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Emil O. W. Kirkegaard – 2018 – Is national mental sport ability a sign of intelligence? An analysis of the top players of 12 mental sports [data]

… Zambian biochemist Chanda Chisala (2016 etc.) argued that Nigerian Scrabble performance was much higher than one would expect based on its national IQ estimate (given as 71.2 by Lynn and Vanhanen). His interpretation is that the tests are missing real ability present in this and other African populations. His study, however, was not systematic and did not include many other mental sports. The purpose of this study was to systematically examine the relationship between national skill at mental sports and national cognitive ability.

Ability in mental sports is g-loaded:

… a meta-analysis of studies of chess players and non-chess players round a mean group difference of .50 d (Sala et al., 2017). In another study, Quiroga et al (Ángeles Quiroga et al., 2015; see also Foroughi, Serraino, Parasuraman, & Boehm-Davis, 2016) administered 12 video games to 188 students as well as traditional standardized tests, and found that they measured nearly identical constructs (r’s .93 to .96).

The games used to test Chinda Chisala’s thesis:

For games, we included every esport listed at with at least 1,000 top players. This resulted in the inclusion of 8 games: DOTA 2 (dota2), League of Legends (lol), Counter-Strike: Global Offensive (csgo), Starcraft 2 (sc2), Counter-Strike (cs), Hearthstone (hs), Overwatch (ow), and Super Smash Bros. Melee (ssbm). Furthermore, we included major non-esports: Chess, Go, Poker and Scrabble.

Controlling for population size, performance in mental sports correlated r=0.79 with Lynn and Vanhanen’s published national IQs.


General gaming ability score and national IQ. Orange line = linear fit (top left), blue line = local regression fit (span = 1.00). Weighted by square root of population size.

Contra Chisala’s arguments that Nigeria’s IQ estimates were spuriously low due to its good performance in Scrabble, not only were its results concordant with its reported IQ levels of ~70, but it was also the poorest performing country in the world when controlling for population size.

In reality, there were actually just four major outliers. North Korea was the biggest negative outlier, presumably due to very low Internet penetration. South Africa, Brazil, and the United States were positive outliers, which Kirkegaard suggests could be a smart fraction effect.

So why Nigeria’s (relative to its IQ) outstanding performance on Scrabble?


Because it has by far the least mental sports loading (correlation with performance in other games) out of the twelve games, less so even than go, which is almost entirely constricted to East Asia.

Kirkegaard concludes:

With regards to the arguments by Chisala concerning Nigeria and Scrabble, we find no support for mismeasured Nigerian intelligence. It is true, as he noted, that Nigerians are much better at Scrabble than one would expect (standardized residual for Scrabble is 1.55, rank 3). However, Nigerians underperform on the remaining 11 sports (all residuals are negative), and the overall factor score of Nigeria (-1.39) is about what one would expect based on the current estimates of the country’s mean cognitive ability and the relation to national IQ. Indeed, based on a linear regression with just IQ, the standardized residual for Nigeria is only -0.16, meaning that the country performs very slightly worse at mental sports in general than one would expect based on its mean national intelligence. The predicted IQ of Nigeria was 73.1 based on a nonlinear model with just game performance as the predictor, Lynn and Vanhanen’s (2012) estimate was 71.2, and a recent large-scale study (n ≈ 11k) using Raven’s Standard Progressive Matrices found a mean IQ of 65.5 (Hur, Nijenhuis, & Jeong, 2017). The anomalously high Scrabble performance is not plausibly interpreted as hidden ability, but rather as a cultural specific preference for a specific sport.

• Category: Race/Ethnicity • Tags: Chess, IQ, Nigeria, Psychometrics, Video Games 
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While data from various IQ tests are useful for global scale analyses (e.g. GDPcc correlations), they are far less reliable for particular countries. That’s why I’m a big fan of the OECD’s PISA assessments, which are highly standardized, have large samples from similar age groups, take place concurrently once every three years, test those aspects of intelligence most intuitively relevant to economic success (i.e. application of numeracy and literacy skills in novel situations), and enjoy strong face validity (i.e. very few “strange” results).

However, there is also the temporal dimension. All these IQ maps that you see today are almost entirely based on testing children/teenagers from the current year to 1948, the earliest year on David Becker’s database as of now (although with attempts to correct them through reference to contemporary UK standardization samples). PISA and TIMSS are rather tidier, with large, representative samples of teenagers getting tested at set ages and at set years. Still, even this isn’t perfect, because countries vary in their educational and auxological histories, which will have varying knock-on effects on the intelligence of different cohorts.

The correlations between cohorts will still be very good (after all, IQ is strongly hereditary, and the quality of the environment will itself tend to be strongly correlated to average IQ). But there will be some interesting outliers, both positive and negative. For instance, the gap between the youngest and oldest cohorts can be expected to be greater in countries such as South Korea, which transitioned from the Third World to the First in the space of half a century. It can likewise be expected to be smaller in countries like the United Kingdom, which sprang off from a high base – it started the last century as the workshop of the world, and was less damaged by WW2 than most other European countries – but plummeted in relative terms ever since. Understanding cohort dynamics will also make it possible to do, say, more fine-grained analyses between national IQ and socio-economic success.

So it’s a bit surprising that hardly any attention has been devoted to another OECD program, PIAAC (Programme for the International Assessment of Adult Competencies), which tests a range of cohorts instead of just teenagers.

The first round of the assessment in 2012 covered the following 22 countries: Australia, Austria, Canada, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Ireland, Italy, Japan, Korea, the Netherlands, Norway, Poland, the Slovak Republic, Spain, Sweden the United States; Chile, Greece, Indonesia, Israel, Lithuania, New Zealand, Singapore, Slovenia and Turkey joining in 2014.

The following documents/dataset refers refers to the first round of PIAAC:

Unfortunately, I have been unable to find data for the later countries in one place, though I haven’t looked very hard. It appears that the next round of PIAAC will take place in 2020.

In the rest of this post, I will highlight some of the more interesting data from there. For comprehensibility, all numbers have been converted to the IQ scale, with the England/N. Ireland average set to its traditional “Greenwich Mean” of 100 and S.D. = 15.

PIAAC 2012: Literacy, Numeracy, Average IQ

. Literacy Numeracy Average
Japan 107.1 107.3 107.2
Finland 104.5 105.7 105.1
Netherlands 103.4 105.1 104.3
Sweden 102.0 104.8 103.4
Norway 101.8 104.6 103.2
Flanders (Belgium) 100.9 105.2 103.0
Czech Republic 100.4 103.9 102.2
Slovak Republic 100.4 103.9 102.1
Estonia 101.0 103.2 102.1
Denmark 99.5 104.6 102.0
Australia 102.4 101.6 102.0
Russian Federation 100.8 102.3 101.5
Austria 99.1 103.7 101.4
Germany 99.2 102.8 101.0
Canada 100.3 101.1 100.7
Korea 100.0 100.5 100.3
England/N. Ireland (UK) 100.0 100.0 100.0
Cyprus 98.9 100.8 99.8
Poland 98.3 99.5 98.9
United States 99.2 97.5 98.4
Ireland 98.2 98.3 98.3
France 96.9 97.9 97.4
Spain 93.8 95.6 94.7
Italy 93.4 96.0 94.7
Average 100.1 101.9 101.0

No surprises here, except perhaps Korea’s figures being a bit lower than expected. We’ll come to that.

Difference in Performance: Youngest (16-24) vs. Oldest (55-65)

. Literacy Numeracy Average
Korea 14.6 14.7 14.7
Spain 11.1 10.4 10.7
France 9.9 8.8 9.3
Finland 11.1 7.4 9.2
Poland 9.7 7.5 8.6
Netherlands 10.1 7.0 8.6
Flanders (Belgium) 9.0 6.9 7.9
Austria 8.4 6.5 7.4
Italy 8.2 6.6 7.4
Estonia 7.9 5.7 6.8
Germany 7.6 5.6 6.6
Australia 6.4 5.9 6.1
Ireland 6.0 5.9 5.9
Japan 7.8 3.0 5.4
Czech Republic 5.4 4.4 4.9
Canada 4.6 5.1 4.8
Denmark 7.1 2.3 4.7
Sweden 6.1 3.0 4.5
Slovak Republic 3.0 3.8 3.4
Cyprus 1.9 4.2 3.1
Norway 3.9 1.9 2.9
United States 2.6 0.7 1.6
Russian Federation -0.2 1.8 0.8
England/N. Ireland (UK) 0.2 0.0 0.1
Average 7.3 5.6 6.4

As hypothesized, Korea has the largest cohort Flynn effect; in age-adjusted terms, while its young perform as well as the best (Japan, Netherlands, Finland), its elderly are near the back of the queue.

Incidentally, Turkey – not covered in the first round of this assessment, but I found figures for it in its national report from the second round – has a difference of 13.8 IQ points between its oldest and youngest cohorts. This makes patent sense in the context of it going from a Third World country in the 1950s, to an upper middle-income one today.

In contrast, the UK and the US – already relatively well developed countries in the 1950s, when their boomers appeared – barely eked out any increase in the ensuing fifty years.

The big exception here is Russia. As I speculated in my mega-article on Russian IQ for Sputnik and Pogrom, this may have been linked to the alcohol epidemic that began in Russia from around the mid-1960s, when life expectancy plateaued and consequently stagnated for the next half-century. It is not a big stretch to imagine there were similar dynamics in the country’s psychometric profile, with any Flynn effects from continuing development being annulled by the flood of vodka of the late Soviet era.

On the bright side, Russia’s alcohol epidemic has more or less ended, and – as I predicted back in 2012 – IQ amongst the youngest cohorts has been going up for the past decade (e.g. from 95 in PISA 2000-2009 to 99 by PISA 2015; Sugonyev’s yet unpublished military data).

Sociological observation of questionable validity: The three laggards here, the US, Russia, and the UK, are all especially (in)famous for developing a sizable lumpenproletariat class during this period (respectively, white/trailer trash, gopniks, and chavs).

Difference in Performance: Men vs. Women

. Literacy Numeracy Average
Flanders (Belgium) 2.0 4.4 3.2
Germany 1.6 4.8 3.2
Norway 2.0 4.1 3.1
Netherlands 1.2 4.6 2.9
Spain 2.0 3.5 2.7
Sweden 1.6 3.8 2.7
Canada 1.3 4.0 2.7
Australia 1.3 3.8 2.6
Ireland 1.6 3.3 2.4
England/N. Ireland (UK) 0.8 4.0 2.4
United States 0.7 3.9 2.3
Korea 1.7 2.9 2.3
Austria 0.7 3.7 2.2
Japan 0.7 3.4 2.0
Denmark 1.1 2.9 2.0
Czech Republic 1.4 2.5 1.9
France 0.6 3.0 1.8
Finland 0.7 2.8 1.8
Italy 0.1 3.0 1.5
Estonia 0.8 1.7 1.2
Cyprus -0.3 2.0 0.9
Slovak Republic -0.5 0.7 0.1
Poland -0.5 0.5 0.0
Russian Federation -1.3 -0.9 -1.1
Average 1.0 3.2 2.1

The Germanic lands – or perhaps countries characterized by the authoritarian family model – are characterized by significantly brighter males, while the Latin and Slavic lands lean in the other direction.

In Russia, it seems women are brighter, not only on average, but even in terms of numerical skills. Possibly this is also a function of Russian men having borne the brunt of the 1965-2015 alcohol epidemic.

Difference in Performance: Natives vs. Immigrants

. Literacy Numeracy Average
Sweden 15.8 16.0 15.9
Finland 16.1 13.9 15.0
Norway 13.1 15.5 14.3
Flanders (Belgium) 14.5 13.9 14.2
Korea 16.2 12.2 14.2
Netherlands 12.1 13.2 12.6
Denmark 12.8 11.9 12.4
France 10.6 12.4 11.5
England/N. Ireland (UK) 10.3 11.8 11.0
Australia 11.1 10.5 10.8
Austria 9.4 11.2 10.3
Spain 10.2 9.4 9.8
Germany 9.3 9.8 9.5
Canada 9.9 8.7 9.3
United States 9.2 6.7 8.0
Italy 8.8 6.6 7.7
Ireland 8.7 6.2 7.4
Cyprus 7.8 6.0 6.9
Estonia 4.7 2.6 3.6
Czech Republic 1.0 1.5 1.3
Slovak Republic -0.5 0.4 -0.1
Japan . . .
Poland . . .
Russian Federation . . .
Average 10.1 9.5 9.8

No surprises here, I think. Seems to correlate with the PISA data (see “Not Sending Their Best”: World Map of IQ Drop Due to Immigration).

