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Testosterone has a similar heritability to IQ (between .4 and .6; Harris, Vernon, and Boomsma, 1998; Travison et al, 2014). To most, this would imply a significant effect of genes on the production of testosterone and therefore we should find a lot of SNPs that affect the production of testosterone. However, testosterone production is much more complicated than that. In this article, I will talk about testosterone production and discuss two studies which purport to show a few SNPs associated with testosterone. Now, this doesn’t mean that the SNPs cause high/low testosterone, just that they were associated. I will then speak briefly on the ‘IQ SNPs’ and compare it to ‘testosterone SNPs’.
Complex traits are ‘controlled’ by many genes and environmental factors (Garland Jr., Zhao, and Saltzman, 2016). Testosterone is a complex trait, so along with the heritability of testosterone being .4 to .6, there must be many genes of small effect that influence testosterone, just like they supposedly do for IQ. This is obviously wrong for testosterone, which I will explain below.
Back in 2011 it was reported that genetic markers were discovered ‘for’ testosterone, estrogen, and SHGB production, while showing that genetic variants in the SHGB locus, located on the X chromosome, were associated with substantial testosterone variation and increased the risk of low testosterone (important to keep in mind) (Ohlsson et al, 2011). The study was done since low testosterone is linked to numerous maladies. Low testosterone is related to cardiovascular risk (Maggio and Basaria, 2009), insulin sensitivity (Pitteloud et al, 2005; Grossman et al, 2008), metabolic syndrome (Salam, Kshetrimayum, and Keisam, 2012; Tsuijimora et al, 2013), heart attack (Daka et al, 2015), elevated risk of dementia in older men (Carcaillon et al, 2014), muscle loss (Yuki et al, 2013), and stroke and ischemic attack (Yeap et al, 2009). So this is a very important study to understand the genetic determinants of low serum testosterone.
Ohlsson et al (2011) conducted a meta-analysis of GWASs, using a sample of 14,429 ‘Caucasian’ men. To be brief, they discovered two SNPs associated with testosterone by performing a GWAS of serum testosterone concentrations on 2 million SNPs on over 8,000 ‘Caucasians’. The strongest associated SNP discovered was rs12150660 was associated with low testosterone in this analysis, as well as in a study of Han Chinese, but it is rare along with rs5934505 being associated with an increased risk of low testosterone(Chen et al, 2016). Chen et al (2016) also caution that their results need replication (but I will show that it is meaningless due to how testosterone is produced in the body).
Ohlsson et al (2011) also found the same associations with the same two SNPs, along with rs6258 which affect how testosterone binds to SHGB. Ohlsson et al (2011) also validated their results: “To validate the independence of these two SNPs, conditional meta-analysis of the discovery cohorts including both rs12150660 and rs6258 in an additive genetic linear model adjusted for covariates was calculated.” Both SNPs were independently associated with low serum testosterone in men (less than 300ng/dl which is in the lower range of the new testosterone guidelines that just went into effect back in July). Men who had 3 or more of these SNPs were 6.5 times more likely to have lower testosterone.
Ohlsson et al (2011) conclude that they discovered genetic variants in the SHGB locus and X chromosome that significantly affect serum testosterone production in males (noting that it’s only on ‘Caucasians’ so this cannot be extrapolated to other races). It’s worth noting that, as can be seen, these SNPs are not really associated with variation in the normal range, but near the lower end of the normal range in which people would then need to seek medical help for a possible condition they may have.
In infant males, no SNPs were significantly associated with salivary testosterone levels, and the same was seen for infant females. Individual variation in salivary testosterone levels during mini-puberty (Kurtoglu and Bastug, 2014) were explained by environmental factors, not SNPs (Xia et al, 2014). They also replicated Carmaschi et al (2010) who also showed that environmental factors influence testosterone more than genetic factors in infancy. There is a direct correlation between salivary testosterone levels and free serum testosterone (Wang et al, 1981; Johnson, Joplin, and Burin, 1987), so free serum testosterone was indirectly tested.
This is interesting because, as I’ve noted here numerous times, testosterone is indirectly controlled by DNA, and it can be raised or lowered due to numerous environmental variables (Mazur and Booth, 1998; Mazur, 2016), such as marriage (Gray et al, 2002; Burnham et al, 2003; Gray, 2011; Pollet, Cobey, and van der Meij, 2013; Farrelly et al, 2015; Holmboe et al, 2017), having children (Gray et al, 2002; Gray et al, 2006; Gettler et al, 2011); to obesity (Palmer et al, 2012; Mazur et al, 2013; Fui, Dupuis, and Grossman, 2014; Jayaraman, Lent-Schochet, and Pike, 2014; Saxbe et al, 2017) smoking is not clearly related to testosterone (Zhao et al, 2016), and high-carb diets decrease testosterone (Silva, 2014). Though, most testosterone decline can be ameliorated with environmental interventions (Shi et al, 2013), it’s not a foregone conclusion that testosterone will sharply decrease around age 25-30.
Studies on ‘testosterone genes’ only show associations, not causes, genes don’t directly cause testosterone production, it is indirectly controlled by DNA, as I will explain below. These studies on the numerous environmental variables that decrease testosterone is proof enough of the huge effects of environment on testosterone production and synthesis.
How testosterone is produced in the body
There are five simple steps to testosterone production: 1) DNA codes for mRNA; 2) mRNA codes for the synthesis of an enzyme in the cytoplasm; 3) luteinizing hormone stimulates the production of another messenger in the cell when testosterone is needed; 4) this second messenger activates the enzyme; 5) the enzyme then converts cholesterol to testosterone (Leydig cells produce testosterone in the presence of luteinizing hormone) (Saladin, 2010: 137). Testosterone is a steroid and so there are no ‘genes for’ testosterone.
Cells in the testes enzymatically convert cholesterol into the steroid hormone testosterone. Quoting Saladin (2010: 137):
But to make it [testosterone], a cell of the testis takes in cholesterol and enzymatically converts it to testosterone. This can occur only if the genes for the enzymes are active. Yet a further implication of this is that genes may greatly affect such complex outcomes as behavior, since testosterone strongly influences such behaviors as aggression and sex drive. [RR: Most may know that I strongly disagree with the fact that testosterone *causes* aggression, see Archer, Graham-Kevan and Davies, 2005.] In short, DNA codes only for RNA and protein synthesis, yet it indirectly controls the synthesis of a much wider range of substances concerned with all aspects of anatomy, physiology, and behavior.
Genes only code for RNA and protein synthesis, and thusly, genes do not *cause* testosterone production. This is a misconception most people have; if it’s a human trait, then it must be controlled by genes, ultimately, not proximately as can be seen, and is already known in biology. Genes, on their own, are not causes but passive templates (Noble, 2008; Noble, 2011; Krimsky, 2013; Noble, 2013; Also read Exploring Genetic Causation in Biology). This is something that people need to understand; genes on their own do nothing until they are activated by the system.
What does this have to do with ‘IQ genes’?
My logic here is very simple: 1) Testosterone has the same heritability range as IQ. 2) One would assume—like is done with IQ—that since testosterone is a complex trait that it must be controlled by ‘many genes of small effect’. 3) Therefore, since I showed that there are no ‘genes for’ testosterone and only ‘associations’ (which could most probably be mediated by environmental interventions) with low testosterone, may the same hold true for ‘IQ genes/SNPS’? These testosterone SNPs I talked about from Ohlsson et al (2011) were associated with low testosterone. These ‘IQ SNP’ studies (Davies et al, 2017; Hill et al, 2017; Savage et al, 2017) are the same—except we have an actual idea of how testosterone is produced in the body, we know that DNA is indirectly controlling its production, and, most importantly, there is/are no ‘gene[s] for’ testosterone.
Testosterone has the same heritability range as IQ, is a complex trait like IQ, but, unlike how IQ is purported to be, it [testosterone] is not controlled by genes; only indirectly. My reasoning for using this example is simple: something has a moderate to high heritability, and so most would assume that ‘numerous genes of small effect’ would have an influence on testosterone production. This, as I have shown, is false. It’s also important to note that Ohlsson et al (2011) showed associated SNPs in regards to low testosterone—not testosterone levels in the normal range. Of course, only when physiological values are outside of the normal range will we notice any difference between men, and only then will we find—however small—genetic differences between men with normal and low levels of testosterone (I wouldn’t be surprised if lifestyle factors explained the lower testosterone, but we’ll never know that in regards to this study).
Testosterone production is a real, measurable physiologic process, as is the hormone itself; which is not unlike the so-called physiologic process that ‘g’ is supposed to be, which does not mimic any known physiologic process in the body, which is covered with unscientific metaphors like ‘power’ and ‘energy’ and so on. This example, in my opinion, is important for this debate. Sure, Ohlsson et al (2011) found a few SNPs associated with low testosterone. That’s besides the point. They are only associated with low testosterone; they do not cause low testosterone. So, I assert, these so-called associated SNPs do not cause differences in IQ test scores; just because they’re ‘associated’ doesn’t mean they ’cause’ the differences in the trait in question. (See Noble, 2008; Noble, 2011; Krimsky, 2013; Noble, 2013.) The testosterone analogy that I made here buttresses my point due to the similarities (it is a complex trait with high heritability) with IQ.
There are a lot of conceptual problems with IQ tests that I never see talked about. The main ones are how the tests are constructed (to fit a normal curve, no less); to the fact that there is no construct validity to the tests (IQ tests aren’t calibrated against a biological model like breathalyzers are calibrated against a model of blood in the blood stream); and how the Raven’s Progressive Matrices test is actually biased despite being touted as the most culture-free test since all you’re doing is rotating abstract symbols to see what comes next in the sequence. These three assumptions have important implications for the ‘power’ of the IQ tests, the most important being the test construction and validity.
I) IQ test construction
IQ tests are constructed with the assumption that we know what IQ tests test (we don’t) and with the prior ‘knowledge’ of who is or is not intelligent. Test constructors construct the tests to reveal presumed differences between individuals.
