exposed to the items on the test. Richardson (1991) took 10 of the hardest Raven’s items and couched them in familiar terms with familiar, non-geometric, objects. Twenty eleven-year-olds performed way better with the new items than the original ones, even though they used the same exact logic in the problems that Richardson (1991) devised. This, obviously, shows that the Raven is not a “culture-free” measure of inductive and deductive logic.
The Raven is administered in a testing environment, which is a cultural device. They are then handed a paper with black and white figures ordered from left to right. Note that Abel-Kalek and Raven (2006: 171) write that Raven’s items “were transposed to read from right to left following the custom of Arabic writing.” So this is another way that the tests are biased and therefore not “culture-free.”) Richardson (2000: 164) writes that:
For example, one rule simply consists of the addition or subtraction of a figure as we move along a row or down a column; another might consist of substituting elements. My point is that these are emphatically culture-loaded, in the sense that they reflect further information-handling tools for storing and extracting information from the text, from tables of figures, from accounts or timetables, and so on, all of which are more prominent in some cultures and subcultures than others.
Richardson (1991: 83) quotes Keating and Maclean (1987: 243) who argue that tests like the Raven “tap highly formal and specific school skills related to text processing and decontextualized rule application, and are thus the most systematically acculturated tests” (their emphasis). Keating and Maclean (1987: 244) also state that the variation in scores between individuals is due to “the degree of acculturation to the mainstream school skills of Western society” (their emphasis). That’s the thing: all types of testing is biased towards a certain culture in virtue of the kinds of things they are exposed to—not being exposed to the items and structure of the test means that it is in effect biased against certain cultural/social groups.
Davis (2014) studied the Tsimane, a people from Bolivia, on the Raven. Average eleven-year-olds 78 percent or more of the questions correct whereas lower-performing individuals answered 47 percent correct. The eleven-year-old Tsimane, though, only answered 31 percent correct. There was another group of Tsimane who went to school and lived in villages—not living in the rainforest like the other group of Tsimane. They ended up scoring 72 percent correct, compared to the unschooled Tsimane who scored only 31 percent correct. “… the cognitive skills of the Tsimane have developed to master the challenges that their environment places on them, and the Raven’s test simply does not tap into those skills. It’s not a reflection of some kind of true universal intelligence; it just reflects how well they can answer those items” (Heine, 2017: 189). Thus, measures of “intelligence” are not an innate skill, but are learned through experience—what we learn from our environments.
Heine (2017: 190) discusses as-of-yet-to-be-published results on the Hadza who are known as “the most cognitively complex foragers on Earth.” So, “the most cognitively complex foragers on Earth” should be pretty “smart”, right? Well, the Hadza were given six-piece jigsaw puzzles to complete—the kinds of puzzles that American four-year-olds do for fun. They had never seen such puzzles before and so were stumped as to how to complete them. Even those who were able to complete them took several minutes to complete them. Is the conclusion then licensed that “Hadza are less smart than four-year-old American children?” No! As that is a specific cultural tool that the Hadza have never seen before and so, their performance mirrored their ignorance to the test.
The term “logical” comes from the Greek term logos, meaning “reason, idea, or word.” So, “logical reasoning” is based on reason and sound ideas, irrespective of bias and emotion. A simple syllogistic structure could be:
If X, then Y
We can substitute terms, too, for instance:
If it rains today, then I must bring an umbrella.
It’s raining today.
∴ I must bring an umbrella.
Richardson (2000: 161) notes how cross-cultural studies show that what is or is not logical thinking is not objective nor simple, but “comes in socially determined forms.” He notes how cross-cultural psychologist Sylvia Scribner showed some syllogisms to Kpelle farmers, which were couched in terms that were familiar to them. One syllogism given to them was:
All Kpelle men are rice farmers
Mr. Smith is not a rice farmer
Is he a Kpelle man? (Richardson, 2002: 162)
The individual then continuously replied that he did not know Mr. Smith, so how could he know whether or not he was a Kpelle man? Another example was:
All people who own a house pay a house tax
Boima does not pay a house tax
Does Boima own a house? (Richardson, 2000: 162)
The answer here was that Boima did not have any money to pay a house tax.
In regard to the first syllogism, Mr. Smith is not a rice farmer so he is not a Kpelle man. Regarding the second, Boima does not pay a house tax, so Boima does not own a house. The individual could give a syllogism that is something like:
All the deductions I can make are about individuals I know.
I do not know Mr. Smith.
Therefore I cannot make a deduction about Mr. Smith. (Richardson, 2000: 162)
They are using what are familiar terms to them, and so, they get the answer right for their culture based on the knowledge that they have. These examples, therefore, show that what can pass for “logical reasoning” is based on the time and place where it is said. The deductions the Kpelle made were perfectly valid, though they were not what the syllogism-designers had in mind. In fact, I would say that there are many—equally valid—ways of answering such syllogisms, and such answers will vary by culture and custom.
The bio-ecological framework, culture, and social class
The bio-ecological model of Ceci and Bronfenbrenner is a model of human development that relies on gene and environment interactions. The model is a Vygotskian one—in that learning is a social process where the support from parents, teachers, and all of society play an important role in the ontogeny of higher psychological functioning. (For a good primer on Vygotskian theory, see Vygotsky and the Social Formation of Mind, Wertsch, 1985.) Thus, it is a model of human development that, most hereditarians would say, that “they use too.” Though this is of course, contested by Ceci who compares his bio-ecological framework with other theories (Ceci, 1996: 220, table 10.1):
Cognition (thinking) is extremely context-sensitive. Along with many ecological influences, individual differences in cognition are understood best with the bio-ecological framework which consists of three components: (1) ‘g’ doesn’t exist, but multiple cognitive potentials do; (2) motivational forces and social/physical aspects of a task or setting, how elaborate a knowledge domain is not only important in the development of the human, but also, of course, during testing; and (3) knowledge and aptitude are inseparable “such that cognitive potentials continuously access one’s knowledge base in the cascading process of producing cognitions, which in turn alter the contents and structure of the knowledge base” (Ceci, 1996: 123).
Block (1995) notes that “Blacks and Whites are to some extent separate cultural groups.” Sternberg (2004) defines culture as “the set of attitudes, values, beliefs and behaviors shared by a group of people, communicated from one generation to the next via language or some other means of communication.” In regard to social class—blacks and whites differ in social class (a form of culture), Richardson (2002: 298) notes that “Social class is a compound of the cultural tools (knowledge and cognitive and psycholingustic structures) individuals are exposed to; and beliefs, values, academic orientations, self-efficacy beliefs, and so on.” The APA notes that “Social status isn’t just about the cars we drive, the money we make or the schools we attend — it’s also about how we feel, think and act …” And the APS notes that social class can be seen as a form of culture. Since culture is a set of attitudes, beliefs and behaviors shared by a group of people, social classes, therefore, are forms of culture as different classes have different attitudes, beliefs and behaviors.
Ceci (1996 119) notes that:
large-scale cultural differences are likely to affect cognition in important ways. One’s way of thinking about things is determined in the course of interactions with others of the same culture; that is, the meaning of a cultural context is always negotiated between people of that culture. This, in turn, modifies both culture and thought.
While Manstead (2018) argues that:
There is solid evidence that the material circumstances in which people develop and live their lives have a profound influence on the ways in which they construe themselves and their social environments. The resulting differences in the ways that working‐class and middle‐ and upper‐class people think and act serve to reinforce these influences of social class background, making it harder for working‐class individuals to benefit from the kinds of educational and employment opportunities that would increase social mobility and thereby improve their material circumstances.
In fact, the bio-ecological model of human development (and IQ) is a developmental systems-type model. The types of things that go into the model are just like Richardson’s (2002) “sociocognitive affective nexus.” Richardson (2002) posits that the sources of IQ variation are mostly non-cognitive, writing that such factors include (pg 288):
(a) the extent to which people of different social classes and cultures have acquired a specific form of intelligence (or forms of knowledge and reasoning); (b) related variation in ‘academic orientation’ and ‘self-efficacy beliefs’; and (c) related variation in test anxiety, self-confidence, and so on, which affect performance in testing situations irrespective of actual ability
Cole (2004) concludes that:
Our imagined study of cross-cultural test construction makes it clear that tests of ability are inevitably cultural devices. This conclusion must seem dreary and disappointing to people who have been working to construct valid, culture-free tests. But from the perspective of history and logic, it simply confirms the fact, stated so clearly by Franz Boas half a century ago, that “mind, independent of experience, is inconceivable.”
It is a noteworthy feature of all preceding (cognitive approaches) that they make no reference whatsoever to the environment in which the person actually lives and grows. The implicit assumption is that the attributes in question are constant across place; the person carries them with her wherever she goes. Stating the issue more theoretically, the assumption is that the nature of the attribute does not change, irrespective of the context in which one finds one’s self.
Such contextual differences can be found in the intrinsic and extrinsic motivations of the individual in question. Self-efficacy, what one learns and how they learn it, motivation instilled from parents, all form part of the context of the specific individual and how they develop which then influences IQ scores (middle-class knowledge and skills scores).
If blacks and whites are, to some extent, different cultural groups, then they will—by definition—have differing cultures. So “cultural differences are known to exist, and cultural differences can have an impact on psychological traits [also in the knowledge one acquires which then is one part of dictating test scores] (see Prinz, 2014: 67, Beyond Human Nature). If blacks and whites are “separate cultural groups” (Block, 1995) and if they have different experiences by virtue of being cultural groups, then they will score differently on any test of ability (including IQ; see Fagan and Holland, 2002, 2007) as all tests of ability are culture-bound (see Cole, 2004).
1 Blacks and whites are different cultural groups.
2 If (1), then they will have different experiences by virtue of being different cultural groups.
3 So blacks and whites, being different cultural groups, will score differently on tests of ability, since they are exposed to different knowledge structures due to their different cultures and so, all tests of ability are culture-bound.
So, what accounts for the intercorrelations between tests of “cognitive ability”? They validate the new test with older, ‘more established’ tests so “based on this it is unlikely that a measure unrelated to g will emerge as a winner in current practice … [so] it is no wonder that the intelligence hierarchy for different racial/ethnic groups remains consistent across different measures. The tests are highly correlated among each other and are similar in item structure and format” (Suzuki and Aronson, 2005: 321).