Difference in Performance: Skilled vs. Elementary Occupations

. Literacy Numeracy Average
Austria 7.9 9.4 8.7
England/N. Ireland (UK) 7.8 9.5 8.6
Canada 7.6 9.1 8.4
United States 7.5 8.2 7.8
Sweden 7.3 8.3 7.8
France 6.1 9.3 7.7
Norway 7.6 7.7 7.7
Czech Republic 6.8 8.4 7.6
Australia 7.1 7.7 7.4
Netherlands 7.0 7.2 7.1
Italy 6.0 8.1 7.1
Flanders (Belgium) 6.3 7.3 6.8
Germany 6.0 6.8 6.4
Poland 5.9 6.9 6.4
Finland 5.4 6.7 6.0
Denmark 5.5 6.0 5.7
Korea 5.7 5.6 5.7
Spain 5.1 6.1 5.6
Estonia 4.7 6.2 5.4
Japan 3.6 6.9 5.3
Cyprus 3.3 7.1 5.2
Ireland 3.8 5.0 4.4
Slovak Republic 2.9 5.3 4.1
Russian Federation 2.1 . 2.1
Average 6.1 7.3 6.7

To maximize output and social welfare, you want to cluster your brighter people in the skilled, complex jobs of the “O-Ring economy“, while simple, “foolproof” jobs can be done by pretty much anybody reasonably effectively. It doesn’t matter if a waiter is 145 IQ or 100 IQ, but it certainly does if he’s a CEO.

As Murray and Herrnstein showed in The Bell Curve, the effectiveness of this cognitive sorting mechanism has increased by leaps and bounds in the US since the 1950s.

The PIAAC data suggests Anglos and Scandinavians are the best at this, which might be one more factor that explains their unusual economic and scientific dynamism, even relative to their IQs.

The Japanese do worse at this, possibly being held back by cultural factors (deference to age and other elements of social status).

Russia is at the very bottom of the list, suggesting highly inefficient cognitive selection. The pessimistic but plausible explanation that comes to mind is endemic corruption and nepotism.

Parting Thoughts

1. In particular, we need a more serious, in-depth analysis of the PIAAC data. Conversion of disparate tables floating about in PDF and Excel format on the Internet into one database.

2. In general, greater focus on tracking IQ across all relevant dimensions (nations; subregions; time; cohorts) to enable deeper, finer-grained economic/demographic analysis.

• Category: Economics • Tags: Flynn Effect, IQ, Psychometrics 
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Just came back from a workshop on “Intelligence and Culture as Factors of National Competitiveness” organized by the Institute of Psychology RAS.


The most interesting presentation was by Konstantin Sugonyev, which may be published in a forthcoming paper. It concerned the following test:

This is a test on the Russian Defense Ministry’s website, where potential contract soldiers are offered to take an IQ test (30 questions, testing verbal, numerical, logical), and a couple of personality tests, to assess their suitability for military service (unfortunately, it doesn’t seem to give you your score, only a pass or a fail).

Over the years 2012-2017, almost 250,000 Russians have done this test, possibly making this the largest source of regional psychometric data on Russia apart from the Unified State Exams (regional data about them is carefully secreted away).

The results:


While people born between 1973 and 1987 performed at a stable 19.5-20/30, the post-1988 period saw a steady improvement towards an average score of 21/30.

S.D. is around 6 points.

Whether this is due to a Flynn effect or ageing isn’t clear.



Only the top/bottom 5 regions were displayed, but they were exactly as expected. The difference between the best performers and worst performers was almost 1 S.D.

Best regions:

  1. Saint-Petersburg
  2. Yaroslavl
  3. Moscow
  4. Kirov oblast
  5. Chuvashia

Worst regions:

  1. Ingushetia
  2. Tyva
  3. Chechnya
  4. Dagestan
  5. Kabardino-Balkaria

So nice when new investigations continue building on stereotypes, especially n=250,000 investigations.

Note that I have long thought Yaroslavl might have a high IQ.

It had the highest literacy rate of any non-capital Russian region in 1897:

Incidentally, I am not surprised to see Yaroslavl being the top non-Baltic/non-capital Russian region by literacy rate in 1897. It struck me as by far the cleanest and most civilized provincial Russian town on the Golden Ring when I visited it in 2002 (a time when Russia was still shaking off the hangover of the Soviet collapse). Curiously enough, it also hosted one of the most vigorous insurrections against the Bolshevik regime in central Russia. Although it was not one of the regions covered by PISA, I would not be surprised if Yaroslavl oblast was to get a 100-102 score on it should it be carried out there (and as would be implied by the correlation curve).

They also had the biggest percentage of Russian peasant families with passbooks (needed for savings accounts) in 1897 and 1913.


The major disadvantage of this test that it selects for some degree of Internet proficiency (so also a mild sort of IQ test). No easy way to correct for this.

The major advantage of it is that you can also get a good idea of the “patriotism” of different Russian regions by the percentage of their population who do these tests.

Most patriotic regions:

  1. Sevastopol
  2. Altay
  3. Buryatia
  4. Murmansk
  5. Amur
  6. Zabaykal
  7. Adygea
  8. Kaliningrad
  9. Tyva

Least patriotic regions:

  1. Chechnya
  2. Ingushetia
  3. Tyumen
  4. Sakha (Yakutia)
  5. Tatarstan
  6. Khanty-Mansiysk
  7. Yamalo-Nenets
  8. Dagestan
  9. Karachay-Cherkassia

Note that Sevastopol was first, even though Crimea only joined up with Russia in 2014, i.e. about 40% of the way through this “experiment.”

The patriotism of the Buryats and Tuvans is also noted. This is not all that surprising – recall that Buryats had the highest percentage rate of military deaths in WW2 alongside Russians.

In contrast, DICh – especially Chechnya and Ingushetia – are distinguished by their lack of patriotism.

Saint-Petersburg was more patriotic than Moscow, as well as being more intelligent.

Results were robust according to a variety of statistical checks.

Several other people, including myself, made presentations.


One, by Denis Davydov, was about a 19 region (n=4010) survey of 18-50 year old Russians with Raven’s tests carried out in 2005-2007. (For some reason, its detailed results remain unpublished – at the least, they don’t appear in Lynn’s or Becker’s database).

They found no correlation with income, though I suspect the problem there is low sample + no adjustment for oil income.

There was also a negative correlation with homicides, suicides, and alcohol consumption, which is of course unusual. My pet theory is that this is due to the Finno-Ugric admixture in northern Russia making them both more intelligent and more prone to alcohol abuse, with most homicides/suicides in Russia themselves being a function of alcohol abuse.

• Category: Race/Ethnicity • Tags: IQ, Moscow, Patriotism, Psychometrics, Russia, The AK 
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Kulivets & Ushakov – 2016 – Modeling Relationship between Cognitive Abilities and Economic


We propose that problem solving is the mediator between human competencies and achievements. Creation of goods and services is based on problem solving in design, production and delivery. The quality of problem solving depends on human competencies and, in turn, determines economic achievements. More importantly, the choice of problems to be solved creates or does not create the possibility for application of highly qualified labor and, as a result, for full-fledged realization of human capital. We propose a mathematical model based on these assumptions. The simulation reproduces most important traits of Lynn and Vanhanen’s (2002) findings. The simulation shows a non-linear growth of economic achievements with national IQ growth as well as an increase of between countries variance. Thereby the proposed model can serve as a satisfactory explanation for empirical data on links between national IQs and economic achievements.

It’s well established that there is a very close correlation between average national IQ and GDP per capita, especially when corrected for resource windfalls and Communism.


(One such standard graph from Garett Jones).

However, there remain two additional results that correlational exercises cannot adequately explain:

  1. “First, the relationship between national IQs and income is not linear. As it was shown later this relationship can be well approximated by quadratic function (Whetzel & McDaniel, 2006). The mere assumption that more capable, competent and educated people produce better economic results is not sufficient to explain this specific finding.
  2. “Second, residuals of the regression of GDP on national IQ grow proportionally with the IQ. It means that in some high-IQ countries human potential leads to serious economic realizations while in others it is out of demand. So a comprehensive explanation of Lynn and Vanhanen’s data includes understanding of factors stimulating the use of highly qualified labor.”

So Sergey Kulivets, a mathematician at the Trapeznikov Institute, and Dmitry Ushakov, a psychologist at the Institute of Psychology RAN, created a model in which problem solving plays a central role to investigate these two puzzles.

They model a world composed of different countries, in which every resident has a “talent” with a bell curve distribution around different means. Each country has two types of people: Entrepreneurs and specialists. Entrepreneurs hire specialists to produce goods, the quality of which is determined by the talents of the specialists working on them. These goods are then sold on the international market, where any country can buy them. The “GDP” of each country is the sum of the income of its entrepreneurs, or the value of all the goods produced by the entrepreneurs within a country and sold in the international product market, during a set period.


Here is how the model works:

  1. Each entrepreur chooses a task for solving. There are two types of tasks: “Threshold” and “open type” ones. Threshold problems require a minimum competence level to complete, but additional competence beyond that threshold offers no further advantages beyond that minimal point; the value of the solutions to open problems increases with the talent of the specialists allocated to it.*
  2. The entrepreneur hires specialists from his own country to perform that task, attracting specialists by offering higher salaries for more competitive candidates.
  3. The entrepreneur produces goods. Quantity dependent on number of workers and money allocated to them; quality depends on the competence (talent) level of the hired specialists.
  4. The entrepreneur sells the good on an international market, competing with other enterpreneurs on price and quality.
  5. Income from this goes to entrepreneur, which in turn – after subtracting production costs and salaries – determines his budget for the next round of problem solving.

Consult the paper for the specific formulae used to describe task selection, the labor market, and the product market.

Towards the end, K&V compare their theoretical models against Lynn and Vanhanen’s. They match up near perfectly.


Competence: I; Development: D.
Left: Lynn & Vanhanen 2002; Right: Simulation results.

Also one can observe that K&V get a nicer fit than L&V, presumably because the Communist legacy (negative outliers) and resource windfalls (positive outliers) aren’t modeled.


Over time both consumers and entrepreneurs become much richer in competent countries relative to incompetent ones, as the “rise in entrepreneurs’ income influences the consumer income through salary rises.”

In this model, entrepreneurs choose tasks in a random way; unsuccessful ones are abandoned, while those that bring a return continue to be produced. As K&V note, if the quality of entrepreneur predictions as to the profitability of various tasks were to also depend on competence levels, then this cognitively-determined pattern of the wealth and poverty of nations can be expected to be even starker.

However, they do end with a cautionary note of some relevance to today’s political economy: Our model is based on the assumption that entrepreneurs’ income comes from organizing people to produce goods and services. This mechanismfunction is impaired if natural rent becomes the main source of profit.

* Incidentally, I would note that this division is justified by and reinforced by Garett Jones’ theory of the O-Ring sector: “I posit that there are two kinds of jobs: O-ring jobs where strategic complementarities to skill are large, and a diminishing-returns Foolproof sector, where two mediocre workers provide the same effective labor as one excellent worker… In a world where countries vary only slightly in the average skill of workers, these assumptions are sufficient to generate massive differences in cross-country income inequality while generating only small amounts of intra-country income inequality.

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Main News

issam-zahreddine* The legendary Major General Issam Zahreddine was blown up by a land mine in Deir ez-Zor.

What damn bad luck.

Surviving an ISIS siege for three years, only to go like that.

* Iraq takes back Kirkuk. Seemingly prearranged return to the status quo of 2014.

* Haaretz: White Nationalist Richard Spencer Gives Israel as Example of Ethno-state He Wants in U.S.

* Investor Mark Faber lands in hot water with the handshakeworthy crowd:

“And thank God white people populated America, and not the blacks. Otherwise, the US would look like Zimbabwe, which it might look like one day anyway, but at least America enjoyed 200 years in the economic and political sun under a white majority,” he wrote.

“I am not a racist, but the reality — no matter how politically incorrect — needs to be spelled out.”