It is assumed that 1) IQ scores lie on a normal distribution (they don’t) and 2) few natural bio functions conform to this curve. Another problem with IQ test construction is the assumption that it increases with age and levels off after puberty. Though this, like the other things, has been built into the test by choosing items that an increasing proportion of children pass. You can, of course, reverse this effect by choosing items that older people do well on and younger people don’t.
Further, they keep 50 percent of items that children get right while keeping a smaller proportion of items that children get right, which, in effect, presupposes who is or is not intelligent.
Though, you never see those who believe that IQ is a ‘good enough’ proxy for intelligence ever being this up. Why? This is very important for the validity of these tests. Because if how the tests are constructed is wrong and test scores are not to fit a normal distribution when no normal distribution actually exists for most human mental (including IQ scores) and physiological traits, then the assumptions and conclusions drawn from them are wrong. IQ tests are constructed with the prior idea of who is or is not ‘intelligent’ and this is done by how the items are chosen—50 percent of the items that people get right are kept while the smaller proportion of items people get right or wrong are kept. This is how this so-called ‘normal curve’ appears in IQ tests and is why the book The Bell Curve has the name it has. But bell curve don’t exist for a modicum of traits including IQ!!
II) IQ test validity
Another problem with IQ tests are its validity. People attempt to ‘prove’ its validity with correlating job performance success with IQ scores, though there are huge flaws in the studies purporting to show a .5 correlation between IQ and job performance (Richardson, 2002; Richardson and Norgate, 2015). IQ tests are not like, say, breathalyzers (which are calibrated against a model of blood alcohol) or white blood cell count (which is a proxy for disease in the body). Those two measures have a solid theoretical basis and underpinning; as blood alcohol rises, the individual had increased alcohol consumption. The same is true for white blood cell count. The same is not true for IQ tests.
One of the biggest measures used in regards to job performance and IQ testing (people attempt to use job performance to attempt to validate IQ tests) is supervisor rating. However, supervisory ratings are hugely subjective and a lot of factors that would have a supervisor be said to be a ‘good worker’ are not variables that entail just that job.
The only ‘validity’ that IQ test have is correlations with other IQ tests and tests like the SAT. This is not validity. Say the breathalyzer wasn’t calibrated against a model of blood alcohol in the body, would breathalyzers still be a valid tool to test people’s blood/alcohol level? On that same note let’s say that white blood cells wasn’t construct valid. Would we be able to reliably use white blood cell count as a valid measure for disease in the body? These very same problems plague IQ tests and people accept them as ‘proxies’ for intelligence, they test ‘enough of intelligence’ to be able to say that one is smarter than another because they scored higher in a test and therefore tap into this mystical ‘g’ that they have more of which is like a ‘power’ or ‘energy’.
These tests, therefore, are constructed with the idea of who is or is not intelligent and you can see that by looking at how the items are chosen for the test. That’s not scientific. So a true test of ‘intelligence’ may not even exist since these tests have this type of construct bias already in them.
IQ tests have no validity like breathalyzers and white blood cell count, and the so-called ‘culture-free’ IQ test Raven’s Progressive Matrices is anything but.
III) Raven’s and culture bias
I specifically asked Dr. James Thompson about Raven’s being culture-fair. I said that I recall Linda Gottfredson saying that people say that Ravens is culture-fair only because Jensen said it:
So that’s one thing about Ravens that crumbles. A quote from Ken Richardson’s book Genes, Brains, and Human Potential: The Science and Ideology of Intelligence:
It is well known that families and subcultures vary in their exposure to, and usage of, the tools of literacy, numeracy, and associated ways of thinking. Children will vary in these because of accidents of background. …that background experience with specific cultural tools like literacy and numeracy is reflected in changes in brain networks. This explains the importance of social class context to cognitive demands, but is says nothing about individual potential.
(This argument on social class is much more complex than ‘poor people are genetically predisposed to be dumb and poor’.
Consider a recent GCTA study by Plomin et al., who reported a SNP-based heritability estimate of 35% for “general cognitive ability” among UK 12 year olds (as compared to a twin heritability estimate of 46%) . According to the Wellcome Trust “genetic map of Britain,” striking patterns of genetic clustering (i.e. population stratification) exist within different geographic regions of the UK, including distinct genetic clusterings comprised of the residents of the South, South-East and Midlands of England; Cumbria, Northumberland and the Scottish borders; Lancashire and Yorkshire; Cornwall; Devon; South Wales; the Welsh borders; Anglesey in North Wales; Scotland and Ireland; and the Orkney Islands . Now consider the title of a study from the University and College Union: “Location, Location, Location – the widening education gap in Britain and how where you live determines your chances” . This state of affairs (not at all unique to the UK), combined with widespread geographic population stratification, is fertile ground for spurious heritability estimates.
I think this argument is interesting, and it throws a wrench into a lot of things, but more on that another day.)
In other words, items like those in the Raven contain hidden structure which makes them more, not less, culturally steeped than any other kind of intelligence testing items, like the Raven, as somehow not knowledge-based, when all are clearly learning dependent. Ironically, such cultural-dependency testing is sometimes tacitly admitted by test users. For example, when testing children in Kuwait on the Raven in 2006, Ahmed Abdel-Khalek and John Raven transposed the items “to read from left to right following the custom of Arabic writings.” (Richardson, 2017: 99)
Finally, we have this dissertation which shows that urban peoples score better than hunter-gatherers (relevant to this present article):
Reading was the greatest predictor of performance Raven’s, despite controlling for age and sex. Attendance was also strongly correlated with Raven’s performance. These findings suggest that reading, or pattern recognition, could be fundamentally affecting the way an individual problem solves or learns to learn, and is somehow tapping into ‘g’. Presumably the only way to learn to read is through schooling. It is, therefore, essential that children are exposed to formal education, have the motivation to go/stay in school, and are exposed to consistent, quality training in order to develop the skills associated with improved performance. (pg. 83)
This is telling: This means that there is no such thing as a ‘culture-free’ IQ test and there will always be something involved that makes it culture un-fair.
People may say ‘It’s only rotating pictures and shapes to get the final answer, how much schooling could you need??’, well as seen above with the Tsimane, schooling is very important to IQ tests since they test learned skills. I’ve seen some people claim that IQ tests don’t test learned ability and that it’s all native, unlearned ability. That’s a very incorrect statement.
So although the symbols in a test like the RPM are experience-free, the rules governing their changes across the matrix are certainly not, and they are more likely to be already represented in the minds of children from middle-class homes, less so in others. Performance on the Raven’s test, in other words, is a question not of inducing ‘rules’ from meaningless symbols, in a totally abstract fashion, but of recruiting ones that are already rooted in the activites of some cultures rather than others. Like so many problems in life, including fields as diverse as chess, science and mathematics (e.g. Chi & Glaser, 1985), each item on the Raven’s test is a recognition problem (matching the covariation structure in a stimulus array to ones in background knowledge) before it is a reasoning problem. The latter is rendered easy when the former has been achieved. Similar arguments can be made about other so-called ‘culture-free’ items like analogies and classifications (Richardson & Webster, 1996). (Richardson, 2002: pg 292-292)
Everyday life is also more complex than the hardest items on Raven’s Matrices, while the test is not complex in its demands compared to tasks undertaken in everyday life (Carpenter, Just, and Shell, 1990). They conclude that the cause is differences in working memory, but that is an ill-defined concept in psychology. They do say, though, that “The processes that distinguish among individuals are primarily the ability to induce abstract relations and the ability to dynamically manage a large set of problem-solving goals in working memory.” So item complexity doesn’t make Raven’s items more difficult for others, since everyday life is more complex.
I’ll end with a bit of physiology. What physiological process is does IQ mimic in the body? If it is a physiological process, surely you’re aware that physiological processes *are not* static. IQ is said to be stable at adulthood, what a strange physiological process. Let’s say for arguments’ sake that IQ really does test some intrinsic, biological process. Does it seem weird to you that a supposed real, stable, biological, bodily function of an individual would be different at different times?
There are a lot of assumptions about IQ tests that are never talked about. The most important being how the tests are constructed to fit a normal curve when most traits important for survival aren’t normally distributed. IQ tests are constructed with the assumption of who is or isn’t intelligent just on the knowledge of how the items are prepared for the test. When you look at how the tests are constructed you can see how they are constructed to fit the normal curve because most of their assumptions and conclusions rest on the reality of the normal curve. There is no construct validity to IQ tests, they’re not like breathalyzers for instance which are calibrated against a model of blood alcohol or white blood cell count as a proxy for disease in the body. Raven’s—despite what is commonly stated about the test—is not unbiased, it perhaps is the most biased IQ test of them all. This highlights the problems with IQ tests that are rarely ever spoken about, and should have you call into question the ‘power’ of the IQ test which assumes who is or isn’t intelligent ahead of time.
Steve Sailer published an article the other day titled Wieseltier vs. “The Bell Curve” and I left a comment saying that psychological traits are not normally distributed. Two people responded to me, and I replied back but Sailer didn’t approve my two comments. I have a blog, so I can post it here.
They do actually exist.
“Human resource management: Human Resource Management (HRM) is the term used to describe formal systems devised for the management of people within an organization. The responsibilities of a human resource manager fall into three major areas: staffing, employee compensation and benefits, and defining/designing work.”
Organizational behavior: “the study of the way people interact within groups. Normally this study is applied in an attempt to create more efficient business organizations. The central idea of the study of organizational behavior is that a scientific approach can be applied to the management of workers.”
Industrial and organizational psychology: “This branch of psychology is the study of the workplace environment, organizations, and their employees. Technically, industrial and organizational psychology – sometimes referred to as I/O psychology or work psychology – actually focuses on two separate areas that are closely related.”
We conducted 5 studies involving 198 samples including 633,263 researchers, entertainers, politicians, and amateur and professional athletes. Results are remarkably consistent across industries, types of jobs, types of performance measures, and time frames and indicate that individual performance is not normally distributed—instead, it follows a Paretian (power law) distribution. Assuming normality of individual performance can lead to misspecified theories and misleading practices. Thus, our results have implications for all theories and applications that directly or indirectly address the performance of individual workers including performance measurement and management, utility analysis in preemployment testing and training and development, personnel selection, leadership, and the prediction of performance, among others.
