Looking beyond the data

 

General intelligence (g factor) as a function of alleles associated with educational attainment (Education polygenic score). (Fuerst et al. 2021, p. 165)

Among non-Hispanic European Americans, cognitive ability shows a positive correlation with Amerindian admixture. The reason is to be found in the history of European settlement.

 

 

We know that cognitive ability differs among human populations, but are those differences innate? Or are they purely cultural? The question is difficult to answer because a purely cultural difference can, over time, become innate. If you are better able to meet the demands of your culture, you will probably live longer, have more offspring, and pass on many of your characteristics. Thus, over succeeding generations, those heritable characteristics will become more and more widespread in the gene pool, and they will increasingly determine certain abilities that were initially created by culture.

 

This is a recurring problem when we try to distinguish between cultural and genetic determination. The two often run parallel to each other, and we can seemingly rule out the existence of genetic determination by showing that cultural determination runs in the same direction.

 

But there is another recurring problem in our efforts to distinguish between culture and genetics. We lack the proper tools. For a long time, we could only infer genetic influences by using twin studies or adoption studies. 

 

Things have changed with the advent of a new tool: genomic data. Specifically, we can now:

 

·         Measure ethnic ancestry in mixed populations, as opposed to using self-report or inferring from skin color.

·         Measure the genetic component of cognitive ability, by using genetic variants associated with educational attainment. Although these variants explain only 11-13% of the variance in educational attainment among individuals, they explain a much higher percentage of the variance among populations (Piffer 2019). This is because genetic variants within the same population are exposed to the same pressure of selection and will thus vary in the same direction. They act, so to speak, as “weathervanes” that tell us the strength and direction of selection in that population.

·         Measure skin color, by looking at the relevant genes. We can thus control for the effects of “colorism” in mixed populations, i.e., discrimination in favor of lighter-skinned individuals.

 

In my last post, I described how Bryan Pesta used these tools to understand differences in mean cognitive ability between African Americans and European Americans (Lasker et al. 2019). To that end, his research team looked at cognitive ability among African Americans in relation to European admixture and in relation to genetic variants associated with educational attainment.

 

They made several findings: 1) among African Americans, cognitive ability correlates with European admixture; 2) the correlation is modestly reduced, but not eliminated, when controlled for parental education; 3) controlling for skin color has no effect; and 4) the correlation seems to be largely explained by genetic variants associated with educational attainment.

 

The same data source was then used by Fuerst et al. (2021) to investigate cognitive ability not only in European Americans and African Americans but also in Hispanic Americans. The research team thus looked at cognitive ability in relation to Amerindian admixture, and not just in relation to European and African admixture.

 

Most of their findings are similar to those of the first study:

 

·         Among Hispanic Americans, cognitive ability shows a positive correlation with European admixture and a negative correlation with African admixture and Amerindian admixture.

·         Among Hispanic Americans, the correlations are reduced but not eliminated by controlling for parental education. Controlling for skin color has no effect.

·         The above correlations are partially explained by variants associated with educational attainment, but not by skin color.

·         Among non-Hispanic European Americans, cognitive ability shows a positive correlation with Amerindian admixture.

 

The last correlation may seem curious. Keep in mind that the data came from residents of Pittsburgh and that the native peoples of the Eastern U.S. intermixed mostly with early settlers of British, Dutch, or French origin. There is much less Amerindian admixture among the descendants of later immigrants from southern and eastern Europe. The correlation may thus be due not to Amerindian admixture per se but rather to variation in cognitive ability among Europeans.

 

Until the eleventh century, mean IQ was relatively low throughout Europe, perhaps hovering in the low 90s. It then rose during late medieval and post-medieval times through the expansion of the middle class. There was in fact a broad mental and behavioral change: "Thrift, prudence, negotiation, and hard work were becoming values for communities that previously had been spendthrift, impulsive, violent, and leisure loving" (Clark 2007, p. 166; see also Clark 2007, 2009a, 2009b). More people could better understand probability, cause and effect, and another person’s perspective, whether real or hypothetical (Rinderman 2018, pp. 49, 86-87; Oesterdiekhoff 2012). As the "smart fraction" grew in size, a point was reached when intellectuals were no longer voices crying in the wilderness. They were now numerous enough to form learned societies and collaborate in projects of various sorts (Frost 2019b, pp. 175-176).

 

Western Europe was where the middle class began to expand, and that was where the expansion would have its greatest impact, not only demographically but also behaviorally and cognitively. Gregory Clark (2009a) has shown that the English, even in the lower classes, are largely descended from people who were middle-class several generations earlier. The same is likely true elsewhere in Western Europe. We should therefore see a cognitive gradient between the Western European core and its periphery, as can indeed be seen between northern and southern Italy. When Piffer and Lynn (2022) looked at genomic data from that country, they found a north-south gradient in alleles associated with educational attainment. That difference corresponds to historical differences in economic development. By the 18th century, the South had already fallen behind the North; its middle class had remained small and economic relations were still structured by paternalism and familialism (De Rosa 1979).

