Tag Archives: IQ

Why does shared environment affect some IQ tests more than others?

04 Saturday Apr 2020

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Using twin studies, scientists divide phenotypic variation into three categories: DNA variation, shared environmental variation, and unshared environmental variation. Shared environment are all the experiences MZ twins reared together have in common (same upbringing, same schools, same womb) while unshared environment are all the experiences they don’t share (position within the womb, getting hit on the head, having an inspiring teacher).

The best estimate using massive datasets suggest that within Western democracies, DNA explains 41% of IQ variation at age 9, 55% at age 12, 66% at age 17, and 74% in adulthood. By contrast shared environment explains 33% at age 9, 18% at age 12, 16% at age 17, and 10% in adulthood (Bouchard 2013, figure 2). That leaves unshared environment explaining 26% of the variation at age 9, 27% at age 12, 19% at 17, and 16% in adulthood.

You don’t have to believe these associations are causal, but they are real. They’ve been more or less replicated using studies comparing (1) MZ twins with DZ twins, (2) MZ twins raised apart, (3) unrelated people reared in the same home. Although all of these methods depend of different assumptions, they all converge on the same conclusion: the predictive power of DNA skyrockets from childhood to adulthood while the predictive power of shared environment plummets. The same pattern (known as the Wilson effect) has also been observed for other phenotypes and in other species.

But why? Shouldn’t environment get more important as we age since experience has increasing time to accumulate? One theory is that more and more genes become active as we age. A more popular theory is that we select environments that maximize our genotype, so environment becomes just a magnifier of genes, not a causal force in its own right. So genetically smart people will stay in school and genetically strong people will lift weights and take steroids etc. People invest in where they’re more likely to be rewarded.

But here’s where things get really interesting. The Wilson effect behaves differently on different types of IQ tests. In his book Does your Family make you smarter? James Flynn notes that cognitive inequality increases from childhood to later adulthood (because good genes cause good environments and bad genes cause bad environments, the smart get smarter and the dumb get dumber, relative to the average person their age) but this pattern is much more pronounced on some tests than others.

Flynn describes three types of tests:

  • Type 1: Tests that show large family effects (shared environment) that decay slowly. This include tests involving vocabulary (define “rudimentary”), general knowledge (How old is the Earth?) verbal abstraction (how are a brain and a computer the same?) and social comprehension (why do you need a passport to travel?)
  • Type 2: Tests that show small family effects that decay fast. These include spatial manipulation (use these two triangles to make a square) and noticing incongruities (what’s missing or absurd in a picture of a common object or scene).
  • Type 3: Tests that show that large family effects that decay fast. These tests include clerical speed and arithmetic.

Flynn argues that type 1 tests involve skills that children learn from observing their parents talk, hence the large family effect. By contrast he says of type 2 tests:

Aside from the occasional jigsaw puzzle, they have no part in everyday life. Children never see their parents performing these cognitive tasks as part of normal behavior. Family effects are weak, even among preschoolers. Since these subtests match environment with genetic potential so young, they would be an ideal measure (for, say, 5-year-olds) of genes for intelligence.

From pages 53-54 of Does Your Family Make You Smarter? by James Flynn

In other words, Type 2 tests measure “novel problem solving”, while type 1 tests measure acquired abilities. A more provocative interpretation is type 2 tests measure real intelligence, while type 1 just measure knowledge and experience. This is the age-old distinction between aptitude tests vs achievement tests, culture fair vs culture loaded, fluid vs crystallized.

And yet Flynn largely rejects Cattell-Horn-Carroll’s theory that fluid ability (novel problem solving) is invested to acquire crystallized ability (accumulated knowledge) writing:

…fluid skill is just as heavily influenced by family environment as the most malleable crystallized skill (vocabulary) and therefore, neither skill deserves to be called an investment and the other a dividend.

From page 132 of Does Your Family Make You Smarter? by James Flynn

Flynn of course is referring to the greatest irony in the history of psychometrics and the biggest mistake of Arthur Jensen’s career: the Raven Progressive Matrices (long worshiped by Jensen and Jensenistas as the most culture fair measure of pure intelligence ever invented) is a type 1 test!