Even most types of job performance and performance measures don’t fit a normal curve.
You say, “…psychological traits aren’t normally distributed.”
But the abstract you linked says,
…individual performance is not normally distributed.
Yes, those of us who have had the misfortune to manage work groups know all about 80/20. This is performance, not “psychological traits.”
Psychological tests aren’t a measure of performance? Traits like IQ only show a normal distribution because the normal distribution is built into the tests (see below).
The other one linked says,
… at many physiological and anatomical levels in the brain, the distribution of numerous parameters is in fact strongly skewed . . .
Okay. The cylinders in the straight-six engine of my BMW lean over to one side, but that doesn’t seem to effect the horsepower. This is a physical trait.
So, what of those “psychological traits”? Like IQ? Granted, it is a kind of performance, one of taking IQ tests, but the results have a normal distribution, and it’s not the kind of performance being measured in the study referenced anyway. IQ, by definition, is a “psychological trait,” and it has a normal distribution.
IQ tests have been constructed so that the scores will exhibit a bell curve distribution. That is, the tests themselves are constructed to reveal differences that are already presumed. IQ tests are constructed with the assumption that the scores are normally distributed, however, the normal distribution is built into the test. Items that 50 percent of the testees get right are kept, along with the smaller proportion of items that many testees get right. (See Richardson, 2002 for more information.) Even most psychological constructs are not normally distributed. This is like g being supposedly physiological when—if it were—it wouldn’t mimic any known physiologic process in the body.
Buzsaki and Muzuseki (2014) review data that sensory acuity, reaction time, memory word usage and sentence lengths are not normally distributed. Basic physiologic processes, too, are not normally distributed, like visual acuity, resting heart rate, metabolic rate, etc. And this makes sense, because those traits are crucial to human survival and therefore need to be malleable. Hormones raise, for instance, during a life-or-death situation, and that is what is needed for survival. So, therefore, few physiological traits are normally distributed.
Honestly, I don’t know what your point is, but I don’t disagree with what you have shown me. I know it’s true, but I’m just too far left on your ski jump curve of losers to grasp why you responded to me that way.
Wieseltier was referring to The Bell Curve, in which results have a normal distribution.
Rigbt, the IQ book. But tests are constructed with the assumption of a normal distribution, but psychological traits are not normally distributed. Read Mizsukei and Buzsaki’s work.
Burt (1967) writes:
A detailed analysis of test results obtained from a large sample of English children (4,665 in all), supplemented by a study of the meagre data already available, demonstrates beyond reasonable doubt that the distribution of individual differences in general intelligence by no means conforms with strict exactitude to the so-called normal curve.
In sum, IQ tests are constructed with the assumption that whatever is being tested lies on a bell curve. Clearly, since they are constructed in such a way, the results are forced to fit a normal distribution. But, as seen above, most traits that are critical to survival are not normally distributed, so why should intelligence/IQ be the same? The data from Buzsaki and Mizuseki (2014) show that “skewed … distributions are fundamental to structural and functional brain organization.”
(Also read The Myth of the Bell Curve and The Unicorn, The Normal Curve, and Other Improbable Creatures. where Micceri shows that achievement measures in “language arts, quantitative arts/logic, sciences, social studies/history, and skills such as study skills grammar, and punctuation” are not normally distributed. Human performance does not follow a bell curve. Also read The Bell Curve Is A Myth — Most People Are Actually Underperformers. The Bell Curve in Psychological Research and Practice: Myth or Reality?: “If IQ scores distribute normally, this does not mean that intelligence equally distribute normally in the population.” … “ In this way, a normal distribution in summated test scores, for example, would be seen as the sign of the presence of an error sufficient to give scores the characteristic bell shape, not as the proof of a good measurement.“)
In my last article on brain size and IQ, I showed how people with half of their brains removed and people with microcephaly can have IQs in the normal/above average range. There is a pretty large amount of data out there on microcephalics and normal intelligence—even a family showing normal intelligence in two generations despite having dominantly inherited microcephaly.
Microcephaly is a condition in which an individual has a head circumference of 2 SD below the mean. Though most would think that would doom all microcephalics to low IQs, 15 percent of microcephalics have IQs in the normal range. This is normally associated with mental retardation, but this is a medical myth (Skoyles and Sagan, 2002: 239), though there are numerous cases of microcephalics having normal IQs (Dorman, 1991). Numerous studies show that it’s possible for normal people to have small brains. Giedd et al (1996) showed a wide variation in head circumference. Of the 104 individuals who had their heads scanned, volume for the cerebellum ranged from 735 cc in a 10 year old boy to 1470 cc in a 14 year old boy (Skoyles, 1999: 4, para 12). Though Giedd et al (1996) did not report total brain volumes in their subjects, brain volume can be inferred. Skoyles (1999; 4, para 12) writes:
The cerebral cortex makes up only 86.4% of brain volume when measured by MRI (Filipek, Richelme, Kennedy & Caviness, 1994), so the total brain volume of the 10-year-old would be larger at 850.7 cc. Brains at 10 years are about 4.4% smaller than adult size (Dekaban & Sadowsky, 1978), suggesting that that brain would grow to an adult size of 888 cc. Even using the lower figure of 80% cerebrum to brain ratio derived from anatomical studies suggests a figure of only 960 cc.
The variation of 888 cc to 960 cc depending on which value for the cerebrum to brain ratio you use still shows that people can have brains 450-300 cc lower than average and still be ‘normal’.
Researchers began noticing many cases of both individuals and families exhibiting features of microcephaly—but they had normal intelligence (Simila, 1970;Seemanova et al, 1985; Rossi et al, 1987; Teebi et al, 1987; Sherrif and Hegab, 1988; Desch et al, 1990; Opitz and Holt, 1990; Evans, 1991; Heney et al, 1991; Green et al, 1995; Rizzo and Pavone, 1995; Teebi and Kurash, 1996; Innis et al, 1997; Kawame, Pagon, and Hudgens, 1997; Abdel-Salam et al, 1999; Digweed, Reis, and Sperling, 1999; Woods, Bond, and Enard, 2005; Ghaoufari-Fard et al, 2015). This is a pretty huge blow to the brain size/IQ correlation, for if people with such small heads can have normal IQs, why do we have such large brains that leave us with such large problems (Skoyles and Sagan, 2002: 240-244)?
If we can have smaller heads—which would make childbirth easier and allow us to continue to have smaller pelves which would be conducive to endurance running since we are the running ape, why would brains have gotten so much larger from that of erectus (where modern people can have normal IQs with erectus-sized brains) if it is perfectly possible to have a brain on around the size of early erectus? In any event, these anomalies need an explanation, and Skoyles (1999) hypothesizes that people with smaller heads but normal IQs may have a lower capacity for expertise. This is something that I will look into in the future, as it may explain these anomalies, along with the true reason why our brains began increasing around 3 mya.
Sells (1977)—using the criteria of 2 SD below mean head size—showed that 1.9 percent of the children he tested (n=1009) had IQs indistinguishable from their normocephalic peers. Watemberg et al (2002) studied 1,393 patients. They found that almost half of their patients with microcephaly (15.4% of their patients studies had microcephaly) had IQs within the normal limits, while among those with sub-normal intelligence, 30 percent had borderline IQs or were mildly mentally retarded (it’s worth noting that l-glutamate can raise IQ scores by 5-20 points in the mild to moderate mental deficiency; Vogel, Braverman and Draguns, 1966 review numerous lines of evidence that glutamate raises IQ in mentally deficient individuals). Sassaman and Zartler (1982) showed that 31.9 percent of microcephalics had normal intelligence, 6.9 percent of them had average intelligence.
Head circumference does not directly correlate with IQ in microcephalic patients (Baxter et al, 2009). Dorman (1991: 268) writes: “Decreased head size may or may not be associated with lowered intelligence, indicating that small head size by itself does not affect intelligence. The presence of subgroups of microcephalic persons who typically have normal intelligence is sufficient to rule out a causal relationship between head size and intellect. … It can be added that reduction in brain size without such structural pathology, as mayvoccur in some genetic conditions or evenvas a result of normal variation, does not
affect intelligence. ”
Tenconi et al (1981) write: “We were able to examine five other members of this family (1-3; 11-1; 11-4; 11-5; 11-8) and found no abnormalities: they were of normal intelligence, head circumference, and ophthalmic evaluation. Members of the grandmother’s family who refused to be examined appeared to be of normal intelligence and head appearance and did not have any serious eye problems.”
Stoler-Poria et al (2010) write: “There was a K-ABC cognitive score < 85 (signifying developmental delay) in two (10%) children from the study group and in one (5%) child from the control group: one of the children in the study group (the one with HC below − 3 SD) scored significantly below the normal range (IQ = 70), while the other scored in the borderline range (IQ = 83); the child from the control group also scored in the borderline range (IQ = 84).” Whereas Thelander and Pryor (1968) showed that individuals with head circumferences 2-2.6 SDs below the mean had average IQs, though the smaller their HC, the lower their IQ. Ashwal et al (2009: 891) write: “The students with microcephaly had a similar mean IQ to the normocephalic group (99.5 vs 105) but had lower mean academic achievement scores (49 vs 70).” So it seems that microcephalics can have normal IQs, but have lower academic achievement scores.
Primary microcephalics have higher IQs than secondary microcephalics (Cowie, 1987). Primary microcephaly is microcephaly that one is born with whereas secondary microcephaly is acquired.
There is one case study of a girl with microcephaly where Tan et al (2014) write: “Most recent measures of general intelligence (performed at 6½ years of age) reveal a below average full scale IQ of 75 with greatest impairment in processing speed. On the Wechsler Preschool and Primary Scale of Intelligence III Revised (for children 2 years 6 m – 7 years 3 m), she obtained a Verbal IQ of 83, Nonverbal IQ of 75, and Processing speed 71. On the Wechsler Individual Achievement Testing (WIAT) she showed significant struggles in secondary language on tasks of early reading (SS 60), word reading (SS 70), reading comprehension (SS 69) and struggles in math on the task of numerical operations (SS 61) (WPPSI – R and WIAT mean = 100 and SD = 15). Parents report subjectively that differences in development relative to her sisters are becoming more apparent with time.”
