Genetics / behavioral genetics intelligence / IQ / cognitive ability Science

Sesardić’s conjecture: preliminary evidence in favor

In Making sense of Heritability, Sesardić wrote:

On the less obvious side, a nasty campaign against H could have the unintended effect of strengthening H [hereditarianism] epistemically, and making the criticism of H look less convincing. Simply, if you happen to believe that H is true and if you also know that opponents of H will be strongly tempted to “play dirty,” that they will be eager to seize upon your smallest mistake, blow it out of all proportion, and label you with Dennett’s “good epithets,” with a number of personal attacks thrown in for good measure, then if you still want to advocate H, you will surely take extreme care to present your argument in the strongest possible form. In the inhospitable environment for your views, you will be aware that any major error is a liability that you can hardly afford, because it will more likely be regarded as a reflection of your sinister political intentions than as a sign of your fallibility. The last thing one wants in this situation is the disastrous combination of being politically denounced (say, as a “racist”) and being proved to be seriously wrong about science. Therefore, in the attempt to make themselves as little vulnerable as possible to attacks they can expect from their uncharitable and strident critics, those who defend H will tread very cautiously and try to build a very solid case before committing themselves publicly. As a result, the quality of their argument will tend to rise, if the subject matter allows it.22

It is different with those who attack H. They are regarded as being on the “right” side (in the moral sense), and the arguments they offer will typically get a fair hearing, sometimes probably even a hearing that is “too fair.” Many a potential critic will feel that, despite seeing some weaknesses in their arguments, he doesn’t really want to point them out publicly or make much of them because this way, he might reason, he would just play into the hands of “racists” and “right-wing ideologues” that he and most of his colleagues abhor. 23 Consequently, someone who opposes H can expect to be rewarded with being patted on the back for a good political attitude, while his possible cognitive errors will go unnoticed or unmentioned or at most mildly criticized.

Now, given that an advocate of H and an opponent of H find them- selves in such different positions, who of the two will have more incentive to invest a lot of time and hard work to present the strongest possible defense of his views? The question answers itself. In the academic jungle, as elsewhere, it is the one who anticipates trouble who will spare no effort to be maximally prepared for the confrontation.

If I am right, the pressure of political correctness would thus tend to result, ironically, in politically incorrect theories becoming better developed, more carefully articulated, and more successful in coping with objections. On the other hand, I would predict that a theory with a lot of political support would typically have a number of scholars flocking to its defense with poorly thought out arguments and with speedily generated but fallacious “refutations” of the opposing view. 24 This would explain why, as Ronald Fisher said, “the best causes tend to attract to their sup- port the worst arguments” (Fisher 1959: 31).

Example? Well, the best example I can think of is the state of the debate about heritability. Obviously, the hypothesis of high heritability of human psychological variation – and especially the between-group heritability of IQ differences – is one of the most politically sensitive topics in contemporary social science. The strong presence of political considerations in this controversy is undeniable, and there is no doubt about which way the political wind is blowing. When we turn to discussions in this context that are ostensibly about purely scientific issues two things are striking. First, as shown in previous chapters, critics of heritability very often rely on very general, methodological arguments in their attempts to show that heritability values cannot be determined, are intrinsically misleading, are low, are irrelevant, etc. Second, these global methodological arguments – although defended by some leading biologists, psychologists, and philosophers of science – are surprisingly weak and unconvincing. Yet they continue to be massively accepted, hailed as the best approach to the nature–nurture issue, and further transmitted, often with no detailed analysis or serious reflection.

Footnotes are:

22 This is not guaranteed, of course. For example, biblical literalists who think that the world was created 6,000 years ago can expect to be ridiculed as irrational, ignorant fanatics. So, if they go public, it is in their strong interest to use arguments that are not silly, but the position they have chosen to advocate leaves them with no good options. (I assume that it is not a good option to suggest, along the lines of Philip Gosse’s famous account, that the world was created recently, but with the false traces of its evolutionary history that never happened.)

23 A pressure in the opposite direction would not have much force. It is notorious that in the humanities and social science departments, conservative and other right-of-center views are seriously under-represented (cf. Ladd & Lipset 1975; Redding 2001).

24 I am speaking of tendencies here, of course. There would be good and bad arguments on both sides.

The Fisher (1959) reference given is actually about probability theory, that context Fisher is not writing about genetics or biology and its relation to politics.

Did no one come up with this idea before? Seems unlikely. Robert Plomin and Thomas Bouchard came close in 1987 chapters in the same book Arthur Jensen: Consensus And Controversy (see also this earlier post). Bouchard:

One might fairly claim that this chapter does not constitute a critical appraisal of the work of Arthur Jensen on the genetics of human abilities, but rather a defense. If a reader arrives at that conclusion he or she has overlooked an important message. Since Jensen rekindled the flames of the heredity vs environment debate in 1969, human behavior genetics has undergone a virtual renaissance. Nevertheless, a tremendous amount of energy has been wasted. In my discussions of the work of Kamin, Taylor, Farber, etc., I have often been as critical of them as they have been of the hereditarian program. While I believe that their criticisms have failed and their conclusions are false, I also believe that their efforts were necessary. They were necessary because human behavior genetics has been an insufficiently self-critical discipline. It adopted the quantitative models of experimental plant and animal genetics without sufficient regard for the many problems involved in justifying the application of those models in human research. Furthermore, it failed to deal adequately with most of the issues that are raised and dealt with by meta-analytic techniques. Human behavior geneticists have, until recently, engaged in inadequate analyses. Their critics, on the other hand, have engaged in pseudo-analyses. Much of the answer to the problem of persuading our scientific colleagues that behavior is significantly influenced by genetic processes lies in a more critical treatment of our own data and procedures. The careful and systematic use of meta-analysis, in conjunction with our other tools, will go a long way toward accomplishing this goal. It is a set of tools and a set of attitudes that Galton would have been the first to apply in his own laboratory.


More behavioral genetic data on IQ have been collected since Jensen’s 1969 monograph than in the fifty years preceding it. As mentioned earlier, I would argue that much of this research was conducted because of Jensen’s monograph and the controversy and criticism it aroused.

A decade and a half ago Jensen clearly and forcefully asserted that IQ scores are substantially influenced by genetic differences among individuals. No telling criticism has been made of his assertion, and newer data consistently support it. No other finding in the behavioral sciences has been researched so extensively, subjected to so much scrutiny, and verified so consistently.

Chris Brand also has a chapter in this book, perhaps it has something relevant. I don’t recall it well.

To return to Sesardić, his contention is that non-scientific opposition to some scientific claim will result in so called double standards: higher standards for proponents of the claim, and if reality supports the claim, then higher quality evidence will be gathered and published. It is the reverse for critics of the claim, they will face less scrutiny, so their published arguments and evidence will tend to be poorer. Do we have some kind of objective way to test this claim? We do. We can measure scientific rigor by scientific field or subfield, and compare. Probably the most left-wing field of psychology will be social psychology, and it has massive issues with the replication crisis. Intelligence and behavioral genetics research, on the other hand, have no such big problems. One of the least left-wing fields of psychology (nearly 50-50 balance of self-placed politics), should thus have high rigor. A simple way to measure this is compiling data about statistical power by field. This sometimes calculated as part of meta-analyses. Sean Last has compiled such values, reproduced below.

Citation Discipline Mean / Median Power
Button et al. (2013) Neuroscience 21%
Brain Imaging 8%
Smaldino and McElreath (2016) Social and Behavioral Sciences 24%
Szucs and Ioannidis (2017) Cognitive Neuroscience 14%
Psychology 23%
Medical 23%
Mallet et al (2017) Breast Cancer 16%
Glaucoma 11%
Rheumatoid Arthritis 19%
Alzheimer’s 9%
Epilepsy 24%
MS 24%
Parkinson’s 27%
Lortie-Forgues and Inglis (2019) Education 23%
Nuijten et al (2018) Intelligence 49%
Intelligence – Group Differences 57%

The main issue with this is that the numbers concern either median or mean power, with some inconsistency across fields. The median is usually lower, so one could convert the values using their mean observed ratio.

I should very much like someone to do a more detailed study of this. I imagine that one will do the following:

  1. Acquire a large dataset of scientific articles, including title, authors, abstract, keywords, fulltext, and references. This can be done either via Scihub (difficult) or by mining open access journals (probably easy).
  2. Use algorithms to extract data of interest. Usually studies calculating power rely on so-called focal analyses, i.e., main or important statistical tests. These are hard to identify using simple algorithms, but they can extract all of them (those with standardized format, that is!). Check out the work by Nuijten et al linked above. A better idea is to get a dataset of manually extracted data, and then train neural network to also extract them. I think one can succeed in training such an algorithm that is at least as accurate as human raters. When this is done, one can use it on every paper one has data about. Furthermore, one should look into additional automated measures of scientific rigor or quality. This can be relatively simple stuff like counting table, figure, reference density, or presence of robustness tests, or mentioning of key terms such as “statistical power” “publication bias”. It can also be more complicated, such as an algorithm that predicts whether a paper will likely replicate based on data from large replication studies. Such a prototype algorithm has been developed which reached AUC of .77!
  3. Relate the measures of scientific rigor to indicators of political view of authors, or the conclusions of the paper, or the topic in general. Control for any obvious covariates such as year of publication.
Book review Psychiatry Psychology Science

Genius: The Natural History of Creativity (Hans Eysenck, 1995)

I continue my Eysenck readings with his popular genius book (prior review The Psychology of Politics (1954)). Having previously read some of Simonton’s work, Eysenck sure is a very different beast! The writing style follows the usual style: candid, emphasizing of uncertainty when present, funny, and very wide ranging. In fact, regarding replication, Eysenck is almost modern, always asking for replications of experiments, and saying that it is a waste of time to do studies with n < 100!

