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Do genes account for 50—70% of racial differences in intelligence?
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It is perfectly reasonable for critics to ask, every so often, if there is any work showing that genes make a contribution to intellectual differences between genetic groups. I assume it can be accepted that genes make a difference within a genetic group, and the animus arises only when genetic groups are being compared.

One approach is to begin by mentioning the major findings of the last century of research, which set the context of the debate. Although reasonable, the reading involved may seem unreasonable to those who want immediate answers. A brief summary would be that, despite many interventions over seven decades, African Americans remain roughly one standard deviation behind European Americans. Whatever the reason for the ability gap, it has not proved malleable.

Another approach is to discuss a selection of recent papers. This ought to be welcome, but unfortunately for those who want to skip the reading, it is necessary to go back to some old debates.

For example, although differences in intelligence between racial groups could be caused by different genetics, they might also be caused by trivial aspects of race like skin colour, which then triggers non-trivial bad treatment by other races. This bad treatment, the argument goes, could cause intellectual under-performance, either by denying educational access and quality, occupational opportunity, sufficient encouragement and mentoring, or leads to some other broad, unfair impositions. So, if a research finding is to be believed, it must distinguish between deep intrinsic causes and superficial social ones.

Furthermore, if some ancestral backgrounds really create higher intelligence in offspring, then those who have less of that advantageous genetic material should have progressively lower intellectual ability; that is to say, there must be a linear dose-response relationship. Purely European children must be brighter than those with a little less European in their genetic mix; and they must be brighter in turn than those with even less European blood. No excuses allowed.

Global Ancestry and Cognitive Ability.
Jordan Lasker, Bryan J. Pesta, John G. R. Fuerst and Emil O. W. Kirkegaard
Psych 2019, 1(1), 431-459;
30 August 2019

This is a very detailed paper, which makes use of a natural experiment. Since Europeans, African Americans, and the children of European/African American parents have varying amount of European ancestry, it ought to be possible to check whether that genetic mix predicts intelligence, and whether is does so better than superficial characteristics like skin colour.

The paper is set out in a series of logical steps, each countering objections commonly raised against the hereditarian hypothesis.

They say:

The present work uses a population-representative Philadelphia-based sample, the Philadelphia Neurodevelopmental Cohort (PNC), otherwise known as the Trajectories of Complex Phenotypes study (TCP). Due to the location, the results are directly comparable to those of Scarr et al.[52]. Our analysis has numerous advantages compared to earlier admixture studies.

First, participants all came from the same location, so geographic confounding is not an issue.

Second, we assessed measurement invariance (MI) for the cognitive test battery using multi-group confirmatory factor analysis (MGCFA;[64]).

Third, the heritabilities of the g factor and subtest scores have already been estimated for this sample. Specifically, Mollon et al.[65] reported heritabilities for g of 0.61 (standard error (S.E.) = 0.14) and 0.72 (S.E. = 0.07) for the non-Hispanic African and European-Americans in this sample respectively.

Fourth, we included estimates of skin, hair, and eye color to evaluate phenotypic discrimination (i.e., colorism) models of the observed differences.

Fifth, we validated polygenic scores (PGS) associated with cognitive ability for both the African- and European-American samples and we examined to what extent cognitive ability- and education-related PGS (eduPGS), could account for group differences.

Sixth, we tested for Jensen effects in relation to ancestry, heritability, and eduPGS.

Seventh, we examined whether MI was tenable across the full range of European ancestry using local structural equation modeling (LSEM).

Measurement invariance means that the tests are testing the same things in all populations. This is done by carrying out confirmatory factor analyses in both populations. The study already has calculations of the heritability of intelligence in different racial groups. The fourth point is a great addition: they have predictions of what people looked like in racial terms, so one can test if people have been treated differently because of skin-colour and hair-type superficial characteristics. If intelligence is affected by racism, then these superficial appearances will be useful predictors of the size of the deleterious effect on intelligence. Fifth, on the basis of DNA taken from most of the subjects, polygenic risk scores have been calculated, which show the genetic estimates for intelligence for each person. The sixth and seventh points are further tests for whether the genetic explanation is tenable for the test scores in these different racial groups.

There is a great deal in this paper, so I will pick out the main features only, and the technical details are all there in the text, many of them dealing with possible methodological objections.

The total sample includes data from 9421 genotyped participants assessed primarily from 2010 to 2013. Demographically, the sample was 51.7% female, 55.8% European-American, 32.9% African-American, and 11.4% Other, with a mean age of 14.2 (standard deviation (SD) = 3.7) years of age. Participants were recruited from the Philadelphia area. Persons with severe cognitive or medical impairments were excluded from the final sample. The subjects were English-speaking people aged 8–21 years at the time of testing.

Participants were administered the Penn Computerized Neuro-cognitive Battery. This battery was built to be highly-reliable, psychometrically-robust, and to incorporate tasks linked to specific brain systems. The battery consists of 14 tests grouped into five broad behavioral domains: Executive Control, Episodic Memory, Complex Cognition, Social Cognition, and Sensori-motor Speed.

The tests in the battery are as follows: Penn Conditional Exclusion Test (meant to assess Mental Flexibility), Penn Continuous Performance Test (Attention), Letter N-Back Task (Working Memory), Penn Word Memory Task (Verbal Memory), Penn Face Memory Task (Face Memory), Visual Object Learning Test (Spatial Memory), Penn Verbal Reasoning Test (Language Reasoning), Penn Matrix Reasoning Test (Nonverbal Reasoning), Penn Line Orientation Test (Spatial Ability), Penn Emotion Identification Test (Emotion Identification), Penn Emotion Differentiation Test (Emotion Differentiation), Motor Praxis Test (Sensorimotor Speed), Finger Tapping (Sensori-motor Speed), and the Penn Age Differentiation Test (Age Differentiation). The sample also completed the Wide Range Achievement Test, which is a highly-reliable broad ability measure.

Of the included participants, there were 5183 European-Americans, 3155 African-Americans, and 242 biracial African-European-Americans.

• Category: Race/Ethnicity, Science • Tags: Heredity, IQ, Race and Iq 
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Tony Elliott was at Keele University, from which I graduated in 1968, the same year he dropped out and founded Time Out, thus becoming by far the most famous and influential graduate of that radical institution, which pioneered a 4 year degree course (not the usual 3) , the entire first year dedicated to a foundation course in Western civilization and its achievements; the second to studying Minors in both science and art together with two Majors, which carried for another two years.