Fortunately he’s old, presumably more or less retired, and lives in East Asia, where nobody gives a fuck.

* Emil Kirkegaard: “Did Lynn fudge the national IQs? Independent recalculation by David Becker. All open and verifiable. So far, n = 305 studies covered. r=.90.” [blog post forthcoming]


Incidentally, German psychometrist David Becker is due to start up a blog any day now. Feel free to help him come up with a name.

* Vincent Law: Bike-Sharing Leads Directly To Complete Societal Collapse

* gwern’s September newslatter: On genomic prediction:

Accurate Genomic Prediction Of Human Height, Lello et al 2017

A vindication of Steve Hsu’s predictions: the GWAS lasso works!(Hsu 2014/Vattikuti et al 2014/Ho & Hsu 2015) The height polygenic score has doubled and now explains the full SNP heritability.

This has many implications: primarily, polygenic scores are going to start doubling or quadrupling regularly as contemporary datasets (UKBB in particular?) start hitting the threshold. Years of incremental improvements in GWAS will be compressed into single papers. It will be exciting to have polygenic scores for intelligence which explain up to 30% of variance! These IQ PGSes will highly likely be available by 2019, and it’s possible that they could be computed this year in 2017 (depending on whether existing datasets are big enough to push past the threshold, perhaps assisted by genetic correlation techniques like MTAG). Plus, of course, more accurate genetic correlations. Aside from being one last bullet in the head of genetics denialism, it will massively increase the value of embryo selection and genome synthesis. Has it really been only 4 years since Rietveld et al 2013 was published? It feels like so much longer… It’s worth noting that the cumulative number of genomes is substantially larger than the annual output, and the former is what counts; for example, under one set of assumptions with a fixed annual investment and the observed exponential decrease in cost, there will be 5x total genomes than annually produced, so since 23andMe/ are reportedly collecting approaching millions of samples per year… (In a since deleted post: AncestryDNA alone attracted 1.4 million customers in the fourth quarter of 2016, with an additional two million in the first half of 2017…) The genome sequencing exponentials have been quite a tiger to ride. Very Kurzweilian: everything important happens near the end.


* Eliezer Yudkowsky: There’s No Fire Alarm for Artificial General Intelligence

Progress is driven by peak knowledge, not average knowledge.

If Fermi and the Wrights couldn’t see it coming three years out, imagine how hard it must be for anyone else to see it.

If you’re not at the global peak of knowledge of how to do the thing, and looped in on all the progress being made at what will turn out to be the leading project, you aren’t going to be able to see of your own knowledge at all that the big development is imminent. …

By saying we’re probably going to be in roughly this epistemic state until almost the end, I don’t mean to say we know that AGI is imminent, or that there won’t be important new breakthroughs in AI in the intervening time. I mean that it’s hard to guess how many further insights are needed for AGI, or how long it will take to reach those insights. After the next breakthrough, we still won’t know how many more breakthroughs are needed, leaving us in pretty much the same epistemic state as before. …

But no matter how the details play out, I do predict in a very general sense that there will be no fire alarm that is not an actual running AGI—no unmistakable sign before then that everyone knows and agrees on, that lets people act without feeling nervous about whether they’re worrying too early. That’s just not how the history of technology has usually played out in much simpler cases like flight and nuclear engineering, let alone a case like this one where all the signs and models are disputed.

* On this note: It was only 1.5 years ago that AlphaGo beat world’s then second best player Lee Sedol four matches to one.


Latest iteration, AlphaGo Zero, reached that level in just three days only playing by itself, and took only 21 days to surpass AlphaGo Master, which beat number one Ke Jie and sixty other top players this May.

Writing in the journal Nature, the researchers describe how AlphaGo Zero started off terribly, progressed to the level of a naive amateur, and ultimately deployed highly strategic moves used by grandmasters, all in a matter of days. It discovered one common play, called a joseki, in the first 10 hours. Other moves, with names such as “small avalanche” and “knight’s move pincer” soon followed. After three days, the program had discovered brand new moves that human experts are now studying. Intriguingly, the program grasped some advanced moves long before it discovered simpler ones, such as a pattern called a ladder that human Go players tend to grasp early on.




* Putin mutters some vaguely Alt Right sounding things about White Christians being a minority in the USA and preserving Russia as a European space (while continuing to repeat German policies of the 1960s).

Says that Russians and Ukrainians are one people that will unite. Before you get excited/panic, by unite, he means the restoration of normal relations with the Ukraine – a rather strange definition of the term.

We love Ukraine. And I consider them a brotherly people, if not part of the Russian people. Neither Russian nationalists nor Ukrainian nationalists like this, but I believe they will unite, sooner or later. Not at the state level, but in terms of the restoration of relations.

And, of course, this is a total inversion of the standard Russian nationalist position on the Ukraine.

Also issues some thoughts on foreign policy:

The biggest mistake our country made was that we put too much trust in you; and your mistake was that you saw this trust as weakness and abused it.

… and on the Bolshevik Revolution:

However, the largely utopian social model and ideology, which the newly formed state tried to implement initially following the 1917 revolution, was a powerful driver of transformations across the globe (this is quite clear and must also be acknowledged), caused a major revaluation of development models, and gave rise to rivalry and competition, the benefits of which, I would say, were mostly reaped by the West.

I am referring not only to the geopolitical victories following the Cold War. Many Western achievements of the 20th century were in answer to the challenge posed by the Soviet Union. I am talking about raising living standards, forming a strong middle class, reforming the labour market and the social sphere, promoting education, guaranteeing human rights, including the rights of minorities and women, overcoming racial segregation, which, as you may recall, was a shameful practice in many countries, including the United States, a few short decades ago.

This is mostly a myth, but a convenient one.


* Ksenia Sobchak announces she is running for the Russian Presidency.

Now you, an “educated” and “informed” person, are probably thinking that she is just a brainless celebrity running to give Putin artificial competition in lieu of Navalny. In reality, this is a vicious JIDF smear! My FSB sources tell me this is just the front Ksenia “She-Wolf of the SS” Sobchak (as she is widely known in ultranationalist circles) puts on to infiltrate the PutlerZOG, acting in cahoots with Taylor Swift and American far right militia leader Ben Garrison.

Although I do consider myself somewhat of a nationalist, she sounds far too crazy even for me. I disavow Ksenia “14/88 not 282″ Sobchak and her hateful, extremist ideology. Hopefully Jeb! will save the day.

* #Russiagate. In between the usual nonsense ($100,000 in Facebook ads; Pokemon), we the most serious numerical allegation yet – $2.3 million on a troll factory (broken by the Russian news outlet RBC – so much for the trope of “no adversarial investigation journalism” in Russia).

The obvious question: If all it takes to swing a US election is a few millions of dollars (versus the almost a billion spend by the respective campaigns), why isn’t everyone doing it?


* Bryan MacDonald: Ukraine has a Nazi problem and a Western media problem

This is a typical pattern:

  • Western MSM 1,000 Nazis march in Charlottesville: OY VEY DRUMPF & PUTLER MUST PAY
  • 20,000 Nazis march in Kiev: meh

* Russia now plans to build a $10 billion bridge to… Sakhalin, with its half a million people. $10 million is approximately what the federal government gives to the Ministry of Education every year.

Rotenbergs are more important, though.

There are hopes of getting Japan involved:

Russia is counting on Japan to join the project by connecting its northern island of Hokkaido to Sakhalin with a 40-kilometer link of its own, the people said. While an overland crossing from Japan could be an economic game changer for Russia’s Far East, they cautioned there’s been no talks or agreements yet with the government in Tokyo.

Japanese Prime Minister Shinzo Abe was circumspect when asked about the plans at the Vladivostok forum with Putin last month.

“It would be fine to travel to Vladivostok by train,” Abe said. “But for this, our countries need to strengthen mutual trust to make all projects achievable.”

But this is Japanesespeak for “LOL, no.”



* Audacious Epigone: Dysgenics much stronger for Blacks and Latinos than for Whites. JayMan has also noticed this.

Also notes that number of children is positively correlated with mental health.

* The Economist: College students are more accepting of controversial speech



* is an Ossetian nationalist site (in Russian). In case you are interested in what (very little) Ossetians think of their Ingush, Dagestani, and Georgian neighbors.

Apparently the Ingush believe that Ossetians effect territorial expansion through “hospitable prostitution.” Small country nationalisms are so cute.

The style and format clearly owes a lot to Sputnik i Pogrom, which has – amongst other things – inspired a Ukrainian, a Belorussian, and a radical Islamist (!) copycat.


* Latest from (Russian language) ROGPR podcast: Our main host Kirill Nesterov makes a highly autistic 45 minute video review of TES: Morrowind, and we discuss Putin’s legacy.

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What the commenter Cicerone wrote in response to the study about dysgenic decline in Germany.

The findings come rather surprizing to me and I am always sceptical of using these low N studies to make out trends.

Using fertility by education data from the Wittgenstein database, my estimate for the intrinsic IQ loss over the next generation is 1.0. That of course doesn’t take migration into account and only incorporates differences in fertility rates by education classes. Contrary to the past, these fertility rates don’t differ that much anymore. University educated women in Germany have a TFR of 1.3, vs. 1.45 for medium educated women and 1.6 for the least educated.

Fertility driven IQ losses per generation for other countries:

Belgium and Finland: 0 (the best scoring countries in the world, no dysgenic fertility here, rest of Scandinavia not far behind)

Canada: -0.4
Indonesia: -0.6 (best scoring developing country)
Japan: -0.8
UK: -1.0
Germany: -1.0
Italy: -1.2
China: -1.3
France: -1.3 (France has a very fertile underclass compared to the UK or Germany)
South Korea: -1.4
Singapore: -1.4 (the only country openly following eugenic fertility policies, with dismal results it seems)
Australia: -1.6
USA: -1.7
Russia: -1.8
Poland: -2.2
Romania: -2.9 (worst scoring European country, everyone knows why)
India: -3.2
Mexico: -3.3
Nigeria: -3.4
Iran: -3.6
Turkey: -3.6
Brazil: -3.9 (worst scoring major country, educated women in Brazil have extremely few children (1.2 on average))
Afghanistan: -5.1 (worst scoring country on earth)

• Category: Race/Ethnicity • Tags: Dysgenic, Psychometrics 
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I posted about German regional academic performance back in 2016.

The evidence seemed to indicate that German IQ was fairly uniform across Germany, once you took the immigrants out.

However, soon afterwards I got the following curious email from one Carolin:

I stumbled upon a few studies (one done by the German military, when there was still a mandatory draft), that put the regional differences at much higher values than a few IQ points. Basically, there were many regions, where the AVERAGE recruit was in the best/worst 10%, which would dwarf even the black-white-gap.

You can read the report here (I can’t read German so you’ll have to tell me the details):

Map of conscript test performance according to a 1998 study:


What I take to be some test administered in schools:


They also reference another school test carried out by Bertelsmann and published in the Deutsche Lernatlas around 2011:




• Category: Race/Ethnicity • Tags: Germany, IQ, Psychometrics 
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Will be going off to my dacha this week so probably not much poasting.



This week’s events have been dominated by the Charlotteville clashes, and the resulting cyberpurge of the Alt Right and mass felling of Confederate monuments.

Now comes news of the resignation of Steve Bannon.

It will certainly be fun to see the 666D chess theorizing on this one. T he man himself, at any rate, isn’t bothering: “The Trump presidency that we fought for, and won, is over.”

This just leaves Stephen Miller and Sebastian Gorka as representatives of the populist wave that brought Trump to power. All the others have been purged.

Meanwhile, power has drifted towards Wall Street/Goldman Sachs globalists, the Kushner-Trumps, and a triumvirate of warhawk generals (Chief of Staff Gen. Kelly; NatSec Advisor Gen. McMaster; Secretary of Defence Gen. Mattis).

In foreign policy terms, I suppose the main saving grace of this administration – as opposed to an alternate history Hillary Clinton’s – is that Trump has alienated much of the rest of the world. Acording to a recent PEW poll, most countries trust Trump even less than Putin, who needless to say has some major PR problems of his own.


This was, perhaps, unfortunate back when America First was the order of the day, but now that the US is ruled by a nepotistic junta guided by Kushner’s vision, the world’s skepticism towards Trump might become a blessing in disguise, limiting the damage that the people around him can do in the next three years.