I don’t have time to write a big review, but I have marked a bunch of interesting passages, and I will quote them here. Before doing so, however, the reader should know that there is now a memorial site for Hans Eysenck too, with free copies of his work. It’s not complete yet, his bibliography is massive! I host it, but it’s created by a 3rd person.

Let’s begin. Actually, I forgot to note interesting passages in the first half of the book, so these are all from second part. Eysenck discusses the role of the environment in origins of genius, and illustrates with an unlikely case:

Our hero was born during the American Civil War, son of Mary, a Negro slave on a Missouri farm owned by Moses Carver and his wife Susan. Mary, who was a widow, had two other children – Melissa, a young girl, and a boy, Jim; George was the baby. In 1862 masked bandits who terrorized the countryside and stole livestock and slaves attacked Carver’s farm, tortured him and tried to make him tell where his slaves were hidden; he refused to tell. After a few weeks they came back, and this time Mary did not have time to hide in a cave, as she had done the first time; the raiders dragged her, Melissa and George away into the bitter cold winter’s night. Moses Carver had them followed, but only George was brought back; the raiders had given him away to some womenfolk saying ‘he ain’t worth nutting’. Carver’s wife Susan nursed him through every conceivable childhood disease that his small frame seemed to be particularly prone to; but his traumatic experiences had brought on a severe stammer which she couldn’t cure. He was called Carver’s George; his true name (if such a concept had any meaning for a slave) is not known. When the war ended the slaves were freed, but George and Jim stayed with the Carvers. Jim was sturdy enough to become a shepherd and to do other farm chores; George was a weakling and helped around the house. His favourite recreation was to steal off to the woods and watch insects, study flowers, and become acquainted with nature. He had no schooling of any kind, but he learned to tend flowers and became an expert gardener. He was quite old when he saw his first picture, in a neighbour’s house; he went home enchanted, made some paint by squeezing out the dark juices of some berries, and started drawing on a rock. He kept on experimenting with drawings, using sharp stones to scratch lines on the smooth pieces of earth. He became known as the ‘plant doctor’ in the neighbourhood, although still only young, and helped everyone with their gardens.

At some distance from the farm there was a one-room cabin that was used as a school house during the week; it doubled as a church on Sundays. When George discovered its existence, he asked Moses Carver for permission to go there, but was told that no Negroes were allowed to go to that school. George overcame his shock at this news after a while; Susan Carver discovered an old spelling-book, and with her help he soon learned to read and write. Then he discovered that at Neosho, eight miles away, there was a school that would admit Negro children. Small, thin and still with his dreadful stammer, he set out for Neosho, determined to earn some money to support himself there. Just 14 years old, he made his home with a coloured midwife and washerwoman. ‘That boy told me he came to Neosho to find out what made hail and snow, and whether a person could change the colour of a flower by changing the seed. I told him he’d never find that out in Neosho. Maybe not even in Kansas City. But all the time I knew he’d find it out – somewhere.’ Thus Maria, the washerwoman; she also told him to call himself George Carver – he just couldn’t go on calling himself Carver’s George! By that name, he entered the tumbledown shack that was the Lincoln School for Coloured Children, with a young Negro teacher as its only staff member. The story of his fight for education against a hostile environment is too long to be told here; largely self-educated he finally obtained his Bachelor of Science degree at the age of 32, specialized in mycology (the study of fungus growths) became an authority in his subject, and finally accepted an invitation from Booker T. Washington, the foremost Negro leader of his day, to help him fund a Negro university. He accepted, and his heroic struggles to create an institute out of literally nothing are part of Negro history. He changed the agricultural and the eating habits of the South; he created single-handed a pattern of growing food, harvesting and cooking it which was to lift Negroes (and whites too!) out of the abject state of poverty and hunger to which they had been condemned by their own ignorance. And in addition to all his practical and teaching work, administration and speech-making, he had time to do creative and indeed fundamental research; he was one of the first scientists to work in the field of synthetics, and is credited with creating the science of chemurgy – ‘agricultural chemistry’. The American peanut industry is based on his work; today this is America’s sixth most important agricultural product, with many hundreds of by-products. He became more and more obsessed with the vision that out of agriculture and industrial waste useful material could be created, and this entirely original idea is widely believed to have been Carver’s most important contribution. The number of his discoveries and inventions is legion; in his field, he was as productive as Edison. He could have become a millionaire-many times over but he never accepted money for his discoveries. Nor would he accept an increase in his salary, which remained at the 125 dollars a month (£100 per year) which Washington had originally offered him. (He once declined an offer by Edison to work with him at a minimum annual salary of 100000 dollars.) He finally died, over 80, in 1943. His death was mourned all over the United States. The New York Herald Tribune wrote: ‘Dr, Carver was, as everyone knows, a Negro. But he triumphed over every obstacle. Perhaps there is no one in this century whose example has done more to promote a better understanding between the races. Such greatness partakes of the eternal.’ He himself was never bitter, in spite of all the persecutions he and his fellow-Negroes had to endure. ‘No man can drag me down so low as to make me hate him.’ This was the epitaph on his grave. He could have added fortune to fame, but caring for neither, he found happiness and honour in being helpful to the world.

On Simonton‘s model of creativity:

Simonton’s own theory is interesting but lacks any conceivable psychological support. He calls his theory a ‘two-step’ model; he postulates that each individual creator begins with a certain ‘creative potential’ defined by the total number of contributions the creator would be capable of producing in an unrestricted life span. (Rather like a woman’s supply of ova!) There are presumably individual differences in this initial creative potential, which Simonton hardly mentions in the development of his theory. Now each creator is supposed to use up his supply of creative potential by transforming potential into actual contributions. (There is an obvious parallel here with potential energy in physics.) This translation of creative potential into actual creative products implies two steps. The first involves the conversion of creative potential into creative ideation, in the second step these ideas are worked into actual creative contributions in a form that can be appreciated publicly (elaboration). It is further assumed that the rate at which ideas are produced is proportional to the creative potential at a given time, and that the rate of elaboration if ‘proportional to the number of ideas in the works’ (Simonton, 1984b; p. 110). Simonton turns these ideas into a formula which generates a curve which gives a correlation between predicted and observed values in the upper 90s (Simonton, 1983b). The theory is inviting, but essentially untestable – how would we measure the ‘creative potential’ which presumably is entirely innate, and should exist from birth? How could we measure ideation, or elaboration, independently of external events? Of course the curve fits observations beautifully, but then all the constants are chosen to make sure of such a fit! Given the general shape of the curve (inverted U), many formulae could be produced to give such a fit. Unless we are shown ways of independently measuring the variables involved, no proper test of any underlying psychological theory exists.

On geniuses misbehavior, featuring Newton:

Less often remarked, but possibly even more insidious, is the resistance by scientists to ‘scientific discovery’, as Barker (1961) has named this phenomenon. As he point out, in two systematic analyses of the social process of scientific discovery and invention, analyses which tried to be as inclusive of empirical facts and theoretical problems as possible, there was only one passing reference to such resistance in the one instance and none at all in the second (GilfiUan, 1935; Barker, 1952). This contrasts markedly with the attention paid to the resistance to scientific discovery on the part of economic, technological, religious ideological elements and groups outside science itself (Frank, 1957; Rossman, 1931; Shyrock, 1936; Stamp, 1937). This neglect is probably based on the erroneous notion embodied in the title of Oppenheimer‘s (1955) book The Open Mind; we assume all too readily that objectivity is the characteristic of the scientist, and that he will impartially consider all the available facts and theories. Polanyi (1958, 1966) has emphasized the importance of the personality of the scientist, and no one familiar with the history of science can doubt that individual scientists are as emotional, jealous, quirky, self-centred, excitable, temperamental, ardent, enthusiastic, fervent, impassioned, zealous and hostile to competition as anyone else. The incredibly bellicose, malevolent and rancorous behaviour of scientists engaged in disputes about priority illustrates the truth of this statement. The treatment handed out to Halton Arp (1987), who dared to doubt the cosmological postulate about the meaning and interpretation of the red-shift is well worth pondering (Flanders, 1993). Objectivity flies out of the window when self-interest enters (Hagstrom, 1974).