Therefore, what accounts for differences in IQ is not intellectual ability, but cultural/social exposure to information—specifically the type of information used in the construction of IQ tests—along with the test constructors attempting to construct new tests that correlate with the old tests, and so, they get the foregone conclusion of their being racial differences, for example, in IQ which they trumpet as evidence for a “biological cause”—but it is anything but: such differences are built into the test (Simon, 1997). (Note that Fagan and Holland, 2002 also found evidence for test bias as well.)
Thus, we should take the logical conclusion: what explains racial IQ differences are not biological factors, but environmental ones—specifically in the exposure of knowledge—along with how new tests are created (see Suzuki and . All human cognizing takes place in specific cultural contexts—therefore “culture-free tests” (i.e., tests devoid of cultural knowledge and context) are an impossibility. IQ tests are experience-dependent so if one is not exposed to the relevant experiences to do well in a testing situation, then they will score lower than they would have if they were to have the requisite culturally-specific knowledge to perform well on the test.
Japan has a caste system just like India. Their lowest caste is called “the Burakumin”, a hereditary caste created in the 17th century—the descendants of tanners and butchers. (Buraku means ‘hamlet people’ in Japanese which took on a new meaning in the Meiji era.) Even though they gained “full rights” in 1871, they were still discriminated against in housing and work (only getting menial jobs). A Burakumin Liberation League has formed, to end discrimination against Buraku in 1922, protesting to end job discrimination by the dominant Ippan Japanese. Official numbers of the number of Buraku in Japan are about 1.2 million, but unofficial numbers bring it up to 6000 communities and 3 million Buraku.
Note the similarities here with black Americans. Black Americans got their freedom from American slavery in 1865. The Burakumin got theirs in 1865. Both groups get discriminated against—the things that the Burakumin face, the blacks in America have faced. De Vos (1973: 374) describes some employment statistics for Buraku and non-Buraku:
For instance, Mahara reports the employment statistics for 166 non-Buraku children and 83 Buraku children who were graduated in March 1859 from a junior high school in Kyoto. Those who were hired by small-scale enterprises employing fewer than ten workers numbered 29.8 percent of the Buraku and 13.1 percent of the non-Buraku children; 15.1 percent of non-Buraku children obtained work in large-scale industries employing more than one thousand workers, whereas only 1.5 percent of Buraku children did so.
Certain Japanese communities—in southwestern Japan—have a belief and tradition in having foxes as pets. Those who have the potential to have such foxes descends down the family line—there are “black” foxes and “white” foxes. So in this area in southwestern Japan, people are classified as either “white” or “black”, and marriage between these artificial color lines is forbidden. They believe that if someone from the “white” family marries someone from the “black” family that every other member of the “white” family becomes “black.”
Discrimination against the Buraku in Japan is so bad, that a 330 page list of Buraku names and community placements were sold to employers. Burakumin are also more likely to join the Yakuza criminal gang—most likely due to such opportunities they miss out on in their native land. (Note similarities between Buraku joining Yakuza and blacks joining their own ethnic gangs.) It was even declared that an “Eta” (the lowest of the Burakumin) was 1/7th of an ordinary person. This is eerily familiar to how blacks were treated in America with the three-fifths compromise—signifying that the population of slaves would be counted as three-fifths in total when being apportioned to votes for the Presidential electors, taxes and other representatives.
Now let’s get to the good stuff: “intelligence.” There is a gap in scores between “blacks”, “whites”, and Buraku. De Vos (1973: 377) describes score differences between “blacks”, “whites” and Buraku:
[Nomura] used two different kinds of “intelligence” tests, the nature of which are unfortunately unclear from his report. On both tests and in all three schools the results were uniform: “White” children averaged significantly higher than children from “black” families, and Buraku children, although not markedly lower than the “blacks,” averaged lowest.
According to Tojo, the results of a Tanaka-Binet Group I.Q. Test administered to 351 fifth- and sixth-grade children, including 77 Buraku children, at a school in Takatsuki City near Osaka shows that the I.Q. scores of the Buraku children are markedly lower than those of the non-Buraku children. [Here is the table from Sternberg and Grigorenko, 2001]
Also see the table from Hockenbury and Hockenbury’s textbook Psychology where they show IQ score differences between non-Buraku and Buraku people:
De Vos (1973: 376) also notes the similarities between Buraku and black and Mexican Americans:
Buraku school children are less successful compared with the majority group children. Their truancy rate is often high, as it is in California among black and Mexican-American minority groups. The situation in Japan also probably parallels the response to education by certain but not all minority groups in the United States.
How similar. There is another group in Japan that is an ethnic minority that is the same race as the Japanese—the Koreans. They came to Japan as forced labor during WWII—about 7.8 million Koreans were conscripted to the Japanese, men participating in the military while women were used as sex slaves. Most are born in Japan and speak no Korean, but they still face discrimination—just like the Buraku. There are no IQ test scores for Koreans in Japan, but there are standardized test scores. Koreans in America are more likely to have higher educational attainment than are native-born Americans (see the Pew data on Korean American educational attainment). But this is not the case in Japan. The following table is from Sternberg and Grigorenko (2001).
Just as Koreans do better than white Americans on standardized tests (and IQ tests), how weird is it for Koreans in Japan to score lower than ethnic Japanese and even the Burakumin? Sternberg and Grigorenko (2001) write:
Based on these cross-cultural comparison, we suggest that it is the manner in which caste and minority status combine rather than either minority position or low-caste status alone that lead to low cognitive or IQ test scores for low-status groups in complex, technological societies such as Japan and the United States. Often jobs and education require the adaptive intellectual skills of the dominant caste. In such societies, IQ tests discriminate against all minorities, but how the minority groups perform on the tests depends on whether they became minorities by immigration or choice (voluntary minorities) or were forced by the dominant group into minorities status (involuntary minorities). The evidence indicates that immigrant minority status and nonimmigrant status have different implications for IQ test performance.
The distinction between “voluntary” and “involuntary” minority is simple: voluntary minorities emigrate by choice, whereas involuntary minorities were forced against their will to be there. Black Americans, Native Hawaiians and Native Americans are involuntary minorities in America and, in the case of blacks, they face similar discrimination to the Buraku and there is a similar difference in test scores between the high and low castes (classes in America). (See the discussion in Ogbu and Simons (1998) on voluntary and involuntary minorities and also see Shimihara, (1984) for information on how the Burakumin are discriminated against.)
Ogbu and Simons (1988) explain the school performance of minorities using what Ogbu calls a “cultural-ecological theory” which considers societal and school factors along with community dynamics in minority communities. The first part of the theory is that minorities are discriminated against in terms of education, which Ogbu calls “the system.” The second part of the theory is how minorities respond to their treatment in the school system, which Ogbu calls “community forces.” See Figure 1 from Ogbu and Simons (1998: 156):
Ogbu and Simon (1998: 158) write about the Buraku and Koreans:
Consider that some minority groups, like the Buraku outcast in Japan, do poorly in school in their country of origin but do quite well in the United States, or that Koreans do well in school in China and in the United States but do poorly in Japan.
Ogbu (1981: 13) even notes that when Buraku are in America—since they do not look different from the Ippan—they are treated like regular Japanese-Americans who are not discriminated against in America as the Buraku are in Japan and, what do you know, they have similar outcomes to other Japanese:
The contrasting school experiences of the Buraku outcastes in Japan and in the United States are even more instructive. In Japan Buraku children continue massively to perform academically lower than the dominant Ippan children. But in the United States where the Buraku and the Ippan are treated alike by the American people, government and schools, the Buraku do just as well in school as the Ippan (DeVos 1973; Ito,1967; Ogbu, 1978a).
So, clearly, this gap between the Buraku and the Nippon disappears when they are not stratified in a dominant-subordinate relation. It’s because IQ testing and other tests of ability are culture-bound (Cole, 2004) and so, when Burakumin emigrate to America (as voluntary minorities), they are seen as and treated like any other Japanese since there are no physical differences between them and their educational attainment and IQs match the other non-Burakumin Japanese. The very items on these tests are biased towards the dominant (middle-)class—so when the Buraku and Koreans emigrate to America they then have the types of cultural and psychological tools (Richardson, 2002) to do well on the tests and so, their scores change from when they were in their other country.
Note the striking similarities between black Americans and Buraku and Korean-Japanese—all three groups are discriminated against in their countries, all three groups have lower levels of achievement than the majority population, two groups (the Buraku and black Americans, there is no IQ data for Koreans in Japan that I am aware of) show the same gap between them and the dominant group, the Buraku and black Americans got their freedom at around the same times but still face similar types of discrimination. However, when Buraku and Korean-Japanese people emigrate here to America, their IQ scores and educational attainment match that of other East Asian groups. To Americans, there is no difference between Buraku and non-Buraku Japanese people.
Koreans in Japan “endure a climate of hate“, according to The Japan Times. Koreans are heavily discriminated against in Japan. Korean-Japanese people, in any case, score worse than the Buraku. Though, as we all know, when Koreans emigrate to America they have higher test scores than whites do.
Note, though, IQ scores for “voluntary minorities” that came to the US in the 1920s. The Irish, Italians, and even Jews were screened as “low IQ” and were thusly barred entry into the country due to it. For example, Young (1922: 422) writes that:
Over 85 per cent. of the Italian group, more than 80 per cent. of the Polish group and 75 per cent. of the Greeks received their final letter grades from the beta or other performance examination.
While Young (1922) shows the results of an IQ test administered to Southern Europeans in certain areas (one of the studies was carried out in New York City):
These types of score differentials are just like what these lower castes in Japan and America show today. Though, as Thomas Sowell noted in regard to the IQs of Jews, Polish, Italians, and Greeks:
Like fertility rates, IQ scores differ substantially among ethnic groups at a given time, and have changed substantially over time— reshuffling the relative standings of the groups. As of about World War I, Jews scored sufficiently low on mental tests to cause a leading “expert” of that era to claim that the test score results “disprove the popular belief that the Jew is highly intelligent.” At that time, IQ scores for many of the other more recently arrived groups—Italians, Greeks, Poles, Portuguese, and Slovaks—were virtually identical to those found today among blacks, Hispanics, and other disadvantaged groups. However, over the succeeding decades, as most of these immigrant groups became more acculturated and advanced socioeconomically, their IQ scores have risen by substantial amounts. Jewish IQs were already above the national average by the 1920s, and recent studies of Italian and Polish IQs show them to have reached or passed the national average in the post-World War II era. Polish IQs, which averaged eighty-five in the earlier studies—the same as that of blacks today—had risen to 109 by the 1970s. This twenty-four-point increase in two generations is greater than the current black-white difference (fifteen points). [See also here.]
