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50 years on
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Philanthropy is a fine thing. A good sum of money put in the right place can benefit many people. Commerce is also a fine thing. A small sum of money put in the right place can create goods and services which people want, which can lead to profit which leads to more money being available to create goods and services. Virtuous circle. A man who dies rich is not disgraced. He dies in grace if his companies outlive him, and continue to provide things that people want.

This leads to an interesting question: did Bill Gates do more good for the world by founding Microsoft or by founding the Gates Foundation? Probably the former, I would estimate. I say that without being a fan of Microsoft’s products, which have often exasperated me, but just as a cool calculation about the long-term impact of readily accessible business and household programming power, which made computation accessible to billions of people. Tim Berners-Lee and Vincent Cerf could claim greater impact, and with consummate flair Steve Jobs packaged components into the right combination for the ultimate portable communication device (he knew our limitations), but much earlier than that Microsoft had turbo-charged the computer revolution, and pushed Apple aside in the business world, by a country mile.

Now Bill Gates is doing good works, and why not? His 2019 letter is just out.

It deals with 9 topics: Africa being the youngest continent (fastest growing population); DNA testing might prevent premature births (but they may be due to racism); the world’s building stock may double by 2060 (global warming); data may be sexist (not enough suitable data collected on women); helping teenage delinquents cope with their anger; a nationalist case for globalism; flush toilets (sanitation world-wide); textbooks go digital; mobile phones help poor women;

Frankly, apart from Bill’s day with teenage miscreants, there is little about education in this letter.

In fact, the education stuff is in his 2018 letter.

We made education the focus of our work in the United States because it is the key to a prosperous future, for individuals and the country. Unfortunately, although there’s been some progress over the past decade, America’s public schools are still falling short on important metrics, especially college completion. And the statistics are even worse for disadvantaged students.

To help raise those graduation rates, we supported hundreds of new secondary schools. Many of them have better achievement and graduation rates than the ones they replaced or complemented. Early on, we also supported efforts to transform low-performing schools into better ones. This is one of the toughest challenges in education. One thing we learned is that it’s extremely hard to transform low-performing schools; overall they didn’t perform as well as newly created schools. We also helped the education sector learn more about what makes a school highly effective. Strong leadership, proven instructional practices, a healthy school culture, and high expectations are all key.

We have also worked with districts across the country to help them improve the quality of teaching. This effort helped educators understand how to observe teachers, rate their performance fairly, and give them feedback they can act on. But we haven’t seen the large impact we had hoped for. For any new approach to take off, you need three things. First you have to run a pilot project showing that the approach works. Then the work has to sustain itself. Finally, the approach has to spread to other places.

How did our teacher effectiveness work do on these three tests? Its effect on students’ learning was mixed, in part because the pilot feedback systems were implemented differently in each place. The new systems were maintained in some places, such as Memphis, but not in others. And although most educators agree that teachers deserve more-useful feedback, not enough districts are making the necessary investments and systemic changes to deliver it.

To get widely adopted, an idea has to work for schools in a huge variety of settings: urban and rural, high-income and low-income, and so on. It also has to overcome the status quo. America’s schools are, by design, not a top-down system. To make significant change, you have to build consensus among a wide range of decision makers, including state governments, local school boards, administrators, teachers, and parents.

Melinda Gates said:

When economists describe the conditions under which countries prosper, one of the factors they stress is “human capital,” which is another way of saying that the future depends on young people’s access to high-quality health and education services. Health and education are the twin engines of economic growth.

Human capital can also refer to how bright people are, given only reasonable health and education. The phrase is often used as a coy way of commenting on the quality of the people. Boosting health and education gives early gains which plateau pretty fast. The first $5000 has a big effect, but at about $15000 not many more gains are found.

The Economist says:

Some [problems] require the exercise of ingenuity and discretion by small teams (eg, inventing a new vaccine); some demand the programmatic mobilisation of legions of people (immunisation drives). Others require both.

Improving education falls into this third, difficult category. It is not a problem that a small team of brilliant people can crack. Nor can a good education be delivered, like a vaccine, by following a strict protocol to the letter. Instead it requires legions of teachers to respond thoughtfully and conscientiously to pupils’ needs. Mr Gates left his BAM (Becoming a Man) circle wishing every classroom could emulate its intimacy and respectfulness. But that is hard to bottle.

Well, The Economist is championing a very traditional view. Some people have proposed proposed brilliant short cuts to learning, and some of them might work, although most of them haven’t.

Doug Detterman tracked these intelligence-boosting notions for over 50 years, and found them a perpetual disappointment.

Others propose more pedestrian and strict protocols followed to the letter, because those have traditionally worked throughout the ages, mixed with rewards and punishments. A very well thought out sequence of instruction should be instructive to the average pupil. Doing standard teaching well has much to commend it. However, it does not annul individual differences.

I do not rate The Economist as a good source on the question of intelligence and the effects of early education:

Consider the unwieldiness and impracticality of “legions of teachers to respond thoughtfully and conscientiously to pupils’ needs”. This is a prescription for schools being a cottage industry providing Saville Row suits for every shape and size of intellect. Really? Are reading, writing and arithmetic so idiosyncratic that instruction must be tailored to each individual? It is like saying that every computing problem is different, and must have its own operating system. Surely some instructions can be grasped by most students?

Bill Gates is a practical man, and is working with the old system, though new schools seem to be giving better results. Do these new schools use different techniques, different teachers or different students?

• Category: Science • Tags: Arthur Jensen, Bill Gates, Education, IQ 
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Newspapers have very warmly received an international project which, in the author’s views, strongly suggests that healthy babies are all alike in their developmental milestones, at least as determined by a study of particular centres in different parts of the world.