The most famous example of a priority dispute is that between Newton and Leibnitz, concerning the invention of the calculus (Manuel, 1968). The two protagonists did not engage in the debate personally, but used proxies, hangers-on who would use their vituperative talents to the utmost in the service of their masters. Newton in particular abused his powers as President of the Royal Society in a completely unethical manner. He nominated his friends and supporters to a theoretically neutral commission of the Royal Society to consider the dispute; he wrote the report himself, carefully keeping his own name out of it, and he personally persecuted Leibnitz beyond the grave, insisting that he had plagiarized Newton’s discovery – which clearly was untrue, as posterity has found. Neither scientist emerges with any credit from the Machiavellian controversy, marred by constant untruths, innuendos of a personal nature, insults, and outrageous abuse which completely obscured the facts of the case. Newton behaved similarly towards Robert Hooke, Locke, Flamsted and many others; as Manuel (1968) says. ‘Newton was aware of the mighty anger that smouldered within him all his life, eternally seeking objects. … many were the times when (his censor) was overwhelmed and the rage could not be contained’ (p. 343). ‘Even if allowances are made for the general truculence of scientists and learned men, he remains one of the most ferocious practitioners of the art of scientific controversy. Genteel concepts of fair play are conspicuously absent, and he never gave any quarter’ (p. 345). So much for scientific objectivity!

More Newton!:

Once a theory has been widely accepted, it is difficult to displace, even though the evidence against it may be overwhelming. Kuhn (1957) points out that even after the publication of De Revolutionibus most astronomers retained their belief in the central position of the earth; even Brahe (Thoren, 1990) whose observations were accurate enough to enable Kepler (Caspar, 1959) to determine that the Mars orbit around the sun was elliptical, not circular, could not bring himself to accept the heliocentric view. Thomas Young proposed a wave theory of light on the basis of good experimental evidence, but because of the prestige of Newton, who of course favoured a corpuscular view, no-one accepted Young’s theory (Gillespie, 1960). Indeed, Young was afraid to publish the theory under his own name, in case his medical practice might suffer from his opposition to the god-like Newton! Similarly, William Harvey’s theory of the circulation of the blood was poorly received, in spite of his prestigious position as the King’s physician, and harmed his career (Keele, 1965). Pasteur too was hounded because his discovery of the biological character of the fermentation process was found unacceptable. Liebig and many others defended the chemical theory of these processes long after the evidence in favour of Pasteur was conclusive (Dubos, 1950). Equally his micro-organism theory of disease caused endless strife and criticism. Lister’s theory of antisepsis (Fisher, 1977) was also long argued over, and considered absurd; so were the contributions of Koch (Brock, 1988) and Erlich (Marquardt, 1949). Priestley (Gibbs, 1965) retained his views of phlogiston as the active principle in burning, and together with many others opposed the modern theories of Lavoisier, with considerable violence. Alexander Maconochie’s very successful elaboration and application of what would now be called ‘Skinnerian principle’ to the reclamation of convicted criminals in Australia, led to his dismissal (Barry, 1958).

But today is different! Or maybe not:

The story is characteristic in many ways, but it would be quite wrong to imagine that this is the sort of thing that happened in ancient, far-off days, and that nowadays scientists behave in a different manner. Nothing has changed, and I have elsewhere described the fates of modern Lochinvars who fought against orthodoxy and were made to suffer mercilessly (Eysenck, 1990a). The battle against orthodoxy is endless, and there is no chivalry; if power corrupts (as it surely does!), the absolute power of the orthodoxy in science corrupts absolutely (well, almost!). It is odd that books on genius seldom if ever mention this terrible battle that originality so often has when confronting orthodoxy. This fact certainly accounts for some of the personality traits so often found in genius, or even the unusually creative non-genius. The mute, inglorious Milton is a contradiction in terms, an oxymoron; your typical genius is a fighter, and the term ‘genius’ is by definition accorded the creative spirit who ultimately (often long after his death) wins through. An unrecognized genius is meaningless; success socially defined is a necessary ingredient. Recognition may of course be long delayed; the contribution of Green (Connell, 1993) is a good example.

On fraud in science, after discussing Newton’s fudging of data, and summarizing Kepler‘s:

It is certainly startling to find an absence of essential computational details because ‘taediesum esset’ to give them. But worse is to follow. Donahue makes it clear that Kepler presented theoretical deduction as computations based upon observation. He appears to have argued that induction does not suffice to generate true theories, and to have substituted for actual observations figures deduced from the theory. This is historically interesting in throwing much light on the origins of scientific theories, but is certainly not a procedure recommended to experimental psychologists by their teachers!

Many people have difficulties in understanding how a scientist can fraudulently ‘fudge’ his data in this fashion. The line of descent seems fairly clear. Scientists have extremely high motivation to succeed in discovering the truth; their finest and most original discoveries are rejected by the vulgar mediocrities filling the ranks of orthodoxy. They are convinced that they have found the right answer; Newton believed it had been vouchsaved him by God, who explicitly wanted him to preach the gospel of divine truth. The figures don’t quite fit, so why not fudge them a little bit to confound the infidels and unbelievers? Usually the genius is right, of course, and we may in retrospect excuse his childish games, but clearly this cannot be regarded as a licence for non-geniuses to foist their absurd beliefs on us. Freud is a good example of someone who improved his clinical findings with little regard for facts (Eysenck, 1990b), as many historians have demonstrated. Quod licet Jovi non licet bovi – what is permitted to Jupiter is not allowed the cow!

One further point. Scientists, as we shall see, tend to be introverted, and introverts show a particular pattern of level of aspiration (Eysenck, 1947) – it tends to be high and rigid. That means a strong reluctance to give up, to relinquish a theory, to acknowledge defeat. That, of course, is precisely the pattern shown by so many geniuses, fighting against external foes and internal problems. If they are right, they are persistent; if wrong, obstinate. As usual the final result sanctifies the whole operation (fudging included); it is the winners who write the history books!

The historical examples would seem to establish the importance of motivational and volitional factors, leading to persistence in opposition against a hostile world, and sometimes even to fraud when all else fails. Those whom the establishment refuses to recognize appropriately fight back as best they can; they should not be judged entirely by the standards of the mediocre!

This example and the notes about double standards for genius is all the more interesting in the recent light of problems with Eysenck’s own studies, published with yet another maverick!

And now, to sunspots and genius:

Ertel used recorded sun-spot activity going back to 1600 or so, and before that by analysis of the radiocarbon isotope CI4, whose productions as recorded in trees, which give an accurate picture of sun-spot activity. Plotted in relation to sun-spot activity were historical events, either wars, revolutions, etc. or specific achievements in painting, drama, poetry, science and philosophy. Note that Ertel’s investigations resemble a ‘double blind’ paradigm, in that the people who determined the solar cycle, and those who judged the merits of the artists and scientists in question, were ignorant of the purpose to which Ertel would put their data, and did not know anything about the theories involved. Hence the procedure is completely objective, and owes nothing to Ertel’s views, which in any case were highly critical of Chizhevsky’s ideas at the beginning.

The irregularities of the solar cycle present difficulties to the investigator, but also, as we shall see, great advantages. One way around this problem was suggested by Ertel; it consists of looking at each cycle separately; maximum solar activity (sol. max.) is denoted 0, and the years preceding or succeeding 0 are marked -1, -2, -3 etc., or +1, +2, +3 etc. Fig. 4.2 shows the occurrence of 17 conflicts between socialist states from 1945 to 1982, taken from a table published by the historian Bebeler, i.e. chosen in ignorance of the theory. In the figure the solid circles denote the actual distribution of events, the empty circles the expected distribution on a chance basis. Agreement with theory is obvious, 13 of the 17 events occurring between – 1 and + 1 solar maximum (Ertel, 1992a,b).

Actually Ertel bases himself on a much broader historical perspective, having amassed 1756 revolutionary events from all around the world, collected from 22 historical compendia covering the times from 1700 to the present. There appears good evidence in favour of Chizhevsky’s original hypothesis. However, in this book we are more concerned with Ertel’s extension to cultural events, i.e. the view that art and science prosper most when solar activity is at a minimum. Following his procedure regarding revolutionary events, Ertel built up a data bank concerned with scientific discoveries. Fig. 4.3 shows the outcome; the solid lines show the relation between four scientific disciplines and solar activity, while the black dots represent the means of the four scientific disciplines. However, as Ertel argues, the solar cycle may be shorter or longer than 11 years, and this possibility can be corrected by suitable statistical manipulation; the results of such manipulation, which essentially records strength of solar activity regardless of total duration of cycle, are shown on the right. It will be clear that with or without correction for duration of the solar cycle, there is a very marked U-shaped correlation with this activity, with an average minimum of scientific productivity at points -1,0 and -I-1, as demanded by the theory.

Intriguing! Someone must have tested this stuff since. It should be easy to curate a large dataset from Murray’s Human Accomplishment or Wikipedia based datasets, and see if it holds up. More generally, it is somewhat in line with quantitative historical takes by clio-dynamics people.

Intuition vs. thinking, system 1 vs. 2, and many other names:

It was of course Jung (1926) who made intuition one of the four functions of his typology (in addition to thinking, feeling, and sensation). This directed attention from the process of intuition to intuition as a personality variable – we can talk about the intuitive type as opposed to the thinking type, the irrational as opposed to the rational. (Feeling, too, is rational, while sensation is irrational, i.e. does not involve a judgment.) Beyond this, Jung drifts of Tinto the clouds peopled with archetypes and constituted of the ‘collective unconscious’, intuitions of which are held to be far more important than intuitions of the personal unconscious. Jung’s theory is strictly untestable, but has been quite important historically in drawing attention to the intuitive person’, or intuition as a personality trait.