Ron Unz notes that Sowell says about the Eastern and Southern European immigrants IQs: “Slovaks at 85.6, Greeks at 83, Poles at 85, Spaniards at 78, and Italians ranging between 78 and 85 in different studies.” And, of course, their IQs rose throughout the 20th century. Gould (1996: 227) showed that the average mental age for whites was 13.08, with anything between 8 and 12 being denoted a “moron.” Gould noted that the average Russian had a mental age of 11.34, while the Italian was at 11.01 and the Pole was at 10.74. This, of course, changed as these immigrants acclimated to American life.
For an interesting story for the creation of the term “moron”, see Dolmage’s (2018: 43) book Disabled Upon Arrival:
… Goddard’s invention of [the term moron] as a “signifier of tainted whiteness” was the “most important contribution to the concept of feeble-mindedness as a signifier of racial taint,” through the diagnosis of the menace of alien races, but also as a way to divide out the impure elements of the white race.
The Buraku are a cultural class—not a racial or ethnic group. Looking at America, the terms “black” and “white” are socialraces (Hardimon, 2017)—so could the same reasons for low Buraku educational attainment and IQ be the cause for black Americans’ low IQ and educational attainment? Time will tell, though there are no countries—to the best of my knowledge—that blacks have emigrated to and not been seen as an underclass or ‘inferior.’
The thesis by Ogbu is certainly interesting and has some explanatory power. The fact of the matter is that IQ and other tests of ability are bound by culture, and so, when the Buraku leave Japan and come to America, they are seen as regular Japanese (I’m not aware if Americans know about the Buraku/non-Buraku distinction) and they score just as well if not better than Americans and other non-Buraku Japanese. This points to discrimination and other environmental causes as the root of Buraku problems—noting that the Buraku became “full citizens” in 1871, 6 years after black slavery was ended in America. That Koreans in Japan also have similarly low educational attainment but high in America—higher than native-born Americans—is yet another point in favor of Ogbu’s thesis. The “system” and “community forces” seem to change when the two, previously low-scoring, high-crime group comes to America.
The increase in IQ of Southern and Eastern European immigrants, too, is another point in favor of Ogbu. Koreans and Buraku (indistinguishable from other native Japanese), when they leave Japan, are seen as any other Asians immigrants, and so, their outcomes are different.
In any case, the Buraku of Japan and Koreans who are Japanese citizens are an interesting look into how a group is treated can—and does—decrease test scores and social standing in Japan. Might the same hold true for blacks one day?
The “fade-out effect” occurs when interventions are given to children to increase their IQs, such as Head Start (HS) or other similar programs. In such instances when IQ gains are clear, hereditarians argue that the effect of the interventions “washes” away or “fades out.” Thus, when discussing such studies, hereditarians think they are standing in victory. That the effects from the intervention fade away is taken to be evidence for the hereditarian position and is taken to refute a developmental, interactionist position. However, that couldn’t be further from the truth.
Think about where the majority of HS individuals come from—poorer environments and which are more likely to have disadvantaged people in them. Since IQ tests—along with other tests of ability—are experience-dependent, then it logically follows that one who is not exposed to the test items or structure of the test, among other things, will be differentially prepared to take the test compared to, say, middle-class children who are exposed to such items daily.
When it comes to HS, for instance, whites who attend HS are “significantly more likely to complete high school, attend college, and possibly have higher earnings in their early twenties. African-Americans who participated in Head Start are less likely to have been booked or charged with a crime” (Garces, Thomas, and Currie, 2002). Deming (2009) shows many positive health outcomes in those who attend HS. This is beside the case, though (even if we accept the hereditarian hypothesis here, there are still many, many good reasons for programs such as HS).
Students who were randomly assigned to higher quality classrooms in grades K–3—as measured by classmates’ end-of-class test scores—have higher earnings, college attendance rates, and other outcomes. Finally, the effects of class quality fade out on test scores in later grades, but gains in noncognitive measures persist.
So such gains “faded out”, therefore hereditarianism is a more favorable position, right? Wrong.
Think about test items, and testing as a whole. Then think about differing environments that social classes are in. Now, thinking about test items, think about how exposure to such items and similar questions would have an effect on the test-taking ability of the individual in question. Thus, since tests of ability are experience-dependent, then the logical position to hold is that if they are exposed to the knowledge and experience needed for successful test-taking then they will score higher. And this is what we see when such individuals are enrolled in the program, but when the program ends and the scores decrease, the hereditarian triumphs that it is another piece of the puzzle, another piece of evidence in favor of their position. Howe (1997: 53) explains this perfectly:
It is an almost universal characteristic of acquired competences that when their is a prolonged absence of opportunities to use, practise, and profit from them, they do indeed decline. It would therefore be highly surprising if acquired gains in intelligence did not fade or diminish. Indeed, had the research findings shown that IQs never fade or decline, that evidence would have provided some support for the view that measured intelligence possesses the inherent — rather than acquired — status that intelligence theorists and other writers within the psychometric position have believed it to have.
A similar claim is made by Sauce and Matzel (2018):
In simpler terms, the analysis of Protzko should not lead us to conclude that early intervention programs such as Head Start can have no long-term benefits. Rather, these results highlight the need to provide participants with continuing opportunities that would allow them to capitalize on what might otherwise be transient gains in cognitive abilities.
Now, if we think in the context of the HS and similar interventions, we can see why such stark differences in scores appear, and why some studies show a fade out effect. Such new knowledge and skills (what IQ tests are tests of; Richardson, 2002) are largely useless in those environments since they have little to no opportunity to hone their newly-acquired skills.
Take success in an action video game, weight-lifting, bodybuilding (muscle-gaining), or pole-vaulting. One who does well in any one of these three events will of course have countless of hours of training learning new techniques and skills. They continue this for a while. Then they abruptly stop. They are no longer honing (and practicing) their acquired skills so they begin to lose them. The “fade-out effect” has affected their performance and the reason is due to their environmental stimulation—the same holds for IQ test scores.
I’ll use the issue of muscle-building to illustrate the comparison. Imagine you’re 20 years old and just start going to the gym on a good program. The first few months you get what are termed “newbie gains”, as your body and central nervous system begins to adapt to the new stressor you’re placing on your body. Then after the initial beginning period, at about 2 to 3 months, these gains eventually stop and then you’ll have to be consistent with your training and diet or you won’t progress in weight lifted or body composition. But you are consistent with training and diet and you then have a satisfactory body composition and strength gains.
But then things change you stop going to the gym as often as you did before and you get lazy with your nutrition. Your body composition you worked so hard for along with your strength gains start to dissipate since you’re not placing your body under the stressor it was previously under. But there is something called “muscle memory” which occurs due to motor learning in the central nervous system.
The comparison here is clear: strength is IQ and lifting weights is doing tests/tasks to prepare for the tests (exposure to middle-class knowledge and skills). So when one leaves their “enriching environments” (in this case, the gym and a good nutritional environment), they then lose the gains they worked for. The parallel then becomes clear: leave the enriched environments and return to the baseline. This example I have just illustrated shows exactly how and why these gains “fade out” (though they don’t in all of these types of studies).
One objection to my comparison I can imagine an IQ-ist making is that training for strength (which is analogous to types of interventions in programs like HS), one can only get so strong as, for example, their frame allows, or that there is a limit to which one only get to a certain level of musculature. They may say that one can only get to a certain number of IQ and there, their “genetic potential” maxes out, as it would in the muscle-building and strength-gaining example. But the objection fails. Tests of ability (IQ tests) are cultural in nature. Since they are cultural in nature, then exposure to what’s on the test (middle-class knowledge and skills) will have one score better. That is, IQ tests are experience-dependent, as is body composition and strength, but such tests aren’t (1) construct valid and (2) such tests are biased due to the items selected to be on them. When looking at weights, we have an objective, valid measure. Sure, weight-lifting measures a whole slew of variables including, what it is intended to, strength. But it also measures a whole slew of other variables associated with weight training, dependent on numerous other variables.
Therefore, my example with weights illustrates that if one removes themselves from their enriching environments that allows X, then they will necessarily decline. But due to, in this example, muscle memory, they can quickly return to where they were. Such gains will “fade out” if, and only if, they discontinue their training and meal prep, among other things. The same is true for IQ in these intervention studies.
Howe (1997: 54-55) (this editorial here has the discussion, pulled directly from the book) discusses the study carried out by Zigler and Seitz. They measured the effects of a four year intervention program which emphasized math skills. They were inner-city children who were enrolled in the orgrwm at kindergarten. The program was successful, in that those who participated in the program were two years ahead of a control group, but a few heads after in a follow-up, they were only a year ahead. Howe (1997:54-55) explains why:
For instance, to score well at the achievement tests used with older children it is essential to have some knowledge of algebra and geometry, but Seitz found that while the majority of middle-class children were being taught these subjects, the disadvantaged pupils were not getting the necessary teaching. For that reason they could hardly be expected to do well. As Seitz perceived, the true picture was not one of fading ability but of diminishing use of it.
So in this case, the knowledge gained from the intervention was not lost. Do note, though, how middle-class knowledge continues to appear in these discussions. That’s because tests of ability are cultural in nature since culture-fair impossible (Cole, 2004). Cole imagines a West African Binet who constructs a test of Kpelle culture. Cole (2004) ends up concluding that:
tests of ability are inevitably cultural devices. This conclusion must seem dreary and disappointing to people who have been working to construct valid, culture-free tests. But from the perspective of history and logic, it simply confirms the fact, stated so clearly by Franz Boas half a century ago, that “mind, independent of experience, is inconceivable.”
So, in this case, the test would be testing Kpelle knowledge, and not middle-class cultural skills and knowledge, which proves that IQ tests are bound by culture and that culture-fair (“free”) tests are impossible. This, then, also shows why such gains in test scores decrease: they are not in the types of environments that are conducive to that type of culture-specific knowledge (see some examples of questions on IQ tests here).
The fact is the matter is this: that the individuals in such studies return to their “old” environments is why their IQ gains disappear. People just focus on the scores, say “They decreased”—hardly without thinking why. Why should test scores reflect the efficacy of the HS and similar programs and not the fact that outcomes for children in this program are substantially better than those who did not participate? For example:
HS compared to non-HS children faired better on cognitive and socio-emotive measures having fewer negative behaviors and (Zhai et al, 2011). Adults who were in the HS program are more likely to graduate high school, go to college and receive a seconday degree (Bauer and Schanzenbach, 2016). A pre-school program raised standardized test scores through grade 5. Those who attended HS were less likely to become incarcerated, become teen parents, and are more likely to finish high-school and enroll in college (Barr and Gibs, 2017).
The cause of the fading out of scores is simple: if you don’t use it you lose it, as can be seen with the examples given above. IQ scores can and do increase is evidenced by the Flynn effect, so that is not touched by the fade-out effect. But this “fading-out” (in most studies, see Howe for more information) of scores, in my opinion, is ancillary to the main point: those who attend HS and similar programs do have better outcomes in life than those who did not attend. The literature on the matter is vast. Therefore, the “fading-out” of test scores doesn’t matter, as outcomes for those who attended are better than outcomes for those who do not.
HS and similar programs show that IQ is, indeed, malleable and not “set” or “stable” as hereditarians claim. That IQ tests are experience-dependent implies that those who receive such interventions get a boost, but when they leave their abilities decrease, which is due to not learning any new ones along with returning to their previous, less-stimulating environments. The cause of the “fading-out” is therefore simple: During the intervention they are engrossed in an enriching environment, learning about, by proxy, middle-class knowledge and skills which helps with test performance. But after they’re done they return to their previous environments and so they do not put their skills to use and they therefore regress. Like with my muscle-building example: if you don’t use it, you lose it.
Validity for IQ tests is fleeting. IQ tests are said to be “validated” on the basis of performance with other IQ tests and that of job performance (see Richardson and Norgate, 2015). Further, IQ tests are claimed to not be biased against social class or racial group. Finally, through the process of “item selection”, test constructors make the types of distributions they want (normal) and get the results the want through the subjective procedure of removing items that don’t agree with their pre-conceived notions on who is or is not “intelligent.” Lastly, “intelligence” is descriptive measure, not an explanatory concept, and treating it like an explanatory measure can—and does—lead to circularity (of which is rife in the subject of IQ testing; see Richardson, 2017b and Taleb’s article IQ is largely a psuedoscientific swindle). This article will show that, on the basis of test construction, item analysis (selection and deselection of items) and the fact that there is no theory of what is being measured in so-called intelligence tests that they, in fact, do not test what they purport to.
Richardson (1991: 17) states that “To measure is to give … a more reliable sense of quantity than our senses alone can provide”, and that “sensed intelligence is not an objective quantity in the sense that the same hotness of a body will be felt by the same humans everywhere (given a few simple conditions); what, in experience, we choose to call ‘more’ intelligence, and what ‘less’ a social judgement that varies from people to people, employing different criteria or signals.” Richardson (1991: 17-18) goes on to say that:
Even if we arrive at a reliable instrument to parallel the experience of our senses, we can claim no more for it than that, without any underlying theory which relates differences in the measure to differences in some other, unobserved, phenomena responsible for those differences. Without such a theory we can never be sure that differences in the measure correspond with our sensed intelligence aren’t due to something else, perhaps something completely different. The phenomenon we at first imagine may not even exist. Instead, such verification most inventors and users of measures of intelligence … have simply constructed the source of differences in sensed intelligence as an underlying entity or force, rather in the way that children and naïve adults perceive hotness as a substance, or attribute the motion of objects to a fictitious impetus. What we have in cases like temperature, of course, are collateral criteria and measures that validate the theory, and thus the original measures. Without these, the assumed entity remains a fiction. This proved to be the case with impetus, and with many other naïve conceptions of nature, such as phlogiston (thought to account for differences in health and disease). How much greater such fictions are likely to be unobserved, dynamic and socially judged concepts like intelligence.
Richardson (1991: 32-35) then goes on to critique many of the old IQ tests, in that they had no way of being construct valid, and that the manuals did not even discuss the validity of the test—it was just assumed.
If we do not know what exactly is being measured when test constructors make and administer these tests, then how can we logically state that “IQ tests test intelligence”? Even Arthur Jensen admitted that psychometricians can create any type of distribution they please (1980: 71); he tacitly admits that tests are devised through the selection and deselection of items on IQ tests that correspond to the test constructors preconceived notions on what “intelligence” is. This, again, is even admitted by Jensen (1980: 147-148) who writes “The items must simply emerge arbitrarily from the heads of test constructors.”
We know, to build on Richardson’s temperature example, that we know exactly is what being measured when we look at the amount of mercury in a thermometer. That is, the concept of “temperature” and the instrument to measure it (the thermometer) were verified independently, without circular reliance on the thermometer itself (see Hasok Chang’s 2007 book Inventing Temperature). IQ tests, on the other hand, are, supposedly, “validated” through measures of job performance and correlations with other, previous tests assumed to be (construct) valid—but they were, of course, just assumed to be valid, it was never shown.
For another example (as I’ve shown with IQ many times) of a psychological construct that is not valid is ASD (autism spectrum disorder). Waterhouse, London, and Gilliberg (2016) write that “14 groups of findings reviewed in this paper that together argue that ASD lacks neurobiological and construct validity. No unitary ASD brain impairment or replicated unitary model of ASD brain impairment exists.” That a construct is valid—that is, it tests what it purports to, is of utmost importance to test measurement. Without it, we don’t know if we’re measuring something else completely different from what we hope—or purport—to.
There is another problem: the fact that, for one of the most-used IQ tests that there is no underlying theory of item selection, as seen in John Raven’s personal notes (see Carpenter, Just, and Shell, 1990). Items on the Raven were selected based on Raven’s intuition, and not any formal theory—the same can be said about, of course, modern-day IQ tests. Carpenter, Just, and Shell (1990) write that John Raven “used his intuition and clinical experience to rank order the difficulty of the six problem types . . . without regard to any underlying processing theory.”
These preconceived notions on what “intelligence” is, though, fail without (1) a theory of what intelligence is (which, as admitted by Ian Deary (2001), there is no theory of human intelligence like the way physics has theories); and (2) what ultimately is termed “construct validity”—that a test measures what it purports to. There are a few kinds of validity: and what IQ-ists claim the most is that IQ tests have predictive validity—that is, they can predict an individual’s outcome in life, and job performance (it is claimed). However, “intelligence” is “a descriptive measure, not an explanatory concept … [so] measures of intelligence level have little or no predictive value” (Howe, 1988).
Howe (1997: ix) also tells us that “Intelligence is … an outcome … not a cause. … Even the most confidently stated assertions about intelligence are often wrong, and the inferences that people have drawn from those assertions are unjustified.”
The correlation between IQ and school performance, according to Richardson (1991: 34) “may be a necessary aspect of the validity of tests, but is not a sufficient one. Such evidence, as already mentioned, requires a clear connection between a theory (a model of intelligence), and the values on the measure.” But, as Richardson (2017: 85) notes:
… it should come as no surprise that performance on them [IQ tests] is associated with school performance. As Robert L. Thorndike and Elizabeth P. Hagen explained in their leading textbook, Educational and Psychological Measurement, “From the very way in which the tests were assembled [such correlation] could hardly be otherwise.”
Gottfredson (2009) claims that the construct validity argument against IQ is “fallacious”, noting it as one of her “fallacies” on intelligence testing (one of her “fallacies” was the “interactionism fallacy”, which I have previously discussed). However, unfortunately for Gottfredson (2009), “the phenomena that testers aim to capture” are built into the test and, as noted here numerous times, preconceived by the constructors of the test. So, Gottfredson’s (2009) claim fails.
Such kinds of construction, too, come into the claim of a “normal distribution.” Just like with preconceptions of who is or is not “intelligent” on the basis of preconceived notions, the normal distribution, too, is an artifact of test construction, along the selection and deselection of items to conform with the test constructors’ presuppositions; the “bell curve” of IQ is created by the presuppositions that the test constructors have about people and society (Simon, 1997).
Charles Spearman, in the early 1900s, claims to have found a “general factor” that explains correlations between different tests. This positive manifold he termed “g” for “general intelligence.” Spearman stated “The (g) factor was taken, pending further information, to consist in something of the nature of an ‘energy’ or ‘power’…” (quoted in Richardson, 1991: 38). The refutation of “g” is a simple, logical, one: While a correlation between performances “may be a necessary requirement for a general factor … it is not a sufficient one.” This is because “it is quite possible for quite independent factors to produce a hierarchy of correlations without the existence of any underlying ‘general’ factor (Fancer, 1985a; Richardson and Bynner, 1984)” (Richardson, 1991: 38). The fact of the matter is, Spearman’s “g” has been refuted for decades (and was shown to be reified by Gould (1981), and further defenses of his concepts on “general intelligence”, like by Jensen (1998) have been refuted, most forcefully by Peter Schonemann. Though, “g” is something built into the test by way of test construction (Richardson, 2002).
Castles (2013: 93) notes that “Spearman did not simply discover g lurking in his data. Instead, he chose one peculiar interpretation of the relationships to demonstrate something in which he already believed—unitary, biologically based intelligence.”
So what explains differences in “g”? The same test construction noted above along with differences in social class, due to stress, self-confidence, test preparedness and other factors correlated with social class, termed the “sociocognitive-affective nexus” (Richardson, 2002).
Constance Hilliard, in her book Straightening the Bell Curve (Hilliard, 2012), notes that there were differences in IQ between rural and urban white South Africans. She notes that differences between those who spoke Afrikaans and those who spoke another language were completely removed through test construction (Hilliard, 2012: 116). Hilliard (2012) notes that if the tests that the constructors formulate don’t agree with their preconceived notions, they are then thrown out:
If the individuals who were supposed to come out on top didn’t score highly or, conversely, if the individuals who were assumed would be at the bottom of the scores didn’t end up there, then the test designers scrapped the test.
Sex differences in “intelligence” (IQ) have been the subject of some debate in the early-to-mid-1900s. Test constructors debated amongst themselves what to do about such differences between the sexes. Hilliard (2012) quotes Harrington (1984; in Perspectives on Bias in Mental Testing) who writes about normalizing test scores between men and women:
It was decided [by IQ test writers] a priori that the distribution of intelligence-test scores would be normal with a mean (X=100) and a standard deviation (SD=15), also that both sexes would have the same mean and distribution. To ensure the absence of sex differences, it was arranged to discard items on which the sexes differed. Then, if not enough items remained, when discarded items were reintroduced, they were balanced, i.e., for every item favoring males, another one favoring females was also introduced.
One who would construct a test for intellectual capacity has two possible methods of handling the problem of sex differences.
1 He may assume that all the sex differences yielded by his test items are about equally indicative of sex differences in native ability.