 

All of that leads to an interesting corollary: the IQ gap used to be smaller between Europeans and sub-Saharan Africans. On the one hand, European mean IQ had probably remained in the low 90s until late medieval times. On the other hand, mean IQ may have been in the upper 80s among those Black African groups that Europeans had first encountered, particularly the Nubians. By the time of Classical Antiquity they had reached a high level of material culture, social complexity and State formation.

 

A smaller IQ gap would be in line with an observation by Jason Malloy. He noted that blacks were often described in the ancient world as having large penises but not as being less intelligent. Indeed, I have found only two Greco-Roman texts in which the writer disparaged Black Africans as being unintelligent. One of them is of doubtful authenticity, and both come from Late Antiquity (Frost 2019b). By then, blacks in the Roman world were increasingly slaves who came from farther within the African interior. Thereafter, a stereotype of low intelligence is regularly attested in Middle Eastern and European sources.

 

 

References

 

Clark, G. (2007). A Farewell to Alms. A Brief Economic History of the World. Princeton University Press: Princeton and Oxford.

 

Clark, G. (2009a). The indicted and the wealthy: surnames, reproductive success, genetic selection and social class in pre-industrial England.  http://www.econ.ucdavis.edu/faculty/gclark/Farewell%20to%20Alms/Clark%20-Surnames.pdf     

 

Clark, G. (2009b). The domestication of man: The social implications of Darwin. ArtefaCTos 2: 64-80. https://www.researchgate.net/publication/277275046_The_Domestication_of_Man_The_Social_Implications_of_Darwin

 

De Rosa, L. (1979). Property Rights, Institutional Change, and Economic Growth in Southern Italy in the XVIIIth and XIXth Centuries. Journal of European Economic History 8(3): 531-551.

 

Frost, P. (2019a). The Original Industrial Revolution. Did Cold Winters Select for Cognitive Ability? Psych 1(1): 166-181. https://doi.org/10.3390/psych1010012   

 

Frost, P. (2019b). Why that stereotype and not the other? Evo and Proud, July 28. https://evoandproud.blogspot.com/2019/07/why-that-stereotype-and-not-other.html

 

Frost, P. (2021). Commentary on Fuerst et al: Do Human Populations Differ in Their Mental Characteristics? Mankind Quarterly 62(2). http://doi.org/10.46469/mq.2021.62.2.9   

 

Fuerst, J., E.O.W. Kirkegaard and D. Piffer. (2021). More research needed: There is a robust causal vs. confounding problem for intelligence-associated polygenic scores in context to admixed American populations. Mankind Quarterly 62(1): 151-185. https://www.researchgate.net/profile/John-Fuerst/publication/354767141_More_Research_Needed_There_is_a_Robust_Causal_vs_Confounding_Problem_for_Intelligence-associated_Polygenic_Scores_in_Context_to_Admixed_American_Populations/links/614bc1dfa595d06017e4c017/More-Research-Needed-There-is-a-Robust-Causal-vs-Confounding-Problem-for-Intelligence-associated-Polygenic-Scores-in-Context-to-Admixed-American-Populations.pdf

 

Lasker, J., B.J. Pesta, J.G.R. Fuerst, and E.O.W. Kirkegaard. (2019). Global Ancestry and Cognitive Ability. Psych 1(1):431-459. https://doi.org/10.3390/psych1010034  

 

Oesterdiekhoff, G.W. (2012). Was pre-modern man a child? The quintessence of the psychometric and developmental approaches. Intelligence 40, 470–478. https://doi.org/10.1016/j.intell.2012.05.005

 

Piffer, D. (2019). Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data. Psych 1(1):55-75. https://doi.org/10.3390/psych1010005

 

Piffer, D., and R. Lynn. (2022). In Italy, North-South Differences in Student Performance Are Mirrored by Differences in Polygenic Scores for Educational Attainment. Mankind Quarterly 62(4), Article 2. https://doi.org/10.46469/mq.2022.62.4.2   

 

Rindermann, H. (2018). Cognitive Capitalism. Human Capital and the Wellbeing of Nations, 1st ed.; Cambridge University Press.

Eppur si muove

 

General intelligence (g) varies with ethnicity, as do genetic variants associated with educational attainment (Lasker et al. 2019, p. 445)

 

 

Bryan Pesta was fired from a tenured university position for a study he coauthored in a peer-reviewed journal. No one actually disputed his findings. It was simply taken for granted that they could not be true.

 

 

Three years ago I contributed a paper to a special issue of Psych. One of the other contributors, Bryan J. Pesta, coauthored a paper on “Global Ancestry and Cognitive Ability.” It was one of several recent studies that had used genetic data to understand how populations differ on average in their capacity for intelligence.

 

Pesta and his coauthors looked at data from an existing neurodevelopment study of 9,421 participants from Philadelphia. A little over half of them were European American, and a third were African American. They had all been genotyped and had all taken a battery of cognitive tests.

 

The study produced several findings:

 

·         Almost 15 IQ points separated the African American participants from the European American participants. About three quarters of the difference was due to general intelligence (g).