Jung, like most philosophers, writers and psychologists, uses the contrast between ‘intuition’ and logic’ as an absolute, a dichotomy of either – or. Yet when we consider the definitions and uses of the terms, we find that we are properly dealing with a continuum, with ‘intuition’ and logic’ at opposite extremes, rather like the illustration in Fig. 5.2. In any problem-solving some varying degree of intuition is involved, and that may be large or small in amount. Similarly, as even Jung recognized, people are more or less intuitive; personalities are ranged along a continuum. It is often easier to talk as if we were dealing with dichotomies (tall vs. short; bright vs. dumb; intuitive vs. logical), but it is important to remember that this is not strictly correct; we always deal with continua.

The main problem with the usual treatment of ‘intuition’ is the impossibility of proof; whatever is said or postulated is itself merely intuitive, and hence in need of translation into testable hypotheses. Philosophical or even common- sense notions of intuition, sometimes based on experience as in the case of Poincare, may seem acceptable, but they suffer the fate of all introspection – they may present us with a problem, but do not offer a solution.

The intuitive genius of Ramanujan:

For Hardy, as Kanigel says, Ramanujan’s pages of theorems were like an alien forest whose trees were familiar enough to call trees, yet so strange they seemed to come from another planet. Indeed, it was the strangeness of Ramanujan’s theorems, not their brilliance, that struck Hardy first. Surely this was yet another crank, he thought, and put the letter aside. However, what he had read gnawed at his imagination all day, and finally he decided to take the letter to Littlewood, a mathematical prodigy and friend of his. The whole story is brilliantly (and touchingly) told by Kanigel; fraud or genius, they asked themselves, and decided that genius was the only possible answer. All honour to Hardy and Littlewood for recognizing genius, even under the colourful disguise of this exotic Indian plant; other Cambridge mathematicians, like Baker and Hobson, had failed to respond to similar letters. Indeed, as Kanigel says, ‘it is not just that he discerned genius in Ramanujan that stands to his credit today; it is that he battered down his own wall of skepticism to do so’ (p. 171).

The rest of his short life (he died at 33) Ramanujan was to spend in Cambridge, working together with Hardy who tried to educate him in more rigorous ways and spent much time in attempting to prove (or disprove!) his theorems, and generally see to it that his genius was tethered to the advance- ment of modern mathematics. Ramanujan’s tragic early death left a truly enormous amount of mathematical knowledge in the form of unproven theorems of the highest value, which were to provide many outstanding mathematicians with enough material for a life’s work to prove, integrate with what was already known, and generally give it form and shape acceptable to orthodoxy. Ramanujan’s standing may be illustrated by an informal scale of natural mathematical ability constructed by Hardy, on which he gave himself a 25 and Littlewood a 30. To David Hilbert, the most eminent mathematician of his day, he gave an 80. To Ramanujan he gave 100! Yet, as Hardy said:

the limitations of his knowledge were as startling as its profundity. Here was man who could work out modular equations and theorems of complex multiplication, to orders unheard of, whose mastery of continued fractions was, on the formal side at any rate, beyond that of any mathematician in the world, who had found for himself the functional equation of the Zeta- function, and the dominant terms of many of the most famous problems in the analytical theory of numbers; and he had never heard of a doubly periodic function or of Cauchy’s theorem, and had indeed but the vaguest idea of what a function of a complex variable was. His ideas as to what constituted a mathematical proof were of the most shadowy description. All his results, new or old, right or wrong, had been arrived at by a process of mingled arguments, intuition, and induction, of which he was entirely unable to give any coherent account (p. 714).

Ramanujan’s life throws some light on the old question of the ‘village Hampden’ and ‘mute inglorious Milton’; does genius always win through, or may the potential genius languish unrecognized and undiscovered? In one sense the argument entails a tautology: if genius is defined in terms of social recognition, an unrecognized genius is of course a contradicto in adjecto. But if we mean, can a man who is a potential genius be prevented from demonstrating his abilities?, then the answer must surely be in the affirmative. Ramanujan was saved from such a fate by a million-to-one accident. All his endeavours to have his genius recognized in India had come to nothing; his attempts to interest Baker and Hobson in Cambridge came to nothing; his efforts to appeal to Hardy almost came to nothing. He was saved by a most unlikely accident. Had Hardy not reconsidered his first decision, and consulted Littlewood, it is unlikely that we would ever have heard of Ramanujan! How many mute inglorious Miltons (and Newtons, Einsteins and Mendels) there may be we can never know, but we may perhaps try and arrange things in such a way that their recognition is less likely to be obstructed by bureaucracy, academic bumbledom and professional envy. In my experience, the most creative of my students and colleagues have had the most difficulty in finding recognition, acceptance, and research opportunities; they do not fit in, their very desire to devote their lives to research is regarded with suspicion, and their achievements inspire envy and hatred.

Eysenck talks about his psychoticism construct, which is almost the same as the modern general psychopathology factor, both abbreviated to P:

The study was designed to test Kretschmer’s (1946, 1948) theory of a schizothymia-cyclothymia continuum, as well as my own theory of a norma- lity-psychosis continuum. Kretschmer was one of the earliest proponents of a continuum theory linking psychotic and normal behaviour. There is, he argued, a continuum from schizophrenia through schizoid behaviour to normal dystonic (introverted) behaviour; on the other side of the continuum we have syntonic (extraverted) behaviour, cycloid and finally manic-depres- sive disorder. He is eloquent in discussing how psychotic abnormality shades over into odd and eccentric behaviour and finally into quite normal typology. Yet, as I have pointed out (Eysenck, 1970a,b), the scheme is clearly incom- plete. We cannot have a single dimension with ‘psychosis’ at both ends; we require at least a two dimensional scheme, with psychosis-normal as one axis, and schizophrenia-affective disorder as the other.

In order to test this hypothesis, I designed a method of ‘criterion analysis’ (Eysenck, 1950, 1952a,b), which explicitly tests the validity of continuum vs. categorical theories. Put briefly, we take two groups (e.g. normal vs. psycho- tic), and apply to both objective tests which significantly discriminate between the groups. We then intercorrelate the tests within each group, and factor analyse the resulting matrices. If and only if the continuum hypothesis is correct will it be found that the factor loadings in both matrices will be similar or identical, and that these loading will be proportional to the degree to which the various tests discriminate between the two criterion groups.

An experiment has been reported, using this method. Using 100 normal controls, 50 schizophrenics and 50 manic-depressives, 20 objective tests which had been found previously to correlate with psychosis were applied to all the subjects (Eysenck, 1952b). The results clearly bore out the continuum hypothesis. The two sets of factor loadings correlated .87, and both were proportional to the differentiating power of the tests r = .90 and .95, respecti- vely). These figures would seem to establish the continuum hypotheses quite firmly; the results of the experiment are not compatible with a categorical type of theory.

Eysenck summarizes his model:

Possessing this trait, however, does not guarantee creative achievement. Trait creativity may be a necessary component of such achievement, but many other conditions must be fulfilled, many other traits added (e.g. ego-strength), many abilities and behaviours added (e.g. IQ, persistence), and many socio- cultural variables present, before high creative achievement becomes prob- able. Genius is characterized by a very rare combination of gifts, and these gifts function synergistically, i.e. they multiply rather than add their effects. Hence the mostly normally distributed conditions for supreme achievement interact in such a manner as to produce a J-shaped distribution, with huge numbers of non- or poor achievers, a small number of high achievers, and the isolated genius at the top.

This, in very rough outline, is the theory here put forward. As discussed, there is some evidence in favour of the theory, and very little against it. Can we safely say that the theory possesses some scientific credentials, and may be said to be to some extent a valid account of reality? There are obvious weaknesses. Genius is extremely rare, and no genius has so far been directly studied with such a theory in mind. My own tests have been done to study deductions from the theory, and these have usually been confirmatory. Is that enough, and how far does it get us?

Terms like ‘theory’, of course, are often abused. Thus Koestler (1964) attempts to explain creativity in terms of his theory of’bisociation’ according to which the creative act ‘always operates on more than one plane’ (p. 36). This is not a theory, but a description; it cannot be tested, but acts as a definition. Within those limits, it is acceptable as a non-contingent proposition (Smets- lund, 1984), i.e. necessarily true and not subject to empirical proof. A creative idea must, by definition, bring together two or more previously unrelated concepts. As an example, consider US Patent 5,163,447, the ‘force-sensitive, sound-playing condom’, i.e. an assembly of a piezo-electric sound transducer, microchip, power supply and miniature circuitry in the rim of a condom, so that when pressure is applied, it emits ‘a predetermined melody or a voice message’. Here is bisociation in its purest form, bringing together mankind’s two most pressing needs, safe sex and eternal entertainment. But there is no proper theory here; nothing is said that could be disproved by experiment. Theory implies a lot more than simple description.

And he continues outlining his own theory of scientific progress:

The philosophy of science has thrown up several criteria for judging the success of a theory in science. All are agreed that it must be testable, but there are two alternative ways of judging the outcome of such tests. Tradition (including the Vienna school) insists on the importance of confirmation’, the theory is in good shape as long as results of testing deductions are positive (Suppe, 1974). Popper (1959, 1979), on the other hand, uses falsification as his criterion, pointing out that theories can never be proved to be correct, because we cannot ever test all the deductions that can possibly be made. More recent writers like Lakatos (1970, 1978; Lakatos and Musgrave, 1970) have directed their attention rather at a whole research programme, which can be either advancing or degenerating. An advancing research programme records a number of successful predictions which suggest further theoretical advances; a degenerating research programme seeks to excuse its failures by appealing to previously unconsidered boundary conditions. On those terms we are surely dealing with an advancing programme shift; building on research already done, many new avenues are opening up for supporting or disproving the theories making up our model.

It has always seemed to me that the Viennese School, and Popper, too, were wrong in disregarding the evolutionary aspect of scientific theories. Methods appropriate for dealing with theories having a long history of development might not be optimal in dealing with theories in newly developing fields, lacking the firm sub-structure of the older kind. Newton, as already men- tioned, succeeded in physics, where much sound knowledge existed in the background, as well as good theories; he failed in chemistry/alchemy where they did not. Perhaps it may be useful to put forward my faltering steps in this very complex area situated between science and philosophy (Eysenck, 1960, 1985b).

It is agreed that theories can never be proved right, and equally that they are dependent on a variety of facts, hunches and assumptions outside the theory itself; these are essential for making the theory testable. Cohen and Nagel (1936) put the matter very clearly, and take as their example Foucault’s famous experiment in which he showed that light travels faster in air than in water. This was considered a crucial experiment to decide between two hypotheses: H1? the hypothesis that light consists of very small particles travelling with enormous speeds, and H2 , the hypothesis that light is a form of wave motion. H1 implies the proposition Pl that the velocity of light in water is greater than in air, while H2 implies the proposition P2 that the velocity of light in water is less than in air. According to the doctrine of crucial experiments, the corpuscular hypothesis of light should have been banished to limbo once and for all. However, as is well known, contemporary physics has revived the corpuscular theory in order to explain certain optical effects which cannot be explained by the wave theory. What went wrong?

As Cohen and Nagel point out, in order to deduce the proposition P1 from H1 and in order that we may be able to perform the experiment of Foucault, many other assumptions, K, must be made about the nature of light and the instruments we employ in measuring its velocity. Consequently, it is not the hypothesis H1 alone which is being put to the test by the experiment – it is H1 and K. The logic of the crucial experiment may therefore be put in this fashion. If Hl and K, then P1; if now experiment shows P1 to be false, then either Hl is false or K (in part or complete) is false (or of course both may be false!). If we have good grounds for believing that K is not false, H1 is refuted by the experiment. Nevertheless the experiment really tests both H1 and K. If in the interest of the coherence of our knowledge it is found necessary to revise the assumptions contained in K, the crucial experiment must be reinterpreted, and it need not then decide against H1.

What I am suggesting is that when we are using H + K to deduce P, the ratio of H to K will vary according to the state of development of a given science. At an early stage, K will be relatively little known, and negative outcomes of testing H + K will quite possibly be due to faulty assumptions concerning K. Such theories I have called ‘weak’, as opposed to ‘strong’ theories where much is known about K, so that negative outcomes of testing H + K are much more likely to be due to errors in H (Eysenck, 1960, 1985b).

We may now indicate the relevance of this discussion to our distinction between weak and strong theories. Strong theories are elaborated on the basis of a large, well founded and experimentally based set of assumptions, K, so that the results of new experiments are interpreted almost exclusively in terms of the light they throw on H1, H2, …, Hn . Weak theories lack such a basis, and negative results of new experiments may be interpreted with almost equal ease as disproving H or disproving K. The relative importance of K can of course vary continuously, giving rise to a continuum; the use of the terms ‘strong’ and ‘weak’ is merely intended to refer to the extremes of this continuum, not to suggest the existence of two quite separate types of theories. In psychology, K is infinitely less strong than it is in physics, and consequently theories in psychology inevitably lie towards the weaker pole.

Weak theories in science, then, generate research the main function of which is to investigate certain problems which, but for the theory in question, would not have arisen in that particular form; their main purpose is not to generate predictions the chief use of which is the direct verification or confirmation of the theory. This is not to say that such theories are not weakened if the majority of predictions made are infirmed; obviously there comes a point when investigators turn to more promising theories after consistent failure with a given hypothesis, however interesting it may be. My intention is merely to draw attention to the fact – which will surely be obvious to most scientifically trained people – that both proof and failure of deductions from a scientific hypothesis are more complex than may appear at first sight, and that the simple-minded application of precepts derived from strong theories to a field like psychology may be extremely misleading. Ultimately, as Conant has emphasized, scientific theories of any kind are not discarded because of failures of predictions, but only because a better theory has been advanced.

The reader with a philosophy background will naturally think of this in terms of The Web of Belief, which takes us back to my earlier days of blogging philosophy!

intelligence / IQ / cognitive ability Science

Hereditarianism: a progressive research program

I am posting this because this is not widely known, but I think this angle should be taken more seriously. I hope philosophers will read this and get inspired!

Peter Urbach (this guy, not this guy!) was a student of Imre Lakatos, and in 1974 he wrote a frank assessment of the status of the contrasting research programs in psychology: the hereditarian program and the environmentalist one. Hereditarian here is concerned with genetic causation in general not limited to between group differences. There is no abstract, but part one opens with:

In the question of intelligence, all roads lead back to the work of Francis Galton in the late nineteenth century. He was the first to formulate a theory of ‘general intelligence’ 1 ; he pioneered the construction of mental tests; and he was the inventor of experimental methods for investigating the inheritance of mental abilities.

The controversy between those who hold that individual and group differences in intelligence test scores are primarily due to inherited differ- ences and those who hold they are primarily the products of environmental differences is one of the oldest and most acrimonious in social science. The controversy has been ahnost universally marred by a lack of clearly defined standards by which to assess the rival theories. Whenever such standards have been invoked, they have been either Utopian 2 or unsatis- factory. 3

I intend to describe and appraise the rival views of intelligence in terms of Lakatos’s methodology of scientific research programmes and thereby to evaluate the two competing programmes in the light of their objective merits. This will also detach the debate from the political positions with which they are falsely associated in the public mind.

My thesis is that the hereditarian-environmentalist rivalry has existed not between two competing theories but between two competing research programmes. For there have been a series of—falsifiable and, indeed, falsified—hereditarian and environmentalist theories, each term in each of the two series dealing with some of the refutations (or anomalies) faced by its predecessor. Each of the two series can be characterised by a set of assumptions (‘hard cores’) common to all the terms. Moreover, each of the series is associated with certain ‘heuristic’ machinery guiding the con- struction of successive hypotheses in the series. Thus both the hereditarian and environmentalist approaches possess all the features identified by Lakatos in major physical scientific research programmes. 4

And his conclusion of part one:

The hereditarian programme has anticipated many novel facts. I have discussed the successful predictions (t) of the degree of family resemblances in IQ B , («) of IQ-related social mobility, 6 (Hi) of the distribution of IQ’s, and (iv) of the differences in sibling regression for American Negroes and whites, 1 since these are the most striking examples. When the environ- mentalist programme has attempted to account for the novel facts produced by the hereditarian programme, it has been unable to do so except in an ad hoc fashion. The hereditarian programme is not free from anomalies— but in this respect it is not exceptionally placed among scientific research programmes. Anomalies are anticipated by a good research programme and the puzzle-solving techniques for resolving them are articulated in advance. The crucial criterion for deciding whether a programme is progressive is whether it has anticipated novel facts. By this criterion, the hereditarian programme has been scientifically progressive and has contributed to the growth of knowledge. 2

This is even more true now than when it was written in 1974. The era of genomics has vindicated yet more predictions from the hereditarian program: 1) polygenic nature of intelligence and other traits, 2) mostly additive genetic effects (failure of especially GxE and also GxG research to substantiate claims), 3) newer methods to quantify heritability find substantial estimates (GREML and friends), 4) a decline in polygenic scores over time i.e. dysgenics was confirmed in multiple studies, 5) many more decades of environmentalist ad hoc claims, 6) general agreement now that brain training programs do not work, 7) failure of colorism model in empirical tests, 8) large scale studies of enrichment programs/early intervention failing to find lasting benefit (fade-out) and initial small gains, 9) replication crisis finding massive issues with mainstream and environmentalist research, but not hereditarian research. One could list more.

There is a pressing need to write an update on the Urbach papers. Rushton and Jensen (2005) mentions it but did not expand on it.

Book review Epistemology Math/Statistics Science

Book review: The Book of Why: The New Science of Cause and Effect (Judea Pearl, Dana Mackenzie)

This is an interesting but annoying book. The basic pattern of the book goes like this:

  1. Scientists used to totally not know anything proper about how to do X or think about X.
  2. But no worries, then I, the Great Pearl (+ students), came along and invented Causal Diagrams and some equations, and now the field has been revolutionized.

The book contains basically no real life applications of these methods, and any working scientist should scoff at this. A particularly concise example toward the end of the book:

Elias Bareinboim [i.e. Pearl’s student] has managed to do the same thing for the problem of transportability [Pearl’s term for validity generalization] that Ilya Shpitser did for the problem of interventions. He has developed an algorithm that can automatically determine for you whether the effect you are seeking is transportable, using graphical criteria alone. In other words, it can tell you whether the required separation of S from the do-operators can be accomplished or not.

Bareinboim’s results are exciting because they change what was formerly seen as a threat to validity into an opportunity to leverage the many studies in which participation cannot be mandated and where we therefore cannot guarantee that the study population would be the same as the population of interest. Instead of seeing the difference between populations as a threat to the “external validity” of a study, we now have a methodology for establishing validity in situations that would have appeared hopeless before. It is precisely because we live in the era of Big Data that we have access to information on many studies and on many of the auxiliary variables (like Z and W) that will allow us to transport results from one population to another.

I will mention in passing that Bareinboim has also proved analogous results for another problem that has long bedeviled statisticians: selection bias. This kind of bias occurs when the sample group being studied differs from the target population in some relevant way. This sounds a lot like the transportability problem—and it is, except for one very important modification: instead of drawing an arrow from the indicator variable S to the affected variable, we draw the arrow toward S. We can think of S as standing for “selection” (into the study). For example, if our study observes only hospitalized patients, as in the Berkson bias example, we would draw an arrow from Hospitalization to S, indicating that hospitalization is a cause of selection for our study. In Chapter 6 we saw this situation only as a threat to the validity of our study. But now, we can look at it as an opportunity. If we understand the mechanism by which we recruit subjects for the study, we can recover from bias by collecting data on the right set of deconfounders and using an appropriate reweighting or adjustment formula. Bareinboim’s work allows us to exploit causal logic and Big Data to perform miracles that were previously inconceivable.
Words like “miracles” and “inconceivable” are rare in scientific discourse, and the reader may wonder if I am being a little too enthusiastic. But I use them for a good reason. The concept of external validity as a threat to experimental science has been around for at least half a century, ever since Donald Campbell and Julian Stanley recognized and defined the term in 1963. I have talked to dozens of experts and prominent authors who have written about this topic. To my amazement, not one of them was able to tackle any of the toy problems presented in Figure 10.2. I call them “toy problems” because they are easy to describe, easy to solve, and easy to verify if a given solution is correct.

At present, the culture of “external validity” is totally preoccupied with listing and categorizing the threats to validity rather than fighting them. It is in fact so paralyzed by threats that it looks with suspicion and disbelief on the very idea that threats can be disarmed. The experts, who are novices to graphical models, find it easier to configure additional threats than to attempt to remedy any one of them. Language like “miracles,” so I hope, should jolt my colleagues into looking at such problems as intellectual challenges rather than reasons for despair.

I wish that I could present the reader with successful case studies of a complex transportability task and recovery from selection bias, but the techniques are still too new to have penetrated into general usage. I am very confident, though, that researchers will discover the power of Bareinboim’s algorithms before long, and then external validity, like confounding before it, will cease to have its mystical and terrifying power.

Alright then! For those who are wondering what he is talking about. He is merely talking about the conditions under which we can extrapolate the validity of some effect in one population to another that might differ in some characteristics. In Pearl’s world, this means that we just draw up a simple Causal Diagram for it, and then we figure out how to modify the effect size given changes to this diagram. What his student did is come up with an algorithm that can handle arbitrary changes to this diagram. Of course, in the real world, we don’t have any simple causal diagrams everybody agrees on, and neither do we know how they might differ between one population and another. So these methods, though cool, are inapplicable to the real world.

Pearl causal diagram for transportability. (FIGURE 10.2. Differences between the studied populations, expressed in graphical form.)

Pearl himself takes some pride in this otherworldly approach:

In Chapter 3 I wrote about some of the reasons for this slow progress. In the 1970s and early 1980s, artificial intelligence research was hampered by its focus on rule-based systems. But rule-based systems proved to be on the wrong track. They were very brittle. Any slight change to their working assumptions required that they be rewritten. They could not cope well with uncertainty or with contradictory data. Finally, they were not scientifically transparent; you could not prove mathematically that they would behave in a certain way, and you could not pinpoint exactly what needed repair when they didn’t. Not all AI researchers objected to the lack of transparency. The field at the time was divided into “neats” (who wanted transparent systems with guarantees of behavior) and “scruffies” (who just wanted something that worked). I was always a “neat.”

I was lucky to come along at a time when the field was ready for a new approach. Bayesian networks were probabilistic; they could cope with a world full of conflicting and uncertain data. Unlike the rule-based systems, they were modular and easily implemented on a distributed computing platform, which made them fast. Finally, as was important to me (and other “neats”), Bayesian networks dealt with probabilities in a mathematically sound way. This guaranteed that if anything went wrong, the bug was in the program, not in our thinking.

Even with all these advantages, Bayesian networks still could not understand causes and effects. By design, in a Bayesian network, information flows in both directions, causal and diagnostic: smoke increases the likelihood of fire, and fire increases the likelihood of smoke. In fact, a Bayesian network can’t even tell what the “causal direction” is. The pursuit of this anomaly—this wonderful anomaly, as it turned out—drew me away from the field of machine learning and toward the study of causation. I could not reconcile myself to the idea that future robots would not be able to communicate with us in our native language of cause and effect. Once in causality land, I was naturally drawn toward the vast spectrum of other sciences where causal asymmetry is of the utmost importance.
So, for the past twenty-five years, I have been somewhat of an expatriate from the land of automated reasoning and machine learning. Nevertheless, from my distant vantage point I can still see the current trends and fashions.

In recent years, the most remarkable progress in AI has taken place in an area called “deep learning,” which uses methods like convolutional neural networks. These networks do not follow the rules of probability; they do not deal with uncertainty in a rigorous or transparent way. Still less do they incorporate any explicit representation of the environment in which they operate. Instead, the architecture of the network is left free to evolve on its own. When finished training a new network, the programmer has no idea what computations it is performing or why they work. If the network fails, she has no idea how to fix it.

Perhaps the prototypical example is AlphaGo, a convolutional neural-network-based program that plays the ancient Asian game of Go, developed by DeepMind, a subsidiary of Google. Among human games of perfect information, Go had always been considered the toughest nut for AI. Though computers conquered humans in chess in 1997, they were not considered a match even for the lowest-level professional Go players as recently as 2015. The Go community thought that computers were still a decade or more away from giving humans a real battle.

That changed almost overnight with the advent of AlphaGo. Most Go players first heard about the program in late 2015, when it trounced a human professional 5–0. In March 2016, AlphaGo defeated Lee Sedol, for years considered the strongest human player, 4–1. A few months later it played sixty online games against top human players without losing a single one, and in 2017 it was officially retired after beating the current world champion, Ke Jie. The one game it lost to Sedol is the only one it will ever lose to a human.

All of this is exciting, and the results leave no doubt: deep learning works for certain tasks. But it is the antithesis of transparency. Even AlphaGo’s programmers cannot tell you why the program plays so well. They knew from experience that deep networks have been successful at tasks in computer vision and speech recognition. Nevertheless, our understanding of deep learning is completely empirical and comes with no guarantees. The AlphaGo team could not have predicted at the outset that the program would beat the best human in a year, or two, or five. They simply experimented, and it did.

Some people will argue that transparency is not really needed. We do not understand in detail how the human brain works, and yet it runs well, and we forgive our meager understanding. So, they argue, why not unleash deep-learning systems and create a new kind of intelligence without understanding how it works? I cannot say they are wrong. The “scruffies,” at this moment in time, have taken the lead. Nevertheless, I can say that I personally don’t like opaque systems, and that is why I do not choose to do research on them.

I still want to give this book 4/5 stars because it certainly is informative about how Pearl works, and Pearl is an interesting guy and no doubt has had a big impact. The book should thus be seen as an inadvertent semi-autobiography of Pearl. And of course, it presents a lot of interesting information about how one can think in simplified causal pathways, even though these aren’t usually so useful in practice.

Genetics / behavioral genetics Psychology Science

Paige-Harden, Turkheimer and the psychometric left

Kathryn Paige Harden is professor of psychology who belongs to the Turkheimerian ‘left psychometrics’ school. I’ve discussed the odd behavior of Eric Turkheimer before, but since then I found a rather amazing essay: The Search for a Psychometric Left 1997 (the journal seems to no longer exist). It’s definitely worth reading in its entirely, but here I quote the conclusion:

I do not wish to commit the very sin I am deploring. The radical scientific left is — obviously — entitled to its views, and in this increasingly biogenetic era their implacable opposition is often a very necessary tonic. I expect to continue to stand with them, albeit slightly to their right, against the smug unanimity of the Wall Street Journal scientific establishment, and in more urgent rejection of the deeply disturbing racism that has lately taken up a beachhead at the rightmost extrema of scientific respectability. But I also expect to continue to be allied with those who continue to investigate the complexities of human ability and its transmission between generations. It is time that the psychometric establishment had a left wing (Who can doubt that it has a right?) that is willing to share enough of its assumptions to engage it in meaningful debate.

A psychometric Left would recognize that human ability, individual differences in human ability, measures of human ability, and genetic influences on human ability are all real but profoundly complex, too complex for the imposition of biogenetic or political schemata. It would assert that the most important difference between the races is racism, with its origins in the horrific institution of slavery only a very few generations ago. Opposition to determinism, reductionism and racism, in their extreme or moderate fonts, need not depend on blanket rejection of undeniable if easily misinterpreted facts like heritability, or useful if easily misapplied tools like factor analysis. Indeed it had better not, because if it does the eventual victory of the psychometric right is assured.