2 He may proceed on the hypothesis that large sex differences on items of the Binet type are likely to be factitious in the sense that they reflect sex differences in experience or training. To the extent that this assumption is valid, he will be justified in eliminating from his battery test items which yield large sex differences.
The authors of the New Revision have chosen the second of these alternatives and sought to avoid using test items showing large differences in percents passing. (McNemar 1942:56)
Change “sex differences” to “race” or “social class” differences and we can, too, change the distribution of the curve, along with notions of who is or is not “intelligent.” Previously low scorers can, by way of test construction, become high scorers, vice-versa for high scorers being made into low scorers. There is no logical—or empirical—justification for the inclusion of specific items on whatever IQ test is in question. That is, to put it another way, the inclusion of items on a test is subjective, which comes down to the test designers’ preconceived notions, and not an objective measure of what types of items should be on the test—as Raven stated, there is no type of underlying theory for the inclusion of items in the test, it is based on “intuition” (which is the same thing that modern-day test constructors do). These two quotes from IQ-ists in the early 20th century are paramount in the attack on the validity of IQ tests—and the causes for differences in scores between groups.
He and van de Vijver (2012: 7) write that “An item is biased when it has a different psychological meaning across cultures. More precisely, an item of a scale (e.g., measuring anxiety) is said to be biased if persons with the same trait, but coming from different cultures, are not equally likely to endorse the item (Van de Vijver & Leung, 1997).” Indeed, Reynolds and Suzuki (2012: 83) write that “Item bias due to“:
… “poor item translation, ambiguities in the original item, low familiarity/appropriateness of the item content in certain cultures, or influence of culture specifics such as nuisance factors or connotations associated with the item wording” (p. 127) (van de Vijver and Tanzer, 2004)
Drame and Ferguson (2017) note that their “Results indicate that use of the Ravens may substantially underestimate the intelligence of children in Mali” while the cause may be due to the fact that:
European and North American children may spend more time with play tasks such as jigsaw puzzles or connect the dots that have similarities with the Ravens and, thus, train on similar tasks more than do African children. If African children spend less time on similar tasks, they would have fewer opportunities to train for the Ravens (however unintentionally) reflecting in poorer scores. In this sense, verbal ability need not be the only pitfall in selecting culturally sensitive IQ testing approaches. Thus, differences in Ravens scores may be a cultural artifact rather than an indication of true intelligence differences. [Similar arguments can be found in Richardson, 2002: 291-293]
The same was also found by Dutton et al (2017) who write that “It is argued that the undeveloped nature of South Sudan means that a test based around shapes and analytic thinking is unsuitable. It is likely to heavily under-estimate their average intelligence.” So if the Raven has these problems cross-culturally (country), then it SHOULD have such biases within, say, America.
It is also true that the types of items on IQ tests are not as complex as everyday life (see Richardson and Norgate, 2014). Types of questions on IQ tests are, in effect, ones of middle-class knowledge and skills and, knowing how IQ tests are structured will make this claim clear (along with knowing the types of items that eventually make it onto the particular IQ test itself). Richardson (2002) has a few questions on modern-day IQ tests whereas Castles (2013), too, has a few questions from the Stanford-Binet. This, of course, is due to the social class of the test constructors. Some examples of some questions can be seen here:
‘What is the boiling point of water?’ ‘Who wrote Hamlet?’ ‘In what continent is Egypt?’ (Richardson, 2002: 289)
‘When anyone has offended you and asks you to excuse him—what ought you do?’ ‘What is the difference between esteem and affection?’ [this is from the Binet Scales, but “It is interesting to note that similar items are still found on most modern intelligence tests” (Castles, 2013).]]
Castles (2013: 150) further notes made-up examples of what is on the WAIS (since she cannot legally give questions away since she is a licensed psychologist), and she writes:
One section of the WAIS-III, for example, consists of arithmetic problems that the respondent must solve in his or her head. Others require test-takers to define a series of vocabulary words (many of which would be familiar only to skilled-readers), to answer school-related factual questions (e.g., “Who was the first president of the United States?” or “Who wrote the Canterbury Tales?”), and to recognize and endorse common cultural norms and values (e.g., “What should you do it a sale clerk accidentally gives you too much change?” or “Why does our Constitution call for division of powers?”). True, respondents are also given a few opportunities to solve novel problems (e.g., copying a series of abstract designs with colored blocks). But even these supposedly culture-fair items require an understanding of social conventions, familiarity with objects specific to American culture, and/or experience working with geometric shapes or symbols.
All of these factors coalesce into forming the claim—and the argument—that IQ tests are one of middle-class knowledge and skills. The thing is, contrary to the claims of IQ-ists, there is no such thing as a culture-free IQ test. Richardson (2002: 293) notes that “Since all human cognition takes place through the medium of cultural/psychological tools, the very idea of a culture-free test is, as Cole (1999) notes, ‘a contradiction in terms . . . by its very nature, IQ testing is culture bound’ (p. 646). Individuals are simply more or less prepared for dealing with the cognitive and linguistic structures built in to the particular items.”
Cole (1981) notes that “that the notion of a culture free IQ test is an absurdity” because “all higher psychological processes are shaped by our experiences and these experiences are culturally organized” (this is a point that Richardson has driven home for decades) while also—rightly—stating that “IQ tests sample school activities, and therefore, indirectly, valued social activities, in our culture.”
One of the last stands for the IQ-ist is to claim that IQ tests are useful for identifying at-risk individuals for learning disabilities (as Binet originally created the first IQ tests for). However, it is noted that IQ tests are not necessary—nor sufficient—for the identification of those with learning disabilities. Siegal (1989) states that “On logical and empirical grounds, IQ test scores are not necessary for the definition of learning disabilities.”
When Goddard brought the first IQ tests to America and translated them into English from French is when the IQ testing conglomerate really took off (see Zenderland, 1998 for a review). These tests were used to justify current social ranks. As Richardson (1991: 44) notes, “The measurement of intelligence in the twentieth century arose partly out of attempts to ‘prove’ or justify a particular world view, and partly for purposes of screening and social selection. It is hardly surprising that its subsequent fate has been one of uncertainty and controversy, nor that it has raised so many social and political issues (see, for example, Joynson 1989 for discussion of such issues).” So, what actual attempts at validation did the constructors of such tests need in the 20th century when they knew full-well what they wanted to show and, unsurprisingly, they observed it (since it was already going to happen since they construct the test to be that way)?
The conceptual arguments just given here point to a few things:
(1) IQ tests are not construct valid because there is no theory of intelligence, nor is there an underlying theory which relates differences in IQ (the unseen function) to, for example, a physiological variable. (See Uttal, 2012; 2014 for arguments against fMRI studies that purport to show differences in physiological variables cognition.)
(2) The fact that items on the tests are biased against certain classes/cultures; this obviously matters since, as noted above, there is no theory for the inclusion of items, it comes down to the subjective choice of the test designers, as noted by Jensen.
(3) ‘g’ is a reified mathematical abstraction; Spearman “discovered” nothing, he just chose the interpretation that, of course, went with his preconceived notion.
(4) The fact that sex differences in IQ scores were seen as a problem and, through item analysis, made to go away. This tells us that we can do the same for class/race differences in intelligence. Score differences are a function of test construction.
(5) The fact that the Raven has been shown to be biased in two African countries lends credence to the claims here.
So this then brings us to the ultimate claim of this article: IQ tests don’t test intelligence; they test middle-class knowledge and skills. Therefore, the scores on IQ tests are not that of intelligence, but of an index of one’s cultural knowledge of the middle class and its knowledge structure. This, IQ scores are, in actuality, “middle-class knowledge and skills” scores. So, contra Jensen (1980), there is bias in mental testing due to the items chosen for inclusion on the test (we have admission that score variances and distributions can change from IQ-ists themselves)
On Twitter, getting into discussions with Charles Murray acolytes, someone asked me to write a short piece describing the argument in The Bell Curve (TBC) by Herrnstein and Murray (H&M). This is because I was linking my short Twitter thread on the matter, which can be seen here:
In TBC, H&M argue that America is becoming increasingly stratified by social class, and the main reason is due to the “cognitive elite.” The assertion is that social class in America used to be determined by one’s social origin is now being determined by one’s cognitive ability as tested by IQ tests. H&M make 6 assertions in the beginning of the book:
(i) That there exists a general cognitive factor which explains differences in test scores between individuals;
(ii) That all standardized tests measure this general cognitive factor but IQ tests measure it best;
(iii) IQ scores match what most laymen mean by “intelligent”, “smart”, etc.;
(iv) Scores on IQ tests are stable, but not perfectly so, throughout one’s life;
(v) Administered properly, IQ tests are not biased against classes, races, or ethnic groups; and
(vi) Cognitive ability as measured by IQ tests is substantially heritable at 40-80%/
In the second part, H&M argue that high cognitive ability predicts desireable outcomes whereas low cognitve ability predicts undesireable outcomes. Using the NLSY, H&M show that IQ scores predict one’s life outcomes better than parental SES. All NLSY participants took the ASVAB, while others took IQ tests which were then correlated with the ASVAB and the correlation came out to .81.
They analyzed whether or not one has ever been incarcerated, unemployed for more than one month in the year; whether or not they dropped out of high-school; whether or not they were chronic welfare recipients; among other social variables. When they controlled for IQ in these analyses, most of the differences between ethnic groups, for example, disappeared.
Now, in the most controversial part of the book—the third part—they discuss ethnic differences in IQ scores, stating that Asians have higher IQs than whites who have higher IQs than ‘Hispanics’ who have higher IQs than blacks. H&M argue that the white-black IQ gap is not due to bias since they do not underpredict blacks’ school or job performance. H&M famously wrote about the nature of lower black IQ in comparison to whites:
If the reader is now convinced that either the genetic or environmental explanation has won out to the exclusion of the other, we have not done a sufficiently good job of presenting one side or the other. It seems highly likely to us that both genes and environment have something to do with racial differences. What might the mix be? We are resolutely agnostic on that issue; as far as we can determine, the evidence does not yet justify an estimate.
Finally, in the fourth and last section, H&M argue that efforts to raise cognitive ability through the alteration of the social and physical environment have failed, though we may one day find some things that do raise ability. They also argue that the educational experience in America neglects the small, intelligent minority and that we should begin to not neglect them as they will “greatly affect how well America does in the twenty-first century” (H&M, 1996: 387). They also argue forcefully against affirmative action, in the end arguing that equality of opportunity—over equality of outcome—should be the role of colleges and workplaces. They finally predict that this “cognitive elite” will continuously isolate themselves from society, widening the cognitive gap between them.