Which of the 8 choices completes the above pattern? Image from  from Carpenter, P., Just, M., & Shell, P. (1990, July)

But let’s not throw the baby out with the bath water. There’s no need to abandon CHC investment theory just because a major test got mischaracterized. But at the same time, it doesn’t feel right to reclassify the Raven as a crystallized test, Research is needed to understand why the Raven is so culturally sensitive when it superficially looks like a measure of novel problem solving. Is it measuring some kind of implicit crystallized knowledge we’re not conscious of like being familiar with patterns, columns and rows and reasoning through the process of elimination, or are the family effects on the non-cognitive part of the test (having the motivation to persist and concentrate on such an abstract task). Flynn argues that the brain is like a muscle, but if so, the Raven is an exercise most have never done before, so why isn’t it a type 2 test?

Flynn might argue that if your family helped you with abstract problems in algebra or had philosophical discussions about hypothetical concepts, you’ve been exercising for the Raven all your life, but this seems like a bit of a stretch. All the research shows that cognitive training has narrow transfer (i.e. practicing chess will only make you slightly better at checkers, and not at all better at scrabble) though perhaps the Raven’s uniquely abstract (general) nature allows it to slightly buck this trend.

The true distribution of intelligence

31 Tuesday Mar 2020

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Modern IQ tests force test scores to fit a normal distribution, but I’ve long suspected the distribution of intelligence is anything but normal. After all, if you look at the distribution of wealth and income (a crude measure of intelligence), you find the richest people are worth millions of times more than the poorest. And that’s just because they’re not paying their fair share, as Elizabeth Warren would have us believe. We see the same skewed distribution in academic output, with the most productive scientists publishing orders of magnitude more than the least productive.

A member of Prometheus society once hypothesized that the human mind works in parallel, so that complex problem solving speed doubles every 10 IQ points (he later suggested 5)?

And yet at the same time, Arthur Jensen seemed to believe intelligence was normally distributed and in support of this cited cognitive measures that form a natural scale with equal intervals and a true zero point such as the total number of words a person knows or the number of digits they can repeat after one hearing, both of which were normally distributed. What was missing however from Jensen’s examples was complex on-the-spot problem solving.

Thanks to my research on how people today would score on the oldest Wechsler tests (the ancient WBI) I have some novel data on how long it takes people to solve visuo-spatial items. The WBI includes a subtest called Object Assembly where you have to fit a bunch of odd shaped cardboard cutouts together to make a familiar object, and over the past decade or so, this was administered to a relatively random sample of White young adults (n = 17). One seven piece item was easy enough that all 17 were able to complete it within the 3 minute time limit, yet hard enough that no one could solve it immediately.

Normally I wouldn’t show items from an actual IQ test, but the WBI is over 80 years old and Object Assembly is no longer part of current Wechsler subtests.

[update april 1, 2020, I decided to remove the photos to be safe, but it’s too bad because those were gorgeous photos I took]

When one test participant saw these cardboard cutouts being placed on the table, he apologized for being unable to contain his laughter. A painful reminder that my life’s work is considered a joke by much of the population. And yet for all their apparent absurdity, these silly little tests remain the crowning achievement of social science with one’s score being largely destiny .

Even on this one item, there seemed to be a correlation between IQ and occupation/education. The time taken to complete the puzzle ranged from 14 seconds (a professional with a Masters degree in Engineering from a top Canadian university) to a 137 seconds (a roofer with only a high school diploma). Below are the times of all 17 participants ranked from fastest to slowest.

14, 18, 21,30,31,33,34,35,48,58,60,65,68,69,82,89*,137

Mean = 52 seconds, Standard Deviation = 30 seconds

In a normal distribution, 68% fall within one standard deviation of the mean. In this distribution, 71% fell within one standard deviation of the mean (22 to 82 seconds) which is pretty damn close. Also in a normal distribution, 95% fall within two standard deviations (-8 to 112 seconds) and in my sample, 94% did (even closer!).

image found here

So simply by picking at least a moderately g loaded novel problem that is both easy enough that no one gives up, yet hard enough that everyone is forced to think, and measuring performance on a natural scale (time taken in seconds) a normal curve emerges, though a somewhat truncated one (the slowest time is much further from the mean than the fastest, perhaps because human hands can only assemble puzzles so fast, regardless of how quick the mind is).

