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It is that time of year when Oxford and Cambridge universities are in the doghouse again, accused of being biased against black students. A politician, Mr David Lammy, has called for special measures to be taken to boost the numbers of Africans at those universities. Calls like this seem to be accepted at face value, but universities are tertiary educators, fed by secondary schools. What does the pipeline deliver them?

Well, to get to a good university you need at least 3 A grades, and for the best colleges preferably 5, all in respectable, that is to say, hard subjects. For example, an A in Maths, and another A in Further Maths reassures good universities that the place they offer a candidate is unlikely to be wasted. If one looks at the average offer extended to Oxbridge candidates it is A*AA (three As, one of them being A starred). That is what they must get in their exams to secure a place, the actual subjects depending on what discipline they wish to read.

Here is the official Department of Education summary of the ethnic success rate in most recent results for 3 A grades.

3 A grades or better at A level was achieved by 24% of Chinese students, 11% of Mixed students, 11% of White students, 11% of Other ethnic group students, 10% of Asian students and 5% of Black students.

Chinese students were consistently most likely to achieve 3 A grades or better at A level and Traveller of Irish Heritage students and Gypsy/Roma students were least likely to.

The summary is not entirely clear about mixed students. The detailed tables are hard to display, so I have made a simplified version. By the way, two things should be borne in mind when considering the numbers of ethnic students who gain entry to highly selective universities: the percentage of each ethnic group who reach the basal standard, and the actual size of the ethnic group.

3 As or better

Oxford and Cambridge offer roughly 6,600 undergraduate places in total, and roughly five times as many students apply as are accepted. So, 7600 white students who reach the minimal standard do not get admitted to Oxbridge every year. Tough luck.

Every statistic based on ethnicity is influenced by the immigration history of the nation in question. For example, Black British used to mean “from the West Indies”. These are the group who have had most time to get the benefits of life in the United Kingdom, and are almost all British born, using the NHS from conception and the education system throughout. Now the African population is larger than the Caribbean population, a consequence of recent mass migration. Many will have been born abroad.The Indians in the UK are drawn from particular populations, and India is heterogenous as regards ability.

Many people will find the statistics startling. Can it really be the case that only 62 Black Caribbean students achieve 3 A grades? Here is a very rough calculation: assume 594,825 Caribbeans in the UK. Assume that, as for other populations, only 2.33% of that population are of an age to go to university, and that all apply. Assume that the best estimate of Afro-Caribbean intelligence is 90, and that IQ 130 is the minimal Oxbridge entrance requirement. In that case there will be 53 qualified applicants. This estimate is in broad agreement with the observed figure.

The larger (and very probably pre-selected) African ethnic group seems a more promising pool for recruitment, if the requirement is simply that the candidate be of African genetics. The African group is bimodal in terms of occupational level: lots of professional African immigrants, plus lots who are unemployed. They are drawn from a vast population.

The table is also informative about racial admixture. The children of Whites have gained by mixing with Asian genetic groups (actual group unspecified) and lost somewhat when mixing with Black Africans and more so with Black Caribbeans. Interestingly, the White/Black Caribbean mix of 11% and 3% pass rates results in exactly a 7% pass rate for the mixed group.

It seems that British people do not blink when it is proposed that another genetic group should be granted extra privileges. There is no call for White British candidates to be put on the same footing as Chinese and Indian students. I suppose the supposition is that they are brighter or studied harder, probably both.

It might help the public debate about university entry if more people were to look at the official education statistics. The focus of discussion may one day move to secondary schools. Then, after a while, it may move to primary schools and then kindergartens. Since racial differences in ability can be detected at age 3, expect special measures to be required for kindergartens.

• Category: Science 
118 cm3
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Sex diffs in brain size Ritchie

Pity the poor blogger’s lot: there are more interesting papers being published every week than any essayist, however diligent, can possibly cope with. And there will be more, as the vast genetic databases give up their secrets. No sooner does one team scoop the others with a savage novelty than their rivals counter-attack with their own surprising findings. If you are curious about mankind, it is the best time to be alive. We are likely to learn more about ourselves in the next few decades than was possible in the last few centuries.

So back we go to an old theme, but with a new twist: how do women’s brains work?

To sort out this mildly contentious issue, Stuart Ritchie, up and coming member of the Edinburgh crew and its international affiliates, has provided intrigued men with a map of women’s brains. Smaller, of course, as many a man has surmised in the midst of an unexpectedly heated domestic discussion, but apparently able to function as well, or almost as well, as the male variety. Let us dig deeper into these mysteries, in the calm and measured way which befits this distinguished audience.