* Scott Alexander covers Effective Altruism Global 2017:

I got to talk to people from the Qualia Research Institute, who point out that everyone else is missing something big: the hedonic treadmill. People have a certain baseline amount of happiness. Fix their problems, and they’ll be happy for a while, then go back to baseline. The only solution is to hack consciousness directly, to figure out what exactly happiness is – unpack what we’re looking for when we describe some mental states as having higher positive valence than others – and then add that on to every other mental state directly. This isn’t quite the dreaded wireheading, the widely-feared technology that will make everyone so doped up on techno-super-heroin (or direct electrical stimulation of the brain’s pleasure centers) that they never do anything else. It’s a rewiring of the brain that creates a “perpetual but varied bliss” that “reengineers the network of transition probabilities between emotions” while retaining the capability to do economically useful work. Partly this last criteria is to prevent society from collapsing, but the ultimate goal is:

…the possibility of a full-fledged qualia economy: when people have spare resources and are interested in new states of consciousness, anyone good at mining the state-space for precious gems will have an economic advantage. In principle the whole economy may eventually be entirely based on exploring the state-space of consciousness and trading information about the most valuable contents discovered doing so.

If you’re wondering whether these people’s research involves taking huge amounts of drugs – well, read their blog. My particular favorites are this essay on psychedelic cryptography ie creating messages that only people on certain drugs can read, and this essay on hyperbolic geometry in DMT experiences.

* Wired: Biohackers Encoded Malware in a Strand of DNA.

So this is how Tyranids beat Necrons.


* Wongupparaj, Peera – 2017 – The Flynn effect for verbal and visuospatial short-term and working memory: A cross-temporal meta-analysis

Based on the findings from a cross-temporal meta-analysis using 1754 independent samples (n = 139,677), the Flynn effect was observed across a 43-year period, with changes here expressed in terms of correlations (coefficients) between year of publication and mean memory test scores. Specifically, the Flynn effect was found for forward digit span (r = 0.12, p < 0.01) and forward Corsi block span (r = 0.10, p < 0.01). Moreover, an anti-Flynn effect was found for backward digit span (r = − 0.06, p < 0.01) and for backward Corsi block span (r = − 0.17, p < 0.01). Overall, the results support co-occurrence theories that predict simultaneous secular gains in specialized abilities and declines in g.

James Thompson review: Working memory bombshell

* Davies, Gill – 2017 – Ninety-nine independent genetic loci influencing general cognitive function include genes associated with brain health and structure (N = 280,360)

We found 9,714 genome-wide significant SNPs (P<5 x 10-8) in 99 independent loci… Genetic association results predicted up to 4% of general cognitive function variance in independent samples. There was significant genetic overlap between general cognitive function and information processing speed, as well as many health variables including longevity.

The pace of progress in this sphere is blistering, with major papers published nigh near every month.

* Rabbit reacts to Trump’s Alt Left smear.

(The traditional Alt Left considers itself to be a subset of the Alt Right that but with less thot hate and more rocket ships and radical life extension).

* Noah Carl – 2017 – Cognitive ability and socio-political beliefs and attitudes.

This thesis looks like a very solid, comprehensive overview of the subject.


* New York Times: The engines in North Korea’s newest ICBM’s have been pinpointed to the Yuzhmash missile factory in the Ukraine.

/r/worldnews comment:

After doing some of my own investigation (thank you Google), I am of the opinion that this story is well-supported by multiple sources of evidence. The engine that NK has been using since Sept 2016 is definitely related to the Soviet engine that this factory built until the 1990′s. This factory still has these engines, and officially continued maintaining them until mid-2015. North Korean spies/officials were detained by Russia in 2011-2012 when they attempted to enter Ukraine to head to this factory. Ukraine fell apart economically and politically in the 2013-2016 period, and this factory announced it would go bankrupt in early 2015, but then somehow managed to survive. Ukraine has a long history of substantial black market arms trading, some of their rockets have ended up in Iran, Syria, and Pakistan. The best Soviet engineers were stationed in Eastern Ukraine during the Cold War for mainly political reasons (most Soviet leaders were ethnically Ukrainian). As for the engine/missile itself, the trajectory of the launches are similar to tests in the Soviet Union during the 70′s-80′s. The design is very similar in the photos that NK has shown. The dimension of the rocket body and the stages are almost a mirror image of the 1980′s examples. US intelligence officials, and the former CIA head, hinted that the US intelligence community was “caught offguard” by the “unlikely pace of the NK missile program” because of “certain factors”. That seems to indicate that the CIA believed (as of late 2016) that NK had somehow received foreign help that substantially boosted the program. Finally, NK has utilized similar tactics to gain a hold of short and medium range missile technology in the 1990′s. They worked closely with Central Asia, Pakistan, and Ukraine to boost their Ulan missile program. Let’s not forget that NK is well-known for its very savvy black market program and unofficial spy network. There were even NK officials found in Syria back in 2015, most likely eyeing the S-300 missiles that Russia brought there.


* Thomas Piketty et al. – 2017 – From Soviets to Oligarchs: Inequality and Property in Russia, 1905-2016

Uses his methods from Capital in the 21st Century to calculate historical inequality in Russia, one of his conclusions is that the welfare of the median Russia hasn’t budged relative to 1989.

There is a point to Bershidsky’s critique that inequality in the USSR was primarily expressed in terms of access, not income differentials, so making direct comparisons with capitalist countries are questionable.

* Latest Navalny investigation: The son of Putin’s spokesman Peskov, Nikolay Chole, lived as hoodlum chav in the UK, with convictions and prison time for stealing cell phones with his Black and Pakistani gangmates; gets luxury car collection, horses on returning to Russia.

* Apart from all his other faults, Alexey Navalny is also a console peasant. Sad!

* Kirill Nesterov, my partner on the ROGPR podcast, has produced two (Russian-language) videos:


* Steve Sailer: Is India the world’s most reactionary civilization?

* Nicholas Nassim Taleb: The insidious racism of Mary Beard and the “diversity” operators

* Some baizuo: Beyond the pale: China’s cheerful racists

To many Chinese, ideas about racial hierarchies are not outdated anathema but unquestioned belief.

In Britain, a politician who uses a defunct idiom like ‘nigger in the woodpile’ loses the whip. In China, racism is a standard undercurrent of public debate. A few months ago, Pan Qinglin, a Tianjin politician, announced to reporters that he had found out how to ‘solve the problem of the black population in Guangdong’ — a province with a small amount of African migration. Warning that the new arrivals brought drugs, sexual assault and infectious diseases, he urged local policy-makers to tighten controls to prevent China turning ‘from a yellow country to a black-and-yellow country’. …

If China wants to realise its aspiration of replacing America as the country the world looks up to, it will need to sort out its race problem. It is an issue which fuels unrest at home, and damages the country’s reputation abroad. Xi Jinping has talked about a ‘Chinese dream’ — let’s hope it exports tolerance, not racism.


* % Europeans that say that generally most people can be trusted. Belorussia can into Hajnal Line!

* Nature: China’s embrace of embryo selection raises thorny questions. (Can anyone spell them out to me?).

* James Thompson: Google Culture Wars (if anyone is still interested in the James Damore affair)


This is really just about the continuing fallout from Charlottesville.


* NYT: Amateur Sleuths Aim to Identify Charlottesville Marchers, but Sometimes Misfire.

The intensity of the meltdowns is something to behold. I have seen people disowning their children/parents/siblings just for supporting the racist/fascist Trump. Really hard to understand this mindset.

sjws-never-relent For instance, the father of Peter Tefft, a participant in the Unite the Right rally, went so far as to write a public letter denouncing and disowning his son. Not that this saved him from the SJW horde, which began to ask questions about the family’s responsibility for the son’s racism.

His sister, BTW, is a pot-smoking lesbian anarchist. One can perhaps imagine why he radicalized.

sjws-report-pharmacist It’s hard to be surprised after this, but perhaps the most striking case of Charlottesville Derangement Sundrome I found is a man with self-evident mental problems thinking about reporting his pharmacist for Nazism at /r/politics.

The patient’s reasons for suspicion? Because his pharmacist has a “1776 tattoo and I think maybe an 88 one too, he’s pale and blue eyed and has shaved his head.”

This was apparently an open and shut case according to the denizens of /r/politics: “Get his ass fired!”

The irony that they were singling out someone for persecution on the basis of his skin color flew right over their heads.

No wonder more and more people are writing about the potential of US Civil War II.

But keep things in perspective – the US doesn’t have the ethno-religious fragmentation of Syria or sharp ideological gradient of the Ukraine, and casualties to date have been far lower even than in the 1970/80s terror campaigns of fringe Communist groups in Europe and Japan.

* Audacious Epigone suggests the Alt Right adopt the Maltese Cross of the Crusaders instead of the Nazi swastika.

american-soldiers-support-separation* In response to Jeffrey Goldberg’s strange claim that Saving Private Ryan was about “a group of very aggressive alt-left protesters invading a beach without a permit,” Timofey Pnin points out that American GI’s were hardcore Alt Right by today’s standards.

More on the Cyberpurge

* Matt Forney: Night Of The Digital Knives: Silicon Valley Launches Biggest Internet Censorship Purge In History

* Jason Reza Jorjani, one of the three main people behind (the other two are Richard Spencer and Daniel Friberg), is resigning from the Alt Right to focus on creating an Iranian nationalist party in exile:

What this also means is that from this moment onward my responsibilities to the cause of liberating Iran from the Islamic Republic have dramatically increased. As I see it, we have several years to form the nucleus of a new regime, before rootless globalists and their Islamist pawns succeed in steering the collapse of the Islamic Republic in a direction that further erodes Iran’s territorial integrity and aborts its cultural rebirth.

* Greg Johnson has compiled the most comprehensive list of shuttenings I have seen to date:

  • Counter-Currents has been booted by PayPal and our Facebook page has been deleted.
  • Both Red Ice servers were hacked, as were the site owners’ Twitter accounts, and still have not recovered.
  • VDare,, and AmRen were bounced from PayPal.
  • VDare’s conference next April has been shut down by the venue.
  • TRS was taken down by their webhosting company, but got a new host and were back online in 3 hours.
  • Mike Enoch was banned for the fourth time from Twitter.
  • KickStarter, GoFundMe, and IndieGoGo have all vowed to shut down campaigns related to White Nationalist concerns.
  • Pax Dickinson’s Twitter has been shut down.
  • Hatreon is offline.
  • PolNewsForever’s Twitter has been shut down.
  • The Daily Stormer has been targeted with massive DDOS attacks.
  • The Daily Stormer domain registration was dropped by GoDaddy, transferred to Google, and then seized by Google.
  • The Daily Stormer discord server has been shut down.
  • The discord server has been shut down.
  • Vanguard America’s WordPress and Facebook accounts have been shut down.
  • Spotify has removed 27 “hate” bands as defined by the SPLC.
  • GoFundMe has taken down campaigns to help James Fields.
  • RootBocks has been taken down by its hosting company, but is back online.
  • Xurious has been removed from Bandcamp and Soundcloud.
  • Daniel Friberg and Christopher Dulny, both Swedes, have been barred from entering the United States because of their presence at Unite the Right.
  • Lauren Southern’s Patreon account has been taken down.
  • Lauren Southern’s Instagram has been taken down, but is now back up.
  • NPI’s Paypal account has been shut down.
  • Two upcoming speeches by Richard Spencer have been canceled.
  • Identity Europa’s PayPal has been shut down.
  • Christopher Cantwell’s Facebook, PayPal, and website are gone.
  • Weev’s LinkedIn account has been shut down.
  • The Paranormies and other podcasts have been kicked off of Soundcloud.
  • YouTube had demonitized controversial videos, making it impossible for dissident video bloggers to make a living from their work.
  • Airbnb combed through the social media of people with Charlottesville-area registrations on Unite the Right weekend, and canceled the reservations and accounts of Unite the Right attendees
  • Uber has cancelled Baked Alaska’s and James Allsup’s accounts.
  • Squarespace is dropping multiple Right-wing sites.
  • A Toronto free speech event with Faith Goldy, Jordan Peterson, and Gad Saad has been cancelled.
  • Christopher Cantwell’s OKCupid account has been closed.
  • Expedia cancelled flights of people they suspected were attending Unite the Right.
  • Google removes Gab app from Android store.
  • Alternative Right, ed. Andy Nowicki and Colon Liddell, removed by Blogger
  • Mailchimp drops accounts from American Renaissance and Identity Europa.


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The population of the world’s major regions according to the UN’s World Population Prospects 2017 report.

World Population Prospects (2017) 2015 2050 2100
WORLD 7,383,008,820 9,771,822,753 11,184,367,721
Sub-Saharan Africa 969,234,251 2,167,651,879 4,001,755,801
East Asia 1,635,150,365 1,586,491,284 1,198,264,520
South Asia 1,823,308,471 2,381,796,561 2,230,668,781
South-East Asia 634,609,846 797,648,622 771,527,666
MENA & C. Asia 551,964,576 850,895,914 1,045,856,658
Europe 740,813,959 715,721,014 653,261,252
Latin America 632,380,831 779,841,201 712,012,636
North America 356,003,541 434,654,823 499,197,606
Oceania 39,542,980 57,121,455 71,822,801

Assume the usual S.D.=15, and that their average IQs as of 2017 are as follows: Sub-Saharan Africa 70, East Asia 100, South Asia 80, South-East Asia 85, MENA & C. Asia 85, Europe 100, Latin America 85, North America 100, Oceania 90.

This should look plausible to people who’ve looked at the data. East Asian (Japanese, Korean, Chinese) IQ tends to be higher than 100, usually around 103-105, but I am giving it as 100 because in practice, for unclear reasons, East Asian IQs also tend to be “worth” 5 points less than Euro-American ones so far as economic performance and human accomplishment go.

Anyhow, if we also assume that regional IQs will remain “fixed” for the rest of the century, then the world average IQ will drop from 87 today to 82 by 2100, primarily on account of the massive demographic expansion of Sub-Saharan Africa.

However, fortunately, the number of people belonging to smart fractions” – which I will denote as people with an IQ above 160 (the approximate level that you have to be at to be capable of contributing to elite scientific progress today) – will remain similar to today, though it will be negatively impacted by demographic decline in Europe and East Asia.

Smart Fractions (No Flynn) 2015 2050 2100
WORLD 87,196 87,580 75,397
Sub-Saharan Africa 1 2 4
East Asia 51,787 50,246 37,951
South Asia 88 115 108
South-East Asia 182 229 221
MENA & C. Asia 158 244 300
Europe 23,462 22,668 20,690
Latin America 181 224 204
North America 11,275 13,766 15,810
Oceania 61 87 110

But what happens when we adjust for the FLynn effect? In his 2016 survey of psychometrists, Heiner Rindermann and co. compiled the following expert assessments.


This leads to a massive increase in the number of smart fractions, almost entirely on account of East Asia.

China as a now fully developed country drives global scientific progress pretty much single-handedly, like Europe did in the 19th century.

IQ Flynn (Rindermann) 2015 2100
WORLD 87,196 294,485
Sub-Saharan Africa 1 63
East Asia 51,787 245,857
South Asia 88 1,266
South-East Asia 182 1,181
MENA & C. Asia 158 1,155
Europe 23,462 27,364
Latin America 181 1,504
North America 11,275 15,810
Oceania 61 285

That said, I don’t think those FLynn projects are realistic, in part because East Asia is projected to increase in IQ so incredibly fast even though it is already a reasonably well developed place.

China itself can still probably eke out 3-5 IQ points, but Chinese fertility has been dysgenic since the 1960s, so this won’t last. I suspect East Asia – which in demographic terms is pretty much just China – will remain at a consistent level, with FLynn and dysgenics canceling each other out over the course of the century.

What if we use the following estimates for IQ changes during the 21st century (broadly justified here):

  • +10: Sub-Saharan Africa, South Asia
  • +5: South-East Asia
  • 0: East Asia, MENA & Central Asia, Latin America
  • -5: Europe, North America

Resulting table of smart fractions in 2100:

IQ Flynn (AK) 2015 2100
WORLD 87,196 51,726
Sub-Saharan Africa 1 193
East Asia 51,787 37,951
South Asia 88 3,414
South-East Asia 182 1,181
MENA & C. Asia 158 300
Europe 23,462 4,797
Latin America 181 204
North America 11,275 3,666
Oceania 61 21

So what has basically happened is that smart fractions plummet in the high-IQ world due to a combination of demographic decline, dysgenic fertility, and low-IQ mass immigration.

Meanwhile, the quantity of smart fractions from the Global South will rise, due to some FLynn catchup, but absolute numbers will remain modest.

Overall, this is a pretty catastrophic outcome.

Not only do we see a halving of 160+ IQ smart fractions, but it is also very likely that the threshold for new scientific discoveries will have risen in the meantime, since problems tend to get harder, not easier as you climb up the technological tree.

For instance, if by 2100 the new “discovery threshold” is at an IQ of 175, the people still capable of driving global science forwards might number in the mere hundreds, in a world of more than ten billion.

The likely end result of this would be an end to scientific progress, and eventually, the Age of Malthusian Industrialism once a technologically stagnant and progressively more fecund world bumps up against the limits of the industrial economy.

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I don’t know how, but Lynn, Cheng, and Russian psychometricist Grigoriev have managed to find Russian regional results for PISA 2015.


Moscow has plummeted in the rankings and is now fourth, whereas Saint-Petersburg is now first.

I have calculated the correlations with the PISA 2009 results, for regions that participated in both surveys, to be a pretty weak r=0.52. As you can see, the samples for each region are pretty small, typically around 100, though relatively more schoolchildren were tested in the capitals: 245 in Saint-Petersburg, and 373 in Moscow.

The Yakut-majority Sakha Republic has improved drastically, by half an S.D., so it is no longer last, but modestly below average (this ties in with Vladimir Shibaev’s recent work in 2017 which shows that Yakut IQ might be similar to Russian, and not drastically lower, as an earlier study from 2015 had indicated). That “honor” now belongs to Dagestan, which remains stuck at a PISA-equivalent IQ in the high 80s.


Lynn et al. also did their standard correlation exercises.

Other tests of academic achievement (average Unified State Exam results of those admitted to universities from 2014) and historical literacy (1897 census):

Note in particular that the province of Dagestan has the lowest PISA score (424.1) and the second lowest EQ (84); and also that the city of St. Petersburg has the highest PISA score (524.4), the highest EQ (111) and the highest literacy rate in 1897 (61.6%). The city of Moscow has the fourth highest PISA score (516.4), the second highest EQ (110) and the second highest literacy rate in 1897 (53.1%).

GDP per capita:

Second, the PISA scores were correlated at r = .31 with GDP per capita. The correlation falls just short of statistical significance at p<.05 (r = .32 would be statistically significant).

wealth-iq-russia This is because some Russian regions have resource windfalls amidst low populations, e.g. Khanty-Mansyisk AO, which accounts for half of Russia’s oil output and enjoys a Swiss-like standard of living.

If you only consider “normal” Russian regions, the correlation becomes a much more typical r=0.73 (the graph to the right is based on results from PISA 2009 and PPP-adjusted Gross Regional Products from 2008.

Russian ethnicity:

Third, the PISA scores were significantly correlated at r = .45 (p<.01) with the percentage of the population with Russian ethnicity. This result is confirmed by the multiple regression analysis showing that the percentage of Russian ethnicity was a significant predictor of the PISA scores (β = .36, t = 2.68, p<.01).

Cold winters:

Fourth, the PISA scores were significantly correlated at r = .35 (p<.05) with latitude showing that IQs are higher in the more northerly provinces.

• Category: Race/Ethnicity • Tags: IQ, Paper Review, Psychometrics, Russia 
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Grigoriev, Andrey & Lynn 2009
Studies of Socioeconomic and Ethnic Differences in Intelligence in the Former Soviet Union in the Early Twentieth Century


This paper reviews the studies of socioeconomic and ethnic and racial differences in intelligence carried out in Russia/USSR during the late 1920s and early 1930s. In these studies the IQs of social classes and of ethnic minorities were tested. These included Tatars (a Caucasoid people), Chuvash and Altai (mixed Caucasoid-Mongoloid peoples), Evenk (a mixed Caucasoid-Arctic people), and Uzbeks (a Central-South Asian people). The results of these studies showed socioeconomic differences of 12 IQ points between the children of white collar and blue collar workers, and that with the exception of the Tartars the ethnic minorities obtained lower IQs than European Russians.

This is essentially a short history of psychometrics in the USSR/Russia.

(1) The first measurement of Russian IQ was performed in 1909 by A.M. Schubert, who used the French Binet test with n=229 children: “She concluded that the Binet test appeared to be too difficult for Russian children and the scale should be moved on 1 to 2 ages to be appropriate for them.” Since Mental age ÷ Physical age × 100 = IQ, this implies their average IQ was perhaps one S.D. lower than that of the French, though later researchers pointed out those children were drawn from lower socio-economic strata.

In 1930, now in the USSR, another study found the following:

They tested 414 children aged between 8½ and 11½ with the American Stanford– Binet (administered in Russian translation). The sample consisted of 200 children of peasants,141 children of blue collar workers, and 73 children of white-collar workers. All children were from Moscow or the Moscow region. The results were that the children of peasants obtained a mean IQ of 87 (the standard deviation=10), the children of blue-collar workers a mean IQ of 91 (SD=8.6) and the children of white-collar workers a mean IQ 98 (SD=8.4). The mean IQ (unweighted) for three groups was 92… Thus, the total weighted mean for Russian children in this study was 90.3 (these IQs are in relation to American Stanford–Binet norms).

Capture This brings to mind a 1920s study quoted by Anne Anastasi in her book Differential Psychology (pp.524), in which Russian immigrant children to the US got 90.

This 10 point difference was presumably there because Russia was a more economically backwards country, with a more repressed average IQ due to gaps in schooling, malnutrition, parasitic load, etc.

(2) As in the West, consistent differences were found in the IQs of people from different socio-economic strata.

Another study of relation of IQ to social class was carried out by M. Syrkin (М.Сыркин)(Сыркин,1929) who compared the intelligence of fourth grade children (N=338, age approximately 10 years) belonging to six socio-economic groups. The lowest group was described as “ blue collar workers and at least one of parents illiterate”and the highest group was described as “white-collar workers and at least one parent educated in an institute of higher education”. Intelligence was assessed with five verbal tests measuring comprehension and verbal reasoning. There was a difference of 1.42d(equivalent to 21.3 IQ points) between the lowest and highest socioeconomic groups.

The USSR really did expel, kill off, or otherwise limit the reproductive fitness of its best and brightest.

In 1928, E.I. Zverev (Е.И. Зверев)(Зверев, 1931) tested the IQ of 114 children just admitted to school and aged about 7½– 8 years, in and around the city of Kursk, about 500 km south of Moscow. The children were tested with the Binet– Bert test (a Russian adaptation of the Binet). The mean IQ of these children was 80.8. This is much lower than the IQ of children obtained by Gurjanov, Smirnov, Sokolov, & Shevarev (Гурьянов, Смирнов, Соколов,&Шеварев, 1930) for Moscow and the Moscow region. Probably this difference was due to methodological and sample differences, but there is a possibility that the regional factor was also involved.

The latter hypothesis is likely the correct one.

In the 2009 PISA test, there was a 12 IQ point difference between Kursk and Moscow, which is an incredibly concentrated cognitive cluster.

(3) Now we go on to the most “controversial” part – ethnic differences in IQ.

Central Russia

There were also some studies of the IQs of non-Slavonic but predominantly Caucasoid peoples.I. Bektchentay (И .Бикчентай) and Z. Carimowa (З.Каримова )(Бикчентай &Каримова, 1930) tested the IQs of 380 Tartar children aged 8– 18 in fi ve Tartar schools in Moscow with the Boltunow–Binettest(aRussian adaptation of the Binet). The Tartars are indigenous to the Caucasus in the far south of Russia and the former Soviet Union, but a number of them live in central Russian towns and cities. The mean IQ of the Tartar children in this study was approximately the same as that of Russian children. The correlation between the Boltunow– Binet test and school achievements (assessed by teachers’ estimates) in their study was 0.84.

Yes, this is a pretty major distinction.

The Volga Tatars – the Muslim and Christianized Tatars of central Russia – have an average IQ of around 100 (about equal to modern Russia/Europe). Population genetics studies have found them to be basically acculturated Slavs.

The first of these was reported by F.P. Petrov (Е.П. Петров) (Петров, 1928) who tested the IQs of 1398 Chuvash children aged 3–13 in 1926–1927 with the French Binet–Simon test… The figures inTable 2 show a median IQ of 87 for boys and 84 for girls, and means (unweighted) of 89 for boys and 86 for girls. These are in relation to 100 for French norms, but no normative data are reported for Russian children. The IQs of the Chuvash children show a decline with age, with the lowest IQs among the 12 and 13 year olds.

Chuvashia is currently about average for the Russian regions.


Also tests carried out on indigenous tundric peoples, such as the Evenks (Bulanov 1930):

The results are presented as typical for Evenk children, but because of the small samples, their IQs may not be regarded as reliable. The results are as follows. For the Binet test the mean IQ was 70.16 (for 5 children, and in relation to French norms). The results obtained with the Rossolimo test showed lower average IQs of the Evenk (Tungus) compared with a Moscow sample on some abilities, namely, memory for pictures and words, ability to comprehend combined pictures, ability to comprehend visual incongruities, and, according to Bulanow’s interpreta- tion, ability to retain a high level of attention. As regards memory for pictures, the results contradicted the sometimes described capacity of Evenk (Tungus) to remember exactly long routes on wild territory (Encyclopedic Dictionary by Brockhaus & Efron (Энциклопедический словарь Ф .А . Брок – гауза и И.А .Ефрона ), 1902, vol. 67, p. 66)….

Bulanow also reported some observations on Evenk (Tungus) children and adults concerning their great difficulty in understanding the concepts of measurement and number. He reported that when Evenk children were questioned about devices for measurement, they did not have the concept of an absolute unit of measurement. They thought that the unit changed with the material measured. Bulanow reported further that when he asked Evenk adults how many children they had “ It was difficult, almost impossible, to get from parents precise information as to how many of their children were alive, how many of their children had died, what was the age of their children, and so on.” (p. 198).

… and on the Altai (Zaporochets 1930):

The results for the Binet test were as follows: mean IQ for total group was 66.9 (sd. 8.5), mean IQ for children aged 8– 12 was 69.15, and the mean IQ for children aged 13–16 years was 64.8. As noted by Zaporojets, this test was tedious for the Altai children. Some tasks were especially difficult for them. These were tasks involving calculation, logical operations, and the fluency task to name as many as words as possible during 3 min. As for the Rossolimo test, the most diffi cult tests for Altai children were those requiring the ability to retain a high level of attention and to comprehend visual incongruities. Their mean IQ for the Pintner–Peterson test was 75.

Zaporojets noted that the Altai children did not have a clear understanding of units of measurement. He observed that when they were questioned about the length of a meter, the Altai would often ask: “Which meter?”They thought that the meter in one shop could be longer than in another. An adult Altai said about distance: “It is 100 big versts (approximately 100 kilometers)” (he apparently thought that the number of small versts must be more).

Zaporojets’ paper contains some interesting observations on adult Altai. Although adult Altai performed calculations poorly at the time of study, they showed a remarkable ability for visual estimation of large quantities. A herdsman, who could count only to 20–30, noticed very well the absence of one horse, cow or sheep in a herd of many hundreds. He looked at a huge herd and noted that a particular cow was absent. Another example of the great visualization ability of the Altai was that they could remember and showed the way through wild territory, where they had been only once many years previously.

Common theme: No numeracy (they’d have a very bad Whipple’s index), very premodern and non-abstract ways of thinking, but quite well suited for their environment.

In PISA 2009, Yakutia had the lowest score of any tested Russian region, including Dagestan (though Chechnya and Ingushetia were not included). Ethnic Yakuts, who probably have similar IQs to the Altai and Evenks, constitute 50% of its population, though probably more like 2/3 amongst the children taking PISA due to their higher fertility rates. This might imply that the average Yakut IQ is in the low-to-mid 80s.

Central Asia

First test was carried out in 1926 by A. Schtelerman: He did not give IQs but reported that the scores of the Uzbek children were lower than those of children in Moscow.

A series of studies by V.K. Soloviev on Russian and Uzbek army cadets and professionals found that “the test scores and the educational level of the Uzbeks were lower than those of the Europeans.”

The third study of the intelligence of the Uzbeks was carried out in 1931 by A.R. Luria (А.Р . Лурия ), at that time at the Institute of Psychology in Moscow. Luria did not use intelligence tests but gave a descriptive analysis of the Uzbeks’ cognitive abilities. He distinguished two modes of thought designated graphic recall (memories of how objects in the individual’s personal experience are related) and ca- tegorical relationships (categorisation by abstract concepts). He found that the thought processes of illiterate Uzbek peasants were confined to graphic recall and that they were not able to form abstract concepts. For example, they were shown a hammer, an axe, a log and a saw, and asked which of these did not belong. The typical Uzbek answer was that they all belonged together because they are all needed to make firewood. People who are able to think in terms of categorical relationships identify the log as the answer because the other three are tools (an abstract concept). Illiterate Uzbeks peasants were unable to form concepts of this kind. They were also unable to solve syllogisms. For instance, given the syllogism “There are no camels in Germany; the city of B is in Germany; are there camels there?” Luria gave as a typical Uzbeks answer “I don’t know, I have never seen German cities. If B is a large city, there should be camels there.” Similarly, Luria asked “In the far north, where there is snow, all bears are white; Novia Zemlya is in the far north; what color are the bears in Novia Zemlya?”. A typical Uzbek answer was “I’ve never been to the far north and never seen bears”(Luria,1979, p. 77–8). Thus, Luria concluded that these peoples were not capable of abstract thought: “ the processes of abstraction and generalization are not invariant at all stages of socioeconomic and cultural development. Rather, such processes are pro- ducts of the cultural environment” (Luria, 1979, p. 74). Luria proposed that the ability to think in terms of categorical relationships is acquired through education. He did not suggest that the Uzbeks have any genetic cognitive deficiency.

I wrote about Luria back in the late 2000s when I still agnostic about genetic racial differences in IQ.

Today those factors no longer really hold, but Central Asians do very poorly on international standardized tests.

Kyrgyzstan came at the very bottom of PISA 2009, with a PISA-equivalent IQ of around 75.

Table below is from David Becker’s database of national IQs:

National Ethnic Age N Test IQ Study
Kazakhstan 8 to 16 617 SPM+ 87.30 Grigoriev & Lynn (2014)
Kyrgyz 85.60 Lynn & Cheng (2014)
Tajikistan 13 to 15 674 SPM+ 88.00 Khosimov & Lynn (2017)
Uzbekistan 10 to 15 51 SPM+ 86.00 Grigoriev & Lynn (2014 )
Uzbekistan 11 to 13 614 SPM+ 85.00 Salahodjaev et al. (2017)

Still, Luria has some of the best arguments against that position, so its a bit surprising that the blank slatists don’t cite him more.

stalin-the-tajik(4) Or maybe not, because it still didn’t save him him from the SJWs’ ideological predecessors, Sovok Justice Warriors:

These early studies carried out in the years 1926– 1931 found that there were substantial socioeconomic and ethnic/ racial differences in intelligence in the Soviet Union. These conclusions were not consistent with Marxist orthodoxy which held that these differences would disappear under communism. Accordingly, these studies, particularly that of Luria, attracted a great deal of criticism in the Soviet Union in the early 1930s. This has been described by Kozulin (1984): “Critics accused Luria of insulting the national minorities of Soviet Asia whom he had ostensibly depicted as an inferior race. The results of the expedition were refused publication and the very theme of cultural development was forbidden” . In 1936 intelligence testing was banned in the Soviet Union. It was not until the 1960s and early 1970s that this prohibition was progressively relaxed (Grigorenko & Kornilova, 1997). Luria’s work was not published in Russian until 1974 and English translations were published in 1976 and 1979 (Luria, 1976, 1979).

As Lynn and Grigoriev point out, this was closely correlated to the suppression of genetics research, though at least Luria and Co. weren’t outright murdered like Vavilov.

The history of work on intelligence in the former Soviet Union parallels that of genetics, where mainstream Mendelian theory represented by Nikolai Vavilov in the 1920s was likewise suppressed in the 1930s and replaced by the environmentalist pseudo-genetics of Trofi m Lysenko. The domination of science by political theory was relaxed in the 1960s and 1970s, and in recent decades both intelligence research and Mendelian genetics have been rehabilitated in Russia.

Scientifically, there is real work being done on psychometrics in Russia, though in comparison to the US it is very meager and basically inconsequential.

Since it is not politicized in the US, it is neither promoted nor prosecuted.

If psychometric considerations were to move closer to politics, e.g. by tying them to the hot potato that is Central Asian immigration, things can go any which way. Although Russians have a more commonsense take on these matters – if 25% of Americans seriously think intelligence is a “social construct,” it’s probably more like 5% in Russia. On the other hand, the Leftists, Stalinists, and even many Eurasianists are aggressively opposed to the idea that intelligence is heritable and differs significantly between races, and in the event that the authorities side with them, Russian scientists don’t have the First Amendment or an fair and impartial court system to hide behind.

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Ritchie, Stuart – 2017 – Review of The Rationality Quotient by Stanovich et al.


From Stuart Ritchie’s review of “The Rationality Quotient” by Keith Stanovich et al.:

But it was the reported correlation of the [Comprehensive Assessment of Rational Thinking] with IQ-type tests that was really unexpected, given the authors’ argument that they measure very different constructs. A cognitive composite—made up of tests of analogies, antonyms, and a word checklist (Table 13.11)—was found to have a correlation with the full-scale CART of 0.695. 0.695!

That’s the extent to which actual IQ tests typically load on the g factor and each other. One might even go so far as to propose that rationality is intelligence.

The notion that intelligent people are more prone to irrationality is a cognitive bias, though a very understandable one. The Newton who obsesses over the occult is just considerably more noticeable than some nutter ranting about the End Times.

Greg Cochran counters that Western intellectuals were more likely to fall for “destructive nonsense” than plumbers during the 20th century. I suspect that was more due to intellectuals not understanding plumbers, neither then nor now, rather than any failure of rationality per se. In everyday life, people tend to associate with people of similar intelligence, and have a social circle of about 150 friends and acquaintances.

And guess what? Communism works great within monasteries and universities.

• Category: Race/Ethnicity • Tags: Paper Review, Psychometrics, Rationality 
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Whitley, Elise et al. – 2016 – Variations in cognitive abilities across the life course



New paper by Elise Whitley et al. on age and sex differences in IQ for n=~40,000 British sample.

  • Five tests: Word recall, verbal fluency, and subtraction (loading ~0.5 on g), and number sequence and numerical problem solving (loading ~0.7 on g).
  • Males score about 4 IQ points more on the derived g-factor of cognitive ability.
  • … though this result should be treated with caution on account of: (a) g having different structure across the sexes; (b) it is not an exception to a common problem in IQ and sex studies, namely, the undersampling of men with lower cognitive ability.
  • Better subjective health was associated with higher IQ.
  • The overall pattern across age was a plateau from the late teens to age 65, then a steep fall soon thereafter.

I would say that the ultimate and really the only reason we have mandatory retirement policies are cognitive ones.

EDIT: Emil Kirkegaard had a closer look at the results, including a nicer graph of the age/sex results:

My guess is that the intercept bias/invariance has to do with the composition of the battery. There were only 5 tests, and their breakdown was: 3 math, 1 verbal, 1 memory. Women had better memory but there was no difference in verbal fluency (this is a common finding despite what you have been told). So, the problem likely is that the g factor is colored because 60% of the tests were about math, and that men have an advantage on the math group factor.


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There is a new expert survey out which, amongst other things, queries the world’s top psychometrics experts on the future of the FLynn effect (Flynn + Lynn – clever).

future-FLynn-effect-to-2100 James Thompson has a summary at his column.

The two most important reasons for the end of the FLynn effect in the West are regarded to be “low intelligent more children” (henceforth, “dysgenics“) and migration.

Here is my take (assuming no human genetic editing, neural augs, etc).

East Asia – +0. Have no idea where the high end estimates come from – Japan and Korea are already fully developed and have maxed out their FLynn potential, while China’s indicators on education, nutrition, and social well-being – as is typical in Communist countries – are considerably ahead of its GDP per capita. And the former are more important for IQ than pure wealth. I suspect any further marginal FLynn gains will be canceled out by dysgenics, which have been acting on China since the 1960s (Wang et al., 2016).