To convert from time in seconds to IQ, all one needs to do is make the natural mean of 52 seconds equal to the IQ mean of 100, and make each natural standard deviation (30 seconds) faster or slower than 52 seconds, equal to 15 IQ points (the IQ standard deviation) above or below 100, respectively.

Thus the elite Masters degree in Engineering professional gets an IQ of 119 (14 seconds) and the high school only roofer gets an IQ of 58 (137 seconds). But note that even though IQ appears to be a true interval scale (meaning an X point gap between any two points on the IQ scale are equivalent), it is not a ratio scale, meaning IQs can not be meaningfully multiplied. So even though IQ 119 is about twice as high as IQ 58, the difference in actual problem solving speed is about an order of magnitude. This is because unlike height, weight and time in seconds to solve puzzles (which can be meaningfully multiplied) the IQ scale has no true zero point.

Of course the normal curve only applies to the biologically normal population, so it’s interesting to note that it’s now standard procedure to exclude pathological cases from IQ test norming samples. Indeed one man was excluded from my sample after he told me that years ago he had suffered a stroke (quite unusual for a man in his thirties). This man struggled greatly with the above puzzle, only joining 25% of the cuts within the 3 minute time limit. The only way to estimate what his time would have been had he not given up is divide 3 minutes by 25% which gives 12 minutes (720 seconds). This is more than 22 standard deviations slower than the mean of the normal sample, and equivalent to an IQ of -234! Such extreme deviations remind us how sensitive the normal curve is to the normality of the sample.

*one person solved the puzzle in 67 seconds, but the ear pieces were reversed, so only 75% of the cuts were correctly joined. I thus considered this equivalent to a perfect performance at 75% of the speed (67 seconds/0.75 = 89 seconds).

Why didn’t megafauna go extinct in Africa?

29 Sunday Mar 2020

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Have you ever wondered why we have to go all the way to Africa to see a safari? For Africa is the land of 13000 lb elephants and 18 foot tall giraffes.

But what many do not realize is that 40,000 years ago, the whole World looked like an African safari. North America and Eurasia were home to Pachystruthio dmanisensis, a flightless bird that stood 11.5 feet tall and weighed nearly a 1000 lbs.

image found here

North America was also home to the short-faced bear which stood up to 14 feet tall, weighed about 1700 lbs, and could run up to 40 miles per hour. And of course who could forget the 13000 lb mammoth, which lived on every continent except Australia.

Emily Lindsey writes:

Scientists call these giant animals “megafauna” (mega = big, and fauna = animals). We still have megafauna in the world, but there used to be a whole lot more of it. In fact, it appears that having a large number of large-bodied animals in an ecosystem is actually the normal state for our planet, at least for the geologic era we are living in today, the Cenozoic (or “Age of Mammals”) . But sometime in the past 50,000 years (very recent geologically), everywhere except for Africa, most of those large animals became extinct. And we still aren’t sure why!

Some scientists think megafauna survived in Africa because humans evolved there so large animals had more time to adapt to us. However members of the genus Homo have been living outside Africa for 2 million years, so Eurasian megafauna had time to adapt to us too. Another theory is that megafauna were killed off by the extreme climate changes that megafauna endured outside Africa.

But in asking why megafauna went extinct everywhere except Africa, politically correct scientists are forced to ignore the elephant in the room (pun intended): HBD. If Arthur Jensen was correct about the black-white IQ gap being genetic, perhaps Africans simply hadn’t evolved the intelligence to hunt large game.

But that can’t be the whole story. If racial differences in IQ evolved because we needed more intelligence to survive the non-tropics, how were Australian aboriginals (who retain a tropical phenotype) able to kill off 100% of their giant mammals? Migrating from Africa to Australia means their ancestors must have spent some time in the non-tropical ice age Middle East. Was this enough time for them to evolve the intelligence to hunt big game or was the big game in Australia simply easier to hunt because it had not had the time to evolve ways to avoid humans?

If cold climate selected humans were especially evolved for hunting big game, and if the big game on continents where humans had never been were especially bad at evading human predators, then these two factors predict the biggest megafauna massacre of all should have occurred in the Americas where both conditions were met: cold adapted hunters (humans entered the Americas from Siberia) entering a continent where humans had never been.