The study has the following general features: Find healthy pregnant women in several different comfortable parts of the world and then check whether the development of their children is the same or different between these centres. If the same, argue that race cannot be an explanation for differences between continental groups, since once they are equalized for health, child developmental differences disappear. This could well be true, so the excitement generated by the updated findings is understandable.

Newspapers are hardly to blame for reporting this study in glowing terms. The authors are bold enough to say:

It is evident that across developmental and growth parameters, only a very small percentage (around 10%) of the total variance in these fundamental human functions can be explained by differences among these populations (Fig. 3). The present results and previous publications, presented together in Fig. 3, support the position that most of the observed differences in growth and neurodevelopment across general populations or countries are primarily due to socioeconomic, educational and class disparities, i.e. postal codes define the health profiles of humans better than their genetic code.

For completeness, here is Fig 3

As regards differences between the peoples of different continents, the authors argue there is nothing much to see here, particularly on cognitive abilities, though there may be something happening with children’s behaviour. However, the authors suggest the behaviour difference is because of cultural differences in how people rate behaviour, not because children actually behave differently. Odd, because the authors were trying to ensure standard procedures were used across different sites, so as to be able to make valid statements about differences and similarities. You would have thought they would have ironed these things out in this large and long-term program of work. Anyway, for whatever reason, negative behaviours and emotional reactions vary between sites. Some kids seem to be more of a nuisance in some places.

You may see that Fig 3 shows very little differences in HC (head circumference) which has often been a bone of contention. Here are the actual figures for head circumference in centimeters at 37 weeks taken from the 2014 paper:

UK 34.5 (1.3)
USA 34.5 (1.4)
Brazil 34.2 (1.2)
Kenya 34.2 (1.2)
Italy 34.0 (1.2)
China 33.6 (1.2)
Oman 33.6 (1.1)
India 33.1 (1.1)

As you can see, UK and USA head circumferences are largest and have the largest standard deviations, India the smallest and the smallest standard deviation. Indeed, the mean for Indian head circumference is one UK standard deviation below the UK mean. Put like that, the centres differ somewhat in the brain size of the children.

What can we say about the apparent lack of any study centre differences in cognitive abilities? Few psychometricians would suggest that cognitive abilities could be reliably assessed at age 2. The Wechsler Preschool and Primary Scale of Intelligence makes a brave start at 2 years and 6 months. Others find it better to wait till 4 years of age, or better still 7 years of age or, for the sweet spot of early testing with reasonable predictive power for adulthood, 11 years of age.

Let us see what these researchers have included in their cognitive assessment of two year olds.

The following is taken from their Inter-NDA instruction manual

1) Make a tower of 5 blocks. There are no higher scores for children who can do the task immediately. Any child doing it in 3 trials gets same score as child who does it in the first trial. A child who builds a 4 block tower gets same score as child who only achieves 3 blocks. This may lead to a lack of discrimination among brighter children.
2) Naming 4 colours. Better task, but naming of 1 or 2 colours gets lumped together. Some loss of discrimination.
3) Matching cubes of same colour. Good scoring system, giving a valid 3 point scale.
4) Handing cube to examiner. Simple scoring, the first to use a time cut-off.
5) Puts spoon in cup when asked. This is a very easy test, because many children will have seen spoons in cups. Some kids might put the spoon in the cup without being asked. It isn’t a pure test of language comprehension. The scoring system loses discrimination at the higher end. A child who does it immediately gets the same score as a child who takes 3 trials to get the hang of it. The child who takes a full 5 trials to do it gets the same score as those who do it in 4 trials. Once again, there is a ceiling effect in the scoring system
6) Match 3 shapes on board. Again, a very easy test, with 3 shapes to be put in their respective holes. Using 4 or even 5 might have given a more discriminative test. Again, the scoring system loses discrimination in the higher range, exactly as described above.
7) Point to the door/entrance in the room. Simple task, same loss of discrimination at higher end.
8) Place raisin into a small opening. A coordination motor task, but a weak test of cognition.
9) Drinks water from cup. A weak test of cognition.
10) Looks at something pointed at. A weak test of cognition.
11) Pretends to drink from a cup. Interesting idea, and a better scoring system.
12) Pretends to make a cup of tea. Some cultural loading here? Test of whether the child can do a pouring motion with a toy teapot.
13) Give the dolly some tea. Imitation.
14) Horizontal scribble Again, interesting, but scoring not sensitive to brighter children.
15) Finding a bracelet placed in full view under a cloth. Scoring system again could do with more range.
16) Child’s use of plurals when shown objects. Good language test, but again the scoring could be more precise.

There are then several tasks to be rated on the basis of parental report: can ask for toilet, runs back to mother, goes up steps, throws ball near something, kicks ball.
Then a language item about syllabic babbling, good topic, but again very crudely measured. Next items, all reasonable and interesting: uses two words together; indicates “no” by gesture; uses a pronoun; count of how many words the child uses during the assessment (this is a good item, but with restricted range at the top); how many 3 word sentences used (another good item, but with restricted range at top); whether child can follow the topic of conversation (good); combines word and gesture (good).

• Category: Science • Tags: Heredity, Intelligence 
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If the brightness of European Jews is primarily due to their culture, then we should all seek to be adopted by a Jewish mother. If, on the other hand, it is necessary to be actually born from Jewish parents, then any cultural tips we may get from them may be a bonus, but it is their genes that are crucial.

Some researchers have just had a look at this, and seem to have found a genetic explanation for part of the reason why European Jews are particularly bright.

Dunkel, C. S., Woodley of Menie, M. A., Pallesen, J., & Kirkegaard, E. O. W. (2019, January 24). Polygenic Scores Mediate the Jewish Phenotypic Advantage in Educational Attainment and Cognitive Ability Compared With Catholics and Lutherans. Evolutionary Behavioral Sciences. Advance online publication.

They say:

A newly released multivariate polygenic score for educational attainment, cognitive ability, and self-rated mathematical ability in the Wisconsin Longitudinal Study was examined as a mediator of the group difference between Jews (n 53) and 2 Christian denominations, Catholics (n 2,603) and Lutherans (n 2,027), with respect to educational attainment, IQ, and performance on a similarities measure. It was found that the Jewish performance advantage over both Catholics and Lutherans with respect to all 3 measures was partially and significantly mediated by group differences in the polygenic score. This result is consistent with the prediction that the high average cognitive ability of Jews may have been shaped, in part, by polygenic selection acting on this population over the course of several millennia.

Public Significance Statement

Ashkenazi Jews exhibit high levels of general intelligence. The hypothesis that differences in general intelligence between Jews and Catholics and Lutherans is partially mediated by polygenic scores for educational attainment was tested. The results support the hypothesized partial mediation.

Data were sourced from the Wisconsin Longitudinal Study (WLS). The WLS is a longitudinal study of randomly sampled Wisconsin high school students beginning in 1957; the last wave of data collection was in 2011. The 1957 sample included 10,317 Wisconsin high school seniors. The sample is overwhelmingly of European descent.
9000 of the study participants were genotyped as part of the recent GWAS for intelligence (Lee 2018) and in this study the educational attainment polygenic score was used. It is the stronger predictor. The students were tested on the Henmon-Nelson Test of Mental Ability, a 30-min test consisting of 90 items of increasing difficulty in spatial, verbal, and mathematical ability. The reliability of the test .95; and it correlates .80 to .85 with Wechsler full scale IQ. When subjects were in their 50s they were given 8 items of the Wechsler Similarities test by phone. Intelligence was well tested.

The Jews in this sample are much brighter than the Christians. They had much, much higher educational levels, perhaps a gene-culture synergistic effect, or simply that educational levels measure ability and motivation. Perhaps the 8 point IQ advantage is enough to explain it.

To illustrate the differences between the Jewish and two Christian groups, we combined the two Christian groups and computed Cohen’s d for PGS and IQ. For PGS Cohen’s d 1.33, which is a very large effect size. For IQ, Cohen’s d .57, which is a medium effect size. These group differences are portrayed in Figure 1.

The correlations between the polygenic scores and the intellectual measures are .2 to .3 which is low. Aware that the Jewish sample is small, the authors drew 1000 same sized samples at random from the Christian population to get an estimate of the likelihood of absolutely chance differences between the Jewish and Christian students, and this turns out to be very low, so it is very likely to be a real difference.

The sample of Jewish students is small. However, researchers looking at small samples of ancient genomes argue that DNA is informative even in small samples, because it is a cumulative record of genetic pairings, and is highly informative thereby, but there is still a chance of quirky findings. The authors a well aware of this, and regard their findings as tentative. They certainly do not argue that Jewish cultural transmission is irrelevant, and say that it might support and amplify the genetic factors found by the polygenic scores.

Rare variants associated with lipid storage disorders may indeed confer a heterozygote advantage, which may have augmented the Jewish Group GCA above that which would be predicted by differences in the level of PGS alone, perhaps accounting for the relatively higher frequencies of these disorders in this population. Direct tests of this model still need to be carried out, however.

Dunkel and colleagues have established a tentative link between polygenic scores and Jewish intellectual advantage. This is an important step forwards, and worth testing on larger samples and with better polygenic score data.

• Category: Science 
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Four years ago I claimed that it was more important to have educated parents than rich ones. Parents who are educated were very likely bright to begin with, and judged worth educating as much as possible. They may even have gained in ability by virtue of further education. Brighter parents usually earn more than less bright ones, so many educated parents will also be wealthy. Nonetheless, if you have to chose which is best for children, choose education over wealth. Why? Because intelligence is the greatest wealth.

I’ve known for years that Rindermann had all these results you will see below, and it is great to see them all gathered together, and the analyses extended to complete the overall picture.

In 19 (sub)samples from seven countries (United States, Austria, Germany, Costa Rica, Ecuador, Vietnam, Brazil), we analyzed the impact of parental education compared with wealth on the cognitive ability of children (aged 4–22 years, total N = 15,297). The background of their families ranged from poor indigenous remote villagers to academic families in developed countries, including parents of the gifted. Children’s cognitive ability was measured with mental speed tests, Culture Fair Intelligence Test (CFT), the Raven’s, Wiener Entwicklungstest (WET), Cognitive Abilities Test (CogAT), Piagetian tasks, Armed Forces Qualification Test (AFQT), Progress in International Reading Literacy Study (PIRLS), Trends in International Mathematics and Science Study (TIMSS), and Programme for International Student Assessment (PISA). Parental wealth was estimated by asking for income, indirectly by self-assessment of relative wealth, and by evaluating assets. The mean direct effect of parental education was greater than wealth. In path analyses, parental education also showed stronger impact on children’s intelligence than familial economic status. The effects on mental speed were smaller than for crystallized intelligence, but still larger for parental education than familial economic status. Additional factors affecting children’s cognitive ability are number of books, marital status, educational behavior of parents, and behaviour of children. If added, a general background (ethnicity, migration) factor shows strong effects. These findings are discussed in terms of environmental versus hidden genetic effects.

Socio-economic status is associated with educational attainment, and as we know, a frequently observed correlation suggests an underlying cause. (In this instance, the correlational nature of the association is not seen as a grave disadvantage).

The popular interpretation of these findings in the media as well as in science is that they are caused by differences in the wealth of parents (for examples, see Rindermann & Baumeister, 2015): The rich can support their children through costly interventions that are beyond the ability of less wealthy parents, such as better housing, private schools, educational toys and computers, entrance to expensive museums, and hiring tutors. By the same token, the economically and socially disadvantaged poor cannot offer their children such supports. A straightforward intervention derived from this position was publicly formulated by Richard Nisbett in his keynote “Bring the Family Address” at the 2009 Association for Psychological Science convention in San Francisco: “If we want the poor to be smarter we should make them richer” (Wargo,2009, p. 17).

However, a closer look at different empirical phenomena makes it doubtful that economic differences are really at the root of differences in intellectual outcomes as opposed to underlying causes that they proxy. Consider six types of suggestive evidence for the position that educational mechanisms are stronger drivers of offspring intelligence than economic ones.

1. In many countries, there is only a low or even no positive relationship between indicators of economic wealth of families (e.g., owning TV, mobile phone, computer) and cognitive student assessment results; and sometimes, the relationships are negative.

2. Similarly, in international comparisons with individual-level data (PISA 2006, parental educational level is more strongly associated with children’s abilities than are parental wealth indicators.

3. Cognitive elites such as Nobel Laureates come less often from wealthy social strata than from well-educated ones.

4. A further type of evidence for educational mechanisms is indirect; rather than showing that parental education drives offspring intelligence, it shows that off-spring’s education drives their own intelligence, thus implicating underlying cognitive processes that are inculcated through education as an important contributor to IQ differences. In a narrative review of the historical literature, Ceci (1991) found that each year of missed or delayed schooling led to a decrement in cognitive ability. For example, missed schooling due to family travel, summer vacations, illness, dropping out, or absence of teachers in remote regions all led to reduced IQ performance compared with children who had not missed school: Two adolescents with the same IQ score at age 14 differed by nearly 8IQ points by the age of 18 if one of them remained in school until that age and the other dropped out at age 14 (Ceci, 1991). In a series of analyses, Winship and Korenman (1999) modelled IQ changes under different assumptions about the degree of measurement error. They estimated that the impact of 1 year of schooling results in an average IQ increase of about 2.7 IQ points for each yearof school attendance.

5. Parental ability and attitudes create an important developmental environmentfor children as illustrated by a qualitative Austrian study (Großschedl, 2006): Some parents whose children were cared for and supported by a public social program (the state pays all the rent including water, electricity, and central heat-ing) burned the books and learning materials supplied for their children “for heating” during vacations. They stated that these materials are not important and education is not important for girls, because they will marry later. Großschedl Rindermann and Ceci 301 (2006) found that during home visits, it was difficult to create a learning atmosphere for applying the training program, for homework, and for consulting parents, because parents and their children wanted to watch TV all day.

6. Consistent with the above five sources of empirical research, there are also anecdotal examples that contradict the popular assumption that a more expensive environment favors intellectual development: In Atlanta (based on observations in 2008), there are two famous zoological institutions, one charging US$37), and offering fishes, whales, and other animals swimming in basins with few or no explanatory texts describing the animals’ habitat, evolutionary or ontogenetic development, and behavior. The second institution (the Natural History Museum) had a US$19 entrance charge but offers age-appropriate voluminous written and verbal explanations, of the habits and geographic regions of animals including the presentation of complex topics such as evolution and the Doppler effect. The more expensive but superficial place attracted far larger crowds of which the largest fraction appeared to come from seemingly lower SES strata. The cheaper but cognitively more stimulating museum was nearly empty and the few people attending it appeared, from their dress and manner, to be from the middle or upper classes, many of them were whole families including fathers.

• Category: Science • Tags: Genetics, Heredity, IQ 
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I do not have a dog in the fight about dogs. My dad said that there was a dog in every boy’s life, and so we had some dogs when I was young, and then in my own life, no dogs. I was living a town life, and working, and had neither need nor wish for them. I have nothing against dogs, other than that they should live in the country, not the town, and preferably do something useful. In towns they are captive and, when badly trained, frequently a nuisance. In the country, so long as they are not worrying sheep, they are more agreeable company.

I can see that dogs have very probably evolved with us, in a symbiotic relationship. They know how to flatter us, in return for food and companionship. Parasitism it may be, but it works for many people, and virtually all dogs. Dogs and their owners are reciprocally besotted.

Frankly, I doubted owner’s stories about the intelligence of their pooches. We are creatures of habit, and dogs learn from observation how we are to be handled. So, it was with some initial hesitation that I looked at the research on canine intelligence, and then came to see that, after due allowance for restrictions on which tests which could be used, there was a case for comparing the intelligence of dogs and of dog breeds. The fact that the clever breed were sheep dogs pleased me. We all have to earn our keep.

Here is Rosalind Arden on the intelligence of dogs:

The other thing about dogs, is that they live shorter lives, so their generation pass more quickly, and can be observed as they evolve. Even more important, they can be bred through a selective process into different sorts, for different purposes. Assisted evolution in action. Hence, we can look at these close companions and make judgments about how characteristics and behaviours alter through evolution. We can even tamper so as to breed up dogs for our uses. Guide dogs, for example. Practically, dogs that can detect when we are about to have a fit. Perhaps even dogs that can detect our diseases before any other detection device can do so.

What can we find out from genetic analyses of dog behaviour and dog breeds?

Highly Heritable and Functionally Relevant Breed Differences in Dog Behavior
Authors: Evan L MacLean, Noah Snyder-Mackler, Bridgett M. von Holdt & James A.

* Correspondence to: [email protected] & [email protected]

Below I show the abstract verbatim, and have selected and abbridged the main points of the paper.

Abstract: Variation across dog breeds presents a unique opportunity for investigating the evolution and biological basis of complex behavioral traits. We integrated behavioral data from more than 17,000 dogs from 101 breeds with breed-averaged genotypic data (N = 5,697 dogs) from over 100,000 loci in the dog genome. Across 14 traits, we found that breed differences in behavior are highly heritable, and that clustering of breeds based on behavior accurately recapitulates genetic relationships. We identify 131 single nucleotide polymorphisms associated with breed differences in behavior, which are found in genes that are highly expressed in the brain and enriched for neurobiological functions and developmental processes. Our results provide insight into the heritability and genetic architecture of complex behavioral traits, and suggest that dogs provide a powerful model for these questions.

Studying aggression, fear, trainability, attachment, and predatory chasing behaviors on 14,020 individual dogs with breed-level genetic identity-by-state estimates from two independent studies we found that a large proportion of variance in dog behavior is attributable to genetic factors. The mean heritability was 0.51 ± 0.12 (SD) across all 14 traits (range: h 2 0.27-0.77), and significantly higher than the null expectation in all cases (permutation tests, p < 0.001).

Interestingly, the traits with the highest heritability were trainability (h 2= 0.73), stranger-directed aggression (h 2 = 0.68), chasing (h 2 = 0.62) and attachment and attention seeking (h 2 = 0.56), which is consistent with the hypothesis that these behaviors have been important targets of selection during the cultivation of modern breeds.

Overall, we identified 131 unique SNPs that were significantly associated with at least one of the 14 behavioral traits (Bonferroni p ≤ 0.05, Fig 2). Forty percent of these SNPs (n= 52) were located within a gene – none of which encoded for changes in the amino acid sequence of the protein. On average, the top SNP explained 15% of variance in the behavioral trait. Thus, while we identify multiple variants with moderately large effects, the variance explained by individual SNPs is far less than that explained by additive variation across the genome (heritability), suggesting that as in humans, behavioral traits in dogs are highly polygenic. However, the variance explained by the top SNPs in our analysis across breeds was, on average, more than 5 times higher than that from within-breed association studies.

Many of the gene-level associations with dog behavioral traits include (i) candidate domestication genes, (ii) genes mapped to phenotypes implicated in domestication, (iii) genes implicated in behavioral differences between foxes bred for tameness or aggression, and (iv) genes that underwent positive selection in both human evolution and dog domestication. For example, PDE7B, which is differentially expressed in the brains of tame and aggressive foxes has been identified as a target of selection during domestication, and is highly expressed in the brain where it functions in dopaminergic pathways. In our analyses, SNPs in this gene were associated with breed differences in aggression, which is consistent with data from experimentally bred foxes, as well as hypotheses that selection against aggression was the primary evolutionary pressure during initial domestication events.

The gene-trait associations identified in our study also align closely with similar associations in human populations. For example, breed differences in aggression are associated with multiple genes that have been linked to aggressive behavior in humans. Molecular associations with breed differences in energy include genes previously linked to resting heart rate, daytime rest, and sleep duration in humans. Lastly, breed differences in fear were associated with genes linked with temperament and startle response in humans, and several of the genes implicated in breed differences in trainability have been previously associated with intelligence and information processing speed in humans.

If the variants in genes identified in our analyses make major contributions to behaviour and cognition, then the associated genes should be (i) involved in biological processes related to nervous system development and function, and (ii) primarily expressed in the brain. Indeed, we found that behavior-associated genes (as identified through meta-analysis) were enriched for numerous nervous system processes. These processes include neurogenesis, neuron migration and differentiation, axon and dendrite development, and regulation of neurotransmitter transport and release.

• Category: Science • Tags: Dogs, Intelligence 
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Some things are associated with others. Some things you eat make you ill. Some animals attack you. Some places are dangerous, some people likewise. On a brighter note, some foods are tasty and healthy. Some animals can be domesticated, or at least are easy to hunt or trap. Some places are safe, and some people likewise.

Correlation is not causation, but it’s the way to bet. Your life may depend upon it. Under-predict dangers and you could end up dead. Better to be safe than sorry. Better to be sorry that you have missed some opportunities than to be dead. It is sensible to worry about what may happen. Stereotypes are your friend. They are preliminary observations about life. Improve them as you learn more. Some must be discarded, but many more can be sharpened up and refined.

Life is a dilemma. When searching for a meal you must avoid ending up as a meal. Be careful, but don’t worry so much that you cannot forage for food. Hunger will make you adventurous, and then you are at risk again.

Ideally, we would never calculate correlations coefficients, but would just look at the data properly plotted out, ideally over a long period, and judge things by eye. The shape of the distribution matters. Intellectual and scholastic tests need not be a perfect bell curve, though they can be pretty close to one.

Sometimes an unknown force distorts the distribution, as when illness and infections sap the wits of poor citizens living in bad circumstances. More mysteriously, sometimes distributions are almost normal, but pinched into a narrower range, as if bound by a tighter central limit. Why are some groups narrower than others? Women, for example? African Americans, for another? Easy to see how systematic disadvantage could shift a mean downwards, less easy to see how those forces could both encourage low scorers and discourage high scorers.

A correlation coefficient is a straight-line simplification. Useful, though. It captures a lot in a little number. Standard deviations are also very informative.

It is no disproof of a correlation that it is not unity. Most real-life correlations are far less than perfect, but will be much better than guessing, even though there will always be outliers. Adding up those outliers in terms of residuals (errors of prediction) is a useful way of understanding the power of predictions based on correlations. For example, if you have to predict the height of an unknown person, your best bet (least error prone) is to predict that they are of average height. If you are asked to predict the height of 100 people, betting that everyone of them is of average height results in your error of prediction being the same as the standard deviation of the height of the general population.

If you have extra knowledge, such as being told the height of the individual’s parents, then you can improve your prediction by taking that into account. You will have reduced your error of prediction, and can compare how much it improves your bets by comparing your reduced residual with that of the standard deviation of the population.

Some people really believe they have invalidated a correlation by drawing attention to a particular outlier. If you conceive of a correlation as an ellipse rather than a straight line you can see that the highest scorer on one variable will not be the highest scorer on the other variable. That only happens with perfect correlation. Steve Hsu explains the issue here:

Correlation is not causation, but you are more likely to find a cause in a correlated variable than in an uncorrelated one. Search where there is at least a trace of a putative connective tissue. If you think it was the tomato that upset your digestion, start your controlled trial on tomatoes.

Correlation is not causation, but sometimes a finding is suggestive, like a trout in the milk. It does not prove that the milk was watered, but it makes you suspicious.

The “correlation is not causation” mantra is true as far as it goes, but it tends to be used so as to argue that, despite many correlations linking A with B being found in different circumstances, these will somehow never suffice to strongly suggest a causal link between A and B. On the contrary, correlation is a necessary feature of causation, but not a sufficient proof. Correlation is not always causation, but it helps find causes. Correlation is a pre-condition of causality.

Michael Woodley has set a challenge: “Sure, correlation does not equal causation, but find me just one single instance of a causal relationship where there is no correlation (just one would suffice).”

Whilst it is true that correlation does not necessarily equate to causation, all causally related variables will be correlated. Thus correlation is always necessary (but not in and of itself sufficient) for establishing causation.

Woodley continues:

The claim that ‘correlation does not equal causation’ is therefore meaningless when used to counter the results of correlative studies in which specific causal inferences are being made, as the inferred pattern of causation necessarily supervenes upon correlation amongst variables. Whether the variables being considered are in actuality causally associated as per the inference is another matter entirely.

The correct critique of such findings therefore is from mediation, i.e. the idea that a given correlation might be spurious owing to the presence of ‘hidden’ variables that are generating the apparent correlation. A famous example is yam production and national IQ, which across countries correlate negatively. It would be wrong to say that yam production somehow inhibits IQ, as the association will in fact turn out to be mediated by something like temperature and latitude. These variables are in turn proxies for historical and ecological trends that make the sort of countries that yield fewer yams the sort of countries that are typically populated by higher ability people, and vice versa. The causation in this case is via additional variables, which cause the covariance between the two variables of interest, without there being a direct effect of one on the other.

Properly constructed multivariate models can use these patterns of mediation to infer the likelihood of causation going in one direction or another. Thus, it is possible to actually test causal inference amongst a population of correlated variables. By far the best way of doing this is to compare the fits of models containing specific theoretically prescribed patterns of causal inference against (preferably many) alternative theoretically plausible models, in which alternative patterns of causation are inferred (Figueredo & Gorsuch, 2007).

Sir William Gemmell Cochran termed this “Fisher’s Dictum‟:

“About 20 years ago, when asked in a meeting what can be done in observational studies to clarify the step from association to causation, Sir Ronald Fisher replied; `Make your theories elaborate.’ The reply puzzled me at first, since by Occam’s razor, the advice usually given is to make theories as simple as is consistent with known data. What Sir Ronald meant, as subsequent discussion showed, was that when constructing a causal hypothesis one should envisage as many different consequences of its truth as possible, and plan observational studies to discover whether each of these consequences is found to hold. (Cochran, 1965, §5).


• Category: Science • Tags: Correlation, IQ, Statistics 
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swan white

Thank you to all those who commented on the “Swanning About: Fooled by Algebra” blog and associated tweets. A number of themes came up, so here are individual responses I made to some comments, and also some general points.

Since Taleb thought he could dismiss a century of psychometry, there are rather a lot of references I needed to give in reply. I thought that if I attempted to list them all out it would swamp the text, hence my suggestion that people should use the search bar on my blog to pick up matters of interest, particularly the researchers I had named in my blog. Some people had difficulty with using a search bar or simply did not want to do so, and felt that the lack of specific references was suspicious, so here are some suggested starting points for the process of fact checking.

Brief guide to references

Doug Detterman founded the journal Intelligence and edited it for years, and has seen the field at close quarter for 5 decades. His overview is amusing and instructive. He did an updating of Jensen’s summary of the many relationships intelligence test have with real life achievements. To get even further detail you would have to do further reading, but you already realized that.

Here is another short cut:

Stuart Ritchie is an extremely active younger researcher, who gives an excellent account of more recent findings, and pays attention to those who think it fashionable to decry intelligence testing.

Another short cut:

This is my summary of a review paper written by Ian Deary, the leading researcher on intelligence. You could also just put “Deary” in the search bar and look at the selection of his many papers that I have commented on.

To orient yourself as to what intelligence means in everyday life, here is a summary I wrote some years ago. There is more detail to add to bring it up to date, but it serves to show the differences in ability which are often not visible because people tend to associate mostly with those at their occupational and intellectual level.

For research on occupational selection

For research on the achievements of very high ability people

For research on brain and intelligence

For a counter-intuitive finding about high and low intelligence brains

For a broader look at the field, here is a recent textbook on intelligence, covering the most quoted authors in the field:



The journal “Intelligence” is the main publication for intelligence research.

ISIR runs the international society and its conferences.

Two classic texts which cover many issues raised in comments, about bias and the nature of intelligence

Jensen. Bias in mental testing. 1980
Jensen: The g Factor: The Science of Mental Ability 1998

Some general points

It is no disproof of a correlation that it is not unity. Of course, there will be bright people who don’t achieve much, and less bright people who do very well. This has been known for a long time, perhaps at least two thousand years. The race is not always to the swift. Jensen explained that the range of intelligence was broadest at the lowest levels. Some bright people, for whatever reason, like simpler jobs. As jobs get harder the range begins to narrow as the lower intelligence levels drop out, finding the demands too high. More demanding occupations require brighter people.

A measure can be important and predictive, and the best available, without being perfect. If you can think of a better one than general intelligence, propose it. That old standby, social class of origin, has been superseded. It accounts for less variance than intelligence measured at 11.

Other proposed measures of intelligence are no better than the familiar general intelligence measure.

In summary, the next move should be from those who have something better to suggest, something which predicts human achievements better than general intelligence.

That new something should be better than just guessing.

• Category: Science • Tags: Heredity, Intelligence, IQ, Psychometrics 
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black swan google

Nassim Nicholas Taleb has tweeted a set of remarks about intelligence research.

He has now gathered those together into one format, with links and explanations.

There is no lack of confidence in his essay. There is much to discuss here, and what follows covers what I see as the main points. I have added some links to relevant publications, but you can put any of the concepts and author names in my search bar to get further details.

1 IQ is largely a pseudoscientific swindle

Given that Taleb criticizes the poor statistics used by intelligence researchers, a mild comment is that it would have been better to be more precise. I have assumed he means that more than half of intelligence research findings are wrong, and for malicious reasons. If this is his point, he is factually wrong.

2 IQ is stale, mostly measures very low intelligence, or a lesser form of intelligence for paper shufflers or those ill-suited to real life. “it explains at best between 13% and 50% of the performance in some tasks”. It is based on poor maths, and promoted by racists and swindlers.

It seems that Taleb has a poor opinion of many people. “Paper shufflers” probably include all the backroom workers who keep the books and process the transactions of star traders. The reason for his doubts about the maths behind IQ, Taleb explains, is that he can computer-generate correlations based on particular assumptions which then look like some of the reported findings on intelligence and scholastic attainment. He implies that if he can do that on a simple basis (create a mythical test which only measures below IQ 100 performance and progressively just add noise above that) then that invalidates the actual observations reported by Frey and Detterman (2004). This is not a compelling argument. A far simpler explanation is that a population wide measure (general IQ) is being compared with a scholastic test taken only by a selection of brighter students (SAT) yet still does a pretty good job of showing the link between the two. This is a real-life finding, of the sort that Taleb supposedly favours.

3 If you want to detect how someone fares at a task, say loan sharking, tennis playing, or random matrix theory, make him/her do that task; we don’t need theoretical exams for a real-world function by probability-challenged psychologists.

In fact, psychologists have understood this point. Hunter and Schmidt and Kunzel point out that the best test of whether a person can do a job is to let them try it. However, this is expensive in time and money, since you have to supervise them to prevent disasters, give them detailed instructions and monitor their performance carefully, all of which takes at least two weeks to get a reasonable estimate of the applicant’s capabilities. You cannot do this for all applicants, or it would take up all the staff time required for doing the actual work of the business. The above researchers show that an intelligence test is a close second-best in terms of outcome, and far quicker and cheaper. Add a test of honesty and you have an efficient selection system.

4 Different populations have different variances, even different skewness and these comparisons require richer models.

Again, most psychometricians agree with that and it has been known for decades. At the very least, they like seeing the data plotted out properly, so the actual findings are visible, and so that they can be analyzed by different statistical approaches. Nothing new or insightful here.

5 A measure that works in left tail not right tail (IQ decorrelates as it goes higher) is problematic.

Lubinski and Benbow have shown in prospective studies with a large sample that IQ is still predictive at the very highest levels, and keeps working at each higher band. Taleb’s point is demonstrably wrong.

6 It (IQ) can measure some arbitrarily selected mental abilities (in a testing environment) believed to be useful. However, if you take a Popperian-Hayekian view on intelligence, you would realize that to measure it you would need to know the mental skills needed in a future ecology, which requires predictability of said future ecology. It also requires the skills to make it to the future (hence the need for mental biases for survival).

Intelligence test items are not arbitrary. They are selected to represent a wide range of abilities drawn from actual tasks and real-life problems. They correlate highly with tests which specifically base themselves on real life tasks in American society, such as the Wonderlic Personnel Test. Linda Gottfredson has shown all this, many times, for decades. As to “mental skills needed in a future ecology”, that is an excellent example of intelligent behaviour, as is survival. In a Scottish population study, Ian Deary has shown that intelligence tested at age 11 predicted lifespan into old age. Brighter people were capable of surviving longer than the less bright. Taleb is wrong again.

7 Real life never never offers crisp questions with crisp answers (most questions don’t have answers; perhaps the worst problem with IQ is that it seems to selects for people who don’t like to say “there is no answer, don’t waste time, find something else”.)

If this were a relevant objection, then the crisp answers required in the Scottish 11+ would not have shown any relation to lifespan and decades of achievement. Equally, the crisp answers required of SMPY participants would not have predicted their mid-life achievements (and will probably predict decades of achievement as the follow-ups continue). Digits backwards is a crisp-answer task. It wastes little time, yet is a good predictor of general ability. Crisp test answers also correlate to many brain structure and function measures assessed by neuroimaging (Haier, 2017). Also, given that all puzzles require brain power, these selected items may tap a general ability to solve puzzles of a far more general and urgent nature.

8 It takes a certain type of person to waste intelligent concentration on classroom/academic problems. These are lifeless bureaucrats who can muster sterile motivation. Some people can only focus on problems that are real, not fictional textbook ones.

Taleb is very free with his insults. It might play to those already taking an anti-IQ stance. A rough measure of ability can be obtained in two minutes, which does not tax concentration. Sure, many people favour the practical over the academic, and might concentrate best on real-life problems. This is testable, and once again, on a broad range of people and a broad range of real-life problems, intelligence tests maintain predictive utility. Detterman shows many of the correlations.

9 IQ doesn’t detect convexity (by an argument similar to bias-variance you need to make a lot of small inconsequential mistakes in order to avoid a large consequential one. See Antifragile and how any measure of “intelligence” w/o convexity is sterile…)

• Category: Science • Tags: Intelligence, IQ, Psychometrics, Race and Iq 
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To the 12th Century Church of the Knights Hospitaller of Jerusalem, as is my custom, to celebrate the habits of my tribe. This time the service of the Nine Carols was in the evening under a full moon veiled in winter’s hazy clouds, though enough to light the road past the carp pond. The church was candle lit, and cosy.