·         Among the African Americans, general intelligence correlated with the degree of European admixture.

·         The correlation was modestly reduced, but not eliminated, when controlled for parental education. Controlling for skin color had no effect. Although skin color does correlate with European admixture, it evidently has a less direct relationship to general intelligence. This finding therefore eliminates “colorism” (discrimination in favor of lighter-skinned African Americans) as a possible cause.

·         As much as 20-25% of the difference in general intelligence between the African Americans and the European Americans was explained by genetic variants associated with educational attainment. By comparison, the same variants explain only 11-13% of the variance in educational attainment among individuals.

·         Although these genetic variants predicted general intelligence in both groups, the predictive power for the African Americans was only 20% of the predictive power for the European Americans. This finding is consistent with a growing consensus that the genetic architecture of intelligence is different in the two groups. Because the genetic variants have been identified in Europeans or European Americans, they may contribute less to the capacity for intelligence in people of African descent. In addition, other variants may be found only in African populations and thus remain to be identified.

 

For the above findings, Bryan Pesta would be fired from his tenured position at Cleveland State University. The whole affair is described in The Chronicle of Higher Education. At no point did anyone actually dispute his findings. It was simply taken for granted that they could not be true. And that’s that.

 

Please don’t argue that Bryan Pesta unconsciously looked for data that would provide the findings he wanted. The data had already been collected by another research team for a completely different purpose. So put aside The Mismeasure of Man and tell Stephen Jay Gould to go back to sleep.

 

This story isn’t over. People are curious, and curiosity ends up finding a way—despite the barriers we erect. Below is a screen shot of the paper’s access statistics (Hint: The Chronicle’s article came out on October 13).

 

 

References

 

Lasker, J., B.J. Pesta, J.G.R. Fuerst, and E.O.W. Kirkegaard. (2019). Global Ancestry and Cognitive Ability. Psych 1(1):431-459. https://doi.org/10.3390/psych1010034  

 

Standifer, C. (2022). Racial Pseudoscience on the Faculty. A professor’s research flew under the radar for years. What finally got him fired? The Chronicle of Higher Education. October 13. https://www.chronicle.com/article/racial-pseudoscience-on-the-faculty?cid2=gen_login_refresh&cid=gen_sign_in

The Great Decline

 

Mean polygenic score of Icelanders by year of birth (Kong et al. 2017, Fig. 2)

 

Three polygenic studies have shown that cognitive ability declined among European Americans, British people, and Icelanders during the 20th century. The decline briefly stopped during the postwar baby boom and again with the liberalization of abortion laws.

 

 

How can we measure the genetic component of cognitive ability? For a long time, the only way was to administer an IQ test, but the result would inevitably be influenced by the test-taker’s environment—not only culture and life history but also familiarity with taking tests and answering questions in rapid-fire succession. Yes, twin studies and adoption studies suggest that genetic factors largely explain variation in IQ between individuals. But the same is not necessarily true for variation in IQ between populations. That could be 100% environmental.

 

Recent years have seen the advent of a direct measure of innate cognitive ability: the educational attainment polygenic score. It’s a summation of the predicted effects of genetic variants that together explain 11-13% of the variance in educational attainment among individuals (Lee et al. 2018). It’s especially suited for predicting the mean IQ of a population—the correlation is 98% with the actual mean IQ (Piffer 2019).  Polygenic data predict a mean IQ of about 85 for sub-Saharan Africans, 100 for Europeans, and 105 for East Asians. There is also variation within each of those geographic groups. Among Europeans, predicted IQ varies from 97 for southern Europeans to 102 for Finns and 110 for Ashkenazi Jews. Among sub-Saharan Africans, it seems to be higher among groups who were more advanced during precolonial times, particularly those, like the Igbo, who lived along the Niger and took part in trade between the coast and the interior (Frost 2022).

 

The above predictions should be viewed with some caution. Because the genetic variants have been identified only in people of European descent, the polygenic score is less valid for non-Europeans, particularly those of sub-Saharan African descent. It thus predicts the IQ of African Americans with five times less accuracy than that of European Americans (Lasker et al. 2019).

 

Generational change

 

In addition to predicting differences in mean IQ across space, we can do the same across time. That begs the question: were past generations as intelligent as the latest one? We can answer that question by examining past generations who are still alive. That approach, however, raises the issue of survivorship bias: people who live to an old age are generally smarter than those who do not (Gottfredson and Deary 2004).

 

Beauchamp (2016) deals with this issue point by point when he discusses polygenic data from the Health and Retirement Study (HRS), a longitudinal study of 20,000 Americans shortly before and during retirement:

 

·         The HRS participants are people who have lived to the age of 50; however, about 10% of American women and 15% of American men born in 1940 were already dead by the age of 50.

·         Thus, in Beauchamp’s sample, 85% of the original participants were still alive in 2008, 69% were asked to be genotyped, and 59% consented to be genotyped.

·         Nonetheless, no important differences emerged when he compared the genotyped participants with the total sample. 