It is not a foregone conclusion that if an individual has microcephaly that they will have a low IQ and be mentally retarded, as reviewed above, there are numerous cases of individuals with microcephaly and normal IQs, with this even being seen in families—that is, multiple families with normal IQs yet have microcephaly. Numerous people with Nijmegen breakage syndrome (a type of microcephaly) can have normal IQs. Rossi et al (1987) reported that for 6 Italian families (n=21 microcephalics) with autsomally inherited microcephaly, for those administered psychometric tests (n=12), all had normal IQs but one, with an IQ range of 99 to 112 for a mean of 99.3.
In conclusion, microcephalics can have normal IQs and live normal lives, despite having heads, on average, that are 2 SDs below the mean. These anomalies (and there are many, many more) need explaining. This is great evidence that a larger brain does not always mean a higher IQ, as well as yet more evidence that it was possible for Homo erectus to have an IQ in our range today, which means that we may not need brains our current size for our intellect and achievements. To conclude, I will provide a quote from Dorman (1991):
The normal intelligence found by SELLS in school children with small head size also militates against any straightforward relationship between diminished head size and lowered intelligence.
With the correlation between brain size and IQ being .4 (Gignac and Bates, 2017), this does not rule out the ‘outliers’ reviewed in this article. These cases deserve an explanation, for if large brains lead to high IQs, why do these people with heads significantly smaller have IQs in the normal range? (See Skoyles, 1999: 8, para 31 for an explanation for the brain size/IQ correlation.)
Here is my reply to Jared Taylor’s new article over at AmRen Breakthroughs in Intelligence:
“The human mind is not a blank slate; intelligence is biological”
The mind is not a ‘blank slate’, though there is no ‘biological’ basis for intelligence (at least in the way that hereditarians believe). They’re just correlations. (Whatever ‘intelligence’ is.)
“there is no known environmental intervention—including breast feeding”
There is a causal effect of breast feeding on IQ:
While reported associations of breastfeeding with child BP and BMI are likely to reflect residual confounding, breastfeeding may have causal effects on IQ. Comparing associations between populations with differing confounding structures can be used to improve causal inference in observational studies.
Brion, M. A., Lawlor, D. A., Matijasevich, A., Horta, B., Anselmi, L., Araújo, C. L., . . . Smith, G. D. (2011). What are the causal effects of breastfeeding on IQ, obesity and blood pressure? Evidence from comparing high-income with middle-income cohorts. International Journal of Epidemiology, 40(3), 670-680. doi:10.1093/ije/dyr020
Breastfeeding is related to improved performance in intelligence tests. A positive effect of breastfeeding on cognition was also observed in a randomised trial. This suggests that the association is causal.
Horta, B. L., Mola, C. L., & Victora, C. G. (2015). Breastfeeding and intelligence: a systematic review and meta-analysis. Acta Paediatrica, 104, 14-19. doi:10.1111/apa.13139
“before long we should be able to change genes and the brain itself in order to raise intelligence.“
Which genes? 84 percent of genes are expressed in the brain. Good luck ‘finding’ them…
These results corroborate with the results from previous studies, which have shown 84% of genes to be expressed in the adult human brain …
Negi, S. K., & Guda, C. (2017). Global gene expression profiling of healthy human brain and its application in studying neurological disorders. Scientific Reports, 7(1). doi:10.1038/s41598-017-00952-9
“Normal people can have extraordinary abilities. Prof. Haier writes about a non-savant who used memory techniques to memorize 67,890 digits of π! He also notes that chess grandmasters have an average IQ of 100; they seem to have a highly specialized ability that is different from normal intelligence. Prof. Haier asks whether we will eventually understand the brain well enough to endow anyone with special abilities of that kind.”
Evidence that intelligence is not related to expertise.
“It is only after a weight of evidence has been established that we should have any degree of confidence in a finding, and Prof. Haier issues another warning: “If the weight of evidence changes for any of the topics covered, I will change my mind, and so should you.” It is refreshing when scientists do science rather than sociology.”
Even with the “weight of evidence”, most people will not change their views on this matter.
“Once it became possible to take static and then real-time pictures of what is going on in the brain, a number of findings emerged. One is that intelligence appears to be related to both brain efficiency and structure”
Patterns of activation in response to various fluid reasoning tasks are diverse, and brain regions activated in response to ostensibly similar types of reasoning (inductive, deductive) appear to be closely associated with task content and context. The evidence is not consistent with the view that there is a unitary reasoning neural substrate. (p. 145)
Nisbett R. E., Aronson J., Blair C., Dickens W., Flynn J., Halpern D. F., Turkheimer E. Intelligence: New findings and theoretical developments. American Psychologist. 2012;67:130–159. doi: 10.1037/a0026699.
“Early findings suggested that smart people’s brains require less glucose—the main fuel for brain activity—than those of dullards.”
Cause and correlation aren’t untangled; they could be answering questions in a familiar format, for instance, and this could be why their brains show less glucose consumption.
“It now appears that grey matter is where “thinking” takes place, and white matter provides connections between different areas of grey matter. Some brains seem to be organized with shorter white-matter connections, which appear to allow more efficient communication, and there seem to be sex differences in the ways the part of the brain are connected. One of the effects of aging is deterioration of the white-matter connections, which reduces intelligence.”
Read this commentary (pg. 162): Norgate, S., & Richardson, K. (2007). On images from correlations. Behavioral and Brain Sciences, 30(02), 162. doi:10.1017/s0140525x07001379
“Brain damage never makes people smarter”
This is wrong:
You would think that cutting out one-half of people’s brains would kill them, or at least leave them vegetables needing care for the rest of their lives. But it does not. Consider this striking story. A boy starts having seizures at 10 years of age when his right cerebral hemisphere atrophies. By the time he is 12, the left side of his body is paralyzed. When he is 19, surgeons decide to operate and remove the right side of his brain, as it is causing gits in his intact left one. You might think this would lower his IQ or leave him severely retarded, but no. His IQ shoots up 14 points, to 142! The mystery is not so great when you realize that the operation has gotten rid of the source of his fits, which had previously hampered his intelligence. When doctors saw him 15 years later, they described him as “having obtained a university diploma . . . [and now holding] a responsible administrative position with a local authority.”
Skoyles, J. R., & Sagan, D. (2002). Up from dragons: the evolution of human intelligence. New York: McGraw-Hill (pg. 282)
“Prof. Haier wants a concerted effort: “What if a country ignored space exploration and announced its major scientific goal was to achieve the capability to increase every citizen’s g-factor [general intelligence] by a standard deviation?””
Don’t make me laugh. You need to prove that ‘g’ exists first. Glad to see some commentary on epigenetics that isn’t bashing it (it is a real phenomenon, though the scope of it in regards to health, disease and evolution remains to be discovered).
As most readers may know, I’m skeptical here and a huge contrarian. I do not believe that g is physiological and if it were then they better start defining it/talking about it differently because I’ve shown that if it were physiological then it would not mimick any known physiological process in the body. I eagerly await some good neuroscience studies on IQ that are robust, with large ns, their conclusions show the arrow of causality, and they’re not just making large sweeping claims that they found X “just because they want to” and are emotionally invested in their work. That’s my opinion about a lot of intelligence research; like everyone, they are invested in their own theories and will do whatever it takes to save face no matter the results. The recent Amy Cuddy fiasco is the perfect example of someone not giving up when it’s clear they’re incorrect.
I wish that Mr. Taylor would actually read some of the literature out there on TBI and IQ along with how people with chunks of their brains missing can have IQs in the normal range, showing evidence that most a lot of our brain mass is redundant. How can someone survive with a brain that weighs 1.5 pounds (680 gms) and not need care for the rest of his life? That, in my opinion, shows how incredible of an organ the human brain is and how plastic it is—especially in young age. People with IQs in the normal range need to be studied by neuroscientists because anomalies need explaining.
If large brains are needed for high IQs, then how do these people function in day-to-day life? Shouldn’t they be ‘as dumb as an erectus’, since they have erectus-sized brains living in the modern world? Well, the human body and brain are two amazing aspects of evolution, so even sudden brain damage and brain removal (up to half the brain) does not show deleterious effects in a lot of people. This is a clue, a clue that most of our brain mass after erectus is useless for our ‘intelligence’ and that our brains must have expanded for another reason—family structure, sociality, expertise, etc. I will cover this at length in the future.
Job performance is supposedly one measure that validates the construct of IQ tests since they correlate so highly with IQ tests (Schmidt et al, 1986). However, there are problems with the methods used to get the high correlations (sometimes doubling correlations, there are also questions to the robusticity of the studies meta-analyzed); corrections used have to make a number of assumptions; uncertainty of the interpretation of what the supposed IQ and job performance correlations mean; other non-cognitive factors may also explain differences in job performance. Most surprisingly, intelligence test scores did not predict promotion to senior doctor and intelligence does not predict careers.
Job performance and IQ
Does IQ really correlate around .5 with job performance like is so commonly stated? There are a number of problems citing such the commonly used meta-analyses for evidence that IQ does indeed predict job performance.
Richardson and Norgate (2015) show that one should use caution when interpreting the results of IQ and job performance on the basis of numerous criteria. It is important to note that job performance is rated by supervisors, which is, of course, a problem since supervisors tend to be subjective in their ratings. Further, supervisor ratings have low correlations with work performance, while work knowledge has a correlation of around .3 (Richardson and Norgate 2015; Richardson, 2002). So, one of the main things that the correlation hinges upon is strongly subjective.
However, one of the most important things to note here is that the validation of IQ tests is relied on with correlations with other tests. For instance, blood alcohol and level of consumption are valid constructs. The higher your blood alcohol is, the more alcohol you consumed. There is no such validity for the construct of IQ—except correlations with other tests—which is a huge problem. This goes back to the fact that there is no individual theory of intelligence differences (Deary, 2001: 14) and no neurophysiological theory of g (Jensen, 1998: 257).