I think this needs no comment.

Back to Paige-Harden. She likes to tweet, and yesterday she posted this (archived in case she deletes):

So, let’s translate this from left speak to plain speak: she wants some journalist to tell the public on her behalf that opening up science — i.e. removing gate keepers — results in more science being done that isn’t favorable to left-wing politics. She is naturally very concerned about this because according to followers of the Turkheimerian school, it’s all about not extending a hand to the evil racists of the right psychometrics. What if people were no longer told that All Real Scientists think that “the most important difference between the races is racism”, to give one example?

As for psychometrics — they mean differential psychology, not people who obsess about measurement models — being particularly right-wing, this is of course a very unlikely claim considering that rather crazy left-wing tilt of psychology itself: Lambert 2018 finds a ratio of 17 to 1 of registered Democrats to Republicans among psychology faculty in the US. Indeed, survey evidence disproves this just as it does for evolutionary psychology (Buss and von Hippel 2018): differential psychology, here represented by people who publishes in Intelligence is somewhat left-leaning, though less than other academic areas. As such, because one’s own position biases one’s perception, for someone with far left-wing views, mainstream differential psychology seems particularly right-wing, while in actuality, it is center-left. This perceiver bias effect forms the basis of the usual centrist take: everybody to my right is a Nazi/everybody to my left is a Stalinist.

I think the approach advocated above — putting political goals ahead of scientific ones — are completely in contradiction to the purpose of science. Arthur Jensen said it well:

But the most frequently heard objection to further research into human genetics, particularly research into the genetics of behavioral characteristics, is that the knowledge gained might be misused. I agree. Knowledge also, however, makes possible greater freedom of choice. It is a necessary condition for human freedom in the fullest sense. I therefore completely reject the idea that we should cease to discover, to invent, and to know (in the scientific meaning of that term) merely because what we find could be misunderstood, misused, or put to evil and inhumane ends. This can be done with almost any invention, discovery, or addition to knowledge. Would anyone argue that the first caveman who discovered how to make a fire with flint stones should have been prevented from making fire, or from letting others know of his discovery, on the grounds that it could be misused by arsonists? Of course not. Instead, we make a law against arson and punish those who are caught violating the law. The real ethical issue, I believe, is not concerned with whether we should or should not strive for a greater scientific understanding of our universe and of ourselves. For a scientist, it seems to me, this is axiomatic.

Genetics / behavioral genetics intelligence / IQ / cognitive ability Math/Statistics Science

It works in practice, but does it work in (my) theory?

There’s a certain type of person that doesn’t produce any empirical contribution to “Reducing the heredity-environment uncertainty”. Instead, they contribute various theoretical arguments which they take to undermine the empirical data others give. Usually, these people have a background in philosophy or some other theoretical field. A recent example of this pattern is seen on Reddit, where Jinkinson Payne Smith (u/EverymorningWP) made this thread:

Heritability and Heterogeneity: The Irrelevance of Heritability in Explaining Differences between Means for Different Human Groups or Generations” includes (on its page 398, section 2.1) some interesting paragraphs that decisively refute the claims of Neven Sesardic regarding “heritability”. One particularly relevant quote is this one: “The shortcomings I describe involve matters of logic and methodology; empirical considerations are beside the point.” So those who wish to use the “hitting-them-over-the-head” style* so common of behavior geneticists, involving the deflection conceptual, logical criticisms to focus on narrow technical issues, should keep in mind that superficial empirical concerns are not the only ones worth taking seriously.

*The term “hitting them over the head” was coined by Aaron Panofsky in his 2014 book Misbehaving Science. As defined by Burt & Simons (2015, p. 104), “This approach involves dodging criticisms by misrepresenting arguments and insinuating that critics are politically motivated and reject scientific truths as well as focusing on a few “‘tractable’ empirical objections” while “ignoring the deeper theoretical objections””.

So: It works in practice, but does it work in (my) theory? These philosophy arguments are useless. Any physics professor knows this well because they get a lot of emails allegedly refuting relativity and quantum mechanics using thought experiments and logical arguments (like Time Cube). These arguments convince no one, even if one can’t find the error in the argument immediately (like in the ontological argument). It works the same way for these anti-behavioral genetics theoretical arguments. If these want to be taken seriously, they should produce 1) contrasting models, 2) that produce empirically testable predictions, and 3) show that these fit with their model and do not fit with the current behavioral/quantitative genetics models.

For a historical example of this, see Jensen’s reply (pp. 451ff) to Schönemann’s sophistry (chapter 18) along the same lines regarding an obscure and empirically irrelevant problem in factor analysis (factor score indeterminacy). An excerpt:

Components analysis and factor analys is were invented and developed by the pioneers of differential psychology as a means of dealing with substantive problems in the measurement and anal ysis of human abilities. The first generation of factor analysts—psychologists such as Spearman, Burt, and Thurstone—were first of all psychologists, with a primary interest in the structure and nature of individual differ ences. For them factor analysis was but one methodological means of advancing empirical research and theory in the domain of abilities. But in subsequent generations experts in factor analysis have increasingly become more narrowly specialized. They show little or no interest in psychology, but confine their thinking to the ‘pure mathematics’ of factor analysis, without reference to any issues of substantive or theoretical importance. For some it is methodology for methodology’s sake, isolated from empirical realities, and disdainful of substantive problems and ‘dirty data’. Cut off from its origin, which was rooted in the study of human ability, some of the recent esoterica in factor analysis seem like a sterile, self-contained intellectual game, good fun perhaps, but having scarcely more relevance to anything outside itself than the game of chess. Schönemann is impressive as one of the game’s grandmasters. The so-called ‘factor indeterminacy’ problem, which is an old issue recognized in Spearman’s time, has, thanks to Schönemann, been revived as probably the most esoteric weapon in the ‘IQ controversy’.

A useful follow-up here is also:

  • Jensen, A. R., and Weng, J.J. (1994). “What is a good g?Intelligence, 18, 231—258.

which shows that if one extracts the g factor in lots of different ways, factor scores from these all correlate .99 with each other, so the fact that one cannot precisely give the true scores for a given set of data is empirically irrelevant.

I must say that I do feel some sympathy with Jinkinson’s approach. I am myself somewhat of a verbal tilt person who used to study philosophy (for bachelor degree), and who used to engage in some of these ‘my a priori argument beats your data’ type arguments. I eventually wised up, I probably owe some of this to my years of drinking together with the good physicists at Aarhus University, who do not care so much for such empirically void arguments.

Genetics / behavioral genetics intelligence / IQ / cognitive ability Logic Science

Animal cross-fostering, race and IQ, and the deductivist’s fallacy

I wish to coin a fallacy I’ve seen a number of times, exemplified in this paper:


In this paper the nature of the reasoning processes applied to the nature-nurture question is discussed in general and with particular reference to mental and behavioral traits. The nature of data analysis and analysis of variance is discussed. Necessarily, the nature of causation is considered. The notion that mere data analysis can establish “real” causation is attacked. Logic of quantitative genetic theory is reviewed briefly. The idea that heritability is meaningful in the human mental and behavioral arena is attacked. The conclusion is that the heredity-IQ controversy has been a “tale full of sound and fury, signifying nothing”. To suppose that one can establish effects of an intervention process when it does not occur in the data is plainly ludicrous. Mere observational studies can easily lead to stupidities, and it is suggested that this has happened in the heredity-IQ arena. The idea that there are racial-genetic differences in mental abilities and behavioral traits of humans is, at best, no more than idle speculation.

While explaining the analysis of variance (ANOVA), he writes:

One can find a variety of presentations of analysis of variance which miss this elemental fact. In the heredity-IQ controversy, we see a statement by Feldman and Lewontin (1975) on the nature of analysis of variance that I believe to be totally wrong: “The analysis of variance is, in fact, what is known in mathematics as local perturbation analysis.” In fact, perturbation analysis is a well-defined mathematical-statistical area, and the intersection of that area with the basic idea of the analysis of variance is essentially negligible. They also say “A n analysis would require that we know the first partial derivatives of the unknown function f(G, E).” This illustrates a basic epistemological error. Suppose G and E were real variables and we did know the first partial derivatives; then, so what? They also say “The analysis of variance produces results that are applicable only to small perturbations around the current mean”; again a basic epistemological error. On the matter of the role of variance, to say that additive genetic variance is important “since Fisher’s fundamental theorem of natural selection predicts … ” is wide of the mark, and again exemplifies an error commonly made in population genetics. Fisher’s theorem, if it is correct, deals with fitness, whatever that is (and population geneticists are curiously silent on the matter, using a symbol such as s, and rarely, if ever, discussing the matter of its epistemic correlation to some observation protocol; see, for instance, Kempthorne and Pollak (1970)). It is necessary to my general thesis to bring these matters into the discourse, because understanding of what the analysis of variance does and what it does not do is absolutely critical in the heredity-IQ controversy. These criticisms must not be interpreted to suggest that all of the Feldman-Lewontin paper is suspect.