 

European Americans

 

Beauchamp found evidence that alleles associated with high educational attainment had declined in frequency among European Americans between the 1931 and 1953 birth cohorts. “[M]y results strongly suggest that genetic variants associated with EA have slowly been selected against among both female and male Americans of European ancestry born between 1931 and 1953.”

 

That decline is attributed to differences in fertility: “individuals with high EA typically have children at a more advanced age, which may further reduce their fitness.”

 

Icelanders

 

The above findings have been replicated by Kong et al. (2017) in their study of Icelanders born since 1910. Although survivorship bias is still a problem, it does not easily explain the decline in cognitive ability between the last two cohorts, i.e., Icelanders born in the 1970s and those born in the 1980s. In that decline, any survivorship bias would be due to deaths of people less than 44 years old, and in most cases less than 36 years old. “The samples studied here were collected between 1998 and 2014, with a majority (68%) ascertained before 2006” (Kong et al, 2017, p. E729).

 

Iceland’s cognitive decline had two “pauses”: one in the 1950s and another in the 1970s. The first pause coincides with the postwar economic boom and a corresponding improvement in the ability of middle class couples to start families early in life. The second pause may reflect the passage in 1975 of Iceland’s abortion law, which, while not allowing abortion on demand, did allow it for cases of rape, mental disability of the mother, and “difficult family situation” (Wikipedia 2022)

 

Kong et al. (2017) concluded that the cognitive decline was due only in part to more intelligent Icelanders staying in school longer and postponing reproduction. In fact, a high educational level, unlike a high polygenic score, was actually associated with somewhat higher fertility among males. A high polygenic score seems to reduce fertility independently of whether one pursues or does not pursue higher education, perhaps because higher intelligence goes hand in hand with greater ability to plan ahead and thus foresee, with trepidation, the costs of raising a family. 

 

British of European descent

 

In a study of British of European origin, using the UK Biobank, Hugh-Jones and Abdellaoui. (2022) found that mean cognitive ability had declined between two successive generations, particularly in lower-income groups. The median birth year was 1950 for the second generation and unknown for the first. The authors also looked at genetic variants that influence non-cognitive traits. In general, the bulk of the population seems to be getting dumber, fatter, and nuttier.

 

The authors nonetheless warn against excessive pessimism:

 

Many people would probably prefer to have high educational attainment, a low risk of ADHD and major depressive disorder, and a low risk of coronary artery disease, but natural selection is pushing against genes associated with these traits. Potentially, this could increase the health burden on modern populations, but that depends on effect sizes.

 

The authors go on to argue that the effect sizes are “small,” although one wonders: smaller than what? They then make the obvious point that generational change can accumulate from one generation to the next: “Although effects on our measured polygenic scores are small even after weighting, individually small disadvantages can cumulate to create larger effects” (Hugh-Jones and Abdellaoui 2022). Beauchamp (2016) makes a similar comment that seems reassuring on first thought, and then not so reassuring on second thought: “natural selection has thus been occurring in that population—albeit at a rate that pales in comparison with the rapid changes that have occurred in recent generations.”

 

Finally, Hugh-Jones and Abdellaoui (2022) point out that their data may suffer from ascertainment bias. For instance, the first generation of their dataset is composed of the parents of the second generation. The dataset thus excludes the childless individuals of the first generation. Were they more intelligent or less intelligent on average than the succeeding generation? Furthermore, participation in the UK Biobank is voluntary. Could that factor also be a source of bias? If so, in what direction?

 

Conclusion

 

As time goes by, intergenerational genetic datasets will become more complete, and the problem of survivorship bias will diminish. Ideally, we should conduct a “genetic census” of each generation, perhaps by collecting a DNA sample from everyone at the time of death. We will thus be able to see how we are evolving.

 

We now have intergenerational polygenic studies from three different Western countries: the U.S., the U.K., and Iceland. In all three cases, the genetic component of cognitive ability declined during the 20th century, with the exception of two pauses: one during the postwar baby boom and the other with the liberalization of access to abortion.

 

If we wish to halt the cognitive decline, we should push for the following measures:

 

·         A return to the protected high-wage economy that prevailed during the postwar era;

·         Free access to abortion, at least for cases of rape, mental disability of either parent, and difficult economic circumstances;

·         Pro-natalist measures to counteract the fear of not having the means to support a family. This fear is particularly strong among people who like to plan and are oriented toward the future.