So IQ tests don’t have the same construct validity that other models that describe biologic/physiologic functions do; hundreds of studies before the 70s showed low correlations between IQ and job performance; corrections for error make a lot of assumptions; the common claim that the IQ/job performance correlation increases with more complex jobs is not observed in more recent studies; and there is great uncertainty in the interpretation of the IQ and job performance correlation, due to the fact that there is no construct validity to IQ tests. This goes back to the question: What is it that IQ tests test (Richardson, 2002)? Is it the ever-elusive general factor of intelligence? I’m skeptical there.
Richardson (2017) writes:
The committee described the differences as “puzzling and somewhat worrisome.” But they noted how the quality of the data might explain it. For example, the 264 newer studies have much greater numbers of participants, on average (146 versus 75). It was shown how the larger samples produced much lower sampling error and less range restriction, also requiring less correction (with much less possibility of a false boost to observed correlations). And there was no need to devise estimates to cover for missing data. So, even by 1989, these more recent results are indicative of the unreliability of those usually cited. But it is the earlier test results that are still being cited by IQ testers. (pg. 89)
IQ and job performance correlations are also substantially weaker in other parts of the world, such as the Middle East and China, where motivation and effort explain school and work performance and not cognitive ability (Byington and Felps, 2010). So, again, caution is to be taken when interpreting any IQ and job performance correlation, as well as—most importantly—asserting that higher IQ means better job performance.
In his 2015 book Intelligence in the Flesh, Guy Claxton wrote:
We saw earlier that Google is not impressed by people’s track records of success, but is equally sceptical of high IQs. Laszlo Bock, the senior vice-president in charge of ‘people operations’ – the head of HR – says: ‘For every job the No. 1 thing we look for is general cognitive ability, and it’s not I.Q. It’s learning agility. It’s the ability to process on the fly.‘ Behind the ability to learn quickly lies what Bock calls ‘intellectual humility.’ You have to be able to give up the knowledge and expertise you thought would see you through, and look with fresh eyes. People with a high IQ ofen have a hard time doing that. They are certainly no better than average at tolerating uncertainty or being able to adopt fresh perspectives.
Now that we know to take caution when speaking about the IQ and job performance correlation, what do IQ tests say about success as a doctor?
Doctors and IQ
Since becoming a doctor is so demanding and takes a lot of time and motivation to complete a doctoral degree, most rightly assume that it takes a higher than average intelligence to acquire these accolades and become a medical doctor. However, reality is more nuanced.
McManus et al (2003) put forth three hypotheses: 1) the achievement argument: A-levels ensure maximum competence on sciences which are basic to medicine (biology and chemistry); 2) the ability argument: Academic success depends mainly on cognitive ability; and 3) the motivation argument: Using A-levels is effective because it University education not only reflects intelligence but motivation and good, consistent study skills.
There is evidence that IQ is irrelevant to becoming a doctor and that it did not predict dropping out of the program, career outcome, amount of research publications published, or stress, burnout and satisfaction with taking a career in medicine (McManus et al, 2003). Diplomas, higher academic degrees, and research publications were significantly correlated with personality.
McManus et al (2003) write:
Intelligence did not independently predict dropping off the register, career outcome, or other measures.
Intelligence does not predict careers, thus rejecting the ability argument. A levels predict because they assess achievement, and the structural model shows how past achievements predict future achievement.
And on the causes for dropping out:
All 511 students registered with the General Medical Council, but only 464 were on the 2001 Medical Register. The 47 doctors who left the register (a mean of 11.1 years after qualifying; SD 5.9; range 2-23) had lower A level grades but not lower AH5 scores (table A, bmj.com); see http://www.bmj.com for ROC analysis. Two doctors subsequently returned to the register. Of the remainder, three had died, contact details were available for 35, and no information was available for seven.
So lower intelligence scores were not the cause for dropping out.
McManus et al (2003), however, could not distinguish between the motivation and achievement argument, but falsified the intelligence argument (Hypothesis 2 was falsified, but not 1 and 3).
This was also replicated by McManus et al (2013), where they should that IQ scores did not predict promotion to senior doctor. A-level scores, yet again, predicted success better when it came to doctoral success.
The relationship between IQ and job performance is not as clear-cut as most would like to believe. One of the most important factors there, in my opinion, is the subjectivity of supervisors on the performance of their workers. Numerous factors could influence a supervisors’ view of an individual, biasing the supervisor to a high rating. Furthermore, the corrected correlations are a problem. More recent analyses show a correlation of .25 (Richardson, 2017: 89).
Perhaps more importantly, two studies show that there is no predictive effect on job performance when it comes to IQ for doctors (McManus et al, 2003; McManus et al, 2013). They show that A-level scores predict success better, with personality variables mediating other relationships—not IQ scores.
The fact of the matter is, job performance and IQ is on shaky ground since IQ tests are not constructed valid, and the job performance ratings are based on supervisor ratings which are highly subjective. Analyses in other locations around the world show that IQ does not predict job performance, however, motivation and effort do. IQ does not predict a doctor’s job performance; job performance tests do not prove the validity of IQ tests.
IQ does not predict a doctor’s job performance; job performance tests do not prove the validity of IQ tests.
[Edit: I have come across more data on doctors IQ. Some studies show that complaints by patients on their doctors are related to infractions. Perry and Crean (2005) show that the average IQ for a doctor is 125. They also state that neurocognitive impairment may be responsible for 63% of all physician related adverse events. This same observation is also noted in other studies (Pitkanen, Hurn, and Kopelman, 2008; Lauri et al, 2009; Kataria et al, 2014). Also of note is that these papers—to the best of my knowledge—do not explore the role of stress in cognitive decline. Though Pitkanen, Hurn, and Kopelman (2008) note that depression, PTSD, amnesia, transient global amnesia, alcoholic brain damage, frontotemporal dimentia, dimentia, alzheimer’s disease, vascular dimentia, and post-traumatic amnesia (PTA) influence cognitive decline in doctors.
Veena et al, (2015) show that 88 percent of medical students had near average intelligence, putting in 6 hours a day of studying, while 10 percent of students had above average IQ, spent less time studying but were sincere in their classes.
Veena et al (2015) conclude:
Students with near average IQ work hard in their studies and their academic performance was similar to students with higher IQ. So IQ can`t be made the basis for medical entrance; instead giving weight-age to secondary school results and limiting the number of attempts may shorten the time duration for entry and completion of MBBS degree.
So students with average intelligence work just as hard (if not harder) than people with above average IQ and have similar educational achievement. This shows that IQ can’t be the basis for medical school entry.
This is a really interesting matter and I will cover it more in the future. I’ve been wondering for years if there is data on physician/doctoral malpractice and race I have yet to come across any papers on the matter. If anyone knows of any, please leave some citations.]
By Scott Jameson
Long and short of this issue is that something has to explain why most of the really, really smart people are men. There are two hypotheses: men have a higher mean, and men have a higher standard deviation. They don’t really have to compete, and so some people believe that both are true. Some believe neither, of course.
Let’s start with three facts:
- Women tend to get slammed by men on Raven’s Progressive Matrices; the second graph in the post linked above details this. It’s a difference of 5 IQ points on average, quite a bit, certainly more than on other IQ tests.
- Women tend to lose even harder in visuospatial measures. John Loehlin pointed out in The Handbook of Intelligence that the gap here was a whopping 13.5 points.
- Raven’s is so g loaded because your score is primarily driven by spatial and verbal-analytic abilities.
The biggest subtest difference is spatial, and I think that likely explains the abnormally large differences in Raven’s scores. Other IQ tests, like the SAT, hardly use visual abilities. Women do about as well as men on the SAT. I’ve also seen the White-Asian gap smaller on the SAT than in other IQ tests, and that gap is also driven in large part by spatial scores. Conversely you might expect the SAT to go better for a hypothetical demographic that scores well in math and verbal abilities, but not especially well in spatial. By hypothetically I mean that these people make up like a fifth of the kids at the Ivy Leagues, even more than you’d expect from an average IQ of, I don’t know, 111ish.
Off topic: these differences are probably going to be slighter still now that they’re fastidiously removing every useful element of the test in an effort to make it less “biased” by race. I wonder if colleges will just throw up their shoulders and start looking for kids who do well on the ACT. Moving on.
There are other sex differences in subtest scores. Pulling from Loehlin again: “females tend to have an advantage on verbal tests involving the fluent production of words belonging to a category, such as synonyms.” Women are known to do better on verbal than on math.
Loehlin also points out that girls do better at math in early childhood, but that boys outstrip them by the time it, uh, matters, when they take standardized tests in adolescence.
I have a wild hypothesis that men and women respectively being more oriented towards mathematical and verbal thought corresponds to observed differences in interests. Women are known to read more often than men on average, whereas male dominated activities like sports and video games often have a distinctly mathematical bent. My spurious hypothesis is that doing these different things differentially develops their abilities, constituting an example of crystallized intelligence rather than fluid intelligence; alternatively, they were differentially selected for ability to perform well on tasks that their respective sex does more of, in which case the abilities are innate.
Even if they aren’t innate, it’d be an instance of secondary heritability because evidence tends to show male-female personality differences as innate; in this scenario they are innately prone to practicing different abilities to different extents.
Loehlin points to Hedges and Nowell’s 1995 meta-analysis, showing a higher male variation in IQ and elucidating a few more small subtest differences. I’ve lifted a meaty bit here:
On average, females exhibited a slight tendency to perform better on tests of reading comprehension, perceptual speed, and associative memory, and males exhibited a
slight tendency to perform better on tests of mathematics and social studies. All of the effect sizes were relatively small except for those associated with vocational aptitude scales (mechanical reasoning, electronics information, and auto and shop information) in which average males performed much better than average females. The effect sizes for science were slightly to moderately positive, and those for perceptual speed were slightly to moderately negative. Thus, with respect to the effect size convention, these data suggest that average sex differences are generally rather small.
- There are sex differences in scores of various IQ subtests, including but not limited to female orientation towards verbal and male orientation towards mathematical ability.
- The largest of these differences is a substantial male advantage in spatial ability.