And indeed that seems to be the case. Paleo-biologist Rebecca Terry at Oregon State University says “pretty advanced weaponry was definitely present, and the extinctions in the New World in North America and South America were really extreme as a result.”

11,000 years ago (shortly after modern humans entered the New World), the average weight of a non-human mammal in North America was about 200 pounds compared to only 15 pounds today.

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.

Why did civilization occur when & where it did?

20 Friday Mar 2020

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Commenter Melo writes:

An ad hoc assertion is essentially a hypothesis that has not been independently verified and is invoked to save a theory from falsification.

You’ve been doing that since I first started commenting here. To the point that the theory itself is just losing any real explanatory power it had. An example would be the statement that cold temperatures select for IQ but if the environment is too inhospitable, civilization will likely not emerge.

Actually it’s been independently verified over and over again and contradicted never. All six independent civilizations were created South of the Caspian sea by peoples who had spent tens of thousands of years outside the tropics. It’s one of the least ad hoc theories you’ve ever heard of because it has not a single exception.

image found here

So even though anatomically modern humans have been around for about 195,000 years, all six civilizations emerged 6000 to 3500 years ago. Coincidence? No. We didn’t evolve the cognitive ability to build civilization until we left the tropics and were exposed to the ice age, and even those who had evolved to the ice age could only build civilization if they ended up in bountiful land (i.e. South of the Caspian sea).

This perfectly explains both why civilization took so long, and why it was only created by certain peoples.

So because the IQ needed to build civilization evolved in high latitude (cold), but the lands amenable to civilization were low latitude (warm) it took our species 189,000 years before we had the right kind of humans on the right type of land during an interglacial period. These were humans who had migrated North but not too far North (i.e. Middle Easterners), or those who migrated as far North as the arctic circle, only to return to the tropics (i.e. the Mayans)

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.

Guessing Clarence Thomas’s IQ

02 Monday Mar 2020

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Prestigious Black national merit finalist GondwanaMan writes in the comment section:

… I’ve heard Thomas speak multiple times over the past 10 years and he seems very intelligent but I’ve heard mixed things about his behavior/intellect. Maybe PP can do an IQ analysis I would be very interested…

Thomas came from nothing to become one of the most powerful men on the planent. He is clearly intelligent compared to the average American, but in my opinion he would score lower on an IQ test than most other members of the super-elite.

For one thing, Thomas is known for his chilling silence. Unlike other supreme court judges who ask questions and make comments, Thomas has been largely silent for decades, much like the dim-witted Jason from the Friday the 13th movies.

Conservatives tend to score lower on IQ tests than liberals and blacks tend to score lower than whites, but because blacks are almost never conservative, the rare combination of being both conservative and black doesn’t bode well.

Of course conservatism is a vaguely defined moving target so Thomas may have very intelligent reasons for his political views that are actually quite liberal in the true spirit of the term. For example Thomas opposes affirmative action, not because he’s anti-black, but because he saw first hand how being seen as a token devalued his Yale Law degree. While white law grads had elite law firms at their beck and call, Thomas had to apply to dozens of firms to even be considered. Of course this was the 1970s when there was a lot more racism.

In general he felt that affirmative action benefits light-skinned blacks from elite backgrounds while dark skinned blacks like himself had to work much harder. Of course if racial IQ differences are genomic, we’d expect darker skinned blacks like Thomas to have lower IQs (on average) than their lighter skinned peers like Obama and Corey Booker. From page 45 of the book Strange Justice written by Jane Mayer and Jill Abramson:

Not only was he short, and in his teen years slight, but he also had exceptionally African features years before the Black is Beautiful movement made them desirable. “He was darker than most kids, and in that generation, people were cruel,” recalled Sara Wright, a librarian for the Savannah Morning News who attended elementary and junior high school with Thomas. “He was teased a lot and they’d call him [N word redacted by PP, 2020-03-02] Naps” for his tightly curled hair. “A lot of the girls wouldn’t want to go out with him.”