 

 

References

 

Beauchamp, J.P. (2016). Genetic evidence for natural selection in humans in the contemporary United States. Proceedings of the National Academy of Sciences 113(28): 7774-7779. https://doi.org/10.1073/pnas.1600398113    

 

Frost, P. (2022). Recent cognitive evolution in West Africa: the Niger’s role. Evo and Proud, April 30. https://evoandproud.blogspot.com/2022/04/recent-cognitive-evolution-in-west.html  

 

Gottfredson, L. S., and I.J. Deary. (2004). Intelligence Predicts Health and Longevity, but Why? Current Directions in Psychological Science 13(1): 1–4. https://doi.org/10.1111/j.0963-7214.2004.01301001.x

 

Hugh-Jones, D., and A. Abdellaoui. (2022). Human Capital Mediates Natural Selection in Contemporary Humans. Behavior Genetics. https://doi.org/10.1007/s10519-022-10107-w  

 

Kong, A., M.L. Frigge, G. Thorleifsson, H. Stefansson, A.I. Young, F. Zink, G.A. Jonsdottir, A. Okbay, P. Sulem, G. Masson, D.F. Gudbjartsson, A. Helgason, G. Bjornsdottir, U. Thorsteinsdottir, and K. Stefansson. (2017). Selection against variants in the genome associated with educational attainment. Proceedings of the National Academy of Sciences 114(5): E727-E732. https://doi.org/10.1073/pnas.1612113114   

 

Lasker, J., B.J. Pesta, J.G.R. Fuerst, and E.O.W. Kirkegaard. (2019). Global ancestry and cognitive ability. Psych 1(1). https://doi.org/10.3390/psych1010034    

 

Lee, J. J., Wedow, R., Okbay, A., Kong, E., Maghzian, O., Zacher, et al. (2018). Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nature Genetics 50(8): 1112-1121. https://doi.org/10.1038/s41588-018-0147-3  

 

Piffer, D. (2019). Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data. Psych 1(1): 55-75. https://www.mdpi.com/2624-8611/1/1/5   

 

Wikipedia (2022). Abortion in Iceland. https://en.wikipedia.org/wiki/Abortion_in_Iceland    

 

Comparing an incomparable?

 

Stigmata Siciliana (1964), David McLure (Wikicommons)

 

 

What is the mean IQ of sub-Saharan Africans? There’s no clear answer. Current estimates come from an early stage of the Flynn effect and are also distorted by qualitative differences in cognition. Furthermore, mean IQ differs among African groups.

 

 

 

At present, there is little consensus on the mean IQ of sub-Saharan Africans. Estimates have ranged from a low of 66 to a high of 82 (Lynn 2010; Wicherts et al. 2010). Rindermann (2013) put forward a "best guess" of 75, which is inexplicably much lower than the estimated African American mean of 85. Yes, African Americans are about 20% European by ancestry, but that degree of admixture would not cause a 10-point difference. Malnutrition? That might depress IQ scores in some African countries but not most.

 

Noah Carl (2022) has reopened the debate by inferring mean IQ from harmonized test scores and GDP per capita. Sub-Saharan Africa looks somewhat better on the first measure and somewhat worse on the second. Both measures correlate roughly with mean IQ, but the correlation isn’t strong enough to tell us whether the mean is 62, 75, or 82. Moreover, the first measure suffers from the same problem that plagues IQ tests: Africa is just starting to experience the secular increase in mean IQ that the West experienced during the 20th century, i.e., the Flynn effect. By how much should we increase the estimate of mean African IQ to adjust for Africa being at an earlier stage of the Flynn effect?

 

As for the second measure, GDP per capita, the ability to create wealth is determined not only by cognitive ability but also by other mental traits: future time orientation (also known as time preference), willingness to follow rules and enforce them, feelings of guilt over breaking rules, reluctance to use violence to settle disputes, tendency toward individualism rather than nepotism and familialism, and so on.

 

In a reply to Carl’s article, Emil Kirkegaard (1922) infers mean IQ from the Social Progress Index. But that measure is no less problematic than GDP per capita. Social progress is driven by a basket of mental qualities, of which cognitive ability is only one. Emil himself makes that point:

 

One cannot just impute IQs reliably from non-IQ data in order to get some kind of unbiased estimates of a region's IQ because the regions themselves may under- or overperform on international rankings for whatever reason, [including] legacy of or current communism, nonWEIRDness, low individualism, or any other difference you can imagine.

 

Emil concludes: “There’s no avoiding having to collect more African IQ data.”

 

More data would be nice, but no amount of data will provide us with a mean African IQ that can be usefully compared with the mean IQs of other populations. There are several reasons:

 

·        Again, estimates of African IQ come from an early stage of the Flynn effect. They are not comparable with estimates of IQ that come from a later stage in other populations.

·        The genetic architecture of cognition is not the same. Sub-Saharan Africans seem to have alleles for cognitive ability that do not exist in other populations. To date, such alleles have been identified only in people of European descent.

·       Recent cognitive evolution, particularly in societies near the Niger, has created differences in mean cognitive ability among African groups. It is no more meaningful to talk about a single mean African IQ than it is to talk about a single mean European IQ.

 

Differences in the stage of the Flynn effect

 

IQ data from Western societies are not comparable with IQ data from African societies. The latter are just beginning to experience the rise in mean IQ that took place earlier in the West, specifically the increase of 13.8 points between 1932 and 1978 (Flynn 1984). The Flynn effect seems to be not so much an increase in cognitive ability as an increase in familiarity with the “test paradigm” at school and, more broadly, in society. Flynn (2013) situates the cause in the modernist paradigm: “We freed ourselves from fixation on the concrete and entered a world in which the mass of people began to use logic on abstractions and universalize their moral principles.”