- On any IQ test that doesn’t weight subtests such that men and women perform equally by default, men tend to score a hair better.
- Men also have a higher standard deviation in IQ.
There are more male geniuses, particularly with respect to mathematical genius. There are also more mentally retarded males. I just explained why men tend to populate CERN, NASA, Silicon Valley, and lists of who’s died in the Running of the Bulls.
The general factor of intelligence (g) is said to be physiological. Jensen (1998: xii) states that “Students in all branches of the behavioral and social sciences, as well as students of human biology and evolution, need to grasp the essential psychometric meaning of g, its basis in genetics and brain physiology, and its broad social significance.” There are, furthermore, “a number of suggestive neurological correlates of g, but as yet these have not been integrated into a coherent neurophysiological theory of g” (Jensen, 1998: 257). I personally don’t care for correlations too much anymore, I’m interested in actual causes. Jensen (1998: 578) also states “Although correlated with g [size of the brain, metabolic rate, nerve conduction velocity, and latency and amplitude of evoked electrical potentials], these physiological variables have not yet provided an integrated explanatory theory.”
This seems suspiciously like Dreary’s (2001: 14) statement that there “is no such thing as a theory of human intelligence differences – not in the way that grown-up sciences like physics or chemistry have theories.” If g is physiological, then where is the explanatory theory? On that same matter, where is the explanatory theory for individual intelligence differences? That’s one thing that needs to be explained, in my opinion. I could muster something up off the top of my head, such as individual differences in glucose metabolism in the brain, comparing both high and low IQ people (Cochran et al, 2006; Jensen, 1998: 137), however, that is still not good enough.
In physiology there is sliding filament theory which explains the mechanism of muscle contraction (Cooke, 2004). Why is there no such theory of why individuals differ in intelligence and why have these “suggestive neurological correlates of g” not been formulated into a coherent neurophysiological theory? There are numerous theories in physiology, but a theory of g or why individuals differ in intelligence is not one of them.
It’s like Darwin only saying “Species change“, and that’s it; no theory of how or why. He’s just stating something obvious. Similarly, saying “Person A is smarter or has a higher IQ than person B” is just an observation; there is no theory of how or why for why individuals differ in intelligence. There are theories for group differences (garbage cold winter theory), but no individual differences in intelligence? Hmmm… Sure it’d be a ‘fact that species change over time’, but without a theory of how or why, how useful is that observation? Similarly, it is true that some people are more intelligent than others (score higher on IQ tests), yet there is no explanatory theory as to why? I believe this ties back to the physiological basis for g: are physiologists studying it, and if not, why?
Reaction time (RT) is one of the most talked about physiological correlates in regards to IQ. However, as a fitness professional, I know that exercise can increase reaction time, especially in those with intellectual disabilities (Yildirim et al, 2001). I am now rethinking the correlate between reaction time and IQ, since it can be trained in children, especially those with intellectual disabilities. Clearly, RT can be trained by exercise, participating in sports, and even by playing video games (Green, 2008). So since RT can be trained, I don’t think it’s a good physiological measure for g.
Individuals do differ in individual physiology, however, I have never heard of a physiologist attempting to rank individuals on different traits, nevermind attempting to say that a higher level of one variable is better than a lower variable, say blood pressure or metabolic rate. In fact, individuals with high blood pressure and metabolic rates would need immediate medical attention.
There are also wide variations in how immune systems act when faced with pathogens, bacteria and viruses. Though, “no one dreams of ranking individual differences on a general scale of immunocompetence” (Richardson, 2017: 166). So if g is physiological then why don’t other physiological traits get placed on a rank order, with physiologists praising certain physiological functions as “better”?
Richardson (2017: 166-167) writes:
In sum, no physiologist would suggest the following:
(a) that within the normal range of physiological differences, a higher level is better than any others (as is supposed in the construction of IQ tests);
(b) that there is a general index or “quotient” (a la IQ) that could meaningfully describe levels of physiological sufficiency or ability and individual differences in it;
(c) that “normal” variation is associated with genetic variation (except in rare deleterious conditions; and
(d) the genetic causation of such variation can be meaningfully separated from the environmental causes of the variation.
A preoccupation with ranking variations, assuming normal distributions, and estimating their heritabilities simply does not figure in the field of physiology in the way that it does in the field of human intelligence. This is in stark contrast with the intensity of the nature-nurture debate in the human cognitive domain. But perhaps ideology has not infiltrated the subject of physiology as much as it has that of human intelligence.
This is all true. I know of no physiologist who would suggest such a thing. So does it make sense to compare g with physiological variables—even when classic physiological variables do not have some kind of rank order? Heritabilities for BMR are between .4 and .8, which is in the same range as the heritability of IQ. Can you imagine any physiologist on earth suggesting a rank order for physiological traits such as BMR or stroke volume? I can’t, and if you knew anything about physiological variables then you wouldn’t either.
In sum, I believe that conflating g with physiology is erroneous; mostly because physiologists don’t rank physiological traits in the same ways that human intelligence researchers do. Our physiology is intelligent in and of itself, and this process begins in the cell—the intelligent cell. Our physiological systems are intelligent—in our bodies are dynamic systems that keenly respond to whatever is going on in the environment (think of how the body always attempts to maintain homeostasis). Physiology deals with the study of living organisms—more to the point, how the systems that run the organisms work.
Looking at physiological variables and attempting to detangle environmental and genetic effects is a daunting task—especially the way our physiological systems run (responding to cues from the environment, attempting to maintain homeostasis). So if general intelligence—g—had a true biological underpinning in the body, and if physiologists did study it, then they would not have a rank ordering for g like psychologists do; it’d just be another human trait to study.
So the answer to the question “Do physiologists study g?” is no, and if they did they would not have the variable on a rank order because physiologists don’t study traits in that manner—if a true biological underpinning for g exists. Physiology is an intelligent and dynamic system in and of itself, and the process begins in the intelligent cell, except it is on a larger scale, with numerous physiological variables working in concert, constantly attempting to stay in homeostasis.
After the publishing of the article debunking r/K selection theory last week, I decided to go to a few places and provide the article to a few sites that talk about r/K selection theory and it’s (supposed) application to humans and psychometric qualities. I posted it on a site called ‘truthjustice.net‘, and the owner of the site responded to me:
Phillippe Rushton is not cited a single time in AC’s book. In no way, shape or form does the Theory depend on his opinions.
AC outlines a very coherent theoretical explanation for the differing psychological behavior patterns existing on a bell curve distribution in our population. Especially when it comes to the functioning of the Amygdala for which we have quite a lot of data by now.
Leftists are indeed in favor of early childhood sexualization to increase the quantity of offspring which will inevitably reduce the quality and competitive edge of children. They rank significantly lower on the moral foundations of “loyalty”, “authority” and “purity” as outlined by Jonathan Haidt’s research into moral psychology. Making them more accepting of all sorts of degeneracy, deviancy, and disloyalty to the ingroup.
They desire a redestribution of resources to the less well performing part of our population to reduce competitive stress and advantage while giving far less to charity and being significantly more narcissistic to increase their own reproductive advantage.
Their general mindset becomes more and more nihilistic, atheistic, anarchistic, anti-authority and overall r-selected the further left you go on the bell curve. A denial of these biological realities in our modern age is ridiculous when we can easily measure their psychology and brain functionality in all sorts of ways by now.
Does that now mean that AC is completely right in his opinions on r/K-Selection Theory? No, much more research is necessary to understand the psychological differences between leftists and rightists in full detail.
But the general framework outlined by r/K-Selection Theory very likely applies to the bell curve distribution in psychological behavior patterns we see in our population.
I did respond, however, he removed my comment and banned me after I published my response. My response is here:
“Phillippe Rushton is not cited a single time in AC’s book. In no way, shape or form does the Theory depend on his opinions.”
Meaningless. He uses the r/K continuum so the link in my previous comment is apt.
“AC outlines a very coherent theoretical explanation for the differing psychological behavior patterns existing on a bell curve distribution in our population. Especially when it comes to the functioning of the Amygdala for which we have quite a lot of data by now.”
No, he doesn’t.
2) even if r/K were a valid paradigm, it would not pertain to within species variation,
3) it’s just a ‘put these traits on one end that I don’t like and these traits at the other end that I like and that’s my team while the other team has all of the bad traits’ thing,
4) his theory literally rests on the r/K continuum proposed by Pianka. Furthermore, no experimental rationale “was ever given for the assignment of these traits [the r/K traits Pianka inserted into his continuum] to either category” (Graves, 2002: 135), and
5) the r/K paradigm was discredited in the late 70s (see Graves 2002 above for a review)
“Leftists are indeed in favor of early childhood sexualization to increase the quantity of offspring which will inevitably reduce the quality and competitive edge of children. They rank significantly lower on the moral foundations of “loyalty”, “authority” and “purity” as outlined by Jonathan Haidt’s research into moral psychology. Making them more accepting of all sorts of degeneracy, deviancy, and disloyalty to the ingroup.”
I love Haidt. I’ve read his book and all of his papers and articles. So you notice a few things. Then see the (discredited) r/K paradigm. Then you say “oh! liberals are bad and are on the r side while conservatives are K!!”
Let me ask you this: where does alpha-selection fall into this?
“They desire a redestribution of resources to the less well performing part of our population to reduce competitive stress and advantage while giving far less to charity and being significantly more narcissistic to increase their own reproductive advantage.”
Oh.. about that… liberals have fewer children than conservatives. Liberals are also more intelligent than conservatives. So going by Rushton’s r/K model, liberals are K while conservatives are r (conservatives are less intelligent and have more children). So the two cornerstones of the (discredited) r/K continuum show conservatives breeding more and also are less intelligent while it’s the reverse for liberals. So who is ‘r’ and ‘K’ again?
“Their general mindset becomes more and more nihilistic, atheistic, anarchistic, anti-authority and overall r-selected the further left you go on the bell curve. A denial of these biological realities in our modern age is ridiculous when we can easily measure their psychology and brain functionality in all sorts of ways by now.”
‘r’ and ‘K’ are not adjectives (Anderson, 1991: 57).
