Tag Archives: Richard Lynn

Northern American IQ: circa 1937 to circa 2014 (2nd edition)

28 Saturday Mar 2020

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The following article is an updated revision of an article I published in August 2019 about how 21st century Northern Americans score on an IQ test normed before the second World War. The reason for the update is that in December 2019, the sample size of my study increased by 13% (from n = 15 to n = 17). I had originally hoped to collect more data before publishing an update but with the uncertainty surrounding the coronavirus crisis, it’s unclear when that will be.

The Flynn effect, popularized by James Flynn, refers to the fact that IQ tests supposedly get easier with time. Although by definition the average IQ of American or British (white) people is always 100, the older the IQ test, the easier it is to score 100. Thus to keep the average at 100, tests like the Wechsler must be renormed every 10 years or so, otherwise the average IQ would increase by about 3 points per decade.

Although scholars continue to debate whether the Flynn effect reflects a genuine increase in intelligence (perhaps caused by prenatal nutrition or mental stimulation) or just greater test sophistication caused by modernity, there’s been remarkably little skepticism about the existence of the Flynn effect itself.

Malcolm Gladwell writes:

If an American born in the nineteen-thirties has an I.Q. of 100, the Flynn effect says that his children will have I.Q.s of 108, and his grandchildren I.Q.s of close to 120—more than a standard deviation higher. If we work in the opposite direction, the typical teen-ager of today, with an I.Q. of 100, would have had grandparents with average I.Q.s of 82—seemingly below the threshold necessary to graduate from high school. And, if we go back even farther, the Flynn effect puts the average I.Q.s of the schoolchildren of 1900 at around 70, which is to suggest, bizarrely, that a century ago the United States was populated largely by people who today would be considered mentally retarded.

While few people believe our grandparents were genuinely mentally retarded, it’s taken for granted that they would have scored in the mentally retarded range by today’s standards.

But is this true? I began having doubts over a decade ago when I examined the items on the first Wechsler intelligence scale ever made: the ancient WBI (Wechsler Bellevue intelligence scale). Meticulously normed on New Yorkers in the 1930s, this test remains far and away the most comprehensive look we have at early 20th century white Northern American intelligence, and while some of the subtests looked easy by today’s standards, others, especially vocabulary, looked harder.

The Kaufman effect

What also struck me was how little instruction, probing or coaching people got when taking the ancient WBI, compared to its modern descendant the WAIS-IV. This matters a lot because the way the Flynn effect is calculated on the Wechsler is by giving a new sample of people both the newest Wechsler and its immediate predecessor, in random order to cancel out practice effects, and then seeing which version they score higher on. If they average 3 points lower on the WAIS-IV normed in 2006 than on the WAIS-III normed in 1995, it’s assumed IQ increased by 3 points in 11 years.

The problem with this method (as Alan Kaufman may have discovered before me) is that the subset of the sample that took the newer version first has a huge advantage on the older version compared to the norming sample of the older test (over and above the practice effect which is controlled for), because the norming sample of the older test was never given coaching and probing.

Statistical artifact

A Promethean once said maybe the Flynn effect is just a statistical artifact of some kind. He never told me what he meant, but it got me thinking:

One problem with how the Flynn Effect is calculated on the Wechsler is that it’s assumed that gains over time can be added. For example it’s assumed that you can add the supposed 7.8 IQ gain from WAIS normings 1953.5 -1978 to the 4.2 IQ gain from normings 1978 – 1995 to the 3.7 IQ gain from normings 1995-2006, for a grand total of 15.7 IQ points from normings 1953.5 – 2006.

This would make sense if he were talking about an absolute scale like height, but is problematic when talking about a sliding scale like IQ. For example, suppose the raw number of questions correctly answered in 1953.5 was 20 with an SD of 2. By 1953.5 standards, 20 = IQ 100 and every 2 points = 15 IQ points above or below 100. Now suppose in 1978, people averaged 22 with an SD of 1. That’s a gain of 15 IQ points by 1953.5 standards. Now suppose in 1995 people average 23 with an SD of 2. That’s a gain of 15 IQ points by 1978 standards. Adding the two gains together implies a 30 point gain from 1953.5 to 1995, but by both 1953 and 1993 standards, the difference is only 23 points.