 

Keep in mind that competitive exams began to appear in the West only in the late 19th century, first for entry into the civil service and then more generally for the educational system (Wikpedia 2022). Previously, people entered the civil service through patronage appointments, and education took the form of apprenticeship and imitation of role models. In those days, people were less inclined to formulate questions and look for the answers. The answers were already known, and you had to learn them. In fact, there was a stigma attached to asking too many questions, especially in rapid-fire succession.

 

Differences in the genetic architecture of cognition

 

As a means to estimate cognitive ability, the IQ test is becoming superseded by the educational polygenic score. This measure is based on SNPs that have been shown to be associated with educational attainment. Your polygenic score is higher to the extent that the alleles at those SNPs are associated with higher educational attainment. It is thus a measure of innate cognitive ability. At present, we have identified 1,271 SNPs that are associated with educational attainment and which, together, explain 11-13% of the variance in educational attainment among individuals (Lee et al. 2018). The educational polygenic score has shown good reliability in predicting the IQ of individuals and even better reliability in predicting the mean IQ of populations.

 

Again, we have identified alleles associated with educational attainment only in people of European descent. For this reason, the educational polygenic score is five times worse at predicting the cognitive ability of African Americans (Lasker et al. 2019). The loss of predictive power seems greatest in the domain of language ability, according to two studies:

 

·        Guo et al. (2019, p. 27) found that the educational polygenic score is ten to eighteen times worse at predicting the verbal ability of African Americans, in comparison to White, Asian, and Hispanic White Americans. They attributed this difference to the smaller size of the African American sample, to gene-environment interactions, and to “significantly less than full coverage of African genetic variants related to cognitive ability.”

·        With a sample of school-age African Americans, Rabinowitz et al. (2019) found that the educational polygenic score fails to predict performance on a standardized reading test but does predict pursuit of postsecondary education, getting a criminal record (only among boys), and performance on a standardized math test (only for one of the three cohorts).

 

When modern humans began to spread out of Africa some 60,000 years ago, those left behind began to pursue their own trajectory of cognitive evolution. The evolutionary change seems to have been greatest in the domain of language, i.e., the ability to express oneself in speech and writing. Polygenic scores cannot predict innate reading ability because too many of the relevant alleles are exclusive to the African gene pool and remain unidentified. Other relevant alleles may simply be more important or less important in other gene pools.

 

Although the educational polygenic score is based on alleles identified in Europeans, it can still be used for rough predictions of cognitive ability among people of African descent. Lasker et al. (2019, pp. 444-445) were able to increase its predictive power for African Americans by almost a factor of three, i.e., an increase from 20% to 54% of its predictive power for European Americans. They achieved this improvement by using alleles from a much smaller subset of SNPs that are less sensitive to decay of linkage disequilibrium.

 

Differences among African groups in the trajectory of cognitive evolution

 

Within the larger African trajectory of cognitive evolution, various African populations have pursued their own sub-trajectories. This has been especially true for populations in West Africa over the past millennium and a half. Their educational polygenic scores vary as you go from west to east, being lowest among the Mende (Sierra Leone) and progressively higher among Gambians, the Esan (Nigeria), and the Yoruba (Nigeria). The Yoruba have almost the same educational polygenic score as that of African Americans, who nonetheless are about 20% admixed with Europeans (Piffer 2021, see Figure 7).

 

Before European contact, West African societies were more complex in the north and the east, i.e., in the Sahel and the Nigerian forest. Those areas saw the creation of towns, the formation of states, and an increasing use of metallurgy and luxury goods from the fourth century onward. The increase in social complexity seems to have been driven by the development of trade along the Niger, which served as the main trading route between the coast and the interior (Frost 2022).

 

In West Africa, cognitive evolution seems to have gone the farthest among the Igbo of the Niger delta. We have no educational polygenic data on them, but their record of academic achievement in Nigeria, the UK, and elsewhere indicates an unusually high level of cognitive ability (Chisala 2015).

 

Conclusion

 

We should get more data, while recognizing the limits of what the data may tell us. IQ tests will always be problematic, and future research should focus on educational polygenic scores. In particular, we need to identify relevant alleles in non-European populations. Some of those alleles may be population-specific, and others may be universal but more important in some populations than in others. Finally, Africa is not a monolith. Different African populations have pursued different trajectories of cognitive evolution.