Why does no one understand r/K selection theory? You are aware that r/K selection theory is density-dependent selection, correct?
“Does that now mean that AC is completely right in his opinions on r/K-Selection Theory? No, much more research is necessary to understand the psychological differences between leftists and rightists in full detail.”
No, he’s horribly wrong with his ‘theory’. I don’t deny psych differences between libs and cons, but to put them on some (discredited) continuum makes no sense in reality.
“But the general framework outlined by r/K-Selection Theory very likely applies to the bell curve distribution in psychological behavior patterns we see in our population.”
No, it doesn’t. Psych traits are not normally distributed (see above). Just like Rushton, AC saw that some things ‘fit’ into this (discredited) continuum. What’s that mean? Absolutely nothing. He doesn’t even cite papers for his assertion; he called Pianka a leftist and said that he tried to sabotage the theory because he thought that it described libs (huh? this makes no sense). AC is a clear ideologue and is steeped in his own political biases as well as wanting to sell more copies of his book. So he will not admit that he is wrong.
Let me ask you a question: where did liberals and conservatives evolve? What selective pressures brought about these psych traits in these two ‘populations’? Are liberals and conservatives local populations?
I’ve also summarily discredited AC and I am waiting on a reply from him (I will be surprised if he replies).
However, unfortunately for AC et al, concerns have been raised “about the use of psychometric indicators of lifestyle and personality as proxies for life history strategy when they have not been validated against objective measures derived from contemporary life history theory and when their status as causes, mediators, or correlates has not been investigated” (Copping, Campbell, and Muncer, 2014). This ends it right here. People don’t understand density-dependent/independent selection since Rushton never talked about it. That, as has been brought up, is a huge flaw in Rushton’s application of r/K theory to the races of Man.
Liberals are, on average, more intelligent than conservatives (Kanazawa, 2010; Kanazawa, 2014) Lower cognitive ability has been linked to greater prejudice through right-wing ideology and low intergroup contact (Hodson and Busseri, 2012), with social conservatives (probably) having lower IQs. There are also three ‘psychological continents’—Europe, Australia, and, Canada and are the liberal countries whereas Southeast Asia, South Asia, South America and Africa contain more conservative countries with all other countries including Russia, the US and Asia in the middle and “In addition, gross domestic product (GDP) per capita, cognitive test performance, and governance indicators were found to be low in the most conservative group and high in the most liberal group” (Stankov and Lee, 2016). Further, economic liberals—as a group—tend to be better educated than Republicans—so intelligence is positively correlated with socially and economically liberal views (Carl, 2014).
There is also a ‘conservative baby boom‘ in the US—which, to the Rushtonites, is ‘r-selected behavior’. Furthermore, women who reported that religion was ‘very important to them’ reported having higher fertility than women who said that it was ‘somewhat important’ or ‘not important’ (Hayford and Morgan, 2008). Liberals are more likely to be atheist (Kanazawa, 2010), while, of course, conservatives are more likely to be religious (Morrison, Duncan, and Parton, 2015; McAdams et al, 2015).
All in all, even if we were to allow the use of liberals and conservatives as local populations, like Rushton’s erroneous use of r/K theory for human races, the use of r/K theory to explain the conservative/liberal divide makes no sense. People don’t know anything about ecology, evolution, or neuroscience. People should really educate themselves on the matters they speak about—I mean a full-on reading into whatever it is you believe. Because people like TIJ and AC are clearly idealogues, pushing a discredited ecological theory and applying it to liberals and conservatives, when the theory was never used that way in the first place.
For anyone who would like a look into the psychological differences between liberals and conservatives, Jonathan Haidt has an outstanding book outlining the differences between the two ideologies called The Righteous Mind: Why Good People are Divided by Politics and Religion. I actually just gave it a second read and I highly, highly recommend it. If you want to understand the true differences between the two ideologies then read that book. Try to always remember and look out for your own biases when it comes to your political beliefs and any other matter.
For instance, if you see yourself frantically attempting to gather support for a contention in a debate, then that’s the backfire effect in action (Nyhan and Reifler, 2012), and if you have a knowledge of the cognitive bias, you can better take steps to avoid such a heavy-handed bias. This, obviously, occurred with TIJ. The response above is airtight. If this ‘continuum’ did exist, then it’s completely reversed with liberals having fewer children and generally being more intelligent with the reverse for conservatives. So liberals would be K and conservatives would be r (following Rushton’s interpretation of the theory which is where the use of the continuum comes from).
A commenter by the name of bbloggz alerted me to a new paper by Lee Ellis published this year titled Race/ethnicity and criminal behavior: Neurohormonal influences in which Ellis (2017) proposed his theory of ENA (evolutionary neuroandrogenic theory) and applied it to racial/ethnic differences in crime. On the face, his theory is solid and it has great explanatory power for the differences in crime rates between men and women, however, there are numerous holes in the application of the theory in regards to racial/ethnic differences in crime.
In part I, he talks about racial differences in crime. No one denies that, so on to part II.
In part II he talks about environmental causes for the racial discrepancies, that include economic racial disparities, racism and societal discrimination and subordination, a subculture of violence (I’ve been entertaining the honor culture hypothesis for a few months; Mazur (2016) drives a hard argument showing that similarly aged blacks with some college had lower levels of testosterone than blacks with less than high school education which fits the hypothesis of honor culture. Though Ellis’ ENA theory may account for this, I will address this below). However, if the environment that increases testosterone is ameliorated (i.e., honor culture environments), then there should be a subsequent decrease in testosterone and crime, although I do believe that testosterone has an extremely weak association with crime, nowhere near high enough to account for racial differences in crime, the culture of honor could explain a good amount of the crime gap between blacks and whites.
Ellis also speaks about the general stress/strain explanation, stating that blacks have higher rates of self-esteem and Asians the lowest, with that mirroring their crime rates. This could be seen as yet another case for the culture of honor in that blacks with a high self-esteem would feel the need to protect their ‘name’ or whatever the case may be and feel the need for physical altercation based on their culture.
In part III, Ellis then describes his ENA theory, which I don’t disagree with on its face as it’s a great theory with good explanatory power but there are some pretty large holes that he rightly addresses. He states that, as I have argued in the past, females selected men for higher rates of testosterone and that high rates of testosterone masculinize the brain, changing it from its ‘default feminine state’ and that the more androgens the brain is exposed to, the more likely it is for that individual to commit crime.
Ellis cites a study by Goodpaster et al (2006) in which he measured the races on the isokinetic dynamometry, pretty much a leg extension. However, one huge confound is that participants who did not return for follow-up were more likely to be black, obese and had more chronic disease (something that I have noted before in an article on racial grip strength). I really hate these study designs, but alas, it’s the best we have to go off of and there are a lot of holes in them that must be addressed. Though I applaud the researchers’ use of the DXA scan (regular readers may recall my criticisms on using calipers to assess body fat in the bench press study, which was highly flawed itself; Boyce et al, 2014) to assess body fat as it is the gold standard in the field.
Ellis (2017: 40) writes: “as brain exposure to testosterone surges at puberty, the prenatally-programmed motivation to strive for resources, status, and mating opportunities will begin to fully activate.” This is true on the face, however as I have noted the correlation between physical aggression and testosterone although positive is low at .14 (Archer, 1991; Book et al, 2001). Testosterone, as I have extensively documented, does cause social dominance and confidence which do not lead to aggression. However, when other factors are coupled with high testosterone (as noted by Mazur, 2016), high rates of crime may occur and this may explain why blacks commit crime; a mix of low IQ, high testosterone and low educational achievement making a life of crime ‘the smart way’ to live seeing as, as Ellis points out, and that intelligent individuals find legal ways to get resources while less intelligent individuals use illegal ways.
ENA theory may explain racial differences in crime
In part IV he attempts to show how his ENA theory may explain racial differences in crime—with testosterone sitting at the top of his pyramid. However, there are numerous erroneous assumptions and he does rightly point out that more research needs to be done on most of these variables and does not draw any conclusions that are not warranted based on the data he does cite. He cites one study in which testosterone levels were measured in the amniotic fluid of the fetus. The sample was 59 percent white and due to this, the researchers lumped blacks, ‘Hispanics’ and Native Americans together which showed no significant difference in prenatal testosterone levels (Martel and Roberts, 2014).
Umbilical cord and testosterone exposure
Ellis then talks about testosterone in the umbilical cord, and if the babe is exposed to higher levels of testosterone in vitro, then this should account for racial/ethnic differences in crime. However, the study he cited (Argus-Collins et al, 2012) showed no difference in testosterone in the umbilical cord while Rohrmann et al (2009) found no difference in testosterone between blacks and whites but found higher rates of SHBG (sex hormone-binding globulin) which binds to testosterone and makes it unable to leave the blood which largely makes testosterone unable to affect organ development. Thusly, if the finding of higher levels of SHBG in black babes is true, then they would be exposed to less androgenic hormones such as testosterone which, again, goes against the ENA theory.
He also cites two more studies showing that Asian babes have higher levels of umbilical cord testosterone than whites (Chinese babes were tested) (Lagiou et al, 2011; Troisi et al, 2008). This, again, goes against his theory as he rightly noted.
Next he talks about circulating differences in testosterone between blacks and whites. He rightly notes that testosterone must be assayed in the morning within an hour after waking as that’s when levels will be highest, yet cites Ross et al (1986) where assay times were all over the place and thusly testosterone cannot be said to be higher in blacks and whites based on that study and should be discarded when talking about racial differences in testosterone due to assay time being between 10 am and 3 pm. He also cites his study on testosterone differences (Eliss and Nyborg, 1993), but, however, just as Ross et al (1986) did not have a control for WC (waist circumference) Ellis and Nyborg (1993) did not either, so just like the other study that gets cited to show that there is a racial difference in testosterone, they are pretty hugely flawed and should not be used in discussion when discussing racial differences in testosterone. Why do I not see these types of critiques for Ross et al (1986) in major papers? It troubles me…
He also seems to complain that Lopez et al (2013) controlled for physical activity (which increases testosterone) and percent body fat (which, at high levels, decreases testosterone). These variables, as I have noted, need to be controlled for. Testosterone varies and fluctuated by age; WC and BMI vary and fluctuate by age. So how does it make sense to control for one variable that has hormone levels fluctuate by age and not another? Ellis also cites studies showing that older East Asian men had higher levels of testosterone (Wu et al, 1995). Nevertheless, there is no consensus; some studies show Chinese babes have higher levels of testosterone than whites and some studies show that whites babes have higher levels of testosterone than Chinese babes. Indeed, this meta-analysis by Ethnicmuse shows that Asians have the highest levels, followed by Africans then Europeans, so this needs to be explained to save the theory that testosterone is the cause of black overrepresentation of violence (as well as what I showed that testosterone is important for vital functioning and is not the boogeyman the media makes it out to be).