Sex Differences in the Adult Human Brain: Evidence from 5216 UK Biobank Participants
Stuart J Ritchie, Simon R Cox, Xueyi Shen, Michael V Lombardo, Lianne M Reus, Clara Alloza, Mathew A Harris, Helen L Alderson, Stuart Hunter, Emma Neilson, David C M Liewald, Bonnie Auyeung, Heather C Whalley, Stephen M Lawrie ,Catharine R Gale, Mark E Bastin, Andrew M McIntoshIan, J Deary.
Cerebral Cortex, bhy109,
Published: 16 May 2018

The authors say:

Sex differences in the human brain are of interest for many reasons: for example, there are sex differences in the observed prevalence of psychiatric disorders and in some psychological traits that brain differences might help to explain. We report the largest single-sample study of structural and functional sex differences in the human brain (2750 female, 2466 male participants; mean age 61.7 years, range 44–77 years). Males had higher raw volumes, raw surface areas, and white matter fractional anisotropy; females had higher raw cortical thickness and higher white matter tract complexity. There was considerable distributional overlap between the sexes. Subregional differences were not fully attributable to differences in total volume, total surface area, mean cortical thickness, or height. There was generally greater male variance across the raw structural measures. Functional connectome organization showed stronger connectivity for males in unimodal sensorimotor cortices, and stronger connectivity for females in the default mode network. This large-scale study provides a foundation for attempts to understand the causes and consequences of sex differences in adult brain structure and function.

There is much to discuss here, but my attention was drawn by two phrases “considerable distributional overlap” (which in my experience means that one group is pretty different from another) and “generally greater male variance” (which agrees with most of the observations on sex differences indicating that men are leptokurtic (more variable), women more platykurtic (less variable).

Women are more at risk of dementia, depression, schizophrenia and dyslexia. Men are better than women at mental rotation tasks, and are more physically aggressive; women are more interested in people than in things, are more neurotic and more agreeable.

One of the most interesting sex differences is intelligence. Here is their introduction to the topic:

There is more to sex differences than averages: there are physical and psychological traits that tend to be more variable in males than females. The best-studied human phenotype in this context has been cognitive ability: almost universally, studies have found that males show greater variance in this trait (Deary et al. 2007a; Johnson et al. 2008; Lakin 2013; though see Iliescu et al. 2016). This has also been found for academic achievement test results (themselves a potential consequence of cognitive differences, which are known to predict later educational achievement; Deary et al. 2007b; Machin and Pekkarinen 2008; Lehre et al. 2009a, 2009b), other psychological characteristics such as personality (Borkenau et al. 2013), and a range of physical traits such as athletic performance (Olds et al. 2006), and both birth and adult weight (Lehre et al. 2009a). To our knowledge, only two prior studies have explicitly examined sex differences in the variability of brain structure (Wierenga et al. 2017; Lange et al. 1997), and no studies have done so in individuals older than 20 years. Here, we addressed this gap in the literature by testing the “greater male variability” hypothesis in the adult brain.
We tested male–female differences (in mean and variance) in overall and subcortical brain volumes, mapped the magnitude of sex differences across the cortex with multiple measures (volume, surface area, and cortical thickness), and also examined sex differences in white matter microstructure derived from DT-MRI and NODDI. We tested the extent to which these differences were regionally-specific or brain-general, by adjusting them for the total brain size (or other relevant overall measurement; for instance, adjusting volume differences for total brain volume and cortical thickness differences for mean cortical thickness), and examining whether the differences found in the raw analyses were still present. We tested the extent to which these structural differences (in broad, regional, and white matter measures) mediated sex variation in scores on two cognitive tests, one tapping a mixture of fluid and crystallized reasoning skills (skills previously found to be linked to brain volumes; Pietschnig et al. 2015) and one testing processing speed (previously found to be linked to white matter microstructural differences; see Penke et al. 2012). At the functional level, we also examined large-scale organization of functional networks in the brain using resting-state fMRI functional connectivity data and data-driven network-based analyses.

The study compared 2750 females (mean age = 61.12 years, SD = 7.42, range = 44.64–77.12) and 2466 males (mean age = 62.39 years, SD = 7.56, range = 44.23–76.99). These are extremely large samples, two orders of magnitude larger than the early studies in the 1980s, and way larger than many of the studies that the Press report so frequently. Consider them “Foxtrot Oscar” samples.

The first result is startling: male brains are very much bigger, a colossal 1.4 effect size. 92% of men will be above the mean for women. On average men have 117.8 cm3 more brain than women. All this extra brain must be doing something for men, you might surmise, other than just helping them perpetually contemplate the relative advantages of the more complicated positions adopted during sexual intercourse. Perhaps not. Broadly the same effect of male advantage can be found in all the brain region sub-comparisons. Male brains are both larger, and also vary more in size. Greater male variability seems a fact of nature. If there were a direct relationship between brain size and cognitive ability, there would be many, many more bright men than bright women.

• Category: Science • Tags: Brain Scans, Gender, Sex Differences 
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Genc Figure_4 fewer connections

The ISIR July 2017 meeting in Montreal seems a long time ago, and that feeling is entirely explicable by it being 10 months since I heard the lecture in question. I was chairing the session, which normally diminishes attention to the actual content, but this talk was the exception. It came up with a counter-intuitive finding, and it has been difficult to avoid talking about it. Brighter brains have fewer connections between neurones. Cool.

It has been a real struggle to keep quiet about this remarkable result, and a relief that the embargo has been lifted today, 14 months after receipt of the paper by the publishers. Publish and be damn delayed. Blogging is the future.

As you will see from the author list, particularly the last author, this is a team which has been working on this topic for decades, (with important results from at least 1988) and has always sought to have reliable measures and large sample sizes before publishing anything. In ISIR 2014, tired of reading neuro-bollocks in the media, I lobbed Rex Jung what I thought might be a tricky question: How reliable are your neuro-imaging measures? He replied that he and Rich Haier had always put their subjects into the scanner twice: once briefly so as to get benchmark reliability measures, and then again for the full session. Jung and Haier also held back from publication until they had large sample sizes, although in early years this meant a long wait, since they were mostly working in the odd free spaces between the high priority medical school clinical use of the sole scanner available. Things have got better in recent years.

Another feature of this duo is that when they were offered an celebratory session at ISIR 2017 they chose to invite their critics to knock hell into them. Several did, and I pursue them every now and then to make their P-FIT theory more specific. So, it is great to be able to report some new and very specific findings.

Diffusion markers of dendritic density and arborization in gray matter predict differences in intelligence. Erhan Genç, Christoph Fraenz, Caroline Schlüter, Patrick Friedrich, Rüdiger Hossiep, Manuel C. Voelkle, Josef M. Ling, Onur Güntürkün & Rex E. Jung

Nature Communications volume 9, Article number: 1905 (2018)

The first two authors contributed equally. Take a good look at their reference list, which is a roll-call of the top people in the field, and those one should turn to for further comments on this paper and its implications.

Here is the main finding in full screen size, with the relevant explanations.

Here is the link to the entire paper:

Here is the abstract:

Previous research has demonstrated that individuals with higher intelligence are more likely to have larger gray matter volume in brain areas predominantly located in parieto-frontal regions. These findings were usually interpreted to mean that individuals with more cortical brain volume possess more neurons and thus exhibit more computational capacity during reasoning. In addition, neuroimaging studies have shown that intelligent individuals, despite their larger brains, tend to exhibit lower rates of brain activity during reasoning. However, the microstructural architecture underlying both observations remains unclear. By combining advanced multi-shell diffusion tensor imaging with a culture-fair matrix-reasoning test, we found that higher intelligence in healthy individuals is related to lower values of dendritic density and arborization. These results suggest that the neuronal circuitry associated with higher intelligence is organized in a sparse and efficient manner, fostering more directed information processing and less cortical activity during reasoning.

“Intelligence is not a function of how hard the brain works but rather how efficiently it works”.

In terms of method, the team collected 259 participants (138 males) between 18 and 40 years of age (M = 24.31, SD = 4.41) which gives the analysis of results sufficient power. Participants had no history of psychiatric or neurological disorders and matched the standard inclusion criteria for fMRI examinations. Each participant completed the matrix-reasoning test and neuroimaging measurements.
To validate the results obtained from sample of 259 subjects, the team downloaded additional data provided by the Human Connectome Project, namely, the “S500 plus MEG2” release. This set includes 506 participants with data suitable for their analyses. The best papers now give what would formerly have been two papers, for the price of one. The first sample is the sample of discovery, the second the sample of validation. Some things in science are getting better.

The measures themselves are a new variant of diffusion imaging analysis. If you will forgive a simplistic analysis: a pipe full of water will show different measures if measured end-on (where all the water in the pipe vibrates with the imposed resonance) as compared to when measured at right angles to the pipe (where only a small amount of water is available for resonance to be detected). In this way you can deduce which way the dendrites run in the brain.

Currently, the most promising technique for the quantification of neurite morphology is a diffusion MRI technique known as neurite orientation dispersion and density imaging (NODDI). This technique is based on a multi-shell high-angular-resolution diffusion imaging protocol and offers a novel way to analyze diffusion-weighted data with regard to tissue microstructure. It features a three-compartment model distinguishing intra-neurite, extra-neurite, and cerebrospinal fluid (CSF) environments. NODDI is based on a diffusion model that was successfully validated by histological examinations utilizing staining methods in gray and white matter of rats and ferrets. In addition, Zhang, Schneider have shown that NODDI is also capable of estimating diffusion markers of neurite density and orientation dispersion by in vivo measurements in humans. Direct validation of NODDI has recently been performed in a study investigating neurite dispersion as a potential marker of multiple sclerosis pathology in post-mortem spinal cord specimens. The authors reported that neurite density obtained from NODDI significantly matched neurite density, orientation dispersion, and myelin density obtained from histology. Furthermore, the authors also found that NODDI neurite dispersion matched the histological neurite dispersion. This indicates that NODDI metrics are closely reflecting their histological conditions.

The point is that this study confirms previous findings, that “measures of neurite density and arborization show negative relationships to measures of intelligence, implicating neural efficiency, particularly within parieto-frontal brain regions, as suggested by the vast majority of neuroimaging studies of intelligence”.

The study also provides a partial confirmation of the P-FIT theory, in that a majority of the observed associations between brain areas and intelligence conform to the predictions from P-FIT as proposed by Haier and Jung, or as further elaborated by Basten. The score could be called a 4 out of 5 area confirmation.

• Category: Science • Tags: Brain Scans, Brighter Brains, Intelligence, IQ 
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world IQ map becker 2018

Mankind’s IQ is 84-88. Becker May 2018 update

The London Conference on Intelligence began, as is now traditional, with an update on the project to produce a public database of the world’s IQ. It is hard to get academics to agree to anything, even when they are under bombardment, but this is one point of common purpose. Not surprisingly, there are many issues surrounding the notion of national IQs. Representativeness looms large. Well-organized countries have lots of data, less well-organized ones far less. Restricting the results to those countries which actually have data is an obvious step. For comparative purposes, one can look at the far less satisfactory approach of estimating missing country data by assuming they are like their nearest neighbours.

As befits a German, Becker has taken a systematic approach. He has now sorted the basics, such as the standard Flynn Effect correction to be applied, and now has to turn to the thorny matter of quality estimations, corrections for sample size, and the integrated representation of different measures of cognitive ability. There are also many new studies to be added. There are still many countries for which we do not have data.

When looking at his presentation slides, a few explanations are required.

DB = David Becker
L&V = Lynn and Vanhanen (authors of the original books on national IQs)
RPM = Raven’s Progressive Matrices (in various forms)
WISC = Wechsler Intelligence Scale for Children
CFT = Culture Fair Test

The last data slide Number 14 shows correlations between country IQs and a number of measures.
This slide is a useful summary of important findings so far.

Becker summary of correlations

Here is the link to his lecture:

Finally, we hope that you will look at the data repository, and tell others it is available for inspection and comment.

• Category: Science 
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Like many others, I first heard about the work of the late Hans Rosling through his TED lectures, in which his animated bubbles (nations over the decades shown as bubbles proportional to population size, rising or falling against some criterion, such as lifespan) revealed the mostly good news about human progress across the world. The lecture content was not a surprise. For decades the UN, WHO and other institutions had been showing welcome improvements in health and educational attainments in formerly poor countries. Documentaries in the 1980’s and 1990’s had illustrated the living circumstances of people at different levels of income. I can still remember an African man at the lowest living standards proudly showing off his heart-breaking annual material gains: a good shirt, a pair of trousers, and some shoes. The daily battle of the poor to get water, firewood and other necessities was contrasted at the end of the scale with a middle income European, where water came without any problem from taps in the home, the toilets flushed, and electricity and food were always available. It was all the more impactful because the Austrian’s income was low and his flat was modest, but it seemed bathed in luxury when set in global context.

This good message was amplified by many authors. Matt Ridley’s “Rational Optimist” was an excellent example. For centuries having light at home was a cumbersome and expensive business. The Romans had oil lamps with simple wicks. Candles were a great improvement, paraffin lamps with mantles (I grew up with those) an improvement on candles, and then incandescent bulbs were a paradigm shift, making night work possible. Since then the cost of lighting has fallen even further, with LED lighting consuming a fraction of the wattage of the older lamps. A good story of human ingenuity.

Hans Rosling, with whom I shared a Nobel Prize in 1985, follows a noble tradition of clear-headed helpfulness. A doctor specialising in public health, he used research to focus efforts on bringing health to poor (and poorly ) countries. Like all good educators, he begins with a quiz. The revelation of ignorance is the beginning of wisdom. I did pretty well on his questions, but felt I had cheated. From previous publications and some of my reading I knew the global story was a good one, so if in doubt I just went for the most positive outcomes. There are 13 questions, and I claim 9 right. By the way, question 7 is about the number of deaths from natural disasters. Page 5 says the deaths halved over the last 100 years (true) but page 271 says they doubled. Not good to criticize punters for getting questions wrong if the book can’t consistently get the answers right.

What is the book about? The major theme is that the state of the world is far better than people realise. Rosling does not regard himself as an optimist, but a possibilist. He shows that improvements are possible. While giving the figures, Rosling tries to explain why they come as a surprise to so many people, including aid workers, government officials, journalists, documentary film makers, and leaders of global corporations. He does very well on this, showing that we make a number of errors, particularly in using news broadcasts about exceptional events as a fallible benchmark regarding country differences. A lot of the book is about the proper management of data, and all this is good, and informative. He clearly shows that bad things are decreasing, and explains that publicizing these facts is not tantamount to declaring that no further effort is required to make things even better. Crime seems to be going up because we find murder stories more interesting than proper crime statistics. So long as we get an awful crime story once a week we can maintain our subjective feelings about society falling apart. Rosling is also good about the perils of simple extrapolation, and stresses the need to think in curves rather than just straight lines. Many global statistics are S shaped: a slow start when nothing seems to work, then a very rapid improvement, and then a gently rising plateau.

All this is very well, yet it would be wrong not to mention what the book leaves out. The underlying assumption is that all people all over the world are fundamentally the same, and although some countries have persistently rotten governments the people themselves are sensible, and have worked to achieve the great advances that the book records. Rosling puts no stock on the effects of ideology or religion, but believes that the data show that incremental improvements occur everywhere, despite those supposed differences.

There is validity in this argument, but it is far from a full picture. It is good to show that people make their own decisions about family size regardless of religion. I think that the “fundamental-sameness-of-people” argument somewhat elides obvious objections. Why should the good citizens of Africa require the services of a Swedish epidemiologist? Why not use home-grown talent? Rosling gave up his Christmas to hurry to Africa to sort out the Ebola crisis, having noticed the exponential rise of cases which normally denotes an epidemic. Once there he did a bit of work to distinguish between suspected and confirmed cases, showing that there was an understandable fear-driven over-diagnosis, super-imposed on a real epidemic, but that the steps taken so far were having the desired effect of reducing real cases. Good stuff. How come, some five or six decades after liberation from the colonial yoke, that no one on the ground in Africa had done the necessary spade work with the spreadsheets? (If they had, an apology is required from the authors).

David Landes’ conclusion, having studied the economic history of the world to determine how a nation becomes wealthy, can be summarised in one word: innovate. Rosling never mentions innovation. African inventions should be making their impact by now, at the very least challenging Asian and Indian businesses. He does not mention that China and India shot ahead by turning away from full central planning to their own versions of free enterprise. Rosling sees the growing level 2 world mostly as an investment opportunity for Western businesses. Some Africans have higher ambitions, and would like to be welcomed in Europe as wealthy tourists, once their own economies flourish in the globalised world economy. Too early to say when that will happen.

On the predicted African population boom Rosling is confident the UN is right to predict global population in 2100 as 11 billion, and that getting people out of extreme poverty will bring Africa down to the world pattern of less than 2.5 children per woman. However, he accepts that by 2100 there are predicted to be 3 billion more Africans and 1 billion more Asians, for a world picture of 1 billion Americans, 1 billion Europeans, 4 billion Africans, 5 billion Asians. He says that by 2014 60% of wealthy people (level 4) will live outside the West, and that Western domination of the world economy will be over. I feel that, in a mobile world, and given the track record of African governments, an extra 3 billion Africans will present the world with some problems, not least of which will be African migration to Europe.

• Category: Economics • Tags: Africa, Development 
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Psychological Comments screen grab youtube

Text is a refined type of talking. It involves an extra level of complexity, since reading and writing require some 7 years for a child to master, what with learning alphabets, reading, writing, and the composition of sentences, paragraphs and proper essays. The payoff from this investment is that written messages are compact, efficient, skippable, and eternal. Good quality ink on proper paper can last 500 years with reasonable care in a library. Every few years I look at the Salisbury Magna Carta, readable on vellum after eight centuries. Reading is a fast way of grasping the essentials of an idea, particularly when the writing has been very carefully considered. Words are tools of meaning.

I favour writing over talking because it is more precise, and easily editable. Ambiguities can be detected and corrected. Writing can be edited, errors quickly corrected.

However, speech is the more usual method of human communication. It seems to require no teaching at all, beyond immersion in the society of other talkers. A functional competence emerges in a few years, one of the wonders of human learning, and although vocabulary keeps increasing with the passing years the average 7 year old can give a good account of daily events, and understand much of the basics of language.

Speech reaches a wider audience, since not everyone reads, and listening is often easier than reading when there are other tasks to be done, or when concentration is fading. Ideally, speech can serve as the gentle introduction to deeper reading, a setting out of wares which might encourage some to take a longer look at a particular subject. This is particularly the case when you want to comment in general terms immediately, knowing that writing things up will take too long, or might even never get written up at all.

So, faced with a week in which many interesting papers had been published or publicize again, here is my attempt to supplement written accounts with some spoken commentary. Let me know what you think of it, and if you find it OK, recommend it to those who you think might listen to it.

Additional Notes

The Piffer equation is explained in my last post, and Piffer has added that the new correlation between his prediction and the observed genetic group means is 0.9

The bird migration paper is here, and turns out to be a 2010 study, recently in the news again:

The paper on free diving and larger spleens is here:

The iris response aspect is in another study

By the way, the selective change to the iris is contraction to pin hole size for better focus, not expansion for greater light. My error. Easy to edit in text, hard to change on a video.

• Category: Science 
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Piffer Lee 2018 continental pops

In June 2017 I declared open season on Davide Piffer, inviting criticisms of his findings:

The official response to Piffer is: “publish, and then we will give you our comments in reply.” This will take time, but it is the traditional way of doing things.

The unofficial response is to encourage more criticism right now, because if the finding is the result of a simple error, it should be exposed and corrected as soon as possible.

It is open season on Piffer’s methods. Recruit critics and get them conduct their peer reviews right now.

We are facing a French dilemma: Piffer has an approach to the genetics of racial differences in intelligence which seems to work in practice, but should not work in theory. His technique appears to run against the general trend of genetic research, in that he appears to be getting good results predicting group differences in intelligence on the basis of just 18 SNPs, while genetics researchers are getting only reasonable results in predicting individual intelligence on the basis of lots of SNPs.

For example, people skilled in these matters tell me that they did an out of sample prediction in an independent but European population, and they got 4.8% of the variance, using all SNPs. That is the upper limit of prediction in a non-European population using all SNPs. Pfiffer used just 18 SNPs in non-European populations and his correlation is huge, which does not make sense.

Piffer explained how he was able to achieve his results:

These SNPs that explain variance within populations are markers of polygenic selection. They do not have to explain a lot of variance between populations, or even within populations. The polygenic evolution model predicts that a few SNPs will have frequencies correlated to frequencies of countless other SNPs. I just need to know the few most important SNPs to gather a signal and infer to the distribution of the other unknown SNPs.

If selection pressure acted on these 9 SNPs by driving their frequencies up in population A compared to B, then it has also done the same to other SNPs. We don’t need to know what these other SNPs are because theory predicts that they will have similar distribution.

So, now that the massive James Lee study has been published, where does this leave Piffer’s polygenic evolution model prediction?

By the way, Piffer publishes in the modern sense of that word: he posts up his findings, together with all the code he used to generate his new results, thus allowing all and sundry to see inside the closet, and to check his figures for errors. You can peer review it and tear it apart here:

You can see the results for the 52 populations below:

Piffer Lee results for 52 pops

You can see the results for the major continental groups below:

Piffer Lee 2018 continental pops

You can see Piffer’s conclusions and cautions below:

Piffer conclusions on Lee 2018

In sum, Piffer has provided a further test of his approach. He cautions that some of the sample sizes are far too small. With any luck this can be dealt with by sampling more widely and in greater numbers. Larger samples may become available with time.

The general pattern is interesting, in that it is broadly in line with the expectations from intelligence testing drawn from country averages, and racial group averages.

Once again, in the spirit of the fearless examination of the intellect, I ask you to subject his work to merciless enquiry and savage criticism. Over to you.

• Category: Science 
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Detailed definitions of data and results tables here:

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The concept of “cognitive capitalism” was used by Yann Boutang in 2008 (modern economies are becoming more knowledge based), but I first heard it used by Heiner Rindermann in a somewhat different sense: cognitive ability is the cause of wealth. Heiner’s earliest mention of it in the title of a paper is one which we did together in 2011. Now he has written a major book on the topic, 576 pages long, and published by Cambridge University Press, no less. In this way the argument that it is people, not natural resources, which build national wealth has moved from sedition to the foothills of orthodoxy.

Cognitive Capitalism: Human Capital and the Wellbeing of Nations. Paperback – 31 Jan 2018
by Heiner Rindermann

The range of the book is extraordinary. It begins by looking at large wealth differences across time and nations; then the well-being of nations; human capital, cognitive ability and intelligence; history, culture and the Burgher-civic world; the impact of cognitive-intellectual classes; causes of national differences in cognitive ability (a major section, this one); global models for education, cognitive capital, production, wealth and wellbeing; the challenges of future development and predictions as to what will happen; a detailed review of some notable theoretical positions and ends with a set of detailed suggestions. This book is a tour de force. I hope it will be read by economists and all those interested in international development. In fact, most of the economic indicators are showing very welcome positive changes, but improvements in other continents outstrip those so far achieved in Africa as a whole. Concentrating on human capital could be a sensible way forwards.

Deciding how to describe the book is an intellectual task in itself. One way of starting is with the first table 1.1 showing estimates of global and continental income since 1500. Five centuries ago Africa, America and Australia were on $400, Asia $550 and Europe $688. By 2010 North America led the pack with $47,094, Northern Europe $35,308, Australia $25,438 and then a big fall down to South America with $10,607, Asia (India) with $3,337 and Africa (Kenya) with $1,628. The good news is that all countries are very much richer. The interesting story is that some countries have shot well ahead, prompting a debate as to how this happened.

Rindermann takes great care to compare all the measures of economic activity, and to contrast their various characteristics. He is aware that dollar totals do not capture all of the real wealth of nations, so discusses both narrow and broad measures. He uses Gross National Income as his basic measure, but notices that quality of local services is not fully captured by this measure.

It is because of those shortcomings that he devotes a full chapter to the well-being of nations, looking first at height and then at longevity to provide more substance. The good news for the world is that longevity has shot up in the last six decades. Though far behind, Sub-Saharan Africa has made a gain of 17 years. The Human Development Index gets a thorough examination, and even the less successful Gross National Happiness gets a mention.

As to human capital, Adam Smith understood perfectly that it comprised “superior reasoning and understanding, by which we are capable of discerning the remote consequences of all our actions, and of foreseeing the advantage or detriment which is likely to result from them: and secondly self-command, by which we are enabled to obtain a greater pleasure or to avoid a greater pain in some future time. In the union of those two qualities consists the virtue of prudence, of all the virtues that which is most useful to the individual.”

To my mind, that wraps it up. However, Friedrich List spelt it out once again in his 1841 version: “Everywhere and at all times has the well-being of the nation been in equal proportion to the intelligence, morality, and industry of its citizens; according to these, wealth has accrued or been diminished”.

We know that cognitive abilities are the best predictors of job performance. Rindermann follows through, arguing that the intelligence of nations are the best predictors of national performance. He then turns to what he calls “contentious issues”. He points out that intelligence research is blithely ignored by PISA, PIRLS and TIMSS, who act as if cognitive ability does not vary from one student to another. This is an obtuse posture.

Another misunderstanding is the Nazi attitude to intelligence testing: in fact, the Nazis were opposed to intelligence research, which they saw as an instrument of “Jewry”. They specially opposed the concept of intelligence as a “one-dimensional dimension” and as “one common central factor”. They wanted measures of “realism” and “conscientiousness”, not what they regarded as “theoretical intelligence” and “intellectualism”. They favoured “practical intelligence”. In their view, general intelligence did not exist. Odd, isn’t it, that these views, a commonplace today among those who reject intelligence research, should be so similar to the Nazi position.

Rindermann reviews the literature on international ability differences. This is an important chapter, and well worth reading on its own. Rindermann adds a whole section of what he calls Everyday Life Evidence and Sediments. This section will probably make some people angrily accuse him of descending to anecdotes. Rindermann argues that if the intelligence tests scores are valid, then a visitor to each country should find evidence of how bright the people in that country really are. He discusses his own experiences as a traveller (and since he did research in many countries he has much to report). He reports on airport malfunctions, local variations in the standards of global companies, irrational beliefs, rates of innovation and crime possibly can be dismissed as isolated incidents, yet they are real life tests which, if supported by other travellers, are real data which ought to convince sceptics about country differences.

Rindermann has a look at the traditional explanations for national wealth: investments, economic freedom, rule of law, education, cultural and religious factors, geography, and politics. He evaluates each of these against the dataset. The effects of economic freedom with GNI seem to be strongly positive at r=.60 to .70. Countries which come out from the Communist yoke do better. However, cognitive ability seems to be even more powerful. Market economies favour rational actors who can assess their competences and the quality of their products in the market place and alter their plans accordingly. Quality of institutions is also relevant: rule of law, low corruption and government effectiveness correlate .7 with GNI. As regards the argument Jared Diamond famously put forwards in “Guns, Germs and Steel” that geography is the key determining factor (all this argued without data tables) Rindermann points out that, even if true, why would this be relevant to national wealth today, when every region in the world has access to knowledge, food and commodities? It could only be genetics or culture that would have the lasting imprint of adaptation to the original geographies. Paradoxically, nations with few natural resources have often prospered, since (as David Landes quipped) nothing so concentrates the mind as lack of money.

Rindermann lays more stock on culture, in the sense of the world view of the Burgher-Civic world, which one would usually describe as middle-class or bourgeois: appreciation of education, knowledge and rationality, diligence, order, meritocracy and thrift, rule of law, effective government, self-responsibility, realism and pragmatism. These virtues can be practiced in any geography, and lead to eventual success.

• Category: Science • Tags: Capitalism, IQ, Iq and Wealth 
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Heritable general intelligence

By now you will know that I have often been sceptical about the view that we are becoming less intelligent. Estimating these matters is problematical. For example, can we judge where Stephen Hawkings will stand in the canon of theoretical physicists? I think it would be premature to judge, particularly when at the moment we do not have ways of testing his conjectures. Giving it 50 years seems prudent. Something may turn up. Indeed, I think Charles Murray was absolutely right, in describing human accomplishment, to stop the clock 50 years back. We are too bound up by present enthusiasms. For example, the movie we saw last week comes to mind easily, whereas only the best of those watched a decade ago stand out in memory.

However, one should not permanently discard a hypothesis simply because the early work did not support it. The potential problem was first noted by Galton in 1869. In the 1930s Raymond Cattell was pretty sure that the greater fertility of poorer and duller couples was going to bring down the population average, but was surprised to find that the data showed a contrary trend. Perhaps this was because the effects of copious fertilizer overcame a drop in the quality of the seed, but results are results, and the dysgenic hypothesis looked weak. Of course, to continue the agricultural analogy, yields could also be adversely affected by over-use of pesticides. One possible cause of less capable brains is that these sensitive organs are being poisoned by man-made toxins.

All this and more is covered in the introduction to a new paper:

What Caused over a Century of Decline in General Intelligence? Testing Predictions from the Genetic Selection and Neurotoxin Hypotheses Michael A. Woodley of Menie & Matthew A. Sarraf & Mateo Peñaherrera-Aguirre & Heitor B. F. Fernandes & David Becker

What are we to make of all this? The Woodley et al. argument is that general intelligence, the important and heritable part of mental ability, is falling; and that specific skills, the environmentally-influenced non-heritable part of mental ability, had risen over the last century and is now on a plateau.

The supportive findings are as follows: if you take the g loadings of mental tests (their saturation on the general factor of intelligence) and you link those loadings with the effect sizes of things like inbreeding depression and correlations with motor reaction times, then the strength of selection against intelligence (duller citizens having larger families) is more pronounced on g loaded abilities, but correlates negatively with the Flynn Effect (the secular rise in many, but not all mental tests).

So, it is better to track general ability rather than specific specialised skills.

If you look at the loadings for g over the decades of the last century you will see that the presumed dysgenic effect is not uniform and consistent, as would be expected from a gentle but persistent decline. The authors are aware of this, and provide counter-arguments, but it remains a puzzle, and in my view weakens the hypothesis somewhat.

heritable gen intell by decades

Overall, we have a strong and coherent case for the dysgenic hypothesis, which critics can now respond to.

• Category: Science • Tags: Dysgenic 
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.