In my case I had an early taste of Economics, English Literature and Philosopy, then a whole second year of Physics and English Literature, while starting on my Majors of Philosophy and Psychology, which two I continued till graduation.

Tony Elliott must have done the Foundation Year and then one year of French and History, during which he wrote for the university arts magazine, before leaving to make history.

Keele was hard work, with lectures, practical experiments, essays, discussion groups and evening meetings. Too much like school, said the older sophisticates. Great to be educated said the rest of us. The Kremlin on the Hill, said the locals.

Keele had another claim to radical fame: condoms. It was unusual in that half the undergraduates were women, far more than the 15% at other universities. Visiting the other sex was allowed in the afternoons, but not evenings or nights. Without access to the contraceptive pill, students asked that condoms be sold in the Union shop. The Press were outraged, and contributions to the university fell, and we became famous overnight.

Time Out was a radical publication, giving as much space to agitation and propaganda as to cultural affairs. Elliott picked his time with superb precision: 1968 nearly brought down De Gaulle, and it ushered in the swinging 60s, which had previously been mostly pretty staid. We knew what was happening, and found out exactly when and where by reading Time Out, which also taught us how to dress, think and argue.

The magazine was an egalitarian dream, with all workers on the same salary. As the magazine blossomed Elliot wanted to bring in a highly paid designer to lift it out of its listless lists-of-lists format, but the staff rebelled and went on strike. For 3 months the stand-off continued, and Londoners had no guidance on which films it was proper to see. Elliott sat out the strike at the cost of half a million, but then got 17 higher paid journalists to put together an even slicker version of the magazine before the competition could launch their replacement offerings. The magazine prospered, and local variations spread around the world.

The story of a drop out who does well is designed to taunt those who stayed the university course, and went on to less famous pursuits. These entrepreneurs become beacons of daring, showing us the lives we might have led. Timing counts for a lot, but you have to be aware to notice which way the times are pointing. Elliott was a good guy, by all accounts genuinely amiable and kindly, who learned the hard way that running a business requires meeting the need of customers, not producers. He wised up. As you might expect, he was educated at Stowe, a fee-paying school, so you might say it was bound to happen. Single-handedly, he helped define what was cool in Swinging London, and then in other cities of the world, no mean feat in a world not yet globalized. He surfed the wave, and made it roar.

I would love to tell you my very personal stories about him, but I was well into my third year when he arrived, so had no reason to talk to a newcomer and, as far as I know, never met him. A great pity, and too late now.

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No one paper can determine a debate, but each contributes to a pattern, and eventually to a shifting of opinion as to where the probable truth lies. Until 2011 the studies of the genetics of intelligence were based on twin studies, which are fine; and adoption studies, which give some indications if the samples are of reasonable size and followed for long enough; and admixture studies, which give a rough indication of the likely size of the genetic effect.

The hypothesis that there is a genetic component to all human differences does not stand or fall by a single observation, but to a pattern of results.

At a very simple level, it can be observed that parents have children who share their inherent characteristics, most notably that parents transmit their ancestral group characteristics. That transmission includes many aspects which are more than skin deep, which include differences in brain which lead to differences in behaviour.

At a more complicated level, it can be argued that the genetic transmission of characteristics and behaviours is strongly influenced by the environment, and that the effects of genetics will be less powerful if environments are bad. If so, this could complicate the investigation of genetic factors in racial differences in intelligence. Do heritability estimates vary by race?

This was reviewed earlier this year by Pesta and colleagues:

Racial and ethnic group differences in the heritability of intelligence: A systematic review and meta-analysis
Bryan J.Pesta, Emil O.W.Kirkegaard, Jante Nijenhuis, Jordan Lasker, John G.R.Fuerst

They say:

Via meta-analysis, we examined whether the heritability of intelligence varies across racial or ethnic groups. Specifically, we tested a hypothesis predicting an interaction whereby those racial and ethnic groups living in relatively disadvantaged environments display lower heritability and higher environmentality. The reasoning behind this prediction is that people (or groups of people) raised in poor environments may not be able to realize their full genetic potentials. Our sample (k = 16) comprised 84,897 Whites, 37,160 Blacks, and 17,678 Hispanics residing in the United States. We found that White, Black, and Hispanic heritabilities were consistently moderate to high, and that these heritabilities did not differ across groups. At least in the United States, Race/Ethnicity × Heritability interactions likely do not exist.

These are large samples. Studies of this type compare the relative contributions of heritability (a narrow measure of the additive effect of genes) and everything else: “environmentality”, which has two components: the common, shared circumstances of family life which make families alike, and the unique, personal accidents of fate, and the partly self-created experiences which make family members different; plus plain old error of measurement.

A is for additive genetic inheritance, C is for common family factors, and E is for exceptional events and error. This is the ACE model. It is relatively simple, and if there are any interactions between the three components, these can be identified and measured.

Results for the general population show that the proportion of variance in IQ explained by genes increases with age (Plomin et al., 2014). Specifically, in early childhood, genetic effects explain less than 50% of IQ variance, and the effect of the shared environment is relatively strong. As children age, though, genetic effects become increasingly prominent, and the environmental variance due to factors common to siblings decreases. In adults, the heritability of intelligence is 60–80%, while the effect of common environment is small, if not zero (Plomin et al., 2014). The unshared environment explains the rest.

This is the astounding recent finding which would have confused just about all researchers in the 1960s, including myself, who expected that the common effects of family life would be extremely strong, as the sociologists claimed.

Are these findings true for poor people, whose environments are poor at nurturing talent?

One putative moderator is the quality of one’s environment. Poorer (richer) environments supposedly correspond to lower (higher) heritability, to a presumably measurable degree. Said differently, “natural potentials for adaptive functioning are more fully expressed in the context of more nourishing environmental experiences” (Tucker-Drob & Bates, 2016, p. 1). This prediction is known as the Scarr-Rowe hypothesis (Scarr-Salapatek, 1971; Turkheimer, Harden, D’onofrio, & Gottesman, 2011).

How does this apply to race differences in intelligence? Most people who have paid even passing attention to a century of data now accept that there are racial differences in intelligence, but there is less agreement as to how much of that difference can be attributed to genetics. If bad environments reduce the heritability of intelligence for poorer races, this would buttress the hypothesis that their poor performance is largely due to poor circumstances. Improve those circumstances, and performance should improve quickly and substantially.