Bone density and crime
Nevertheless, the next variable Ellis talks about is bone density and its relationship to crime. Some studies find that blacks are taller than whites while other show no difference. Whites are also substantially taller than Asian males. Blacks have greater bone density than the other three races, but according to Ellis, this measure has not been shown to have a relationship to crime as of yet.
Penis size, race and crime
Now on to penis size. In two articles, I have shown that there is no evidence for the assertion that blacks have larger penises than whites. However, states that penis length was associated with higher levels of testosterone in Egyptian babes. He states that self-reported penis size correlates with self-reports of violent delinquency (Ellis and Das, 2012). Ellis’ main citations for the claim that blacks have larger penises than other races comes from Nobile (1982), the Kinsey report, and Rushton and Boagert (1987) (see here for a critique of Rushton and Boagert, 1987), though he does cite a study stating that blacks had a longer penis than whites (blacks averaging 5.77 inches while whites averaged 5.53 inches). An HBDer may go “Ahah! Evidence for Rushton’s theory!”, yet they should note that the difference is not statistically significant; just because there is a small difference in one study also doesn’t mean anything for the totality of evidence on penis size and race—that there is no statistical difference!
He then cites Lynn’s (2013) paper which was based on an Internet survey and thus, self-reports are over-measured. He also cites Templer’s (2002) book Is Size Important?, which, of course, is on my list of books to read. Nevertheless, the ‘evidence’ that blacks average larger penises than whites is extremely dubious, it’s pretty conclusive that the races don’t differ in penis size. For further reading, read The Pseudoscience of Race Differences in Penis Size, and read all of Ethnicmuses’ posts on penis size here. It’s conclusive that there is no statistical difference—if that—and any studies showing a difference are horribly flawed.
2d/4d ratio and race
Then he talks about 2d/4d ratio, which supposedly signifies higher levels of androgen exposure in vitro (Manning et al, 2008) however these results have been challenged and have not been replicated (Koehler, Simmons, and Rhodes, 2004; Yan et al, 2008, Medland et al, 2010). Even then, Ellis states that in a large analysis of 250,000 respondents, Asians had the lowest 2d/4d ratio, which if the hypothesis of in vitro hormones affecting digit length is to be believed, they have higher levels of testosterone than whites (the other samples had small ns, around 100).
Prostate-specific antigens, race, and prostate cancer
He then talks about PSA (prostate-specific antigen) rates between the races. Blacks are two times more likely to get prostate cancer, which has been blamed on testosterone. However, I’ve compiled good evidence that the difference comes down to the environment, i.e., diet. Even then, there is no evidence that testosterone causes prostate cancer as seen in two large meta-analyses (Stattin et al, 2003; Michaud, Billups, and Partin, 2015). Even then, rates of PCa (prostate cancer) are on the rise in East Asia (Kimura, 2012; Chen et al, 2015; Zhu et al, 2015) which is due to the introduction of our Western diet. I will cover the increases in PCa rates in East Asia in a future article.
He then reviews the evidence of CAG repeats. There is, however, no evidence that the number of CAG repeats influences sensitivity to testosterone. However, intra-racially, lower amounts of CAG repeats are associated with higher spermatozoa counts—but blacks don’t have higher levels of spermatozoa (Mendiola et al, 2011; Redmon et al, 2013). Blacks do have shorter CAG repeats, and this is consistent with the racial crime gap of blacks > whites > Asians. However, looking at the whole of the evidence, there is no good reason to assume that this has an effect on racial crime rates.
Intelligence and education
Next he talks about racial differences in intelligence and education, which have been well-established. Blacks did have higher rates of learning disabilities than whites who had higher levels of learning disabilities then Asians in a few studies, but other studies show whites and South Asians having different rates, for instance. He then talks about brain size and criminality, stating that the head size of males convicted for violent crimes did not differ from males who committed non-violent crimes (Ikaheimo et al, 2007). I won’t bore anyone with talking about what we know already: that the races differ in average brain size. However, a link between brain size and criminality—to the best of my knowledge—has yet to been discovered. IQ is implicated in crime, so I do assume that brain size is as well (no matter if the correlation is .24 or not; Pietschnig et al, 2015).
Prenatal androgen exposure
Now to wrap things up, the races don’t differ in prenatal androgen exposure, which is critical to the ENA theory; there is a small difference in the umbilical cord favoring blacks, and apparently, that predicts a high rate of crime. However, as noted, blacks have higher levels of SHBG at birth which inhibits the production of testosterone on the organs. Differences in post-pubertal testosterone are small/nonexistent and one should not talk about them when talking about differences in crime or disease acquisition such as PCa. DHT only shows a weak positive correlation with aggression—the same as testosterone (Christiansen and Winkler, 1992; however other studies show that DHT is negatively correlated with measures of physical aggression; Christiansen and Krussmann, 1987; further, DHT is not so evil after all).
Summing it all up
Blacks are not stronger than whites, indeed evidence from the races’ differing somatype, grip strength and leverages all have to do with muscular strength. Furthermore, the study that Ellis cites as ‘proof’ that blacks are stronger than whites is on one measure; an isokinetic dynamometry machine which is pretty much a leg extension. In true tests of strength, whites blow blacks away, which is seen in all major professional competitions all around the world. Blacks do have denser bones which is due to androgen production in vitro, but as of yet, there has been no research done into bone density and criminality.
The races don’t differ on penis size—and if they do it’s by tenths of an inch which is not statisitcally significant and I won’t waste my time addressing it. It seems that most HBDers will see a racial difference of .01 and say “SEE! Rushton’s Rule!” even when it’s just that, a small non-significant difference in said variable. That’s something I’ve encountered a lot in the past and it’s, frankly, a waste of time to converse about things that are not statistically significant. I’ve also rebutted the theory on 2d/4d ration as well. Finally, Asians had a similar level of androgen levels compared to blacks, with whites having the least amount. Along with a hole in the theory for racial differences in androgen causing crime, it’s yet another hole in the theory for racial differences in androgens causing racial differences in penis size and prostate cancer.
On intelligence scores, no one denies that blacks have scored about 1 SD lower than whites for 100 years, no one denies that blacks have a lower educational attainment. In regards to learning disabilities, blacks seem to have the highest rates, followed by Native Americans, than non-Hispanic whites, East Asians and the lowest rates found in South Asians. He states only one study links brain size to criminal behavior and it showed a significant inverse relationship with crime but not other types of offenses.
This is a really good article and I like the theory, but it’s full of huge holes. Most of the variables described by Ellis have been shown to not vary at all or much between the races (re: penis size, testosterone, strength [whites are stronger] prostate cancer caused mainly by diet, 2d/4d ratio [no evidence of it showing a digit ratio difference], and bone density not being studied). Nevertheless, a few of his statements do await testing so I await future studies on the matter. He says that androgen exposure ‘differs by race and ethnicity’, yet the totality of evidence shows ‘not really’ so that cannot be the cause of higher amounts of crime. Ellis talks about a lot of correlates with testosterone, but they do not pass the smell test. Most of it has been rebutted. In fact, one of the central tenets of the ENA theory is that the races should differ in 2d/4d ratio due to exposure of differing levels of the hormone in vitro. Alas, the evidence to date has not shown this—it has in fact shown the opposite.
ENA theory is good in thought, but it really leaves a lot to be desired in regards to explaining racial differences in crime. More research needs to be looked into in regards to intelligence and education and its effect on crime. We can say that low IQ people are more likely to drop out of school and that is why education is related to crime. However, in Mazur (2016) shows that blacks matched for age had lower levels of testosterone if they had some college under their belt. This seems to point in the direction of the ENA theory, however then all of the above problems with the theory still need to be explained away—and they can’t! Furthermore, one of the nails in the coffin should be this: East Asian males are found to have higher levels of testosterone than white males, often enough, and East Asian males actually have the lowest rate of crime in the worle!
This seems to point in the direction of the ENA theory, however then all of the above problems with the theory still need to be explained away—and they can’t! Furthermore, one of the nails in the coffin should be this: East Asian males are found to have higher levels of testosterone than white males, often enough, and East Asian males actually have some of the lowest rate of crime in the world (Rushton, 1995)! So this is something that needs to be explained if it is to be shown that testosterone facilitates aggression and therefore, crime.
I’ve shown—extensively—that there is a low positive correlation between testosterone and physical aggression, why testosterone does not cause crime, and have definitively shown that, by showing how flawed the other studies are that purport to show blacks have higher testosterone levels than whites, along with citing large-scale meta-analyses, that whites and blacks either do not differ or the differences is small to explain any so-called differences in disease acquisition or crime. One final statement on the CAG repeats, they are effect by obesity, men who had shorter CAG repeats were more likely to be overweight, which would skew readings (Gustafsen, Wen, and Koppanati, 2003). So depending on the study—and in most of the studies I cite whites have a higher BMI than blacks—BMI and WC should be controlled for due to the depression of testosterone.
It’s pretty conclusive that testosterone itself does not cause crime. Most of the examples cited by Ellis have been definitively refuted, and his other claims lack evidence at the moment. Even then, his theory rests on the 2d/4d ratio and how blacks may have a lower 2d/4d ratio than whites. However, I’ve shown that there is no significant relationship between 2d/4d ratio and traits mediated by testosterone (Kohler, Simmons, and Rhodes, 2004) so that should be enough to put the theory to bed for good.