1843 Magazine published an article back in July titled The Curse of Genius, stating that “Within a few points either way, IQ is fixed throughout your life …” How true is this claim? How much is “a few points”? Would it account for any substantial increase or decrease? A few studies do look at IQ scores in one sample longitudinally. So, if this is the case, then IQ is not “like height”, as most hereditarians claim—it being “like height” since height is “stable” at adulthood (like IQ) and only certain events can decrease height (like IQ). But these claims fail.
IQ is, supposedly, a stable trait—that is, like height, at a certain age, it does not change. (Other than sufficient life events, such as having a bad back injury that causes one to slouch over, causing a decrease in height, or getting a traumatic brain injury—though that does not always decrease IQ scores). IQ tests supposedly measure a stable biological trait—“g” or general intelligence (which is built into the test, see Richardson, 2002 and see Schonemann’s papers for refutations on Jensen’s and Spearman’s “g“).
IQ levels are expected to stick to people like their blood group or their height. But imagine a measure of a real, stable bodily function of an individual that is different at different times. You’d probably think what a strange kind of measure. IQ is just such a measure. (Richardson, 2017: 102)
Neuroscientist Allyson Mackey’s team, for example, found “that after just eight weeks of playing these games the kids showed a pretty big IQ change – an improvement of about 30% or about 10 points in IQ.” Looking at a sample of 7-9 year olds, Mackey et al (2011) recruited children from low SES backgrounds to participate in cognitive training programs for an hour a day, 2 days a week. They predicted that children from a lower SES would benefit more from such cognitive/environmental enrichment (indeed, think of the differences between lower and middle SES people).
Mackey et al (2011) tested the children on their processing speed (PS), working memory (WM), and fluid reasoning (FR). Assessing FR, they used a matrix reasoning task with two versions (for the retest after the 8 week training). For PS, they used a cross-out test where “one must rapidly identify and put a line through each instance of a specific symbol in a row of similar symbols” (Mackey et al, 2011: 584). While the coding “is a timed test in which one must rapidly translate digits into symbols by identifying the corresponding symbol for a digit provided in a legend” (ibid.) which is a part of the WISC IV. Working memory was assessed through digit and spatial span tests from the Wechsler Memory Scale.
The kinds of games they used were computerized and non-computerized (like using a Nintendo DS). Mackey et al (2011: 585) write:
Both programs incorporated a mix of commercially available computerized and non-computerized games, as well as a mix of games that were played individually or in small groups. Games selected for reasoning training demanded the joint consideration of several task rules, relations, or steps required to solve a problem. Games selected for speed training involved rapid visual processing and rapid motor responding based on simple task rules.
So at the end of the 8-week program, cognitive abilities increased in both groups. For the children in the reasoning training, they solved an average of 4.5 more matrices than their previous try. Mackey et al (585-586) write:
Before training, children in the reasoning group had an average score of 96.3 points on the TONI, which is normed with a mean of 100 and a standard deviation of 15. After training, they had an average score of 106.2 points. This gain of 9.9 points brought the reasoning ability of the group from below average for their age. [But such gains were not significant on the test of nonverbal intelligence, showing an increase of 3.5 points.]
One of the biggest surprises was that 4 out of the 20 children in the reasoning training showed an increase of over 20 points. This, of course, refutes the claim that such “ability” is “fixed”, as hereditarians have claimed. Mackey et al (2011: 587) writes that “the very existence and widespread use of IQ tests rests on the assumption that tests of FR measure an individual’s innate capacity to learn.” This, quite obviously, is a false claim. (This claim comes from Cattell, no less.) This buttresses the claim that IQ tests are, of course, experience dependent.
This study shows that IQ is not malleable and that exposure to certain cultural tools leads to increases in test scores, as hypothesized (Richardson, 2002, 2017).
Salthouse (2013) writes that:
results from different types of approaches are converging on a conclusion that practice or retest contributions to change in several cognitive abilities appear to be nearly the same magnitude in healthy adults between about 20 and 80 years of age. These findings imply that age comparisons of longitudinal change are not confounded with differences in the influences of retest and maturational components of change, and that measures of longitudinal change may be underestimates of the maturational component of change at all ages.
Moreno et al (2011) show that after 20 days of computerized training, children in the music group showed enhanced scores on a measure of verbal ability—90 percent of the sample showed the same improvement. They further write that “the fact that only one of the groups showed a positive correlation between brain plasticity (P2) and verbal IQ changes suggests a link between the specific training and the verbal IQ outcome, rather than improvement due to repeated testing.”
Schellenberg (2004) describes how there was an advertisement looking for 6 year olds to enroll them in art lessons. There were 112 children enrolled into four groups: two groups received music lessons for a year, on either a standard keyboard or they had Kodaly voice training while the other two groups received either drama training or no training at all. Schellenberg (2004: 3) writes that “Children in the control groups had average
increases in IQ of 4.3 points (SD = 7.3), whereas the music groups had increases of 7.0 points (SD = 8.6).” So, compared to either drama training or no training at all, the children in the music training gained 2.7 IQ points more.
(Figure 1 from Schellenberg, 2004)
Ramsden et al (2011: 3-4) write:
The wide range of abilities in our sample was confirmed as follows: FSIQ ranged from 77 to 135 at time 1 and from 87 to 143 at time 2, with averages of 112 and 113 at times 1 and 2, respectively, and a tight correlation across testing points (r 5 0.79; P , 0.001). Our interest was in the considerable variation observed between testing points at the individual level, which ranged from 220 to 123 for VIQ, 218 to 117 for PIQ and 218 to 121 for FSIQ. Even if the extreme values of the published 90% confidence intervals are used on both occasions, 39% of the sample showed a clear change in VIQ, 21% in PIQ and 33% in FSIQ. In terms of the overall distribution, 21% of our sample showed a shift of at least one population standard deviation (15) in the VIQ measure, and 18% in the PIQ measure. [Also see The Guardian article on this paper.[
Richardson (2017: 102) writes “Carol Sigelman and Elizabeth Rider reported the IQs of one group of children tested at regular intervals between the ages of two years and seventeen years. The average difference between a child’s highest and lowest scores was 28.5 points, with almost one-third showing changes of more than 30 points (mean IQ is 100). This is sufficient to move an individual from the bottom to the top 10 percent or vice versa.” [See also the page in Sigelman and Rider, 2011.]
Mortensen et al (2003) show that IQ remains stable in mid- to young adulthood in low birthweight samples. Schwartz et al (1975: 693) write that “Individual variations in patterns of IQ changes (including no changes over time) appeared to be related to overall level of adjustment and integration and, as such, represent a sensitive barometer of coping responses. Thus, it is difficult to accept the notion of IQ as a stable, constant characteristic of the individual that, once measured, determines cognitive functioning for any age level for any test.”
There is even instability in IQ seen in high SES Guatemalans born between 1941-1953 (Mansukoski et al, 2019). Mansukoski et al’s (2019) analysis “highlight[s] the complicated nature of measuring and interpreting IQ at different ages, and the many factors that can introduce variation in the results. Large variation in the pre-adult test scores seems to be more of a norm than a one-off event.” Possible reasons for the change could be due to “adverse life events, larger than expected deviations of individual developmental level at the time of the testing and differences between the testing instruments” (Mansukoski et al, 2019). They also found that “IQ scores did not significantly correlate with age, implying there is no straightforward developmental cause behind the findings“, how weird…
Summarizing such studies that show an increase in IQ scores in children and teenagers, Richardson (2017: 103) writes:
Such results suggest that we have no right to pin such individual differences on biology without the obvious, but impossible, experiment. That would entail swapping the circumstances of upper-and lower-class newborns—parents’ inherited wealth, personalities, stresses of poverty, social self-perception, and so on—and following them up, not just over years or decades, but also over generations (remembering the effects of maternal stress on children, mentioned above). And it would require unrigged tests based on proper cognitive theory.
In sum, the claim that IQ is stable at a certain age like another physical trait is clearly false. Numerous interventions and reasons can increase or decrease one’s IQ score. The results discussed in this article show that familiarity to certain types of cultural tools increases one’s score (like in the low SES group tested in Mackey et al, 2011). Although the n is low (which I know is one of the first things I will hear), I’m not worried about that. What I am worried about is the individual change in IQ at certain ages, and they show that. So the results here show support for Richardson’s (2002) thesis that “IQ scores might be more an index of individuals’ distance from the cultural tools making up the test than performance on a singular strength variable” (Richardson, 2012).
IQ is not stable; IQ is malleable, whether through exposure to certain cultural/class tools or through certain aspects that one is exposed to that are more likely to be included in certain classes over others. Indeed, this lends credence to Castles’ (2013) claim that “Intelligence is in fact a cultural construct, specific to a certain time and place.“
Why do some groups of people use chopsticks and others do not? Years back, created a thought experiment. So he found a few hundred students from a university and gathered DNA samples from their cheeks which were then mapped for candidate genes associated with chopstick use. Come to find out, one of the associated genetic markers was associated with chopstick use—accounting for 50 percent of the variation in the trait (Hamer and Sirota, 2000). The effect even replicated many times and was highly significant: but it was biologically meaningless.
One may look at East Asians and say “Why do they use chopsticks” or “Why are they so good at using them while Americans aren’t?” and come to such ridiculous studies such as the one described above. They may even find an association between the trait/behavior and a genetic marker. They may even find that it replicates and is a significant hit. But, it can all be for naught, since population stratification reared its head. Population stratification “refers to differences in allele frequencies between cases and controls due to systematic differences in ancestry rather than association of genes with disease” (Freedman et al, 2004). It “is a potential cause of false associations in genetic association studies” (Oetjens et al, 2016).