For example, Lee et al. (2018) found that they could predict intelligence (or about 13% of it) in Europeans just on the basis of genetics. When they used the European prediction on Africans, they predicted 1.6% of it. Not much, you may say, but Lee et al. explain that all European based predictions lose accuracy when used on Africans, because the snips of genetic code may not be at exactly the same position in the sequence, a problem which goes by the daft name of linkage disequilibrium. (The individual variations which make you unique stand out from the usual pattern for your racial group, so your sequences are a little bit out of equilibrium from the rest of your tribe). The right musical notes, but not necessarily in the right order, as an English comedian said when his dreadful piano playing was criticized by conductor Andre Previn.

The Lee et al. explanation makes sense to me, but it could also be argued that it is the lousy environments which account for the lack of relationship between genetic markers and intelligent outcomes.

In a process which took several years, the authors went through all the studies which had investigated racial differences in intelligence, and had sufficient data to make ACE calculations.

What did the authors find?

There are many comparisons and tables of results, but the most contentious are the black-white comparisons, since those are assumed to have the biggest differences due to historical and cultural factors, and those show no differences in heritability. Despite cognitive differences (White-Black mean d = .83 and White-Hispanic mean d = .60) there were no heritability differences in either case. This damages the argument that a substantial cause of low ability is poverty and poor environments. It makes it more likely that the differences are due to inherited genes.

• Category: Science • Tags: Heredity, IQ, Race and Iq 
Every man has a lurking wish to appear considerable in his native place. Samuel Johnson.
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It is a commonplace of school reunions that ex-pupils make a furtive reckoning as to which of them has Done Well. Comparisons are odious, but all too human. How has it gone for you? Naturally, the actuarial odds are against personal success, since success, by definition, must be that which stands out from the crowd, and accrues to only a minority. 1 in 100 may be the first foothills of note, 1 in 1000 a greater peak more worthy of attention, but for eminence only those at the highest peak of 1 in 10,000 qualify for eminence. That was the requirement Galton set, but he no longer exists, so my reference to him is void for lack of meaning.

Looking at your peer group gives you a cross-sectional comparison, but for a longitudinal one a natural first step is to compare your personal achievements with those of your parents. A one generational change is within the span of apprehension, and has some emotional bite to it. It is probably best to set age 40 or thereabouts as the career midpoint for inter-generational comparisons. Have you risen or fallen? Some intrepid researchers have dared to find out what causes these differences.

The Contribution of Cognitive and Noncognitive Skills to Intergenerational Social Mobility.
Matt McGue, Emily A. Willoughby, Aldo Rustichini, Wendy Johnson, William G. Iacono, and James J. Lee
First Published June 30, 2020 Research Article

They say:

We investigated intergenerational educational and occupational mobility in a sample of 2,594 adult offspring and 2,530 of their parents. Participants completed assessments of general cognitive ability and five noncognitive factors related to social achievement; 88% were also genotyped, allowing computation of educational-attainment polygenic scores. Most offspring were socially mobile. Offspring who scored at least 1 standard deviation higher than their parents on both cognitive and noncognitive measures rarely moved down and frequently moved up. Polygenic scores were also associated with social mobility. Inheritance of a favorable subset of parent alleles was associated with moving up, and inheritance of an unfavorable subset was associated with moving down. Parents’ education did not moderate the association of offspring’s skill with mobility, suggesting that low-skilled offspring from advantaged homes were not protected from downward mobility. These data suggest that cognitive and noncognitive skills as well as genetic factors contribute to the reordering of social standing that takes place across generations.

The authors adroitly encapsulate the dilemma of social mobility studies:

A major challenge to a belief in meritocratic processes is that advantaged parents are much more likely to have advantaged children than are less advantaged parents (Cullen, 2003). Wealth, social capital, and involvement are all ways in which parents can create opportunities for their children that are not widely available to others (Breen & Goldthorpe, 2001). Yet unequal opportunity is not the only factor contributing to the intergenerational transmission of inequality. High-achieving parents also transmit to their children, genetically and environmentally, the skills that contributed to their own success (Swift, 2004).

Cognitive ability was assessed at 17 years of age and on the Wechsler which is excellent; occupational status in late 20s, which the authors admit is too soon (yet it favours the environmental rather than the genetic hypothesis, since parental contributions of money and contacts will be immediate, whereas any genetic contribution will take time to accumulate).

Incidentally, there is a slight problem with studying intergenerational status, which is that some of the measures change (they are not invariant). Formerly, few students went to college, and now a majority do. This alters the meaning of higher education measures, as the authors explain. I have concentrated on occupational level, which is less subject to those problems.

However, the main point of this paper is to study families, and to compare siblings within families. If wealth is the engine which provides children with good jobs, then all wealthy progeny will rise, and children of poor families will languish. This study uses families as their own controls, and looks at what sibling heterogeneity may contribute to life outcomes.

Gloriously, the authors cite Nettle (2003) and use his method of regressing each predictor variable on offspring–parent difference in attainment, parent level of attainment, and their interaction, separately for education and occupation. He made a good contribution to the debate and his paper should be known more widely.

Polygenic scores for intelligence are not yet good enough to explain a major part of intelligence, but one can at least check whether the equations point in the right direction. The authors say:

As expected, the polygenic score based on weights from an independent GWAS of educational attainment was associated with both educational and occupational achievement in both the parent and offspring samples (Fig. 1). Correlations (rs) ranged from .26 to .32 for educational attainment and from .19 to .24 for occupational attainment (Table S3).

Using these scores (not previously available to researchers of social mobility) they find:

Specifically, offspring who achieved a higher educational or occupational level than their parents tended to have higher polygenic scores than their parents. Conversely, children who fell short of their parents’ social achievements tended to have polygenic scores that were lower than their parents.

In the past it was not possible to buttress a genetic hypothesis with genomic analysis, but now polygenic risk scores afford that possibility. The authors are cautious in their interpretation, but it is pretty clear that we are moving towards (partial) causal explanations. This will change the social sciences in a profound way.

Some key points from their discussion section:

We found that a majority of individuals from the least advantaged homes achieved more educationally and occupationally than their parents, and conversely, a majority of individuals from the most advantaged homes achieved less. Our study implicated offspring–parent skill differentials as contributing to the considerable reordering of social standing that we observed across generations. Individuals rarely moved down and frequently moved up when they were more skilled than their parents.
We believe that a reasonable explanation of our findings is that the degree to which individuals are more or less skilled than their parents contributes to their upward or downward mobility.