Thomas himself remembered being called “ABC,” or “America’s Blackest Child.” Even friends recollect taunting him that “if he were any blacker, he’d be blue.” As Lester Johnson, who is now a lawyer in Savannah, recalled, “Clarence had big lips, nappy hair and he was almost literally black. Those folks were at the bottom of the pole. You just didn’t want to hang with those kids.

…The most prominent families in town since before the Civil War were for the most part what a local history of African-Americans called “high yellow,” or mulatto. At the same time, many of those with pure African bloodlines, like Thomas were made to feel inferior.”

…At Yale he talked bitterly about the “light-skinned elite” blacks who had it easier than the darker ones.

pg 45 of Strange Justice

Of course race is only one variable that correlates with IQ and we shouldn’t give it too much emphasis, as some very dark skinned blacks score far higher on IQ tests than 99% of whites and East Asians, however as the below photo with George H.W. Bush shows, Thomas has many physical traits that put him at risk for low IQ.

This image has an empty alt attribute; its file name is thomas.png

Thomas is much shorter and more muscular than his fellow elite George H.W. Bush. Height is positively correlated with IQ and weight/height ratio is negatively correlated with IQ. Also the cranial capacity of the elder Bush seems to dwarf Thomas’s. But to his credit, Thomas is wearing glasses and myopia is thought to be genomically linked to high IQ.

So what is his IQ?

It’s unclear if Thomas ever took an official IQ test but he almost certainly took proxy versions like the SAT and LSAT. However these scores are not known so we’re left only with his grades.

The book Strange Justice describes his academic behavior at Holy Cross college:

But much of his time was spent alone, usually studying. His classmates recalled that when they went to dances at nearby schools on Saturday nights, Thomas often preferred to stay in the basement of the college library. When the school threatened to shorten the Saturday night library hours, he petitioned the authorities to keep the facility open. And when others went away during holidays, he stayed in the otherwise empty school, explaining later that he viewed such breaks as a valuable opportunity to get ahead of the other students.

Academically, his efforts paid off. He wrote to a friend that he had managed to maintain a 3.7 grade point average, and he graduated in 1971 with honors, ranking ninth in his class

According to The New York Times, Thomas’s grades at Holy Cross were in the top 7% of his class.

Let’s assume grades are simply an average of IQ and hard work (averaging is appropriate because two variables are not correlated). If we assume Thomas was in the top 1% in hard work (skipping holidays, petitioning the library to stay open), which is 2.33 standard deviations above the class average, how high would his IQ have to be to end up in the top 7% (+1.6 SD). Simple algebra tells us that if he was +2.33 SD in hard work (relative to Holy Cross students), his IQ could be no higher than +0.87 SD for his grades to be +1.6 SD.

So now that we estimate Thomas’s IQ was +0.87 SD relative to Holy Cross students, we need to know what their IQ distribution was.

Circa 2014 Holy Cross had a median SAT score of 1280 out of 1600 which equates to a mean IQ of 128 (U.S. norms).

However we know Harvard students went from an SAT IQ of 143 to an IQ around 128 with an SD of 12 on a test not used to select them (one third regression to the mean) so the actual IQ distribution at Holy Cross (in 2014 and perhaps historically) was likely around 118 with a standard deviation around 12 (compared to the U.S. distribution of 100 with an SD of 15).

Thus Thomas’s estimated IQ is 118 + 0.87(12) = 128 (U.S. norms) or 127 (white norms). In other words, smarter than 96% of white America.

Is this estimate too high?

There is reason to think this estimate might err on the high side. For example on page 201 of the book Yale Law School and the Sixties: Revolt and Reverberations it states:

…Associate Dean Ralph Brown recalled that “we were admitting blacks very indulgently, and a lot of them could barely do the work.” When courses required in-class exams, minorities tended to end up “in the bottom,” Charles Reich said. “You couldn’t disguise that”. One could get around it, he added, by having students write papers that, after several drafts, might well deserve a high grade, as he did for Clarence Thomas. But first semester courses required exams.