Such population stratification in the chopsticks gene study described above should have been anticipated since they studied two different populations. Kaplan (2000: 67-68) described this well:
A similar argument, bu the way, holds true for molecular studies. Basically, it is easy to mistake mere statistical associations for a causal connection if one is not careful to properly partition one’s samples. Hamer and Copeland develop and amusing example of some hypothetical, badly misguided researchers searching for the “successful use of selected hand instruments” (SUSHI) gene (hypothesized to be associated with chopstick usage) between residents in Tokyo and Indianapolis. Hamer and Copeland note that while you would be almost certain to find a gene “associated with chopstick usage” if you did this, the design of such a hypothetical study would be badly flawed. What would be likely to happen here is that a genetic marker associated with the heterogeneity of the group involved (Japanese versus Caucasian) would be found, and the heterogeneity of the group involved would independently account for the differences in the trait; in this case, there is a cultural tendency for more people who grow up in Japan than people who grow up in Indianapolis to learn how to use chopsticks. That is, growing up in Japan is the causally important factor in using chopsticks; having a certain genetic marker is only associated with chopstick use in a statistical way, and only because those people who grow up in Japan are also more likely to have the marker than those who grew up in Indianapolis. The genetic marker is in no way causally related to chopstick use! That the marker ends up associated with chopstick use is therefore just an accident of design (Hamer and Copeland, 1998, 43; Bailey 1997 develops a similar example).
In this way, most—if not all—of the results of genome-wide association studies (GWASs) can be accounted for by population stratification. Hamer and Sirota (2000) is a warning to psychiatric geneticists to not be quick to ascribe function and causation to hits on certain genes from association studies (of which GWASs are).
Many studies, for example, Sniekers et al (2017), Savage et al (2018) purport to “account for” less than 10 percent of the variance in a trait, like “intelligence” (derived from non-construct valid IQ tests). Other GWA studies purport to show genes that affect testosterone production and that those who have a certain variant are more likely to have low testosterone (Ohlsson et al, 2011). Population stratification can have an effect here in these studies, too. GWASs; they give rise to spurious correlations that arise due to population structure—which is what GWASs are actually measuring, they are measuring social class, and not a “trait” (Richardson, 2017b; Richardson and Jones, 2019). Note that correcting for socioeconomic status (SES) fails, as the two are distinct (Richardson, 2002). (Note that GWASs lead to PGSs, which are, of course, flawed too.)
Such papers presume that correlations are causes and that interactions between genes and environment either don’t exist or are irrelevant (see Gottfredson, 2009 and my reply). Both of these claims are false. Correlations can, of course, lead to figuring out causes, but, like with the chopstick example above, attributing causation to things that are even “replicable” and “strongly significant” will still lead to false positives due to that same population stratification. Of course, GWAS and similar studies are attempting to account for the heriatbility estimates gleaned from twin, family, and adoption studies. Though, the assumptions used in these kinds of studies are shown to be false and, therefore, heritability estimates are highly exaggerated (and flawed) which lead to “looking for genes” that aren’t there (Charney, 2012; Joseph et al, 2016; Richardson, 2017a).
Richardson’s (2017b) argument is simple: (1) there is genetic stratification in human populations which will correlate with social class; (2) since there is genetic stratification in human populations which will correlate with social class, the genetic stratification will be associated with the “cognitive” variation; (3) if (1) and (2) then what GWA studies are finding are not “genetic differences” between groups in terms of “intelligence” (as shown by “IQ tests”), but population stratification between social classes. Population stratification still persists even in “homogeneous” populations (see references in Richardson and Jones, 2019), and so, the “corrections for” population stratification are anything but.
So what accounts for the small pittance of “variance explained” in GWASs and other similar association studies (Sniekers et al, 2017 “explained” less than 5 percent of variance in IQ)? Population stratification—specifically it is capturing genetic differences that occurred through migration. GWA studies use huge samples in order to find the genetic signals of the genes of small effect that underline the complex trait that is being studied. Take what Noble (2018) says:
As with the results of GWAS (genome-wide association studies) generally, the associations at the genome sequence level are remarkably weak and, with the exception of certain rare genetic diseases, may even be meaningless (13, 21). The reason is that if you gather a sufficiently large data set, it is a mathematical necessity that you will find correlations, even if the data set was generated randomly so that the correlations must be spurious. The bigger the data set, the more spurious correlations will be found (3).
Calude and Longo (2016; emphasis theirs) “prove that very large databases have to contain arbitrary correlations. These correlations appear only due to the size, not the nature, of data. They can be found in “randomly” generated, large enough databases, which — as we will prove — implies that most correlations are spurious.”
So why should we take association studies seriously when they fall prey to the problem of population stratification (measuring differences between social classes and other populations) along with the fact that big datasets lead to spurious correlations? I fail to think of a good reason why we should take these studies seriously. The chopsticks gene example perfectly illustrates the current problems we have with GWASs for complex traits: we are just seeing what is due to social—and other—stratification between populations and not any “genetic” differences in the trait that is being looked at.
The most well-known high IQ society (HIS hereafter) is Mensa. But did you know that there are many more—much more exclusive—high IQ societies? In his book The Genius in All of Us: Unlocking Your Brain’s Potential (Adam, 2018) Adam chronicles his quest to raise his IQ score using nootropics. (Nootropics are supposed brain-enhancers, such as creatine that supposedly help in increasing cognitive functioning.) Adam discusses his experience taking the Mensa test (Mensa “is Mexican slang for stupid woman“; Adam, 2018) and talking to others who did with him on the same day. One highschool student he talked to wanted to put that he was a Mensa member on his CV; yet another individual stated that they accepted a challenge from a family member, since other members were in Mensa, she wanted to show that she had what it took.
Adam states that they were handed two sheets of paper with 30 questions, to be answered in three or four minutes, with questions increasing in difficulty. The first paper, he says, had a Raven-like aspect to it—rotating shapes and choosing the correct shape that’s next in the sequence. But, since he was out of time for the test, he says that he answered “A” to the remaining questions when the instructor wasn’t looking, since he “was going to use cognitive enhancement to cheat later anyway” (Adam, 2018: 23). (I will show Adam’s results of his attempted “cognitive enhancement to cheat” on the Mensa exam at the end of this article.) The shapes-questions were from the first paper, and the second was verbal. On this part, some words had to be defined while others had to be placed into context, or be placed into a sentence in the right place. Adam (2018: 23) gives an example of some of the verbal questions:
Is ‘separate’ the equivalent of ‘unconnected’ or ‘unrelated’? Or ‘evade’ — is it the same as ‘evert’, ‘elude’ or ‘escape’?
[Compare to other verbal questions on standard IQ tests:
‘What is the boiling point of water?’ ‘Who wrote Hamlet?’ ‘In what continent is Egypt?’ (Richardson, 2002: 289)
‘When anyone has offended you and asks you to excuse him—what ought you do?’ ‘What is the difference between esteem and affection?’ [this is from the Binet Scales, but “It is interesting to note that similar items are still found on most modern intelligence tests” (Castles, 2013).]]
So it took a few weeks for Adam’s results to get delivered to his home. His wife opened the letter and informed him that he had gotten into Mensa. (He got in despite answering “A” after the time limit was up.) This, though, threw a wrench into his plans: his plan was to use cognitive enhancers (nootropics) to enhance his cognition and attempt to score higher and get into Mensa that way. However, there are much more exclusive IQ clubs than Mensa. Adam (2018: 30) writes:
Under half of the Mensa membership, for example, would get into the Top One Percent Society (TOPS). And fewer than one in ten of those TOPS members would make the grade at the One in a Thousand Society. Above that the names get cryptic and the spelling freestyle.
There’s the Epida society, the Milenija, the Sthiq Society, and Ludomind. The Universal Genius Society takes just one person in 2,330, and the Ergo Society just one in 31,500. Members of the Mega Society, naturally, are one in a million. The Giga Society? One in a billion, which means, statistically, just seven people on the planet are qualified to join. Let’s hope the know about it. If you are friends with one of them, do tell them.
At the top of the tree is the self-proclaimed Grail Society, which sets its membership criteria so high — one in 76 billion — that it currently has zero members. It’s run by Paul Cooijmans, a guitarist from the Netherlands. About 2,000 people have tried and failed to join, he says. ‘Be assured that no one has come close.’
Wow, what exclusive clubs! Mensans are also more likely to have “psychological and physiological overexcitabilities” (Karpinski et al, 2018) such as ADHD, autism, and other physiologic diseases. How psycho and socially awkward a few members of Mensa are is evidenced in this tweet thread.
How spooooky. Surely the high IQ Mensans have un-thought-of ways of killing that us normies could never fathom. And surely, with their high IQs, they can outsmart the ones who would attempt to catch them for murder.
A woman named Jamie Loftus got into Mensa and she says that you get a discount on Hertz car rentals, a link to the Geico insurance website, you get access to the Mensa dating site “Mensa Match” (there is also an “IQ” dating site called https://youandiq.com/), an email address, a cardboard membership card, and access to Mensa events in your area. Oh, and of course, you have to pay to take the test and pay yearly to stay in. (Also read Loftus’ other articles on her Mensa experience: one where she describes the death threats she got, and another in which she describes how Mensans would like her to not write bad things about them (Mensans). Seems like Mensans are in their “feels” about being attacked for their little—useless—club.)
One of the founders of Mensa—Lancelot Ware—stated that he “get[s] disappointed that so many members spend so much time solving puzzles” (quoted in Tammet, 2009: 40). If Mensa were anything but “members [who] spend so much time solving puzzles“, then I think Ware would have stated as much. While the other founder of Mensa—Ronald Berrill— “had intended Mensa as “an aristocracy of the intellect”, and was unhappy that a majority of Mensans came from humble homes” (the Wikipedia article on Mensa International cites Serebriakoff, 1986 as the reference for the quote).
So, when it comes to HISs, what do they bring to the world? Or is it just a dues-paid club so that the people on top can get money from people attempting to stroke their egos saying “Yea, I scored high on a test and am in a club!”
The supervisor of the Japanese Intelligence Network (JIN) writes (his emphasis):
Currently, the ESOTERIQ society has seven members and the EVANGELIQ has one member.
I can perfectly guarantee that the all members exactly certainly undoubtedly absolutely officially keep authentic the highest IQ score performances.
Especially, the EVANGELIQ is the most exclusive high IQ society which has at least one member.
Do you think the one member of EVANGELIQ talks to himself a lot? From the results of Karpinski et al (2018), I would hazard the guess that, yes, he does. Here is a list of 84 HISs, and there is an even more exclusive club than the Grail Society: the Terra Society (you need to score 205 on the test where the SD is 15 to join).
So is there a use for high IQ societies? I struggle to think of one. They seem to function as money-sinks—to sucker people into paying their dues just because they scored high on a test (with no validity). The fact that one of the founders of Mensa was upset that Mensa members spend so much time doing puzzles is very telling. What else do they do with their ‘talent’ other than solve puzzles all day? What has the Mensa group—and any of the other (quite possible, but 84 are linked above) hundreds of HISs—done for the world?