Although offspring inherit all of their genes from their parents, they inherit a random subset of parental alleles because of meiotic segregation. Consequently, some offspring inherit a favorable subset of their parents’ alleles, whereas others inherit a less favorable subset. We found, as did previous researchers (Belsky et al., 2018), that the inheritance of a favorable subset of alleles was associated with an increased likelihood of upward mobility, whereas inheriting a less favorable subset was associated with an increased likelihood of moving down.

• Category: Science • Tags: Heredity, IQ 
Sense and sensitivity
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If someone tells me I must not read something, I am tempted to give it a look. If you are reading this, you probably have the same curiosity, and the same wish to rebel against other people telling you what you may not read, and what you must not think.

In that light, here is an interesting story. Some authors who had published an academic paper on 26 June asked for it to be withdrawn. Very odd: getting papers published is difficult and very time-consuming. Most authors want them to be read as widely as possible. If other researchers have objections, they submit papers criticising the original paper. Sometimes an individual error is found and corrected in an Erratum statement. To withdraw a whole paper in this way is unusual.

Psychological Science 26 June 2020 “Declines in Religiosity Predict Increases in Violent Crime—but Not Among Countries With Relatively High Average IQ”

What mistake did the authors find which made them take down a paper which had been peer reviewed (by four reviewers, including a statistician, plus two members of the editorial team) and accepted into the public domain as a scholarly publication?

The journal, Psychological Science, says that the authors:

requested that this article be retracted out of concern that some of the measures used in the research were invalid. Specifically, they note that the National IQ data used in their analyses, largely based on Lynn and Vanhanen’s (2012) compilation, are plagued by lack of representativeness of the samples, questionable support for some of the measures, an excess of researcher degrees of freedom, and concern about the vulnerability of the data to bias. They also noted that the cross-national homicide data used in the research are unreliable, given that many countries included in the data set provided no actual data on homicides that had occurred. Instead, in these countries, homicide rates were estimated on the basis of other variables that may or may not be closely related to homicide rates. Importantly, some of the variables used to create the estimates were confounded with variables of interest in the research. When the authors re-analyzed the data without the imputed values, the reported effects were no longer apparent.

In the conclusion of their request for retraction, the authors reflected that although articles with certain types of errors may still be helpful to have in the literature, they do not believe theirs falls into that category. They explicitly expressed concern that leaving the article in the literature could “prolong the use of Lynn & Vanhanen’s cross-national IQ measures.”

So, the authors withdrew mainly because of criticisms of Lynn’s work on country IQs. Usually, once a paper has been accepted, other people read it and then write papers in reply. Those papers, like the one they are criticising, go through their own review process, and eventually get published. In that way we, the readers, see what the original authors have said, and what critics have replied. We can judge argument and counter-argument. This is usual academic practice. Debate takes time, but is done in the open.

This case is unusual. The paper was accepted on 26 June, and withdrawn 3 days later, on the basis of arguments we haven’t seen published. We haven’t even seen the re-analysis done by the authors. In fact, because of the inordinate delays imposed by academic journals, (in which authors write for free, referees referee for free, and then every student and member of the public has to pay to read) the paper was accepted “In Press” in January 2020, and caused no particular critical reaction, but as the actual publication date approached they received more criticisms in the final weeks, resulting in this withdrawal.

The Editor, Patricia Bauer, adds:

Critiques of Lynn and Vanhanen’s (2012) National IQ data were available in the literature prior to the publication of Clark et al. (2020). It is unfortunate that these critiques were not consulted, thereby potentially avoiding publication and the necessity for retraction.

Of course, this assumes that the critiques were right. Almost every paper of note generates critiques, and at best these criticisms can improve later work. At worst they throw up a lot of dust. Sometimes criticisms can be shown to be wrong, or that they selectively require standards no other research has achieved. In fact, the authors did consult David Becker, who is in charge of editing the Lynn database, which is now in a public form that allows any critic to make their own evaluations of the quality of individual papers.

We would like to thank David Becker for his helpful correspondence regarding the NIQ dataset and the relative merits of different country-level IQ measures.

You can get the database here, and download it.

Why has usual debate been circumvented? Perhaps, very late in the day, the authors have accepted criticisms which they did not accept or know about when the paper was accepted last year. That seems unlikely. Lynn’s work has been very widely criticized, often by concentrating on a few of the least representative studies. Nonetheless, the general findings been replicated by others, often in the economics literature, coming to the same conclusions without mentioning Lynn, and using different terms like “human capital” which do not arouse so many emotions as IQ. The same general pattern is observable in PISA and other international scholastic studies. Not all countries participate in those studies, but those countries sometime use PISA items in their national tests, so one can deduce what the general levels would be if they did participate.

Becker has ensured that you can compare the Lynn estimates with the scholastic estimates, and anyone can see how the different variations correlate. You can compare Lynn’s list with the shorter reference list that Becker has been able to use, and compare results.

I have read the paper, and in my view the authors are correct in their assessment of the Lynn database, that it is the best source of country intelligence results, and that in the Becker editions there are different variants (some with, and others without, scholastic data, and some with and without estimates for missing countries based on geographic neighbours). That is, they do not go overboard with it, and are aware of restrictions and short comings. On those they note:

Note also that noise in the data, if anything, should obscure our hypothesized pattern of results.

They are cautious about their measures.

Study 2 examined the interaction between country-level IQ and religiosity on homicide rates. All countries for which the relevant data could be obtained were included. Given that there are no objective best measures of religiosity and IQ nor an objective best list of relevant control variables, we conducted a multiverse analysis using three operationalizations of religiosity, three operationalizations of IQ, all possible combinations of four control variables, and additional interactions between those control variables and each operationalization of religiosity.

The author’s conclusion is very modest, and in some ways in favour of religious belief.

• Category: Science • Tags: Censorship, IQ, Political Correctness, Richard Lynn 
Ancestral pathways in the brain
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The great topmost sheet of the mass, that where hardly a light had twinkled or moved, becomes now a sparkling field of rhythmic flashing points with trains of traveling sparks hurrying hither and thither. The brain is waking and with it the mind is returning. It is as if the Milky Way entered upon some cosmic dance. Swiftly the head mass becomes an enchanted loom where millions of flashing shuttles weave a dissolving pattern, always a meaningful pattern though never an abiding one; a shifting harmony of subpatterns.

Few scientists write like that anymore. Science is the poorer for it. Sherrington was able to dash that off when the most complicated device to provide an analogy was a 1801 Jacquard loom capable of weaving complicated patterns on the basis of punched cards. So, Sherrington thought of a loom, Freud of a hydraulic system of pipes, Pavlov of a telephone exchange, and more recently everyone and their uncle think of the brain as a computer.

As we progress, the capacity to image the brain, and image it in motion, improves rapidly. Now we can look at fMRI outputs, and deduce the fine detail of connectivity in the brain. A problem arises which the authors of a recent paper identify as a source of bias: even at rest, these outputs differ according to race.

Here is an interesting study which looks at the patterns detectable in brain activity, and which identifies significant racial differences.

Evidence For Bias Of Genetic Ancestry In Resting State Functional MRI. April 2019
DOI: 10.1109/ISBI.2019.8759284
Conference: IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), 8-11 April 2019, Venice, Italy Volume: 16. Andre Altmann and Janaina Mourão-Miranda

Their abstract:

Resting state functional magnetic resonance imaging (rs-fMRI) is a popular imaging modality for mapping the functional connectivity of the brain. Rs-fMRI is, just like other neuro-imaging modalities, subject to a series of technical and subject level biases that change the inferred connectivity pat-tern. In this work we predicted genetic ancestry from rs-fMRI connectivity data at very high performance (area under the ROC curve of 0.93). Thereby, we demonstrated that genetic ancestry is encoded in the functional connectivity pattern of the brain at rest. Consequently, genetic ancestry constitutes a bias that should be accounted for in the analysis of rs-fMRI data.

Resting state is what the subject does when lying in a scanner without any task to attend to. Of course, resting state can be very busy: thinking of nothing is impossible, so subjects may be worrying about claustrophobia, enumerating their daily tasks and duties, mulling over a recent problem, or idly considering the sensual advantages of polymorphous perversity. I digress, and no digression is ever fully restful.

Although age and sex and health status can affect functional MRI readings “there is one additional subject level characteristic that is known to affect head and brain morphology but is rarely considered as a confound in rs-fMRI studies or brain imaging studies in general: genetic ancestry.”

They took 1003 subjects from the Human Connectome Project with the relevant fMRI data, and for 950 of those for they also had genomic data. They ended up with 764 European, 138 African, and 39 Asian subjects. To increase discriminative power they compared the Europeans against the rest (using various cut-off assumptions).

They use signal detection theory, which entered psychology in the 1960s, and made “Receiver Operating Characteristics” and “Areas Under the ROC curve” familiar to researchers.

It is a tiny matter, but the same analysis of functional MRI which classifies race at 93% accuracy classifies sex at 98% accuracy. Both these categories can be detected on brain waves in the form of minute blood flows.

So, the functional connectivity of the brain differs among racial groups defined by their genomes, and this difference can be picked up with a high level of accuracy (93%).

They caution:

The exact origin of these apparent connectivity differences between continental ancestries remains elusive at the moment. However, we hypothesize that the observed differences are not based on true neuronal differences but that they originate from differences in head and brain morphology as reported in [8, 9]. These morphological differences may be carried forward through the standard rs-fMRI processing pipeline and affect the inferred functional connectivity. In addition, rs-fMRI connectivity is based on correlations between blood-oxygen-level dependent (BOLD) signal time series at rest. Thus, it is conceivable that genetic differences contributing to blood circulation, perfusion and elasticity of the vascular system may modify BOLD dynamics. This is exemplified by reports identifying ethnicity as independent risk factors for cardio blood oxygenation level dependent vascular disease[14] and intracranial artery tortuosity[15]. In addition, brain hemodynamic responses are known to be heritable traits[16].

So, the authors think that it is racial difference in skull and brain shape which may account for these differences, which make it easy to detect the subject’s race from the connectivity of the brain, rather than any neuronal differences.

Perhaps they are keeping this for later work, but subjects in the Human Connectome Project have completed intelligence tests, and will also have a measure of MRI derived brain size.

Previous 2015 work on the Human Connectome Project shows that brain networks are associated with intelligence.

Previous 2017 work on the Human Connectome Project shows that brain networks are associated with intelligence.

Previous 2018 work on Human Connectome Project likewise.

So, it would be possible to see if the differences in connectivity related in any way to intelligence in the three groups studied: Europeans, Africans and Asians. If there were no differences this would tend to disprove assumptions about brain size and brain organization as a source of racial difference in intelligence.

This paper has a very large sample, employs standard measures and has appropriate statistics, cautiously interpreted. All these aspects are reassuring. It is a niggle, but the authors use the notion of “bias” in a particular way, because they have identified human differences which are nothing to do with bias. These differences were detected by very precise measures of brain activity, thus revealing something, not obscuring it. By analogy, their mapping of the sea floor has shown previously unrecognized under-water contours and ships can now navigate more safely.

Like any other study, this needs to be replicated, but this is a significant finding which stands until refuted by a study of similar sample size and uniformly applied measures.

• Category: Science • Tags: General Intelligence, Racial Intelligence 
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If you are a racist, then you are asking for a fight. But science is my ally, not yours, and your fight is not just with me, but with reality.

This book, shortly to be published in the US, is written by a geneticist. Racism is a topic of contemporary interest, and there are certainly different conceptions of reality. The book is diminished by its title, which proclaims it an aggressive polemic, looking for a fight. “How to argue about race” would advertise a better book, on which new readers might choose to rely, finding in it an evaluation of opposing arguments. On the contrary, this author says his book is a weapon. Not a sextant, microscope, thermometer, weighing machine, assay kit or surveyor’s theodolite. He wants arguments to be weaponized. His aim is combat, not an even-handed evaluation of a fascinating science.

If you jump to the References then the one-sided nature of the material is clear to see. Papers critical of race differences in intelligence are presented without the rejoinders.

Despite a publication date of December 2019 much recent work on the genetics of intelligence, including a major study in July 2018 which in passing looks at race differences is simply omitted.

Not only that, but the references are very sparse. Some 40 references cannot do justice to the scope of the argument, and the engaging style cannot compensate for sweeping generalizations and omissions. Potential readers might wish to proceed no further.

However, I believe that there is reason to read on, if only because the title will attract readers and get supportive reviews, but also because the book admits as much as it denies, conceding that many apparent disputes are about nomenclature (“population” “ancestry” “lineage” are described as “more technical”, but although said to be incoherent in scientific taxonomy, the author admits “race” will do). It admits that “racism” will be applied only to Western and European cultures, because they “started it” in the Enlightenment; and also concedes that racial differences are rooted in biology.

Our quintessential nature as wanderers, hunters, farmers, and social creatures meant that, over the last few thousand years, Earth has become smaller, and peoples from around the world have met, traded, mated, fought, conquered and a whole lot more. In these interactions, we engage with people who are different from each other. These differences are rooted in biology, in DNA, and also in our behaviour as social animals – in our dress, our speech, our religions and our interests. In the pursuit of power and wealth, the fetishisation of these differences has been the source of the cruellest acts in our short history.

So, racial differences are rooted in biology, in DNA. The problem does not lie in these differences, but in the fetishization of these differences. It is a matter of degree. All this by page 4. Readers inclined to genetic determinism may be tempted to stop reading: Rutherford has given them enough to feel that they are in agreement with him, and the “fetishisms” are details of minor significance.

Contrary to his claim, cruel acts in our short history have arisen for many reasons, not only race. Contrary ideas have often split families and races sufficiently to make them fight each other in civil wars, despite genetic similarities. Germany and Russia jointly did cruel things to Poland in 1939 because they shared a common political purpose. A detail perhaps. Russia did cruel things to its own citizens, China likewise, and Cambodia as well, because of ideas about social class. All sorts of ideas can lead to unfairness and cruelty.

Rutherford says he will provide:

a scientific description of real human similarities and differences that will provide a foundation to contest racism that appears to be grounded in science. Here, I am focusing on four key areas where we often slip up by adhering to stereotypes and assumptions; I am outlining what we can and cannot know according to contemporary science on the subjects of skin colour, ancestral purity, sports, and intelligence.

I agree with Rutherford that skin colour is part of racial differences, but hardly all or even the most important part of it. It is simply one facet of differences which together make up evident racial groupings: skull shape; body shape and size; muscle and fat distribution; bone density; early motor development; vulnerability to illnesses and others.

Equally, ancestral purity is hardly much of an issue. Some groups have lived together for sufficient generations to have developed characteristics in common. The fact that they are purely that group does not mean that they are better. People who have always lived for generations in Norfolk are purely Norfolk. Whether that is a good or bad thing can be determined by other means.

Rutherford mounts an argument about the genetic isopoint (pg 76):

Everyone alive today is descended from all of the global population in the fourteenth century bce. Irrespective of how plausible that sounds, or how contrary it seems to our own experiences of family and family trees, it is true – the isopoint is a mathematical and genetic certainty. It is likely that the proportion of a person’s ancestors at the isopoint are not equally distributed around the world: a Chinese woman or man will have far fewer southern African ancestors than East Asian, and vice versa. But they will have some, and each of those ancestors has an equal relationship with their living descendants regardless of where on Earth they lived and died.

At times this seems to be intended to lead to the conclusion that we are all one “race” but the explanation concedes that the proportion will vary. However, the conclusion he comes to is:

No nation is static, no people are pure.
Racial purity is a pure fantasy. For humans, there are no purebloods, only mongrels enriched by the blood of multitudes.

However, he accepts there will be “proportions”, and those different proportions develop characteristics which are rooted in biology.

How does the author define racism?

Racism has many definitions; a simple version is that racism is a prejudice concerning ancestral descent that can result in discriminatory action. It is the coupling of a prejudice against biological traits that are inalterable with unfair behaviour predicated on those judgements, and can operate at a personal, institutional or structural level. Pg 20.

I prefer Hazlitt (1830) because it applies to everything and everyone:

Prejudice is prejudging any question without having sufficiently examined it, and adhering to our opinion upon it through ignorance, malice or perversity, in spite of every evidence to the contrary.

Although Rutherford does not spell it out, he implies he would accept valid judgments about ancestral descent, and actions based on good evidence. In the text the accusation of racism is frequent and broadly applied. Rutherford agrees that race exists, but goes on to ask:

Are there essential biological (that is, genetic) differences between populations that account for socially important similarities or divisions within or between those populations? Pg 21

Certainly, to deny the importance of genetics in influencing our behaviours is folly. Pg 23.

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America is in turmoil because of a video in which a Policeman seems very highly likely to have caused the death of an arrested man. He must face trial. Also, the techniques used in making arrests must be put on trial. Kneeling down on the back of the neck of a hand-cuffed man is not remotely a safe procedure.

A few years ago, Europe was in shock at the picture of a refugee child lying dead on a Greek beach, leading to a chain of events which culminated in the German Chancellor, Angela Merkel, inviting into Germany one million refugees. The picture was more powerful than a thousand words. A thousand times more powerful.

A dreadful image, a horrifying video, can have enormous impact. It brings us face to face with death, from which we are now spared in everyday life, since death has been outsourced to professionals, whereas before it was part of family experience to attend to the dying, and to sit by a visible body in a protracted wake. Equally, the videos of riots, beatings, and shootings cannot help but arouse emotions, of fear, pity, anger and hatred. It is easy to be horrified, repelled by human behaviour, outraged at violence on the part of others, and to wish for prompt and savage retaliation.

Bertrand Russell observed that individual cases had an enormous impact in popular argument. When an individual case is made flesh in the virtual reality of a video, it takes on an incontrovertible status: we saw it happen, as if we were there, and no one can contradict us, other than a liar. We regard ourselves as a witness to a broader reality, and are reluctant to accept that we have witnessed a rare and unrepresentative event. Traumatised victims of crime are apt to over-generalise, both about the perpetrators, the circumstances and place of the event, and about the prevalence of crime. And why not? Their lives were mostly good until that point, and then one or two miscreants put them in fear of their lives, on a street somewhere, in a way they will forever remember. Avoiding those types of people (including their race) and those types of circumstances (talking on a phone in a street) and that particular location seems prudent. The victim has learned from experience, and much therapeutic time may be needed to help them out into public again.

In the face of these emotional realities, from which few are exempt, the search for context may seem a betrayal: the cop-out of the feeble, the excuse of the bystander. Quoting the available statistics may seem perverse, as if it were an attempt to deny that a citizen was killed, as depicted.

Would it be better to show videos of other citizens being killed, in the same or similar manner, to reveal that it happens to men of all races? Bizarrely, this might be a good corrective to over-generalization. Say, the last 20 to 30 cases of death of arrested men, each shown in painful personal detail, might show in virtual reality what comes out of the dry government statistics, that in recent years 3 black men per 10,000 arrests have ended up dead, as compared with 4 white men per 10,000 arrests. @LeonydusJohnson

Will these figures have any impact? I doubt it. We have not seen their faces, heard their pleas, witnessed their agony. It is the difference between a great tragedy onstage and the dry recitation of a telephone directory in a side alley. Statistics are of interest to 0.1% of the population.

Of course, the context should be even broader, which is to look at all racial aspects of crime. These data are not available on an annual basis, and tend to be given as bald numbers, requiring readers to do extra work in order to interpret them. A good starting point is to go through the logic before looking at any numbers.

For each group in society, in this case racial groups, we need to know the crime rate per head of population for all arrestable crimes. This gives us a first approximation, subject to reporting errors, which of course could include differential arrest rates because of racial bias. Where possible, we could compare those arrest rates with victim and witness descriptions of perpetrators. Victims very often see their assailants very close up, and can give racial characterisations, if not descriptions which are detailed enough to secure convictions. Witnesses likewise can generally give racial groupings of perpetrators. Interestingly, self-reports are also available from crime surveys, and these serve as another comparison against which to evaluate arrest rates.

To evaluate the argument that all these figures are shot through with specific racial biases, it would be good to look at speed camera infractions by race.

Crime surveys in which citizens recall crimes (which they may not have taken to the Police) and also give racial descriptions of the perpetrators would be another test case. Interestingly, the argument that the Police and justice systems are biased would have to be extended to all victims, arguing that out of personal racial prejudice the victims mis-identify the actual perpetrator so that the police search for the wrong racial group. This seems unlikely.

Government statistics on race and crime have been published, debated and publicised countless times, yet seem to have no effect at all on the nature of the national discussion. They seem to exist only as a footnote, which should not disturb the main narrative. To mention them is to interrupt an action movie with obscure comments on the possibly misleading effects of selective camera angles.

One reason for confusion is that mainstream media (the BBC is a prime example) give a selective presentation of the findings. This week they were showing graphs (as part of “reality-checking”) of fatal police shootings by ethnicity. What could be wrong with that? What could be wrong with prison population by ethnicity?

The error lies in assuming that racial groups are equally law-abiding. That possibility is not included in the BBC reality checking.

What is to be done?

The statistics don’t matter, and statistics are the distillation of innumerable biographies.

• Category: Science • Tags: Floyd Riots 2020, Race Riots 
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Uruguay is a small country on the eastern coast of South America between Argentina and Brazil. Mostly European in demographics, it was long considered the Switzerland of South America because, fearful of the usual local tendency towards dictatorship, it shared power in a plural executive, was early in separating Church and State, in giving votes to women, allowing divorce, and generally being sensible. It has low corruption, high press freedom, a democratic tradition which survived a 70s lapse into military dictatorship, and no terrorism, a good standard of living, and an excellent standard of beaches. In fact, think of a 400-mile beach with an excellent farm attached. In truth, it also has a fine capital city of Montevideo where half the population lives, which gives it a high population density; and Punta del Este, the continent’s premier beach resort, which helps draw in 4 million tourists a year. Agriculture and tourism are major sources of income.

The interest lies in how this country, with only 3.45 million citizens in an area larger than England, has coped with coronavirus, given that it knows with reasonable certainty that the entry point was Montevideo airport on or about 6 March, and is a society in which most people know each other, or at least can trace connections pretty easily. Three arrivals at the airport spread the disease. Two took a 6-hour bus ride north on 8 March, and one already infected lady on 7 March attended a society wedding with 500 guests, and kissed, conversed and danced with enough of them to infect a reported 44 people.

Half of Uruguay’s cases can be traced to that party. One of those infected, a young woman, went to work and infected a male colleague in her office, and that young man passed it on to his mother, a friend of mine, who later recounted her illness in detail. It was over 3 weeks before she felt fully recovered.

The socialite who flew in denied having any knowledge of her infected status, though she had been in Milan in January and fallen ill afterwards, but she was not screened at the airport. She was later reported for having received family visitors while in quarantine. Folklore songs have been composed about her, none of them flattering. Contact tracing has been done on the wedding event but detailed reports are not yet available.

What has happened since?

Coincidentally, on first of March the ruling Left-wing coalition gave way after 15 years to a Centre Right coalition of traditional parties, the more rurally-inclined one celebrating by getting many of its farmers to attend the inauguration on horseback in full gaucho regalia, a spontaneous innovation which was a joy to behold. With only a week’s notice, the newly installed government took advice, and soon went into lockdown. (This had been started progressively the moment cases were announced, with universities, schools, public theatres and cinemas introducing various distancing measures immediately, though the airport was not finally closed till 20 March). Kids at public schools already had a personal computer, so distant learning was already established. Health officials traced contacts, and used widespread testing. Uruguay had had the wit to ensure that the Pasteur Institute, looking for a South American location for a new centre, chose Uruguay (because an ex-president remembered that Uruguay had excused France a post-war bill for meat, and deserved something in return), so test systems were on hand.

The government designed an app so that information could be disseminated by WhatsApp and a system for border control, so that if any flights came in they had advance notice of names and health status.

Currently, Uruguay has had 737 cases and 20 deaths. Here are some comparative rates (rates per million, not percentages).

Brazil death rate 79
Argentina death rate of 8.5
Uruguay death rate of 5.8

Uruguay has been 13 times safer than Brazil, where the President is against lockdowns though many state leaders are for it; and a bit safer than Argentina, which also went into lockdown. Brazilian contacts tell me that compliance has been variable, and much lower among the hard-pressed poor, despite welfare payments. Argentine contacts say that compliance was mostly good, and it remains to be seen if it holds up.

By the way, Uruguay is not a culture in which deaths could be covered up. At most, there seem to be 3 degrees of separation. News travels fast, and family connections are strong, so a body on the street would soon have a crowd at a distance sending social media announcements.

How come Uruguay has few cases and very few deaths? As discussed, Uruguay does not have many airline connections with the countries of origin of the infection, and by March the big holiday season influx of tourists was over. The health service is good, and there are strong professional medical links with the US and also with Europe. The new government maintained progress on transition tasks but concentrated heavily on the threat. Social distancing was observed, and the minority of infractions related to walks on the beach or in parks, which is less dangerous. Given that the transfer of power between sharply contrasting political coalitions (ex-terrorist Tupamaros leaving power, landed gentry and business owners taking power) had been peaceful and even convivial, there was a sense of national unity.

Uruguay even took time out to help some cruise ships with Covid patients on board, who had been refused docking in other countries, treating them and then letting the whole lot get into buses to take flights out. To the great surprise of the cruise passengers, who had been refused a berth at other countries, Uruguayans came out at night to clap and cheer them on their way home.

In the last few weeks, before agreeing to lift lockdown, it started up the construction business under strict distancing protocols, and monitored the workers in a large sample of workplaces. Not a single one tested positive. Equally, they let rural primary schools open, finding that they could do so without further outbreaks. They have worked carefully, testing each step of the way.