The service began with the priestly warning that although his lapel microphone was working, the fixed microphone for the reading of the lessons was out of order. To make the point clear to those who would be doing the readings, he walked over to the mike and tapped it. A loud thumping sound filled the little nave. “It’s a miracle” said several parishioners.

Whereas in former times, when the village was visited by musicians and choirs, “Once in Royal David’s City” always began with the crystal-clear solo from a hidden soprano, these were more straightened circumstances, and the service notes said merely that the first verse would be sung by the women.

For the second carol the Reverend, perhaps conscious of the need for vocal equity, said that one verse would be sung by the men, who did so after their fashion. For the third carol, in a further variation, he proposed that one verse be sung by women and one by men. “Which verse for the gender fluid?” my pewmate muttered, and in the spirit of Christmas I told him to shut up. The rest of the carols we sang together as parishioners of all sexes, guided by familiar melodies.

The first lesson was read by one of our oldest residents, whose progress to the lectern was determined but frail, but with the gospel words he was transformed into a sonorous authority, in full command of himself and his text. The other readers were similarly direct and clear in their solemnity. There were no children doing readings, perhaps because among the 45 or so attending there were only three young children, and two teenagers.

By now the story of the birth defied any sense of news. Even the manifest ambiguities of the account were so familiar as to evoke no bemusement. The congregation was not there on theological grounds alone. The field and woods were wetly outside, and in the relative warmth of the village gathering a small hotplate in the chancel heated up the mulled wine, so the tempo of carols and lesson was in synchrony with these preparations, meaning that the candle light very occasionally gave way to dull torchlight when the stove needed adjusting.

No village can be a representation of a nation, still less a Saxon village with a hundred households, but the impression was of retreat and age, as if clustered round a dying flame, the ritual shorn of the numinous, a prelude only to refreshments, wine to pour out, another year, relatives to collect, problems at the airport, smiling at grandchildren, and outside the double oak doors the pond, Manor and maypole, the emblems of our past.

Saying farewell to the priest, with whom I had had a companionable Harvest Supper some months before I remarked “Thanks for separating us into the men and the women”. “Yes” he replied with a smile, “we make such separations, but do not ask them to cover their heads”. “That will come”, I replied. In jest, perhaps.

On the way back home the moon still shone on the wet road and the old buildings, a village half asleep.

Merry Christmas

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Birthday candle

The early months of 2018 were taken up with dealing with hostile press coverage of the London Conference on Intelligence, attacks which intended to prevent evidence-based discussion of group differences in intelligence, and sought to grossly misrepresent any discussion of genetic components in behaviour, lest new readers think for themselves. Stain the source: obscure the findings.

Analytics 2018 and total pageviews ever

Despite distractions, I wrote 46 somewhat longer posts and got 240,478 pageviews: 5,228 per post, which is most welcome. Thanks for reading. Comments continue to grow, with 516,906 words generated. My overall total since 2012 is roughly 750,000 words written, and 678,000 pages viewed, which is more impact than my published papers, and far more impact than just shouting at the radio or TV set.

More to the point, in 2018 there were notable advances in the understanding of the genetics of intelligence, in artificial intelligence, in brain scanning, and in intelligence research generally, so there were important things to write about. Most aspects of behaviour have a substantial heritable component, and these findings grow more numerous every month. It is an exciting time. Once artificial intelligence gets to grip with the genetics of intelligence then it will get even more exciting. It is possible that by the end of 2019 we will be able to predict close to 20% of intellectual variance from the genome alone.

Top 10 posts are shown below.

Analytics 2018 top ten

Three points stand out: first, although written several years ago, that old standby “The 7 tribes of Intellect” is still popular because it explains what intelligence means in everyday life. Second, James Flynn is now deeply concerned about data showing that children are now far less capable of applying scientific methods, and that that he is also very troubled by attacks on academic freedom and race and intelligence research. Although this last paper was the subject of a very recent post, it still drew enough interest in the very last few days of the year to make it into the Top 10.

Analytics 2018 regulars

Well, this is a test of quality. Over 57,000 sessions are one-night stands. I assume the statistics puts them off. Who knows? After that come the real aficionados, and to my surprise and delight, that includes 42,000 long-time readers. A special thanks to you.

Analytics 2018 demographics

Readers are mostly male, and cover all age ranges, with a peak at 25-34. Why? They may be more interested in blogs generally, but I would like to think that they have moved from the “prizes-for-all” subsidized world of school and college and have entered the world of work, which is far more demanding. There are fewer alibis and fewer glib evasions. Now it is for real. You have to make the grade in the jobs which will take up four decades of your life. This makes you curious about ability and problem-solving.

Analytics 2018 countries

US continues to dominate, in this blog as in real life. No sign of China. Are they being told what they may or may not read?

Many people have short attention spans or, conversely, are quick to realise that the site does not meet their interests. However, I am charmed at those who spent 30 minutes: almost like book reading. Great!

Analytics 2018 brief encounters

In all, a good blogging year.

Twitter followers have grown to 4,500. In the last three months my tweets gained 935,000 impressions. The tweet announcing the post about academic freedom got 26,400 impressions. Most other tweets about posts on the blog get roughly 6,000 impressions.

I am well aware that these are small numbers compared to those who blog about popular subjects, but I always compare them with the ground zero of not having commented at all.

Final plea: try to be kind to other commentators. Not all students do the necessary reading, and if they get insulted they probably never will.

• Category: Science 
James Thompson
About James Thompson

James Thompson has lectured in Psychology at the University of London all his working life. His first publication and conference presentation was a critique of Jensen’s 1969 paper, with Arthur Jensen in the audience. He also taught Arthur how to use an English public telephone. Many topics have taken up his attention since then, but mostly he comments on intelligence research.