Since first semester Yale Law courses require exams, perhaps the best estimate of Thomas’s IQ can be found in this paragraph from Strange Justice:

His academic records remain, with his consent, sealed. But professors and administrators from his era recall him as an average student, hard-working but not particularly brilliant. There is only one professor –Thomas I. Emerson– whose records have been made public. Thomas elected to take Emerson’s first-year course on politics and civil rights in 1972, and Emerson’s notes show that he finished the class near the bottom, with a 69 for the semester. One of only two students who scored lower was Thomas’s friend and later witness against Hill, John Doggett.

Interestingly Doggett is also a black conservative.

Assuming about 20 students per class room, being in the bottom three puts Thomas in the bottom 15%, or roughly 1.13 SD below the class mean.

Although students at the best law schools average around IQ 145 on the LSAT, they likely regress to 128 (with an SD of 12) on tests not used to select them. Thus if Thomas’s bottom 15% performance in Emerson’s law class implies an IQ of:

128 – 1.13(12) = 114 (U.S. norms) or 112 (U.S. white norms).

Higher than 79% of white America.

That sounds about right.

[this article was lightly edited on March 3, 2020]

LSAT-IQ conversion

23 Sunday Feb 2020

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Here’s a thread where people listed their scores on both the LSAT and the ACT/SAT.

Because the SAT is constantly changing, I decided to focus on the LSAT-ACT correlation, ignoring the SAT.

The correlation between self-reported LSAT scores and ACT scores was 0.46+ (n = 19).

The LSAT scores of the sample had a mean of 164 (SD 8.03) and the ACT scores had a mean of 29 (SD 4.02).

Using equipercentile equating, we can infer from the above distributions that the average LSAT taker (LSAT = 150) is a equivalent to a post-April 1995 to pre-March 2016 SAT score (V + M) of 1030 which is equivalent to an IQ of 107 (U.S. norms).

source

Meanwhile, the average Harvard Law student (LSAT = 173) equates to a post-April 1995 to pre-March 2016 SAT score of 1485 which equates to an IQ of 144. Of course Harvardl Law students (like all people selected by a specific test) would regress precipitously on a test not used to select them.

Nonetheless, a simple equation for converting LSAT to IQ is:

IQ = 1.61(LSAT) – 134.3

Of course this data is only based a small sample of self-reported scores so this equation should only be considered preliminary. One potential red flag is the IQ predicted for the average LSAT taker is 107. While this is above the U.S. average, it is surprisingly low for aspiring law students, given that the average university graduate has an IQ of 111 and mostly the above average ones would pursue even higher learning.

But it could be that many people who don’t even graduate from university decide to take the LSAT just in case, including many people from low IQ criminal communities who see a law degree as a way to vindicate themselves or their loved ones:

Average IQ at Harvard law school

02 Sunday Feb 2020

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I’ve always been curious about people who got advanced degrees from elite universities, like Harvard law school graduates for example, because not only do they have the most advanced degrees, but from the most prestigious schools to boot. We know Harvard undergrads average IQs around 17 points higher than the average university undergrad (125 vs 108 (white norms); the difference is much larger on the SAT because it’s used to select Harvard undergrads, thus causing a selection bias.

We also know law school grads average about 11 points higher than the typical university grad (119 vs 108 (white norms)).

A naive reader might think that if Harvard undergrads are 17 points smarter than the average university grad, and if law grads are 11 points smarter than the average university grad, then Harvard law grads must be 17 + 11 = 28 IQ points smarter than the average university grad, giving them an IQ of:

108 + 28 = 136

But this would only be true if Harvard students and law grads were independent groups. In reality, being a Harvard undergrad dramatically increases your odds of getting a Harvard law degree (or equivalent).

Law degrees (i.e Juris Doctor degree) are now classified as a type of doctor’s degree and Harvard confers about 1,455 such degrees a year. Given that U.S. citizens are about 78.9% of Harvard, we can guestimate U.S. citizens recieve only 78.9% of their doctor’s degrees, so roughly 1,148.

Given that about 4 million Americans come of age every year, we can say getting a Harvard Doctor’s degree is a one in 3,484 achievement, and thus the median such person would be a one in 6,969 achiever.

If there were a perfect correlation between IQ and academic success, this would imply an IQ of 154 (U.S. norms) but since the correlation between IQ and highest degree attained is only about 0.55 an IQ of 0.55(54) + 100 = 130 is expected.

Converting to white norms gives an IQ of 128.

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: