The BBC and other media outlets have publicised a disturbing claim in a Parliamentary report, that racism has played “a key role” in the deaths of pregnant mothers.

End racial disparities in maternal deaths – MPs. An MPs’ report is calling for faster progress to tackle “appalling” higher death rates for black women and those from poorer areas in childbirth.

The Women and Equalities Committee report says racism has played a key role in creating health disparities.

But the many complex causes are “still not fully understood” and more funding and maternity staff are also needed.

https://www.bbc.com/news/health-65300168

This is mostly based on a previous official report from: Maternal, Newborn and Infant Clinical Outcome Review Programme November 2022 Saving Lives, Improving Mothers’ Care: Lessons learned to inform maternity care from the UK and Ireland Confidential Enquiries into Maternal Deaths and Morbidity 2018-20. (They have added some interviews with mothers who felt that their concerns were ignored for racist reasons).

https://www.npeu.ox.ac.uk/assets/downloads/mbrrace-uk/reports/maternal-report-2022/MBRRACE-UK_Maternal_MAIN_Report_2022_v10.pdf

The first thing to note is that pregnant mothers are very safe, with a death rate of 6 per 100,000. Even taking a year-long period, and including indirect causes, deaths are extremely rare. Suicide and drugs/alcohol are prominent causes of the few deaths recorded, with cardiac disease and Covid of equal impact. (Hatched bars show direct causes, solid bars indirect causes).

So, for example, Covid was an indirect cause of death, because it happened more widely, and not because of pregnancy.

Half the causes of death are not obstetric. This should be a warning bell about the interpretations later placed on the data.

Later data show that the greatest predictor of later death was pre-existing medical problems including obesity. Obesity is also given as a primary cause. Not receiving advice is also noted as a cause, though not clear if this can be due to not taking advice despite ante-natal classes being offered. Some of the case histories mention this, and it would be relevant to understanding causes, and could be compared to the take up of vaccinations.

Table 2.9 gives us the figures on regarding race differences, the subject of media attention on the Parliamentary statement, but also prominent in the summary of the research report.

The numbers, mercifully, are small. Childbirth is safe in the UK. The White European results are the only one sizeable enough to merit detailed examination, and they show that direct and indirect causes are of almost equal power, slightly favouring indirect. The racial group deaths are few, and some noise is to be expected.

To put this report into context, as regards UK Black Caribbean mothers, we are talking about 3 direct deaths, 6 indirect, so 9 in all. Black Africans (who probably have spent more of their lives in Africa), are 5 direct, 8 indirect, 13 in all. Combine the two, 8 direct, 14 indirect. Tiny numbers, but favouring indirect causes.

Here are the calculations of rates per 100,000

The rates per 100,000 differ considerably, but the base populations also differ considerably, and there are 18 times more whites than blacks. When events are very rare it is probably better to give absolute results, rather than relative risk odds ratios, which could be misleading.

In my view the main finding is that some mothers are unwell prior to childbirth, and often die for reasons not directly caused by childbirth. Some of those causes of ill health are self-imposed.

The Parliamentary group seems to have gone overboard on a racism explanation for which there is no evidence in this study. Indeed, there is virtually no data analysis in this report at all. They give the basic demographics, but few if any two by two tables. They do not show correlations, nor do they construct and test any explanatory models. Can they predict from their findings what puts women at risk? Drugs, drink, being overweight? Little from the authors on these necessary questions. A simple multiple regression on the total sample would have been instructive. The list of participants is impressive, the data analysis rudimentary, and the use of relative risk over-dramatic given the very big differences in sample sizes.

As is usual, they give stern lectures to service providers about the need to further educate themselves. They say less, if anything at all, about mothers keeping themselves healthy, for their own sake, and of their babies.

As you may have noticed, it is not popular to suggest that genetics is a possible cause of individual differences, and distinctly unpopular to even hint that it might be a cause of genetic group differences.

By way of background, when Arthur Jensen was first considering the causes of the black-white difference in scholastic attainment, he gave an entirely environment-based explanation. This was in a lecture in 1967, when he was first looking at the issue. You could not put a cigarette paper (remember those?) between him and any sociologist. It was only when he got far deeper into the literature that he changed his mind. Facts mattered to him, and should matter to everybody. He made an evidence-based alteration in his prior views, and on page 82 of his famous 1969 paper said:

The fact that a reasonable hypothesis has not been rigorously proved does not mean that it should be summarily dismissed. It only means that we need more appropriate research for putting it to the test. I believe such definitive research is entirely possible but has not yet been done. So all we are left with are various lines of evidence, no one of which is definitive alone, but which, viewed all to¬gether, make it a not unreasonable hypothesis that genetic factors are strongly implicated in the average Negro-white intelligence difference. The preponderance of the evidence is, in my opinion, less consistent with a strictly environmental hypothesis than with a genetic hypothesis, which, of course, does not exclude the influence of environment or its interaction with genetic factors.

A cautious statement which was met not with the proposed further research, but with outrage and the circling of defensive wagons which continues to this day. Indeed, any researcher who penned such a paragraph in a paper submitted to a main stream journal today would probably find that it was sent not to the usual two, but to three or four reviewers, the last two expressing severe reservations as to whether it should be accepted.

You know what happened over the last five decades: researchers cautioned, warned, excoriated, censured, censored, unfunded and more recently sacked for considering the hypothesis on an empirical basis.

So, what happens next? Well, if facts exist, someone will notice them and, if brave, find a way of letting people know what they have noticed.

A Multimodal MRI-based Predictor of Intelligence and Its Relation to Race/Ethnicity. Emil O. W. Kirkegaard and John G.R. Fuerst. The Mankind Quarterly · March 2023.
DOI: 10.46469/mq.2023.63.3.2
https://drive.google.com/file/d/1iVjNT1Uv9fC3uZzwBPpVQDRGWbmiPXoV/view?usp=sharing

What have they found?

They say:

We used data from the Adolescent Brain Cognitive Development Study to create a multimodal MRI-based predictor of intelligence. We applied the elastic net algorithm to over 50,000 neurological variables. We find that race can confound models when a multiracial training sample is used, because models learn to predict race and use race to predict intelligence.
When the model is trained on non-Hispanic Whites only, the MRI-based predictor has an out-of-sample model accuracy of r = .51, which is 3 to 4 times greater than the validity of whole brain volume in this dataset. This validity generalized across the major socially-defined racial/ethnic groupings (White, Black, and Hispanic). There are race gaps on the predicted scores, even though the model is trained on White subjects only.

This predictor explains about 37% of the relation between both the Black and Hispanic classification and intelligence.

So, by looking at all the MRI measures they can predict IQ better than by using brain size alone. So, we should stop using the brain size measure (about 0.28) and move to this better measure (0.51) and eventually the even better ones that may be found later.

First of all, some summary data:

These are adolescents, so things may change a bit with age, but these are good sample sizes. Black adolescents have a somewhat lower than expected low score, and a high standard deviation, the latter surprisingly so, since many previous black samples have a standard deviation of 13. I don’t know how to interpret this, but it might be due to the subtests used.

The intelligence tests used were not the best sample of skills (where were Maths, or Wechsler Vocabulary or Block Design?) and they over-represented working memory tests, which I think are weak measures, though fashionable. It may account for the large standard deviation finding. I predict that a more representative range of tests would lead to even higher predictive accuracy overall, and perhaps lower standard deviations.

The learning algorithm they employed was one suitable for use in the tricky setting where there are far more variables than individual subjects. When you apply the algorithm to the whole sample, leaving aside race, then the correlation with IQ is 0.60 which is very high. Using this technique, a brain image gives a good guide to the power of the brain as a problem-solving organ.

Using an MRI-based predictive equation the authors did a better job of predicting a person’s IQ than was possible from knowing their parent-described race, despite the racial differences in intelligence being large. These “social race” labels were redundant for the purposes of predicting intelligence.

The correlations of MRI prediction with actual intelligence test results within each social race were pretty similar: white 0.51, black 0.53, Hispanic 0.54 and other 0.58.

They tried to see if their algorithm could use MRI data to predict the social race of the adolescents, and found they could do so with 73% accuracy. The distinction between blacks and whites could be drawn with almost complete accuracy, only a 2% error rate either way.

They then trained a model to predict genetic ancestry. You might want to call this race.

They say:

We find that MRI-based predictions of genetic ancestry are very accurate. The three correlations of interest are .91, .89, and .61, for European, African, and Amerindian ancestry, respectively. As expected, the correlations were higher for European and African ancestry than for White and Black social race, respectively.

So, you can study a brain image and predict the person’s race with very high accuracy.
A possible counter-argument is that the model has learned to spot race, and then sharpens its intelligence predictors. The authors decided to test a predictive equation for whites only, so as to cut out this possible confounder. In fact, it only goes down from 0.51 on the full dataset to 0.48 for whites only.

As usual, I have left out some of the additional tests carried out to make sure the findings were robust.

the model learned to predict subjects’ social race/genetic ancestry based on the MRI data, and then used this information to predict intelligence. This finding is consistent with those of Gichoya et al. (2022), who report that machine learning can recognize self-reported race/ethnicity from a wide variety of medical imaging data. This is unsurprising because in the USA, socially identified race closely tracks continental genetic ancestry (Kirkegaard et al., 2021; Tang et al., 2005), which certainly is not “only skin deep”.

I am in favour of countries, in the same way that I am in favour of houses having lockable front doors. Countries have good precedents: the first biological cell seen by Robert Hook in 1665 seemed to him like the small cellular rooms monks lived in. The cell is the motor of life, and it has a well-defended boundary. The great advantage of having a national border is that you can repel boarders, in the same way that biological cells repel intruders that seek to invade and destroy it.

Within a country you can establish laws that regulate what happens in the street outside your front door. That is useful, because even if your house is your castle, it is no use to you if strangers are allowed to lay siege to it. You must be able to have the quiet enjoyment of your abode, at the cost of paying taxes for the laws that protect it. Good fences make good neighbours, and fences are strongest when backed up by national laws. By Saxon times most arable land in England was spoken for, and in Mediaeval times most litigation was about access to water power, where every inch of water level mattered.

Question is: What is the right size for a nation? Too large and the nation may fall apart, under the weight of its contradictions. Too small and it is held hostage by more powerful entities. Is there a rational way to scale the optimal size of a nation? Small and homogenous sounds very good for a friendly and tranquil life. Large and sparsely populated sounds better for an independent and more exciting existence. This is an active debate in the United Kingdom, where Scotland wishes, or partly wishes, to leave England, and appears to be an incipient debate in the United States, where some states would like to be rid of some other states, particularly those which are costly nuisances. Right sizing a country is a difficult business.

Russia is very, very large; Canada, China, United States, Brazil and Australia are very large, but the wealthiest countries (on a per capita basis) tend to be smaller. Have those smaller places some secret sauce? Are there beacon countries, admired and envied, as in their time England and the United States were, and then Sweden perhaps, and so on, which have lessons to impart?

Recently the Financial Times suggested Uruguay, as The Economist had done some years ago. It is worth studying that recommendation, using the past beacons of US and UK as comparison, and taking as regional benchmarks Uruguay’s two big neighbours, Argentina and Brazil, and as cultural and genetic reference points Italy and Spain, where most Uruguayans come from.

Is Uruguay a special case?

Consider wealth per adult. Look at the map of the world, and it is evident that Europeans are the wealthiest in the world, (plus Japanese and Koreans). Europeans build wealth even in the frozen wastes of Canada and in the baking deserts of Australia. Not even Gilbert and Sullivan operettas can drive them to penury.

Find South America (bottom left) and note there is only one country on that continent where median wealth is in the $20,000-30,000 dollar range. That country, Uruguay, is 87.7% European. Case proved? It is on a level found in Eastern Europe, and in newly risen China.

Here is a small comparative table, drawn from United Nations or World Bank data. Remember that all these figures contain an error term, and other sources will be slightly different, though the rankings will be pretty similar. I prefer actual figures to rankings, since they are more informative.

Adult mill: adult population in millions
Density: population per square kilometre
GDP: per capita in actual dollars
GDP ppp: per capita adjusted in terms of local buying power (Nominal rates are more important for trade and influence, purchasing power parity for those who wish to emigrate in either direction).
Wealth: median wealth, which is most representative of the average person
GINI: coefficient of wealth differences, high score meaning large differences
HDI: human development index, showing the general quality of life per country
Honesty: meaning the opposite of corrupt
PISA: overall scholastic scores in most recent studies.

Population adult:
Population density: https://worldpopulationreview.com/country-rankings/countries-by-density
GDP: https://en.wikipedia.org/wiki/List_of_countries_by_GDP_(nominal)_per_capita

Median wealth: https://en.wikipedia.org/wiki/List_of_countries_by_wealth_per_adult

Uruguay is a very small country, with low population density, high wages, high GDP, and very wealthy in regional terms. It has a smaller gap between rich and poor than its neighbours, has a good human development index, and is extremely honest. Its countries of origin are more corrupt, its neighbouring countries even more so. (One of Uruguay’s biggest industries, paper mills owned by Finns, came to Uruguay because Argentine corruption was outrageous).

Can all these good things be true? If so, how do you become a resident?

Very simple: You need a clean criminal record and must be able to prove a monthly income of around 1500 USD per person. If you are a family of four, the main applicant having an income of $2,000 is permissible. Married people are preferred. (Despite my pleas, Uruguayans think in months). 1,500 USD is a good wage in Uruguay. Well qualified young people make about 1800 to 2000 USD per month. Those skilled in IT, mostly working for US companies, can earn two or three times that. The above route gets you citizenship in 3 years for families to 5 years singletons. Caution: in your first year you will be expected to be here for 9 to 10 months. By the way, when I say dollars, I mean the real market rate for the greenback. There are no restrictive lower rates imposed by the government.

For those in more of a hurry, invest. For a person to become a tax resident by having main economic interests in Uruguay, they must invest in real estate or an enterprise and stay in Uruguay for at least 60 days per year. The minimum amount accepted for a real estate investment is $390,000. The minimum amount for an enterprise is $1.7 million, so long as that company also creates 15 jobs throughout the year.

Those that move their tax residence to Uruguay are eligible for a tax holiday on their foreign-sourced financial income. As of 2020, a tax residence act extended this holiday to 11 years. After that, tax residents will pay a standard 12% personal income tax on foreign interest and dividends. Uruguay tax residents can live tax-free on any foreign-sourced income for 11 years.

All good? There are some drawbacks. The current Government is still clearing up the excesses of the last one. The economy is picking up, people are feeling richer, though prices are high relative to earnings. Like in other parts of the world, the young are finding it very difficult to buy property. Some youngsters prefer social benefits to employment. A barbershop owner tells me he has vacancies for another 3 to 4 haircutters, but cannot find them. The last candidate lasted a fortnight, then left. The owner was relieved, since the young man had spent most of his time on his iPhone.

Last night I went to hear some old guys talking about having eaten their friends.

I had met one of them, but it was the first time I had seen the others in the flesh, and flesh has a big part to play in this story.

The 1972 plane crash in the Andes of a Uruguayan rugby team, carrying 45 team members, families and friends has been told many times. The 1974 account by Piers Paul Read, Alive: The Story of the Andes Survivors brought it to a very wide audience.

The turbo prop plane crashed into a mountain, instantly changing them from airline passengers into a shattered platoon of dead, dying, injured and traumatised waifs abandoned on a treacherous glacier, alone in the high mountains, bleeding and freezing to death.

16 young men who survived by eating the bodies of their friends. Every one of them knew they were potential survivors and potential fuel, on which their friends could feast. “Take, eat, this is my body”. Soul or not, humans are heat machines.

It is one of the better-known survival stories, and will shortly be even better known to a new generation when the Neflix movie directed by J.A.Bayona is released later this year.

Five of them were onstage last night, on the 50th anniversary year of their Fall.

https://en.wikipedia.org/wiki/Uruguayan_Air_Force_Flight_571

All disasters are natural experiments. A selection of people are subjected to terrible events, and the rest of us later pick over the pieces, looking for heroes and villains, and imagining what we might have done, in armchair comfort and with the benefit of hindsight.

Pablo Vierci. La Sociedad de la Nieve. Planeta, 2008, 2022.

What stories do we want to hear? That in adversity it is “every man for himself”? That in this awful situation whatever happens is truer and more profound than everyday life can ever be? That you “don’t know what is in the teabag till you put it in hot water”? That modern man cannot survive primitive circumstances, and that conventional intelligence counts for very little? That everyone becomes religious in adversity?

One of the survivors, Roberto Canessa, described the crash as a sinister laboratory experiment designed by a mad scientist to test not guinea pigs but a group of young men. He made everything as awful as possible for as long as possible, just to see how much they could take.

Why are people interested in this particular tragedy, when there are so many instances of human suffering? The reason may be the taboo about eating human flesh, the almost supernatural courage and resourcefulness shown by the survivors, and the eternal doubt about what we ourselves would have done in such circumstances.

What was required of survivors in this situation? Everything, one might assume.

Roberto Canessa summed up the essentials:

Team spirit, persistence, sympathy for others, intelligence and, above all, hope.

Their situation was parlous. They were in this dreadful situation because of pilot error. The navigator was at the back of the plane playing cards, the pilots were over-confident, and did not bother to check the one instrument which would could have saved them: their wristwatches. Had they done so they would have realized they were turning North far too soon, and had not allowed for the headwinds against them. They had not yet gone far enough West, were not yet out of the Andes, and mistakenly descended North into the high mountain peaks. After hitting a mountain which tore off the wings, the fuselage careered down a glacier and slammed into snow.

They had many dead, and many injured they had to care for. It was reasonable to believe that planes would come to search for them, and some of those planes could be heard and seen overhead for the next 8 days of search, though they found nothing. Temperatures went down to -30 Centigrade at night, so to keep from freezing to death was essential. Body warmth was their sole source of heat as they huddled together in the remains of the fuselage. Most of them had never seen snow, and had no idea how to survive in high altitudes.

Some days later, when a small group ventured out into the snowy desolation, they all suffered from the bitter cold, one went snow blind, and the lack of implements to help them through the snow showed how helpless they were. Not encouraging. Staying put and waiting for rescue seemed better.

How to survive?

Intelligence is what you use when you don’t know what to do. (Carl Bereiter).

To provide drinking water, Fito Strauch worked out that snow collected in an aluminium shell would catch the sun’s rays and provide a trickle of meltwater, which they shared in very small gulps. He also designed improvised sun glasses to combat snow blindness. They used seat covers as protective clothing and footwear.

Roy Harley improvised an antenna so that a transistor radio they found hidden in a seat could provide them with news, the first being that the search had been abandoned. He also tried to get the batteries and remains of the radio receiver to build a transmitter, a task which understandably proved impossible. The batteries they found were of the wrong voltage to power the available equipment, even if they had been able to assemble it.

The survivors who had found the rear of the fuselage came up with an idea to use insulation foam from the rear of the fuselage, sewed together with copper wire, and waterproof fabric that covered the air conditioning of the plane to fashion a sleeping bag. Nando Parrado and Carlos Paez led the work on this.

Those with medical knowledge did a triage of the wounded, including removing a shaft of metal from a person’s intestines.

In short, when they did not know what to do, they improvised, and innovated. Such knowledge as they had of medicine, mechanics, navigation and engineering was put to good purpose.

When Nando Parrado, Roberto Canessa anid Antonio Vizintin set off on their final rescue mission, they had no technical gear or clothing, no compass, and no climbing experience. Vizintin went back after 3 days, because there was not enough food.

As a matter of painful observation, and guidance from the few who had medical knowledge about the Krebs cycle (the body can convert protein into sugar, and fat into protein, so that on a meat only diet they could survive without malnutrition), it was obvious to the starving survivors that they needed to eat energy rich protein to survive. In ordinary conditions, warm temperatures at sea level, 2000 calories of food would be sufficient. Under sedentary conditions in the cold high glacier, 3,600 to 4,300 calories would be needed. For highly strenuous work in the cold, like climbing up a mountain, 4,200 to 5,000 calories would be required. (British soldiers training in Norway get 5000 calories, and an officer told me “You have to stand over them at breakfast to make sure they eat it”).

The fact that the world had abandoned them within a few days made them better able to feel justified in abandoning the taboo about not eating human flesh. Initially they spoke about this in whispers, then in small group deniable hypotheticals, then finally in open discussion. Not all agreed, though the lack of any rescue plans was an eventual clincher for most. For everyone’s protection, a small group made the first cut in the actual bodies, and gave it to others to further cut and dry the flesh strips in the sun, so that all could eat without knowing whose flesh it was.

National IQs were collected by one psychologist, Richard Lynn, sitting in his study. He said he found them more interesting than collecting stamps. Early in his career he had collected intelligence test results when working in Ireland, but thought that the results would be unpalatable, (they seemed to show that brighter Irish people had emigrated leaving duller ones behind) and so he sat on them for some years. Eventually he began collecting any papers which mentioned intelligence test results in different nations, and thus built up a picture of national intelligence test results. He also began encouraging researchers across the world to collect intelligence results in their countries.

Eventually in 2002 he published the results he had obtained, necessarily based on papers with variable sample sizes, somewhat different tests, administered at different ages. He was open about the fact that some nations had much better data than others, and that for many nations no results were available. Additionally, some nations participated in international scholastic tests, and others did not. The often-forgotten point was that for the first time he had gathered together data not otherwise easily available. He then showed that the results on these paper-and-pencil puzzles correlated substantially with national economic and social variables.