They have also been conducting research, some of which is already published. A local research group has done some backward tracking on the first cases encountered world-wide, showing it was active earlier than publicly stated.

It is too early to make a final judgment about which countries have done best. The debate will be about which of them got the biggest dose to begin with: airport connectivity and entrepot status. Then some debate about population density, and the age structure. Is Africa doing well because of previous experience with Aids and Ebola, or is it just that it is a very young continent? Did Uruguay benefit from being far away in airline terms from China, and having completed most of its summer tourism by mid-February?

• Category: Science • Tags: Coronavirus, Disease, Uruguay 
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Last night the UK Prime Minister said that those who could not work from home, like those in construction and manufacturing should go to work today, maintaining social distancing, and avoiding public transport if possible. Primary schools may begin reopening in June, as may some shops, and some of the hospitality industry may reopen in July. The advice was conditional: if the reproductive rate goes above 1 (it is estimated to be between 0.5 and 0.9) then these relaxations may have to be reversed.

Bizarrely, in my view, he added: “it will soon be the time… to impose quarantine on people coming into this country by air”. If that had been implemented in January the UK would not have had an epidemic. For some reason the argument he gave was that, because good progress had been made in reducing R by shutting down society, it was now appropriate to deal with the supply of the virus and in due course, without any particular urgency, turn off the tap that set the whole country afire.

So, it is not an end to lockdown, nor the beginning of the end, but possibly the end of the beginning.

Lots of ideas are rattling around the country, and it is salutary to note some of them, since we are getting so much history now. Decades when nothing happens, and then days when decades happen.

There is considerable scepticism about the Imperial College model, which is seen as poorly documented, poorly configured in computing terms (bad architecture). There is plain scepticism about the accuracy of any of Prof Ferguson’s predictions, because he has a history of wildly exaggerated death rates. Or that is the claim against him. More likely, each of his simulations involved several predictions: best case, most likely case, worst case and both he and his critics can pick those which best suit their story. What is Prof Ferguson’s Brier score (mean squared difference between predictions and actual outcomes)? How many predictions does he make per simulation? Would he get to super-forecaster levels? At the moment it does not seem likely. Interesting, however, that his predictions are mutative: even if wrong, they have had a big influence on policy, and so alter the outcomes which serve as the test of predictive accuracy.

He did not do well with the foot and mouth outbreak. Long before I took up blogging I wrote to the relevant Ministry to ask for their justification for their slaughter of cow herds, and was fobbed off for months until on the third attempt they sent me what they claimed was their justification: not the work of Ferguson but a calculation by another professor. I contacted him and he replied that his note to the ministry was a back of an envelope calculation, and no basis for any policy at all. Foot and mouth disease does not lead to appreciable drops in animal fitness, and the meat is still fit to eat, so the whole episode remains something of a mystery. I digress.

What should one require of all model simulations on which public policy may be based? At a minimum, it seems essential to have an introductory page giving all the assumptions in plain language, and in a standard agreed format. Then, a second page explaining the basic structure of the computer program. Then, publication of the actual code for inspection and expert testing.

It is extraordinary that one of the most important events in current economic and social history was based on the unexamined workings of a computer model. It appears that politicians believed the numbers because they were printed out by a computer. An accountant friend was once asked to audit a very smart perfume shop in Mayfair, London. It was a palace of marble and chrome, every saleswoman a beauty, and the accounts beautifully printed out by computer, which was novel at that time. He asked himself: If I owned this shop and was trying to steal money, how would I do it? Suspicious, but at a loss where to begin, he spent some days adding up all the entries with his own calculator. The computer totals had been falsified, but very neatly, and they were skimming money out of the business.

Was lockdown a waste of time, because even if it prevented prompt deaths, herd immunity is lowered, leaving us open to a much more dangerous second wave this winter? This is an unpleasant Is it 66% or a far lower figure? If most super-spreaders are already immune, very likely because they were most likely to catch the virus in the first place, then the herd could be safe at a lower threshold. In the UK at least, the picture is still unclear.

On a far brighter note, there is now more clarity about how the infection spreads. As a result of a series of tweets (a chorus of tweets?) Dr Muge Cevik of St Andrews University deserves two medals: one for not having a computer model; the other for looking in detail at 14 studies of close contacts of Covid cases, showing how many infected people go on to infect how many others, and how those rates differ between sustained indoor settings and more casual outdoor ones. Apart from confirming the age gradient in vulnerability, she shows very clearly that sustained exposure in an enclosed space is the greatest vector of infection (houses, offices, public transport). Casual interactions outdoors are far less risky. Looks like droplets, not aerosols, are the main vector. The advice would be: stand apart, wear masks, wash hands, and reconfigure public indoor settings to reduce all respiratory disorders in future.

While the infectious inoculum required for infection is unknown, these studies indicate that close & prolonged contact is required for #COVID19 transmission. The risk is highest in enclosed environments; household, long-term care facilities and public transport.

High infection rates seen in household, friend & family gatherings, transport suggest that closed contacts in congregation is likely the key driver of productive transmission. Casual, short interactions are not the main driver of the epidemic though keep social distancing!

Increased rates of infection seen in enclosed & connected environments is in keeping with high infection rates seen in megacities, deprived areas, shelters. A recent preprint demonstrates that #COVID19 epidemic intensity is strongly shaped by crowding

Although limited, these studies so far indicate that susceptibility to infection increases with age (highest >60y) and growing evidence suggests children are less susceptible, are infrequently responsible for household transmission, are not the main drivers of this epidemic.

Finally, these studies indicate that most transmission is caused by close contact with a symptomatic case, highest risk within first 5d of symptoms. To note: this preprint suggests that most infections are not asymptomatic during infection

In conclusion, contact tracing data is crucial to understand real transmission dynamics. Cautionary note: This data & interpretation is based on the available evidence as of May 4th. Our understanding might change based on community testing/lifting lockdown measures.

Addendum: While we have limited data, similar high risk transmission pattern could be seen in other crowded & connected indoor environments such as crowded office spaces, other workplace environment, packed restaurants/cafes, cramped apartment buildings etc.

Conclusion 2: (a) we need to redesign our living/working spaces & rethink how to provide better, ventilated living/working environment for those who live in deprived & cramped areas; (b) avoid close, sustained contact indoors & in public transport, & maintain personal hygiene.

• Category: Science • Tags: Britain, Coronavirus, Disease 
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.