India – +10. Currently around 80 according to both IQ tests and PISA. I suspect India’s average genotypic IQ is ~95, though strongly differentiated by caste. However, the dysgenics trend seems to be strong, acting via both region (dirt poor and highly illiterate Bihar is the most fertile, while Kerala with its competent governance and historical achievements in mathematics is the least fertile) and caste (scheduled castes have highest fertility, while the Brahmin share of the population is declining since at least the 1930s).

Africa – +10. Currently around 70-75, suspect it “should be” 85-90, but doubt Africa will actually develop enough socio-economically to fully max out its potential FLynn effect.

Latin America – -3. Few of these countries can be described as truly Third World, especially the more significant ones, and nutrition is quite adequate (e.g. Brazil consumes as much meat per capita as Germany). As such, I suspect most of its FLynn gains have already been actualized! Meanwhile, dysgenic trends amongst the elites are strong, while the lower IQ, more indigenous underclass continues to expand rapidly.

Arab/Muslim countries – -3. A lot really depends on whether they start to seriously clamp down on first cousin marriages, which could raise IQs by as much as 10 points. A few like Tajikistan are taking this seriously, but most are not, and first cousin marriages remain stubbornly high. As such, Arab and Muslim IQs will probably decline due to dysgenics and brain drain arising from future geopolitical convulsions (according to some calculations, solar is already reaching cost parity with fossil fuels; what happens when countries like Saudi Arabia lose their oil rents?).

Australia – +0. Agree with the FLynn experts – any modest dysgenics are cancelled out by their cognitively elitist immigration policy.

Eastern Europe – -3. Less likely to be inundated with Third World immigrants, at least so long as Germany doesn’t become a total dump, but East-Central Europe has already maxed out Flynn, continues to experience brain drain, and Hungary, Romania, and Bulgaria in particular have a Gypsy problem. Russia and Ukraine might gain a couple of points if, as expected, their Soviet-legacy alcoholization epidemics continue to recede; but Russia, in particular, has immigration issues of its own (Central Asia = Mexico), while Ukraine is bleeding out brains and will in all likelihood long continue to do so. Finally, as in Western Europe, fertility patterns are dysgenic in all these countries.

Israel – -5. Will probably plummet as duller nationalists and the religious continue outbreeding seculars, plus brain drain.

Canada – -3. Cognitively elite immigration policy like Australia, but annul their own efforts by importing Somali refugees.

Scandinavia – -4. Sweden Yes!

West-Middle Europe – -4. Strong dysgenics, and huge IQ hit from immigration, but at least for now gets many of the more intelligent Mediterranean Europeans.

West in general – -4.

Southern Europe – -6. Triple whammy from Third World immigration, brain drain to northern Europe, and possibly the most strongly dysgenic fertility patterns in the world.

USA – -3. Latin America will of course continue exerting downwards pressure, but dysgenics amongst White Americans is relatively mild, it attracts the world’s cognitive crème de la crème, the Hispanic baby boom has subsided following the Great Recession, and Trump is promising a Big Beautiful Wall. So I am considerably more optimistic about the US than most. Furthermore, if Europe truly goes belly up, the US may even get a big cognitive boost from the richer Europeans fleeing the fruits of their earlier political choices.

• Category: Race/Ethnicity • Tags: Flynn Effect, Futurism, Psychometrics 
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Now that we have established that immigration is not much good, let’s take a look at another component undergirding our transition to Idiocracy – the differential fertility rates of different IQ groups.

This is a highly contentious topic, and not just on account of the usual political kurfuffles, but also on real disagreements as to its actual extent. Psychologists such as Richard Lynn, Edward Dutton, and Michael Woodley are pessimistic (Woodley 2014; Dutton et al. 2016). OTOH, JayMan has argued based on WORDSUM analysis that “Idiocracy can Wait.” This topic is extra difficult because you also have to disentangle the dysgenics trend from the Flynn effect that has raised IQs in the developed by about 10 points during the 20th century.

The PISA Data Explorer is truly an invaluable tool for bringing the light of cold, hard facts on these issues.

While playing around with it, I noticed you can select the variable “same age siblings,” which ranges from zero to ten. Zero siblings implies, of course, that the student in question is an only child; by definition, the survey excludes entirely the childless portion of the population, which is also its brightest. Data only exists for the Mathematics part of PISA 2000, but it is more than enough to get an idea of the general trend – and as you might expect, it’s not a very good one.

I calculated the “slope” in terms of PISA-adjusted IQ points lost per additional sibling for the first four siblings (in practice, since TFR <<6 for all countries in PISA 2000, the IQ of children from even larger families won’t have much of an effect). See the table at the bottom of this post.

Here are some general points to take away:

(1) Indonesia is the only country, at least as judged from the Math portion of PISA 2000, that has eugenic fertility patterns (since its a developing country with a TFR = c.2.5, we can be pretty sure that childlessness will not impact these statistics down by very much since its simply very rare). Second is Thailand. Both are lower-middle income Asian countries that only escaped the Malthusian trap within living memory and are in the middle stages of the demographic transition. (That said, in PISA 2015, coverage of the 15 year old population was not great in either country – 68% in Indonesia, 71% in Thailand – and assuming that was also generally true in 2000, those not turning up are sure to be less bright and will probably come from more rural, bigger families).

[Epistemic status: Speculative]. However, despite also being within the middle-income brackets, the Latin American countries have moderately dysgenic fertility patterns. I wonder if this could explain Steve Sailer’s observation that Latin American countries seem to have smaller smart fractions than Middle Eastern ones, despite similar average IQs. Maybe their European and, critically, Europeanized, upper classes have simply failed to reproduce in the last couple of generations?

(2) The East Asian and European Nordic states have more eugenic fertility patterns. The European Mediterranean – Greece, Italy, Romania, Portugal, Bulgaria – has some of the worst. France, Spain, Brazil, the UK, Germany, Poland, Russia, and the US all cluster close to each other (though American White fertility is probably more eugenic, perhaps around Australia’s and Canada’s level, since minority and especially Black fertility patterns are known to be highly dysgenic even according to JayMan’s optimistic analysis).

(3) The rate of childlessness is considerably lower, at around 10%, in the ex-Soviet bloc and East-Central Europe than in Western Europe and the US.


This means that their real figures will get a modest boost relative to those of Western Europe, since not as big a percentage of the professional class are getting cut out entirely.

(4) You can’t precisely quantify the dysgenic impact from this with any exactitude, since you’ll also need to combine it far more detailed fertility data.

That data does exist, at least for many of the OECD countries and Russia, so its doable, but it would be a pretty big project.

(5) Eyeballing it there seems to be a moderate degree of correlation with commenter Cicerone’s country estimates of dysgenic fertility extracted from fertility data of educational classes.


IQ vs. #Siblings

Country #0 #1 #2 #3 #4 b
Indonesia 78 82 83 81 80 0.37
Thailand 88 91 90 89 88 -0.16
Japan 103 104 103 103 102 -0.48
Ireland 104 106 106 104 102 -0.51
Iceland 103 102 101 101 100 -0.59
Denmark 99 101 100 98 97 -0.70
Finland 108 108 107 107 105 -0.70
Norway 101 102 102 101 98 -0.71
Sweden 102 104 104 102 99 -0.83
Korea 103 104 103 102 100 -0.88
Chile 87 88 88 85 84 -0.93
Israel 95 96 97 94 91 -0.94
Canada 106 106 105 105 102 -1.07
New Zealand 103 107 106 104 99 -1.13
Australia 105 106 105 102 101 -1.13
Peru 75 80 79 74 71 -1.27
Mexico 89 94 92 88 85 -1.37
Switzerland 99 100 100 98 93 -1.42
Austria 100 100 99 97 93 -1.69
Latvia 95 96 94 91 89 -1.70
Albania 76 81 79 75 70 -1.83
France 102 102 102 98 95 -1.86
Spain 101 100 98 96 94 -1.88
Brazil 87 88 86 83 80 -1.93
United Kingdom 107 106 104 102 99 -1.93
Germany 99 100 97 92 93 -1.93
Poland 101 99 97 92 94 -1.95
Russia 98 96 92 90 90 -2.01
United States 103 105 102 99 96 -2.01
Luxembourg 94 93 91 89 85 -2.17
Hong Kong 106 105 103 101 96 -2.41
Belgium 103 104 102 99 93 -2.45
Czechia 101 101 98 95 91 -2.63
Greece 101 97 95 93 90 -2.66
Hungary 99 99 96 92 89 -2.75
FYROM 80 84 78 72 72 -2.84
Romania 93 92 88 85 81 -3.03
Italy 102 99 96 94 89 -3.03
Bulgaria 92 91 85 83 80 -3.19
Portugal 100 97 94 92 87 -3.20
OECD Average 101 101 99 97 95 -1.57
Total Average 97 98 96 94 91 -1.64


• Category: Race/Ethnicity • Tags: Dysgenic, Fertility, IQ, Psychometrics 
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The commenter “m” did some calculations to work out the relative performance of different countries in PISA vs. TIMSS, and in Math vs. Science.


m writes:

Dimension 1 is overall performance across all 4 (PISA Math, PISA Science, TIMMS Math, TIMMS science). Everything goes up with this dimension. Highest performers: Singapore, Chinese Taipei, Japan. Weakest performers: Turkey, UAE, Malta.

Dimension 2 separates stronger performers on TIMMS vs PISA: strongest performers on TIMMS relative to PISA are in order: Turkey, Korea, Russia, Hungary, United Arab Emirates, while strongest performers on PISA relative to TIMMS are: New Zealand, Canada, Australia, Norway, Italy. The five most balanced countries in the tradeoff are roughly: Slovenia, England, Hong Kong, Japan, USA.

Overperformance in TIMSS relative to PISA can arguably be used as a proxy for schooling quality, since it’s more dependent on academic/curricular skills than on raw intelligence. I am not surprised by the good figures for Korea, Russia, and to a lesser extent, the rest of East Asia and the post-Communist world. However, the UAE and Turkey are surprising.

Dimension 3 separates out Science nations vs Math nations: Most heavily Science vs Math: Slovenia, England, USA, New Zealand, Turkey and most heavily Math vs Science: Hong Kong, Malta, Korea, Italy, Norway.

As much as including TIMMS might be a worse proxy of “IQ” than just PISA, I have included in the above graphic a measure of using the PC1 overall performance score to convert to IQ, based on the assumption that England is 100 and Japan 104.3 as in your PISA conversion. There’s a bit of swing, not too much, compared to PISA alone.

m then extended his analysis to encompass Reading, which is unsurprisingly “less correlated with the other measures”:


as well as to the PIAAC Survey of Adult Skills:



Singapore’s the biggest relative loser when the skills measure is rolled in as well, with the least advantage on PIAAC skills relative to TIMMS / PISA. Most other countries gain compared to the other PCA, as they are more advantaged relative to England and the East Asians on young people’s life skills than they are on young people’s education measures.

• Category: Race/Ethnicity • Tags: PISA, Psychometrics, Statistics 
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There were problems with data collection in Argentina, Kazakhstan, and Malaysia, so their results must be treated with caution.

Furthermore: “Because the results of Kazakhstan in 2015 are based only on multiple-choice items, they cannot be reliably compared to the results of other countries, nor to Kazakhstan’s results in previous assessments” (pp. 81 of the report).

Data for China was drawn from four provinces: Beijing, Shanghai, Jiangsu, and Guangdong. Since the first three of these are known to be cognitive clusters, they are not perfectly representative of China. For further discussion go here: PISA 2015 Released: China Disappoints.