 

 

References

 

Carl, N. (2022). How useful are national IQs? Noah’s Newsletter, July 13. https://noahcarl.substack.com/p/how-useful-are-national-iqs  

 

Chisala, C. (2015). The IQ gap is no longer a black and white issue. The Unz Review, June 25.

http://www.unz.com/article/the-iq-gap-is-no-longer-a-black-and-white-issue/   

 

Flynn, J.R. (1984). The mean IQ of Americans: Massive gains 1932–1978. Psychological Bulletin 95(1):29–51. https://psycnet.apa.org/doi/10.1037/0033-2909.95.1.29  

 

Flynn, J.R. (2013). The “Flynn Effect” and Flynn’s paradox. Intelligence 41: 851-857. http://dx.doi.org/10.1016%2Fj.intell.2013.06.014   

 

Frost, P. (2021). Polygenic scores and Black Americans. Evo and Proud, April 27. https://evoandproud.blogspot.com/2021/04/polygenic-scores-and-black-americans.html   

 

Frost, P. (2022). Recent cognitive evolution in West Africa: the Niger’s role. Evo and Proud, April 30. https://evoandproud.blogspot.com/2022/04/recent-cognitive-evolution-in-west.html  

 

Guo, G., Lin, M.J., and K.M. Harris. (2019). Socioeconomic and Genomic Roots of Verbal Ability. bioRxiv, 544411. https://www.biorxiv.org/content/10.1101/544411v1  

 

Kirkegaard, E.O.W. (2022). African IQs without African IQs: it’s complicated. Just Emil Kirkegaard Things. August 7. https://kirkegaard.substack.com/p/african-iqs-without-african-iqs-its?utm_source=substack&utm_medium=email  

 

Lasker, J., B.J. Pesta, J.G.R. Fuerst, and E.O.W. Kirkegaard. (2019). Global ancestry and cognitive ability. Psych 1(1). https://doi.org/10.3390/psych1010034  

 

Lee, J. J., Wedow, R., Okbay, A., Kong, E., Maghzian, O., Zacher, et al. (2018). Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nature Genetics 50(8): 1112-1121. https://doi.org/10.1038/s41588-018-0147-3

 

Lynn, R. (2010). The average IQ of sub-Saharan Africans assessed by the Progressive Matrices: A reply to Wicherts, Dolan, Carlson & van der Maas. Learning and Individual Differences 20(3): 152-154. https://doi.org/10.1016/j.lindif.2010.03.009   

 

Piffer, D. (2021). Divergent selection on height and cognitive ability: evidence from Fst and polygenic scores. OpenPsych. https://openpsych.net/files/submissions/14_Divergent_selection_on_height_and_cognitive_ability_evidence_from_Fst_and_13c3ICJ.pdf     

 

Rabinowitz, J.A., S.I.C. Kuo, W. Felder, R.J. Musci, A. Bettencourt, K. Benke, ... and A. Kouzis. (2019). Associations between an educational attainment polygenic score with educational attainment in an African American sample. Genes, Brain and Behavior, e12558. https://doi.org/10.1111/gbb.12558   

 

Rindermann, H. (2013). African cognitive ability: Research, results, divergences and recommendations. Personality and Individual Differences 55: 229-233. https://doi.org/10.1016/j.paid.2012.06.022   

 

Wicherts, J.M., C.V. Dolan, and H.L.J. van der Maas. (2010). A systematic literature review of the average IQ of sub-Saharan Africans. Intelligence 38: 1-20. https://doi.org/10.1016/j.intell.2009.05.002   

 

Wikipedia. (2022). Imperial examination – Influence - West. https://en.wikipedia.org/wiki/Imperial_examination#West  

Cognitive evolution on the Italian Peninsula

 

A recent polygenic study has shown that mean cognitive ability is higher in the North of Italy than in the South. Cognitive evolution seems to have gone the farthest in the Northeast, perhaps because the Northwest earlier went through the Industrial Revolution, which severed reproductive success from economic success.

 

 

 

As a country, Italy came into existence only a century and a half ago. Regional differences are still strong, particularly between the North and the South. The “Southern question” is usually said to date from the unification of Italy in the 19th century:

 

In the decades following the unification of Italy, the northern regions of the country, Lombardy, Piedmont and Liguria in particular, began a process of industrialization and economic development while the southern regions remained behind. At the time of the unification of the country, there was a shortage of entrepreneurs in the south, with landowners who were often absent from their farms as they lived permanently in the city, leaving the management of their funds to managers, who were not encouraged by the owners to make the agricultural estates to the maximum. Landowners invested not in agricultural equipment, but in such things as low-risk state bonds. (Wikipedia 2022a)

 

De Rosa (1979) argues that the South had already fallen behind the North by the 18th century. At that time, its middle class was small, and economic relations were still structured by paternalism and familialism. One could go back even farther, to the Renaissance or even the late Middle Ages, to identify the moment when northern Italy, and Western Europe in general, embarked on sustained economic growth and thus pulled ahead of the rest of the world.

 

That sustained economic growth brought sustained demographic growth, particularly of the middle class. Gregory Clark found that the English middle class expanded steadily from the twelfth century onward, its descendants not only growing in number but also replacing the lower classes through downward mobility. By the 1800s, its lineages accounted for most of the English population. That demographic change coincided with mental and behavioral changes: higher cognitive ability, lower time preference, and a lower threshold for violent behavior. In a word, the English became more middle-class in character. “Thrift, prudence, negotiation, and hard work were becoming values for communities that previously had been spendthrift, impulsive, violent, and leisure loving” (Clark 2007, p. 166).