Adam—although he guessed at the end of the first Mensa exam (the Raven-like one)—got into Mensa due to his second Mensa test—the verbal one. Adam eventually retook the Mensa exam after taking his nootropic cocktails and he writes (2018: 207):
The second envelope from Mensa was waiting for me when I returned from work, poking out beneath a gas bill. I opened the gas bill first. Its numbers were higher than I expected. I hoped the same would be true of the letter that announced my new IQ.
It was. My cognitively enhanced score on the language test had crept up to 156, from 154 before. And on the Culture Fair Test [the Raven-like test], the tough one with the symbols, it had soared to 137, from 128. That put me on the ninety-ninth percentile on both.
My IQ as measured by the symbols test — the one I had tried to improve on using the brain stimulation — was now 135, up from 125, and well above the required threshold for Mensa Membership.
Adam used Modafinil (a drug used to treat sleeplessness due to narcolepsy, obstructive sleep apnea, and shift work sleep disorder) and electrical brain stimulation. So Adam increased his scores, but he—of course—has no idea what causes his score increases: the nootropic, the electrical stimulation, practice, already having an idea of what was on the test, etc.
In any case, that’s ancillary to the main discussion point in this article: What has Mensa—and other HISs—done for the world? Out of the hundreds of HISs in the world, have they done anything of note or are they just a club of people who score highly on a test who then have to pay money to be in the club? There is no value to these kinds of ‘societies’; they’re just a circlejerk for good test-takers. Mensans have a higher chance of having mental disorders, which is evidenced by the articles above by Jamie Loftus, where they threaten her life with their “criminal element”.
So, until I’m shown otherwise, Mensa and other HISs are just a circlejerk where people have to pay to be in the club—and that’s all it is.
JP Rushton’s career was pretty much nothing but peddling bullshit. In the beginning of his career, he was a social learning theorist. He published a book Altruism, Socialization, and Society (Rushton, 1980). I bought the book a few years back when I was still a hardcore Rushton defender to see what he wrote about before he started pushing IQ and evolutionary theories about human races and I thought it was pretty good. In any case, Rushton got a lot wrong. So much so, that his career was, in my opinion, wasted peddling bullshit. Rushton was shown to be wrong time and time again on r/K theory and cold winter theory; Rushton was shown to be wrong time and time again on his crime theorizing; and Rushton’s and Jensen’s papers on the causes of the black-white IQ gap rest on a misunderstanding of heritability. In this piece, I will cover those three subjects.
Recently, two new papers have appeared that have a bone to pick with Rushton: One by Flynn (2019) and the other by Cernovsky and Litman (2019). Flynn discusses Rushton’s claims on the method of correlated vectors, his cold winter theory (that Asians and Europeans were subjected to harsher climates which led to higher levels of intelligence and therefore IQ) and his misuse of regression to the mean. He also discussed how the black-white IQ gap is environmental in nature (which is the logical position to hold, since IQ tests are tests of middle-class knowledge and skills (Richardson, 2002) and they are not construct valid).
Cold Winters Theory
Rushton theorized that, due to exposure to harsher environments, that Europeans and East Asians evolved to be more intelligent than Africans who stayed in the, what I assume to be, less harsh environments of Africa (Rushton, 1985). This is Rushton’s “Differential K theory.” Flynn (2019) writes that he “can supply an evolutionary scenario for almost any pattern of current IQ scores.” And of course, one can do that with any evolutionary adaptive hypothesis.
Even Frost (2019) admits that “there is no unified evolutionary theory of human intelligence, other than the general theory of evolution by natural selection.” But since “natural selection” is not a mechanism (Fodor, 2008; Fodor and Piattelli-Palmarini, 2010), then it cannot explain the evolution of intelligence differences, nevermind the fact that, mostly, these claims are pushed by differences in non-construct valid IQ test scores.
In any case, Rushton’s theory is a just-so story.
Judith Anderson (1991) refuted Rushton’s hypothesis on ecological grounds. Rushton asserted that Africans were r-selected whereas Asians and Europeans were more K-selected. Rushton, however, did not even use alpha-selection, which is selection for competitive ability. So r- and K selection is based on density-independence and density-dependence. K-selection is expected to favor genotypes that persist at high densities—increasing K—whereas r-selection is expected to favor genotypes that increase more quickly at low densities—increasing r. Alpha-selection can also occur at high or low population densities but is more likely in high densities. Though alpha-selection “favours genotypes that, owing to their negative effects on others, often reduce the growth rate and the maximum population size” (Anderson, 1991: 52). I further discussed the huge flaws with Rushton’s r/K model here. So Rushton’s theory fails on those grounds, along with many others.
When it came to race, Rushton was a lumper, not a splitter. What I mean by these terms is simple: lumpers lump together Native Americans with East Asians and Pacific Islanders with Africans while splitters split them into further divisions. Why was Rushton a lumper? Because it fit more with his theory, of course. I remember back when I was a Rushton-ist, and I was, too, a lumper, that to explain away the low IQs of Native Americans—and in turn their achievements—was that they still had their intelligence from the cold winters and that’s when they did their achievements. Then, as they spent more time in hotter climates, they became dumber. In any case, there is no justification for lumping Native Americans with East Asians. Looking through Rushton’s book, he gives no justification for his lumping, so I can only assume that it is bias on his part. Now I will justify the claim that splitting is better than lumping. (Rushton also gave no definition of race, and according to Cernovsky and Litman (2019: 54), Rushton “failed to provide any scientific definition of race …”
Race is both a social and biological construct. I can justify the claim that Natives and East Asians are distinct races in one way here: ask both groups if the other is the same race. What do you think the answer will be? Now, onto genetics.
Spencer (2014) discusses the results from Tishkoff et al (2009), saying that when they added 134 ethnic groups to the ones found in the HDGP sample of 52, the K=5 partition clustered Caucasians, Mongoloids, and three distinct sets of Africans. Mongoloids, in this case, being East Asians, Native Americans, and Oceanians. But Tishkoff et al oversampled African ethnic groups. This, though, does not undercut my argument: of course when you oversample ethnic groups you will get the result of Tishkoff et al (2009) and since Africans were oversampled, the populations more genetically similar were grouped into the same cluster, which, of course, does not mean they are the same race.
Census racial discourse is just national racial discourse. The census uses defers to the OMB to define race. How does the OMB define race? The OMB defines “race” as “sets of” populations. Race in US racial discourse designates a set of population groups, thus, race is a particular, not a kind.
I can then invoke Hardimon’s (2017) argument for the existence of minimalist races:
1 There are differences in patterns of visible physical features which correspond to geographic ancestry.
2 These patterns are exhibited between real groups.
3 These groups that exhibit these physical patterns by geographic ancestry satisfy conditions of minimalist race.
C Race exists.
Now we can say:
1 If Native Americans and East Asians are phenotypically distinct, then they are different races.
2 Native Americans and East Asians are phenotypically distinct.
C Therefore Native Americans and East Asians are different races.
Rushton arbitrarily excluded data that did not fit his theory. How dishonest. Cernovsky and Litman (2019) write:
When Rushton presented crime statistics derived from 2 Interpol Yearbooks as allegedly supporting his thesis that Negroids are more crime inclined than Caucasoids, he arbitrarily excluded disconfirmatory data sets. When all data from the same two Interpol Yearbooks are re-calculated, most of the statistically significant trends in the data are in the direction opposite to Rushton’s beliefs: Negroids had lower crime rates than Caucasoids with respect to sexual offenses, rapes, theft, and violent theft or robbery, with most correlation coefficients exceeding .60. While we do not place much credence in such Interpol statistics as they only reproduce information provided by government officials of different countries, our re-analysis indicated that Rushton excluded data that would discredit his theory.
Further throwing a wrench into Rushton’s assertions is his claim that Mongoloids constitutes both East Asians and Native Americans. Well, Central America has some of the highest crime rates in the world—even higher than in some African countries. What is the ad-hoc justification for explaining away this anomaly if they truly are the same race? If they are the same race, why is the crime rate so much higher in Central America? Surely, Rushton’s defenders would claim something along the lines of recent evolution towards X, Y, and Z. But then I would say, then on what basis are they the same race? No matter what Rushton’s defenders say, they are boxed into a corner.
Lastly, Rushton and Jensen (2005) argued, on the basis of heritability estimates, and twin studies, that the black-white IQ gap is largely genetic in nature. But there are a few problems. They rely largely on a slew of trans-racial adoption studies, all of which have been called into question (Thomas, 2017). IQ tests, furthermore, are not construct valid (Richardson and Norgate, 2015; Richardson, 2017). Heritability estimates also fail. This is because, in non-controlled environments these stats do not tell us much, if anything (Moore and Shenk, 2016). Likewise, Guo (2000: 299) concurs, writing “it can be argued that the term ‘heritability’, which carries a strong conviction or connotation of something ‘heritable’ in everyday sense, is no longer suitable for use in human genetics and its use should be discontinued.” (For more arguments against heritability, read Behavior Genetics and the Fallacy of Nature vs Nurture.)
Rushton and Jensen (2005) also relied on the use of twin studies, however, all of the assumptions that researchers use to attempt to immunize their arguments from refutation are circular and ad hoc; they also agree that MZs experience more similar environments than DZs, too (Joseph et al, 2014; Joseph, 2016, see a summary here; Richardson, 2017). In any case, the fact that G and E interact means that heritability estimates are, in effect, useless in humans. Farm animals are bred in highly controlled environments; humans are not. Thus, we cannot—and should not—accept the results of twin studies; they cannot tell us whether or not genes are responsible for any behavioral trait.
There was a lot that Rushton got wrong. His cold winters theory is a just-so story; East Asians and Native Americans are not the same race; heritability estimates are not a measure of how much genes have to do with phenotypic variation within or between groups; IQ tests are not construct valid; r/K selection theory was slayed as early as 1991 and then again in 2002 (Graves, 2002); twin studies are not informative when it comes to how much genes influence traits, they only measure environmental similarity; and finally, Rushton omitted data that did not fit his hypothesis on racial differences in crime.
It’s sad to think that one can spend a career—about 25 years—spewing nothing but pseudoscience. One of the only things I agree with him on is that races are real—but when it comes to the nuances, I disagree with him, because there are five races, not three. Rushton got a lot wrong, and I do not know why anyone would defend him, even when these glaring errors are pointed out. (For a good look into Rushton’s lies, see Dutton’s (2018) book J. Philippe Rushton: A Life History Perspective and my mini-review on the book.)