The results were interesting, and began to be incorporated into international studies, though they were infrequently mentioned in international economic studies. His work also drew criticism which cleverly drew attention to the weaker studies, thus seeking to invalidate the overall conclusions, which was that national intelligence levels were closely related to important economic variables. Unfair, but effective. Given the criticisms, I argued that it was necessary to re-work the entire database, listing every study in such a way that each paper could be evaluated in terms of a data quality. David Becker rose to the challenge, and the whole dataset has been worked over again and is available for researchers as an open resource.

One line of criticism of the original work was that the samples were too small and unrepresentative to serve as proper national results. However, since most psychology papers use very small and unrepresentative samples to make claims about all human nature, this would have invalidated all psychology. In fact, psychometric samples tend to be bigger than experimental psychology samples, so have a better claim on our attention.

Despite the re-working of the dataset by David Becker, in the current over-heated climate of denunciation, researchers have been heavily criticised for basing any of their work on national IQs. The usual procedure in academic research is to improve the data by further research, and by suggesting methodological refinements. Oddly, the dominant voice in academia has been those who denounce the work entirely, in a quasi-religious renunciation and condemnation. As the British say, this is somewhat Over The Top. All national measures can be improved, and we should not reject out of hand potential explanatory variables.

Not all national statistics on literacy, income, wealth and health are themselves reliable. A friend who worked at the World Health Organisation headquarters tried to improve their statistics by interviewing every national health minister when they came for a visit. He found that most of the African ones just gave him the figures without linking them to a source he could check, so he felt they represented national pride, not actual verifiable findings.

There are of course other refinements possible, such as comparing cities with provincial locations, so as to determine whether countries have strengths in depth.

Into this fist-fight about national IQs steps Russell Warne, to give his own evaluation of the controversy.

Warne, R.T. National Mean IQ Estimates: Validity, Data Quality, and Recommendations. Evolutionary Psychological Science (2022). https://doi.org/10.1007/s40806-022-00351-y

In a calm and wide-ranging paper, Warne had followed a steady path in his evaluations. He shows that the general picture of national differences has been confirmed as broadly right. He also shows that the low African figures on intelligence tests are probably right when one looks at the similarly low achievements in very simple mathematics shown on scholastic exams. He explains why the low scores do not mean that Africans are mentally defective, as might be the case for low scores in European populations. (Jensen had explained this in 1980).

He also makes the case that Raven’s Matrices may present particular difficulties for African test-takers. I find this a worrying suggestion, because it may imply that Africans are different in kind, not simply in general intellectual power. If this is true, it has severe consequences. Far from just saying “Matrices are not a good measure of African intelligence” it could equally be argued that “Africans cannot follow logical sequences that all other races can solve”. This is not a pleasant proposal, though of course we should be open to testing it. Raven showed that his test items had similar response curves, with only three or four showing deviations from the normal pattern, suggestive of cultural artefacts. Personally, I think that power differences are more likely than type differences. Brains are similar, though they differ in power.

Personally, have listened to David Becker talking about low scores in Africa, I think that on occasion the tests are badly administrated. (As Warne and Rindermann and others have pointed out, many African teachers are of low ability, poorly paid, and consequently poor attenders at school). However, such defective administrations are usually detectable from looking at the results carefully.

As a consequence of his own researches, Warne identifies a matter which must be improved. The Lynn database was put together on the previously acceptable basis of gathering as many studies as possible by searching for them, and increasingly by collaborating with researchers across the world. All this is well and good, but modern standards are more demanding. One has to show exactly how references were searched for. This is a welcome improvement, because it ensures that the database is fully representative of the available publications.

Warne himself has found studies which ought to have been included, and this is of itself a contribution to the research project. Of course, this task is endless, but it would be excellent if more scholars contributed to the joint project. (In reality, this has proved difficult. Some researchers I encouraged to contribute felt that their methodological suggestions had not been taken up, so didn’t participate further. Others simply didn’t want to be associated with national intelligence research, a refusal which damages psychology generally).

Warne has done good work, and has gathered extra data which should be added to the overall database of national intelligence research. He has made a good case for continuing and improving the international research project. His overall judgment is “The database is useful, probably broadly accurate, strongly linked to other national variables, but should be improved by a more systematic inclusion process and the addition of other relevant research”. I hope some scholars will take up the challenge.

A final note: all psychologists should take heart that a single researcher collecting publications on a particular topic can sometimes produce findings of considerable international interest, with strong predictive power, and in line with other massively funded international scholastic studies.