 

Elsewhere in Western Europe, the middle class similarly expanded during late medieval and early modern times. The result would be a growing contrast between regions that had participated in this economic and demographic change and those that had not, such as southern Italy. The contrast can be seen not only on purely economic measures but also on mental ones, like the INVALSI standardized test—an annual test of skills in Italian schools. It is divided into two sections: Italian language skills and Math skills. On both tests, northern Italian students do better than southern Italian students, the difference being a little over half a standard deviation:

 

Yes, the North-South gap in academic achievement could have a purely environmental cause—and this is a recurring problem when we try to tease apart genetic and cultural evolution. If economic development is held back by a culture of poverty, that same culture may discourage students from trying to do better at school. Those students may also have less access to proper nutrition, medical care, libraries, and so on.

 

Polygenic scores for cognitive ability

 

That is why there is so much interest in measures of innate cognitive ability. The most promising one is the polygenic score (PGS)—the summation of alleles (genetic variants) that have been associated with cognitive ability, as measured by educational attainment.  At present, we have identified enough of these alleles to explain 11-13% of the overall variation in cognitive ability (Lee et al. 2018).

 

Yes, those alleles are just a sample of the total number, but why would they be an unrepresentative sample? More to the point: why would PGS data show certain geographic patterns and not a lot of random noise? The mean PGS does indeed differ geographically among human populations. It is highest in Eurasia, with East Asians, Ashkenazi Jews, and Finns having the highest scores. That geographic pattern is in line with IQ data (Piffer 2019).

 

Polygenic scores on the Italian Peninsula

 

In a recent study, Piffer and Lynn (2022) have found regional differences in Italy for alleles associated with educational attainment. They used two datasets: one encompassing 129 Italian individuals and the other 947. All of these individuals had all four grandparents born in the same part of Italy (this requirement was imposed to eliminate the effects of recent interregional migration). When the authors grouped the data into three large regions—North, Central, and South—they found “a clear north-south gradient, with central Italians occupying an intermediate position.” There was more overlap between central and southern Italians than between central and northern Italians.

 

The datasets were too small to show genetic differences within each of the three large regions. If we go back to the INVALSI data, we see that academic achievement is much stronger in the North-Northeast (Lombardia, Trentino, Veneto, Friuli) than in the Northwest (Valle d’Aosta, Liguria).

 

At first thought, that geographic pattern may seem counter-intuitive. In northern Italy, industrialization began in the northwest and came later to the northeast: “the diffusion of industrialisation that characterised the northwestern area of the country largely excluded Venetia and, especially, the South” (Wikipedia 2022b). If economic development had driven cognitive evolution on the Italian Peninsula, why would this evolution have gone farther in the northeast? Why would it be negatively associated with industrialization?

 

Because the Industrial Revolution put a stop to cognitive evolution. It severed the link between economic success and reproductive success. Previously, businesses were family-run, and the family provided the workforce. Successful business owners were incentivized to have larger families, and their children would have the means to marry at a younger age. Then, in the late 19th century, that stage of economic development began to give way to industrial capitalism. Financial success no longer translated into early marriage and large families who could help with the work. If more workers were needed, they would simply be hired. Business owners now tended to have smaller families because of the high maintenance costs of middle-class children (Canlorbe and Frost 2020; Frost 2018).

 

Cognitive evolution thus ended earlier in the Northwest of Italy than in the Northeast. By the same token, interregional migration has had more time to erode the cognitive advantage that evolved in the Northwest. Yes, the datasets were limited to people who had all four grandparents born in the region, but, for most people, that limitation would not eliminate the effects of interregional migration before the mid-20th century.

 

 

References

 

Canlorbe, G., and P. Frost (2020). Why are human groups so different? American Renaissance, March 20. https://www.amren.com/features/2020/03/why-are-human-groups-so-different/  

 

Clark, G. (2007). A Farewell to Alms. A Brief Economic History of the World, 1st ed. Princeton University Press: Princeton, NJ, USA.

 

De Rosa, L. (1979). Property Rights, Institutional Change, and Economic Growth in Southern Italy in the XVIIIth and XIXth Centuries. Journal of European Economic History 8(3): 531-551.

 

Frost, P. (2018). Rise of the West. Part II. Evo and Proud, December 27

https://evoandproud.blogspot.com/2018/12/rise-of-west-part-ii.html  

 

Lee, J. J., Wedow, R., Okbay, A., Kong, E., Maghzian, O., Zacher, et al. (2018). Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nature Genetics 50(8): 1112-1121. https://doi.org/10.1038/s41588-018-0147-3

 

Piffer, D. (2019). Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data. Psych 1(1): 55-75. https://doi.org/10.3390/psych1010005    

 

Piffer, D., & Lynn, R. (2022). In Italy, North-South Differences in Student Performance Are Mirrored by Differences in Polygenic Scores for Educational Attainment. Mankind Quarterly 62(4), Article 2. https://doi.org/10.46469/mq.2022.62.4.2  

 

Wikipedia (2022a). Economy of Italy – Southern Question

https://en.wikipedia.org/wiki/Economy_of_Italy#Southern_question  

 

Wikipedia (2022b). Economic history of Italy.

https://en.wikipedia.org/wiki/Economic_history_of_Italy