Country Math Reading Science Mean “IQ”
Singapore 564 535 556 551.7 107.8
Hong Kong (China) 548 527 523 532.7 104.9
Japan 532 516 538 528.7 104.3
Macao (China) 544 509 529 527.3 104.1
Estonia 520 519 534 524.3 103.7
Canada 516 527 528 523.7 103.6
Chinese Taipei 542 497 532 523.7 103.6
Finland 511 526 531 522.7 103.4
Korea 524 517 516 519.0 102.9
B-S-J-G (China) 531 494 518 514.3 102.2
Ireland 504 521 503 509.3 101.4
Slovenia 510 505 513 509.3 101.4
Germany 506 509 509 508.0 101.2
Netherlands 512 503 509 508.0 101.2
Switzerland 521 492 506 506.3 101.0
New Zealand 495 509 513 505.7 100.9
Denmark 511 500 502 504.3 100.7
Norway 502 513 498 504.3 100.7
Poland 504 506 501 503.7 100.6
Belgium 507 499 502 502.7 100.4
Australia 494 503 510 502.3 100.4
Viet Nam 495 487 525 502.3 100.4
United Kingdom 492 498 509 499.7 100.0
Portugal 492 498 501 497.0 99.6
France 493 499 495 495.7 99.4
Sweden 494 500 493 495.7 99.4
Austria 497 485 495 492.3 98.9
Russia 494 495 487 492.0 98.8
Spain 486 496 493 491.7 98.8
Czech Republic 492 487 493 490.7 98.6
United States 470 497 496 487.7 98.2
Latvia 482 488 490 486.7 98.0
Italy 490 485 481 485.3 97.8
Luxembourg 486 481 483 483.3 97.5
Iceland 488 482 473 481.0 97.2
Croatia 464 487 475 475.3 96.3
Lithuania 478 472 475 475.0 96.3
Hungary 477 470 477 474.7 96.2
Israel 470 479 467 472.0 95.8
Argentina (CABA) 456 475 475 468.7 95.3
Malta 479 447 465 463.7 94.6
Slovak Republic 475 453 461 463.0 94.5
Greece 454 467 455 458.7 93.8
Kazakhstan 460 427 456 447.7 92.2
Chile 423 459 447 443.0 91.5
Malaysia 446 431 443 440.0 91.0
Bulgaria 441 432 446 439.7 91.0
Cyprus 437 443 433 437.7 90.7
Romania 444 434 435 437.7 90.7
United Arab Emirates 427 434 437 432.7 89.9
Uruguay 418 437 435 430.0 89.5
Turkey 420 428 425 424.3 88.7
Trinidad and Tobago 417 427 425 423.0 88.5
Argentina 409 425 432 422.0 88.3
Moldova 420 416 428 421.3 88.2
Montenegro 418 427 411 418.7 87.8
Mexico 408 423 416 415.7 87.4
Costa Rica 400 427 420 415.7 87.4
Albania 413 405 427 415.0 87.3
Thailand 415 409 421 415.0 87.3
Colombia 390 425 416 410.3 86.6
Qatar 402 402 418 407.3 86.1
Georgia 404 401 411 405.3 85.8
Jordan 380 408 409 399.0 84.9
Indonesia 386 397 403 395.3 84.3
Brazil 377 407 401 395.0 84.3
Peru 387 398 397 394.0 84.1
Lebanon 396 347 386 376.3 81.5
Tunisia 367 361 386 371.3 80.7
FYROM 371 352 384 369.0 80.4
Kosovo 362 347 378 362.3 79.4
Algeria 360 350 376 362.0 79.3
Dominican Republic 328 358 332 339.3 75.9
OECD Average 490 493 493 492.0 98.8
• Category: Race/Ethnicity • Tags: Map, PISA, Psychometrics 
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Here is the download link:


First Impressions

(1) China B-S-J-G (Beijing-Shanghai-Jiangsu-Guangdong) has a PISA-equivalent national IQ of 102. This is actually worse than the IQ=103 leaked 2009 results based on 12 provinces, which I posted about a few years ago. Even more curiously, Beijing, Shanghai, and Jiangsu all constitute three of the top five Chinese provinces based on other IQ tests (original), with Guangdong in 7th place; the provinces China uses for PISA are still evidently selected for their likelihood of doing very well. Furthermore, coverage was an unimpressive 64% of the population.

UPDATE: A better source cited by commenter Bobbi based on Raven tests shows Guangdong getting 2 IQ points less than the Chinese average, so this would partially cancel out the inclusion of three otherwise cognitive elite provinces.

(2) Vietnam gets a national IQ of 100, although at 49% based on even smaller coverage than China’s. This, too, was a decline from PISA 2012, when they got around 102. Korea also dropped substantially from 106 in 2012 to 103 this round. All in all – a bad beat for “Team East Asia.”

(3) Russia improved significantly, which went from 96 in 2009 to 97 in 2012 and 99 this year – and this is with 95% coverage. This is likely because the generation that grew up in the 1990s was afflicted by the consequences of the Soviet collapse and shock therapy, which included a near halving of meat consumption and an alcoholism epidemic (education spending also fell, but performance on these tests seems to be pretty inelastic to this factor). But the 2015 PISA cohort was born around 2000, when living standards began to recover along with nutritional diversity and all kinds of other biodemographic indicators. Note that I did expect this to happen: “… in the next decade I expect the Flynn Effect to kick off in Russia’s favor, raising its average IQ levels to their theoretical peak of 100 by the 2020′s.

(4) Poland does not repeat its anomalously good IQ=103 results from 2012, converging down to a still respectable 101.

(5) The US modestly improves to 98.

(6) A major improvement for Argentina, which raised its IQ to 95 by an amazing 10 IQ points. This improvement is so big that questions have to be asked as to how exactly they managed it. It wasn’t because they dropped their commendable habit, first noticed by Steve Sailer, of rounding up their dimmest 15 year olds to take the PISA tests (unlike Mexico, or Vietnam); to the contrary, they continued going well beyond the call of duty, achieving 104% coverage – the highest of any country.

UPDATE: From Sailer’s thread, Gaucho de la Pampa comments:

1) Argentina no longer means Argentina, it’s just the city of Buenos Aires (CABA – Ciudad Autónoma de Buenos Aires) . The results for the rest of the country were invalidated because of cheating:

2) It’s not about rounding up missing schoolchildren, if that many went missing from taking the test the results would be annulled as they were in Argentina, rather in some countries vast numbers of 15 year olds don’t attend school and PISA is a test designed for those attending school.

3) The glass half full interpretation is that as Mexico’s share of 15 year olds that attend school has increased its scores have remained roughly static (though obviously crappy)

LOL, well that explains everything. Good job Argentina!

(7) At the very bottom of the list, the Dominican Republic has a PISA-equivalent IQ of 76, which is roughly equivalent to that of India (which, incidentally, dropped out of PISA 2015, possibly on account of doing so badly in the last assessment). Lynn estimates it at 82. According to an analysis by Jason Malloy, Cuba gets an average of 90 on Raven’s tests, and 105-109 (!) from a couple of UNESCO comparative regional tests. So it’s probably safe to say that Cuba is cognitively better off than the Dominican Republic, which makes its decline from double its income level in the 1950s to 2/3 of it today all the more attributable to central planning.

• Category: Race/Ethnicity • Tags: China, PISA, Psychometrics, Russia 
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This year half of the top 10 best performing universities in the global ACM-International Collegiate Programming Competition were Russian.

Place Name Solved Time Last solved
1 St. Petersburg State University 11 1560 290
2 Shanghai Jiao Tong University 11 1567 272
3 Harvard University 10 1358 269
4 Moscow Institute of Physics & Technology 10 1437 281
5 University of Warsaw 10 1586 278
6 Massachusetts Institute of Technology 9 1021 247
7 St. Petersburg ITMO University 9 1026 208
8 Ural Federal University 9 1167 212
9 University of Wroclaw 9 1193 252
10 Nizhny Novgorod State University 9 1222 292

This isn’t a fluke; Russia does incredibly well in these programming competitions. Since 2000, Russia has won 11 out of 17 years, including the past five years consecutively. The only other winners during this period have been China (four times) and Poland (twice). Ex-commie bloc stronk.

It’s probably not a matter of superior intelligence. Most estimates put Russia’s average IQ at around 97 and I don’t disagree with that.

So presumably it’s significantly a function of (1) motivation and/or (2) superior education.

Regarding motivation, that’s probably significantly higher in the ex-commie bloc. A computer science major from MIT or UC Berkeley is almost guaranteed a high five digit salary upon graduation. A Russian (or a Pole, etc) is not; not only are salaries lower across the economy, but if anything their domestic markets for STEM majors are oversaturated. So they have a lot of incentives to try to stand out and increase their chances of getting a job offer from an American or West European firm. Consequently, they likely take such competitions more seriously.

Regarding education, it is quite possible Russia and Eastern Europe have an advantage in this sphere as well, despite the poor showings of their universities in most international rankings. Russians do relatively poorly on the PISA tests, which feature problems commonly found in everyday life and have heavier g loadings, but in contrast they do very well on the TIMSS tests, which are far more “academic” in format and less heavily g loaded. These is in fact a lot of anecdotal evidence that Russian mathematical pedagogy is better than American. For winning math and programming competitions (if not building successful companies, which require a wider and more general range of talents) this sort of skew in cognitive abilities is probably optimal.

• Category: Race/Ethnicity • Tags: Programming, Psychometrics, Russia 
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Commentator jimmyriddle finds statistics about the ethnic composition of scientific cadres in the Soviet Union in 1973 via Cassad (the original comes via the blogger Burkino Faso).



Drawing on earlier statistical data, although on a more limited sample of different ethnicities, we have the following sets of correlations:

  • 1926 Census, literacy amongst 50 years olds+ – r = .92
  • 1926 Census, overall literacy – r = .72
  • 1939 Census, overall literacy – r = .61
  • 1939 Census, high school graduation – r = .93
  • 1939 Census, higher education – r = .99

Considering this without Jews who are huge outliers everywhere here:

  • 1926 Census, literacy amongst 50 years olds+ – r = .82
  • 1926 Census, overall literacy – r = .74
  • 1939 Census, overall literacy – r = .72
  • 1939 Census, high school graduation – r = .91
  • 1939 Census, higher education – r = .93

So the two best predictors are:

(1) The literacy rate amongst the last Tsarist era generation, i.e. people who were 50+ years old in 1926, hence were born before 1876. That was before the advent of mass schooling in the Russian Empire, so I suspect that was when the literacy rate amongst the various regions of the Russian Empire was also the most “g loaded” (apart from places where the Protestant factor was also at play).

(2) Even more so, the share of people with higher education according to the 1939 Census. This stands to reason.


PISA suggests that the Georgians have very low IQs. I mean literally India-like, in the low 80s. However, the above suggests that its underperformance is more a result of massive brain drain – as in other countries that score ridiculously lower than expected based on their ethnic composition, such as Moldova and Puerto Rico, and before the 1990s, Ireland – as well as possibly the collapse of the schooling system to an extent that didn’t happen elsewhere. Probably the two most highly achieving Georgians today are historical detective fiction writer and political oppositioner Boris Akunin (Chkhartishvili) and the controversial but undoutedbly very talented Moscow based sculptor Zurab Tsereteli.

Armenia does not participate in PISA, but its results from TIMSS were significantly lower than Russia’s, at around Ukraine’s or Romania’s level. However, it might be grossly underperforming for the same reasons that Georgia is. First off, a massive amount of the brainier Armenians have emigrated to Russia and the West. In both places they are prominent relative to their numbers, with a powerful lobby in the US (even if it has nothing on the Jewish lobby) and a very powerful lobby in Russia that one could argue stretches all the way to Sergey Lavrov himself, who is half-Armenian. Former chess champion and oppositionist Gary Kasparov is half-Armenian, while the older Soviet chess champion Tigran Petrosian was fully Armenian. They are also the closest cousins of the Jews in terms of genetic distance. A mischievous observation one can make is that like the Jews, Armenians also seem to be unduly prone to political radicalism when abroad, from Sergey Kurginyan and Gary Kasparov (in their own ways) in Russia to Maoist nutjob Bob Avakian and SJW figurehead Anita Sarkeesian in the US, but maintain a safely homogenous and culturally rightist (if dumber) society at home.

In the overall scheme of things, from Jews down to Gypsies, there are no really big surprises.

Anatoly Karlin
About Anatoly Karlin

I am a blogger, thinker, and businessman in the SF Bay Area. I’m originally from Russia, spent many years in Britain, and studied at U.C. Berkeley.

One of my tenets is that ideologies tend to suck. As such, I hesitate about attaching labels to myself. That said, if it’s really necessary, I suppose “liberal-conservative neoreactionary” would be close enough.

Though I consider myself part of the Orthodox Church, my philosophy and spiritual views are more influenced by digital physics, Gnosticism, and Russian cosmism than anything specifically Judeo-Christian.