Changing content

Another problem with studying the Flynn effect is the content of tests like the Wechsler is constantly changing. This is especially problematic when studying long-term trends in general knowledge and vocabulary. If words that are obscure in the 1950s become popular in the 1970s, then people in the 1970s will score high on the 1950s vocabulary test. Meanwhile the 1970s vocabulary test may contain words that don’t become popular until the 1990s, Thus adding the vocabulary gains from the 1950s to the 1970s to the gains from the 1970s to the 1990s, might give the false impression that people in the 1990s will do especially well on a 1950s vocabulary test, when in reality, many words from the 1950s may have peaked in the 1970s and are even more obscure in the 1990s than they were in the 1950s.

An ambitious study

Given the Kaufman effect, the statistical artifact, and changing content, I realized the only way to truly understand the Flynn effect is to take the oldest quality IQ test I could find and replicate its original norming on a modern sample.

In 2008 I made it my mission to replicate Wechsler’s 1935-1938 norming of the very first Wechsler scale. Ideally I should have flown to New York where Wechsler had normed his original scale, but if Wechsler could use white New Yorkers as representative of all of white America (WWI IQ tests showed white New Yorkers matched the national white average), I could use white Ontarians as representative of all of white Northern America (indeed white Americans and white Canadians have virtually the same IQs). The target age group was 20-34 because this was the reference age group Wechsler had used to norm his subtests.

It took over a decade but I was gradually able to arrange for 17 randomly selected white young adults to take the one hour test. They were non-staff recruited from about half a dozen fast food/ coffeehouse locations in lower to upper middle class urban and suburban Ontario. The final sample ranged in education from 9.5 years (early high school dropout) to 18 years (Masters Degree in Engineering from one of Canada’s top universities). The mean self-reported education level was 12.9 years (SD = 2.12) suggesting that despite the lack of female participants, the sample was fairly representative (the average Canadian over 25 has about 13 years of schooling); in cases where those below the age of 25 were in the process of finishing a degree, they were credited as having it.

Testing conditions were not optimum (environments were sometimes noisy, at least one person had a few beers before testing; another was literally falling asleep during the test) and 17 people is way to small a sample to draw statistically significant conclusions about 11 different subtests. One man with a conspicuously low score was removed from the sample after he stated that he had years ago suffered a stroke.

Nonetheless, the below table shows how whites tested in 2008 to 2019 compared to Wechsler’s 1935-1938 sample, with the last column showing the expected scores of the 21st century sample, extrapolating gains James Flynn calculated from 1953.5 to 2006 (see page 240 of his book Are We Getting SMARTER?) to the current study: circa 1937 to circa 2013.5.

Note: the 11 subtests were scaled to have a mean of 10 and an SD of 3 in the original young adult norming sample, while the verbal, performance and full-scale IQs were scaled to have a mean of 100 and an SD of 15. Note also that vocabulary is alternate test, not used to calculate either verbal or full-scale IQ on the WBI. One third of my sample did not take Digit Symbol so for these, Performance and full-scale IQs were calculated via prorating.

Test:Nationally representative sample of young white adults (NY, 1935 to 1938)Randomish sample of young white adults (2008 to 2019, ON, Canada)Expected WBI scores in 2008-2019 based on Flynn’s calculated rate of increase
Information (general knowledge test)10 (SD 3)8.41 ( SD 2.55)12.3
Similarites (verbal abstract reasoning)10 (SD 3)13.35 (SD 2.91)15.54
Arithmetic (mental math)10 (SD 3)9.18 (SD 4.34)(this subtest contained a unit conversion item that seemed biased against Canadians so for those who advanced far enough to fail this item, scores were prorated; had they not been the mean would have been 7.53 (SD 3.54))11.02
Vocabulary10 (SD 3)9 (SD 2.5)14.95
Comprehension (Common sense & social judgement)10 (SD 3)9.47(SD 2.93)13.93
Digit Span (attention & rote memory)10 (SD 3)9.71 (SD 2.63)11.46 
Picture Completion (visual alertness)10 (SD 3)10.71 (SD 3.1)14.52
Picture Arrangement (social interpretation)10 (SD 3)10.24 (SD 2.73)13.35
Block Design (spatial organization)10 (SD 3)13.12 (SD 3.31)12.91
Object Assembly (spatial integration)10 (SD 3)11.82 (SD 1.89)14.06
Digit Symbol (Rapid eye-hand coordination)10 (SD 3)11.12 (SD 2.82)(note: only 12 of the 17 subjects took this subtest)14.66
Verbal IQ100 (SD 15)103.8 (SD 14.73)
Performance IQ100 (SD 15)109.3 (SD 12.11)
Full-scale IQ100 (SD 15)106.9 (SD 13.63)122

Conclusion

The Flynn effect is dramatically smaller than we’ve been led to believe at least on tests of specific information that may become obscure over generations. By contrast Similarities (abstract reasoning) and Block Design (spatial analysis) have indeed increased by amounts comparable with Flynn’s research. These two abilities may conspire to explain why some of the largest Flynn effects have been claimed on the Raven Progress Matrices, an abstract reasoning test using a spatial medium.

It’s unclear if these are nutritional gains caused by increasing brain size, neuroplastic gains caused by cultural stimulation, or mere teaching to the test caused by schooling, computers and brain games.

Lynn (1990) argued the Flynn effect was caused by nutrition, citing a twin study proving nutrition gains are more pronounced on Performance IQ (consistent with the Flynn effect). Research on identical twins (where one twin gets better prenatal nutrition than the other) has shown that by age 13, the well nourished twin exceeds his less nourished counterpart by about 0.5 SD on both head circumference and Performance IQ, but not at all on verbal IQ. Thus it’s interesting that 21st century young Northern American men today exceed their WWII counterparts by about 0.5 SD on both head circumference (22.61″ vs 22.3″) and Performance IQ (109 vs about 100).

One possibility is that Performance IQ gains are entirely caused by improvements in the biological environment (prenatal health and nutrition), while verbal IQ gains are entirely caused by cultural advances (i.e. education); though somewhat negated by knowledge obsolescence.

Did cold winters select for higher IQ? A reply to W. Buckner

11 Wednesday Mar 2020

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Cold Winter Theory (CWT) is the theory that population differences in IQ are largely explained by the ancestral climates that the peoples evolved in, with colder climates selecting for higher IQs because of the difficulty figuring out how to build warm shelters, make warm clothes, create fire, get food etc. Modern CWT can be credited to Richard Lynn, though the idea is so intuitive that it was independently inferred by multiple historical thinkers throughout the centuries.

Now if you don’t believe population IQ differences are genetic in origin, then you don’t need an evolutionary theory like CWT to explain the correlation between a population’s ancestral climate and their mean IQ; in theory it might be explained by non-genetic factors like parasite load.

But if you do believe they’re genetic, CWT is the obvious cause: Hominoids have spent 25 million years adapting to the tropics so these may not require as much novel problem solving as the arctic, which we only encountered in the last 40,000 years. Among extant hunter-gatherers, the higher the latitude, the more diverse and complex their tool kit. There’s a reason people travel South for vacation and take vacation in the summer and why many camp grounds close for the winter. It seems cold weather is generally more challenging than warm weather.

Nonetheless I’ve been alerted to yet another attempt to debunk CWT, this time by W. Buckner on a blog called TRADITIONS OF CONFLICT (hat-tip to MeLo & RR). Buckner makes three main arguments against CWT.

Argument 1: Climate can’t explain the low IQ of Bushmen because the Kalahari is sometimes cold.

Counterargument

While it’s true that temperatures can sink as low as 0 °C in the Kalahari desert, this is nothing compared to the lows of -30°C in Ukraine, -52°C in Kazakhstan, and -68°C reached in Russia; three countries that makeup the Pontic-Caspian steppe, the homeland of the Indo-Europeans, far and away the most successful language group on the planet, giving rise to nearly half of the World’s population. With their wits perhaps sharpened by millennia of surviving extreme cold, they domesticated the horse and used them to brilliantly exploit the wheel, allowing their chariots to conquer almost everyone from Europe to India in record time.

Argument 2: Cold climates don’t require more intelligence to hunt because tropical people hunt too.

CWT claims that because plant foods are scarce in cold, high latitude places, people needed to be smart enough to cooperatively and strategically hunt large game, while tropical peoples could mindlessly pick berries all day. Buckner debunks this claim by noting that hunter-gatherers of all latitudes depend roughly equally on hunted animals for subsistence.

Counterargument

While Buckner might be correct that today, even tropical hunter-gathers depend as much on hunted animals as their Northern counterparts (at least land-animals, Northern hunter-gatherers do more fishing); it was likely untrue in the Paleolithic when population differences were evolving.

Smithsonian Magazine writes:

Living in Eurasia 300,000 to 30,000 years ago…in places like the Polar Urals and southern Siberia—not bountiful in the best of times, and certainly not during ice ages. In the heart of a tundra winter, with no fruits and veggies to be found, animal meat—made of fat and protein—was likely the only energy source.

Further evidence that cold climate Paleolithic peoples were more hunting dependent than their tropical counterparts is the fact that the former likely drove the mammoth to extinction, while the tropical dwelling elephant remains extant.

Argument 3: cold climates don’t require more intelligence to make clothes because tropical tribes can make clothes too.

Part of CWT is that the need for warm clothing as humans migrated North selected for high intelligence because those lacking the cognitive ability to make such clothes quickly froze to death (or their babies did) leaving those with high IQ DNA as the survivors.

To counter this point, Buckner mentions the elaborate costumes donned by the Bororo hunter-gatherers of Mato Grasso, Brazil during ceremonies, to prove that tropical people evolved just as much tailoring talent.

Anthropologist Vincent Petrullo is quoted:

The dancer was painted red with urucum and down pasted on his breast. His face was also smeared with urucum. Around his arms were fastened armlets made from strips of burity palm leaf, and his face was covered with a mask made of woman’s hair. The foreskin of the penis was tied with a narrow strip of burity palm leaf, for these men under their tattered European clothing still carry this string. A skirt of palm leaf strips was worn, and a jaguar robe was thrown over his shoulders. The skins of practically every speeies of snake to be found in the pantanal hung from his head down his back over the jaguar robe, which was worn with the fur on the ontside. The inner surface of the hide was painted with geometrie patterns, in red and black, but no one could explain the symbolism. A magnificent headdress consisting of many pieces, and containing feathers of many birds of the pantanal completed the costume with the addition of deerhoof rattles worn on the right ankle.

Bororo ceremony from Lowie (1963)

Counterargument

There are three problems with Buckner’s thesis:

Firstly, although the Bororo currently live in the tropics, they are descended from cold adapted people who crossed the Beringia land bridge from Siberia to present-day Alaska during the Ice Age, and then spread southward throughout the Americas over the following generations. Their tailoring skills may have evolved during those ancestral cold journeys.

Secondly, just because some members of the Bororo have elaborate tailoring skills does not mean these people on average have the tailoring skills of high lattitidue hunter-gatherers. The existence of a few talented tropical tailors no more debunks the tailoring supremacy of high latitude people than the existence of a few really tall women debunks the male height advantage.

Lastly, although the Bororo costume is elaborate, it mostly just consists of wearing many skins on top of one another and attaching lots of things to one’s body. While this is impressive, it is nowhere near the proficiency of making body hugging clothes that cling to one snugly during the fierce winter. It reminds me a bit of cold nghts where I throw more and more blankets on myself to feel warm. This never works as well as putting on a pair of tightly knit jogging pants and a figure hugging sweater.

For all their pomp and circumstance, one dressed only in ceremonial Bororo costume could expect frostbite in less than 5 minutes during ice age winter Russia. Clearly this is nowhere near solving the problem of warm clothing, and that’s because it makes no use of one of the most revolutionary inventions of all time.

According to journalist Jacob Pagano  “…researchers found that humans developed eyed sewing needles in what is now Siberia and China as early as 45,000 years ago.” 

So crucial were eyed sewing needles that they are credited with allowing our species to out-survive the Neanderthals. A 2010 article in the guardian describes archaeologist Brian Fagan’s view:

While Neanderthals shivered in rags in winter, humans used vegetable fibres and needles – created by using stone awls – to make close-fitting, layered clothing and parkas: the survival of the snuggest, in short..

Of course no one is suggesting that cold climate was the only cause of population IQ gaps (it certainly doesn’t explain the high IQs of Ashkenazi Jews who largely descend from the warm Middle East). But it may help explain the more ancient differences between macro-level populations like North East Asians, West Eurasians and those from the tropics. I find it interesting to note that IQ tests involving spatial ability show larger gaps between humans from warm and cold regions than tests involving verbal skill. This is the opposite of what a culture bias explanation would predict, but is consistent with CWT since natural selection may have favored spatial ability in the cold for sewing, building shelters, making fires and hunting etc.

Estimating the IQs of 39 countries (new data from 2015)

27 Monday Jan 2020

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In 2002 Richard Lynn and Tatu Vanhanen’s book IQ and Wealth of Nations estimated the IQs of 185 countries. Critics accused them of cherry picking sources, using unrepresentative samples, comparing and combining samples tested on wildly different tests taken decades apart, and daring to think IQ could be measured cross-culturally. And yet despite nearly two decades of opprobrium, those national IQs remain a landmark, cited in countless peer reviewed articles and repeatedly revised.

One way Lynn has validated his numbers is by showing their high correlation with international exams like Programme for International Student Assessment (PISA). Another independent data-set against which Lynn’s numbers can be tested (assuming he already hasn’t done so) is the IEA‘s Trends in International Mathematics and Science Study (TIMSS). Ostensibly an achievement test, the math section resembles an IQ test, and the test is scored so that most countries average between 400 and 600.

Sample items:

Source
Source

Using the score distribution of UK students as a reference group (see technical note below), I converted the scores from 39 countries to IQ equivalents. My source for the TIMMS scores is exhibit 1.2 in this report.

 
Country TIMMS score (8th grade math; 2015) IQ equivalent
Singapore 621 118
Korea, Rep. of, 606 116
Chinese Taipei 599 114
Hong Kong SAR  594 113
Japan 586 112
Russian Federation 538 103
Kazakhstan 528 102
Canada 527 101
Ireland 523 101
United States 518 100
England 518 100
Slovenia 516 99
Hungary 514 99
Norway 512 99
Lithuania 511 98
Israel 511 98
Australia 505 97
Sweden 501 97
Italy 494 95
Malta 494 95
New Zealand 493 95
Malaysia 465 90
United Arab Emirates 465 90
Turkey 458 89
Bahrain 454 88
Georgia 453 88
Lebanon 442 86
Qatar 437 85
Iran, Islamic Rep. of 436 85
Thailand 431 84
Chile 427 83
Oman 403 79
Kuwait 392 77
Egypt  392 77
Botswana 391 77
Jordan  386 76
Morocco 384 76
South Africa 372 73
Saudi Arabia 368 73

Consistent with Lynn’s hierarchy, we find that East Asian countries cluster around the top (Japan IQ 112 to Korea, Repub of, IQ 116), followed by white majority countries (New Zealand IQ 95 to Russian federation IQ 103), followed by Dark Caucasoid countries (Saudi Arabia IQ 73 to United Arab Emirates IQ 90) and lastly sub-Saharan countries (South Africa IQ 73 to Botswana IQ 77). And while Lynn’s data was ridiculed for declaring entire countries “mentally retarded”, it’s perhaps a sign of higher quality data that no country in this data-set averaged below IQ 70 (though most of the poorest countries chose not to participate).

Technical note

On page 95 of the report, we’re told that only 10% of England’s 8th graders could score 625+, 36% could score 550+, 69% could score 475+, and 93% could score 400+. Subtracting these percentages from 100 gives the following percentiles: 90, 64, 31, and 7 which can be converted to the following IQs: 119, 105, 93, and 78. Now that we have the IQ equivalents of four TIMMS scores, we can make a linear equation converting TIMMS to IQ which is IQ = 0.18(TIMMS score) + 6.5:

Exclusive interview with genomic researcher Davide Piffer

19 Sunday Jan 2020

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I am extremely honored that Davide Piffer (who has a blog) was kind enough to give our community an exclusive interview. While the leading geneticists in academia have explained only about 10% of the variance in IQ (or its proxy education) at the individual level, Piffer working on his own has reported near perfect correlations between the mean IQs of entire ethnic groups and their polygenic scores, making him a rock star in the HBD community. Virtually no one else on the planet is doing this kind of cutting edge research (at least not publicly).

In retrospect it makes perfect sense that aggregated data should correlate much better than individual level data. Imagine you visited every country in Eurasia and asked only the first person you met in each country their height. Such a small sample size (n = 1) from each country would tell you nothing about which individual country was taller than which, but if you averaged all the heights from the European countries and compared them to the average heights from the Asian countries, you’d learn a lot about which continent was taller. That’s because the small sample size at the level of individual countries is multiplied by the large sample of countries in each continent.

It’s the same with genomically predicting IQ. The small sample of single nucleotide polymorphisms (SNPs) sampled in each individual is multiplied by the large number of individuals sampled in each ethnic group, so while individual predictions are weak, group predictions are strong because individual error cancels out in the aggregate.

Below is my exclusive interview with Piffer. The interview has been lightly edited to remove typos and other mistakes. I began by asking him about table 5 in a 2019 paper he wrote. My statements are in red, while Davide’s are in blue.

Table 5 from the paper Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data

PP: I’m very impressed by your work. But the correlation between PG score & mean IQ is so high in table 5 of Piffer (2019) that it seems too perfect. What would you say to skeptics who think you cherry-picked SNPs or manipulated your formulas to get such perfect results?

DP: Thanks. I didn’t cherry pick SNPs. I used the polygenic score provided by Lee et al and you can see that different PGS construction methods lead to same results… I used EA, EA Mtag, etc, weighted and unweighted..they all give same results. Also my paper replicates my previous findings and what I had predicted from theory years ago. The IQs aren’t cherry picked either because I used the same as I used in previous papers to avoid post hoc results.

PP: In table 1 of Piffer (2019), Peruvians & Colombians seem to have higher polygenic scores than the black populations, yet in Figure 11, Africa scores higher than the Americas. So who has higher polygenic scores: sub-Saharan Africans or Amerindians?

top part of table 1 from the paper Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data
rest of table 1 from the paper Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data
Figure 11 from the paper Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data

DP: Peruvian and Colombian aren’t pure. They are substantially mixed with Europeans. The groups in figure 11 are natives, so they better reflect the unadmixed population. Also the latter are from low coverage genomes with fewer markers so less reliable. I am working on a high coverage version of same datasets but it will take a while due to my limited funds.

Do you have some basic experience in bioinformatics? I am just looking for someone who could run the code on their laptop because it’s taking me a week to impute each chromosome. So I need to run it on multiple computers. But hey no bother…I will do it myself, it will just take it longer.

PP: No sadly I do not have experience with bioinformatics. But I can ask my blog & twitter readers if anyone has such experience and is willing to volunteer their time.

On table 5 of Piffer (2019) the African American PGS (GWAS sig) is 1.836 lower than the NW European PGS. But since African Americans are only 76% non-white (Bryc et al. 2015), can we roughly infer that un-mixed blacks would be 1.836/0.76 = 2.416 below NW Europeans, giving them a PGS score of 46.834?

DP: yes…also you have unmixed native Africans in the other tables. Kenyans, Yoruba, Mende Sierra Leone, etc

PP: In table 5 Latinos have a PGS (GWAS sig.) of 48.654. Do you think this could be used to estimate the PGS of unmixed Amerindians because according to Bryc et al, 2015, Latino Americans are 65.1% white (mostly southern European), 6.2% black, 18% Amerindian, and 11% unassigned, though the unassigned is broader East Asian/Amerindian so should probably be counted as Amerindian. Since you report the PGS for Southern Europeans and since I estimate the the PGS for pure blacks at 46.834, using simple algebra, I estimate unmixed Amerindians would have a PGS of 47.510.

DP: yes, but you should also cross-check these with the other table with scores for Peruvians and Mexicans and see if they converge.

PP: Good point. In one of your data sets you find a 0.57 correlation between PGS and latitude. Do you agree with Lynn’s cold winter theory of how racial differences in intelligence evolved?

DP: in part, yes. but it doesn’t explain the low Amerindian IQ because Native Americans were in Siberia during the Last Glacial Maximum and then they moved to North America at the end of it, which is also a cold region…So I think most of the differences are due to farming and civilization

PP: Well Lynn argues the anomalies can all be explained by population size. Low population races like Arctic people, Amerindians, Australoids, Bushmen, & pygmies have lower IQs than their climates predict because there weren’t enough positive mutations. Meanwhile high population races like East Asians, whites, South Asians, and West Africans have higher IQs than their climates predict. This would also explain why Neanderthals had lower IQs than their climates predict.

DP: but these SNPs are common among the races..the differences are explained by these common SNPs, not pop specific mutations. pop size is probably related to it through higher competition for resources selecting for higher IQ.

PP: I see…so then it was probably farming and civilization as you say. Just as cold climate boosted IQ because it was a novel environment to adapt to, so was farming, civilization and the literacy and numeracy requirements it imposed. Of course Amerindians also independently created civilization but most remained hunter-gatherers.

DP: yes… plus we don’t know how many of these SNPs are just life history or personality traits like C. stuff that farming selected for. most of them are related to g but a subset will also be related to conscientiousness. Emil et al in their Psych paper vetted their association with g in a sample though so I guess they must be genuine associations with IQ for the most part.

PP: Yes, because no one has given a huge sample (n = 1 million) of genotyped people a highly g loaded test. A perfect study would get a sample of 1 million people (from all over the world) and give them an extremely culture reduced test with many subtests to maximize g loading (i.e. block design, draw a person in the sand, name as many body parts as you can in 1 minute in your own language, pictorial oddities etc) and then enter the composite score, DNA and human development index of each person into a computer and have machine learning create a multiple regression equation predicting IQ using HDI & genomic variants as independent variables. By using such a diverse and global sample, one finds the genomic variants that correlate with IQ everywhere and thus are most likely to be causal.

DP: yes.

PP: Now that the neanderthal genome has been published, why haven’t you tried to estimate their polygenic score? Richard Klein argues that before about 50 kya, modern humans and neanderthals had similar intellect, but suddenly around 50 kya there was a genetic brain change that allowed modern humans to leave Africa, colonize every continent, replace neanderthals & invent art & complex technology. Testing this hypothesis was the main motivation to sequence the neanderthal genome so there’s enormous interest in their intelligence, even in mainstream science.

DP: yes that’s the next step…we’re analyzing genomes from Bronze age now, but Neanderthal would be good. But funds are limited for this kind of research and I am not working in academia.

PP: Above you rejected Lynn’s population size mutation theory on the grounds that all races have all the known IQ related genomic variants, however it also seems you have no high coverage genomes from low population isolated groups like pygmies, bushmen, australoids, arctic people & pure Amerindians. Is it plausible that high coverage genomes of these groups would show they are missing some of the IQ enhancing mutations that appeared in the last 15,000 years?

DP: What I am saying is that you can see a difference even at the common SNPs in their frequencies. I cannot rule out that they are also missing these mutations but that would be an additional factor.

PP: Do you agree with John Hawks’s theory that positive selection in the last 5000 years has been a hundred times faster than in any other period of human evolution because of the explosion of new mutations & environmental change? This is the exact opposite of Gould who argued we have the same bodies and brains we’ve had 40,000 years ago and all subsequent change has been cultural not biological.

DP: from a purely theoretical point of view, yes, but one would need to study ancient genomes to empirically vet that hypothesis.

PP: Is there any strong evidence in support of Michael Woodley’s theory that white genomic IQ has declined by 10 or 15 IQ points since the Victorian era?

DP: I computed the decline based on the paper by Abdellaoui on British [Education Attainment] PGS and social stratification and it’s about 0.3 points per decade, so about 3 points over a century.

It’s not necessarily the case that IQ PGS declined more than the EA PGS..if anything, the latter was declining more because dysgenics on IQ is mainly via education so I think 3 points per century is a solid estimate

Thank you Davide Piffer for this interview. As mentioned above, you can find more of Davide’s thoughts on his blog.

Can the Wechsler Flynn effect be 100% explained by nutrition?

19 Monday Aug 2019

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In March 2016, I wrote the following:

I decided to look at an excellent study that Lynn had cited.  In this study you had 14 pairs of identical twins (one born undernourished, the co-twin born well nourished as measured by birth weight; twin pairs were raised in the same homes).  At an average age of 13, they had their head circumferences measured and were given the WISC IQ test.

The heavier twins had crania that were 0.64 cm bigger than their undernourished co-twin.  At age 13, the within sex standard deviation for head circumference appears to be 1.31 cm, so that’s a difference of 0.49 standard deviations.

When it came to verbal IQ, the well-noursihed twins and the undernourished twins had the exact same average IQ.  And when I saw the exact same average IQ, I mean the exact same average IQ: 98.29 vs 98.29 (unadjusted for old norms)

However when it came to performance IQ, the well nourished twins scored 7.07 IQ points higher than their undernourished co-twins.  That’s a difference of 0.47 standard deviations, virtually identical to the 0.49 standard deviation difference in head circumferences.

So it seems that Richard Lynn was half-right.  Brain size gains caused by  prenatal nutrition do perfectly parallel IQ gains caused by nutrition, but only when it comes to Performance IQ.  Prenatal nutrition seems to have virtually zero impact on Verbal IQ, though given the small sample size (only 14 twin pairs), these conclusions are tentative.

It’s amazing how well this study of identical twins perfectly parallels the difference between North American young adults in the 21st century vs circa WWII.

21st century North American young white adults are to their circa WWII counterparts as well nourished identical twins are to their less nourished co-twin in that their head circumference and Wechsler Performance IQs are both about half an SD larger, while their verbal IQs are about the same.

Because humans are cultural creatures, I believe the brain evolved to prioritize verbal ability during times of malnutrition (which as Lynn noted, includes disease since disease prevents the body from using nutrients), so when sub-optimum nutrition shrinks the brain, mostly spatial IQ suffers, and then when prosperity returns you get a genuine Flynn effect, but it’s 100% concentrated in spatial ability. Spatial ability is a luxury of the well fed.

One might wonder why, with all the increasing education and media, I did not find any verbal Flynn effect on the Wechsler. It’s likely that 21st century education gave us an unfair advantage on verbal tests especially Similarities, but this advantage was negated by the fact that a test created in the 1930s was biased against us (especially in tests of specific knowledge). In other words, two conflicting cultural biases cancelled each other out, thus exposing our true verbal intelligence as unchanged since WWII.