We now turn to what I regard as a shocking error of logic. Suppose:

so that 80% of the variability is associated with groups. It is all too easy to go from this to the totally erroneous statement that 80% of the variability is due to the factor of classification, where due to is interpreted as caused by. What has gone on in the IQ-heredity controversy is little more than this. It is obvious that this analysis of variance can tell us nothing about causation.

So, Kempthorne is basically just being wordy and saying you can’t just infer causation with mathematical certainty from association in ANOVA. But he goes further than that and says it can tell us nothing about causation. This is plainly false, association is evidence of causation, and depending on context and type of association, can be highly informative or not so informative. Probably a mere correlation in social science is not very indicative of causation (, but heritability-related statistics are. Since Kempthorne talks about using experiments to establish causation, we use that example against him.

Suppose we are interested in quantifying the degree to which between group means of two subspecies are due to genetic factors versus some other factors. In animals, we can attack this problem using e.g. cross-fostering experiments in which we basically kidnap very young offspring and place them with other parents, which might be from the other subspecies or not; or better yet, we implant embryos to take into account any uterine effects (see this earlier post for discussion of such for humans). Let’s say we are interested in behavior towards humans, e.g. fearfulness. If we do this experiment, we can work out which amount of variance in the trait is caused by rearing by particular parent, by same-group parent, by other-group parent, and by genetics. This kind of thing has been done a lot of times, and in recent times was used to estimate the between group heritability of human friendliness in the Siberian fox experiment. I quote from the book about it (How to Tame a Fox (and Build a Dog), Dugatkin and Trut, 2017):

WHAT LYUDMILA AND DMITRI WERE EQUIPPED TO investigate further was the other ways that innate traits and learning might be affecting their tame foxes. They were constantly availing themselves of the latest techniques for research, and during the time Lyudmila was living at Pushinka’s house, she and Dmitri decided to see whether they could delve even deeper into what degree the behaviors they were seeing in the tame foxes were genetically based.
Even as they tried to hold all conditions constant for the foxes, there were subtle, almost imperceptible differences that could creep into an experiment. For instance, what if the tamest mothers treated their pups differently than the aggressive moms treated their pups? Maybe pups learned something about how to be tame or aggressive toward humans from the way their moms treated them?

There was only one way to confirm for certain that the behavioral differences they were seeing between the tame and aggressive foxes were due to genetic differences. Dmitri and Lyudmila would have to try what is known as “cross-fostering.” They’d have to take developing embryos from tame mothers and transplant them into the wombs of aggressive females. Then they would let the aggressive foster mothers give birth and raise those pups. If the pups turned out tame themselves, despite having aggressive foster moms, then Lyudmila and Dmitri would know that tameness was fundamentally genetic and not learned. And, for completeness, they would also do the same experiment with the pups of aggressive mothers transplanted into tame mothers to see if they got parallel results.

In principle, cross-fostering was straightforward; researchers had used the procedure to examine the role of nature versus nurture for many years. But in practice it was easier said than done, it was technically difficult to pull off, and it had worked much better with some species than others. No one had ever tried to transplant fox embryos. Then again, no one had tried lots of things they had done, and so Lyudmila decided she would have to learn this delicate procedure on her own. She read all she could on transplant experiments that had been done in other species, and she conferred with the veterinarians they had on staff. Lives were at stake, so she took her time, learning everything she could.

She would be transplanting tiny, delicate embryos—on the order of eight days old—from the womb of one female into the womb of another pregnant female. Some of the embryos from tame mothers would be transplanted into the wombs of aggressive mothers, and some of those of aggressive mothers would be transplanted into the wombs of tame mothers. When the pups were born seven weeks later, she would closely observe their behavior to see if the pups of tame mothers became aggressive and if the pups of aggressive mothers became tame. But how in heaven’s name was she going to know which pups in a litter were the genetic offspring of the mother and which pups were the ones she had transplanted? Without that information, the experiment was futile. She realized that the foxes had their own unique color coding system. Coat color is a genetic trait, so if she carefully selected the males and females so that the coat coloring of their offspring would be predictable, and the pups of the aggressive mothers would have different colors from those of the tame mothers, she’d be able to tell which pups were the genetic offspring of a female, and which had been transplanted.

Lyudmila led the transplant surgeries with her faithful assistant Tamara by her side. Each surgery involved two females, one tame and one aggressive, each about a week into pregnancy. After lightly anesthetizing the foxes, Lyudmila made a tiny surgical incision in each female’s abdomen and located the uterus, with its right and left “horn,” each of which had embryos implanted in it. She then removed the embryos from one uterine horn and left the embryos in the other. Then she repeated the procedure with the second female. She transplanted the embryos that had been removed from one mother into the other in a drop of nutritional liquid that was placed into the tip of a pipette. “The embryos,” Lyudmila recalls with the pride of a job well done, “stayed outside the uterus [at room temperature from 64 to 68 degrees Fahrenheit] for no more than 5–6 minutes.” The females were then moved to a postoperative room and given time to recover.

Everyone at the Institute anxiously awaited the results. Even with the surgeries having gone so well, the transplanted embryos might not survive. Their wait paid off. It was the caretakers who were the first to discover the births of the first litters, which was often the case with new developments with the foxes. They sent word right away to the Institute. “It was like a miracle,” Lyudmila recorded. “All the workers gathered around the cages for a party with wine.”
Lyudmila and Tamara began recording the pups’ behavior as soon as they left their nests and began interacting with humans. One day Lyudmila watched as an aggressive female was parading around with her genetic and foster pups. “It was fascinating,” Lyudmila recalls, “. . . the aggressive mother had both tame and aggressive offspring. Her foster tame offspring were barely walking but they were already rushing to the cage doors, if there was a human standing by, and wagging their tails.” And Lyudmila wasn’t the only one fascinated. The mother foxes were as well. “The aggressive mothers were punishing tame pups for such improper behavior,” Lyudmila recalls. “They growled at them and grabbed their neck, throwing them back in the nest.” The genetic offspring of the aggressive mothers did not show curiosity about people. They, like their mothers, disliked humans. “The aggressive pups on the other hand retained their dignity,” Lyudmila remembers. “They growled aggressively, same as their mothers, and ran to their nests.” This pattern was repeated over and over. Pups behaved like their genetic mothers, not their foster mothers. There was no longer any doubt—basic tameness and aggression towards humans were, in part, genetic traits.
The house experiment with Pushinka had shown that tame foxes had also learned some of their behavior. Living with humans had taught the foxes additional ways of behaving, some of which they shared with their domesticated dog cousins. Genes surely played an important role, but the tame foxes were not simple genetic automatons; they learned to identify individual people and became particularly bonded to them, and even defended them, owing to the process of living with them. That these learned behaviors were so dog-like provided the tantalizing suggestion that wolves in the process of transforming into dogs might also have learned these behaviors by living with people. Dmitri and Lyudmila had produced some of the best evidence that an animal’s genetic lineage and the circumstances of its life combined in generating its behavior, and had done so in a highly innovative way.

What if you wanted to know about human race groups (populations, subspecies, etc. use your preferred term)? It would be quite cruel to do the above kind of experiments in a controlled fashion, but one can of course investigate adoptions, both within and between populations. For IQ, this has famously been done a few times see: MTAS and Tizard. I have also covered a number of recent studies that no one else seems to have paid attention to (see posts under this tag) until I posted them at which point a paper appeared citing them. Let’s disregard those for now. Suppose we carried out a large number of cross-fostering experiments in many species and for many traits, including cognitive, then we could calculate the summary statistics for these and see if there’s any relations to trait cluster, species type etc. Furthermore, we can relate them to the within group heritability-like statistics. Jensen (1998, p. 445) basically assumes a such relationship holds, though he doesn’t cite any animal research in support:

One of the aims of science is to comprehend as wide a range of phenomena as possible within a single framework, using the fewest possible mechanisms with the fewest assumptions and ad hoc hypotheses. With respect to IQ, the default hypothesis relating individual differences and population differences is consistent with this aim, as it encompasses the explanation of both within-group (WG) and between-group (BG) differences as having the same causal sources of variance. The default hypothesis that the BG and WG differences are homogeneous in their causal factors implies that a phenotypic difference of PD between two population groups in mean level of IQ results from the same causal effects as does any difference between individuals (within either of the two populations) whose IQs differ by PD (i.e., the phenotypic difference). In either case, PD is the joint result of both genetic (G) and environmental (E) effects. In terms of the default hypothesis, the effects of genotype X environment co­ variance are the same between populations as within populations. The same is hypothesized for genotype X environment interaction, although studies have found it contributes negligibly to within-population variance in g.

Actually, I would expect subspecies differences to be more heritable than within group differences because within group differences have a lot of environmental causal variance in nature, but less in humans because we reduce it by social policies. The average wild adult length of polar and grizzly bears differs by perhaps 50 cm for males (comparisons). But when we rear these bears in zoos, they keep these average differences, indicating that they are due to genetics not environmental habitat-related factors. As for experiments, many people have tried bringing up wolves to be like dogs. This often but not always fails and the wolves end up in wolf sanctuaries. It also often fails for wolf-dog hybrids. There’s actually a published study comparing wolves, poodles and wolf-poodle hybrids, apparently finding them to be quite wolfy in behavior (I couldn’t obtain a complete copy). Another study mentions that wolf-dog hybridization in the wild is quite common in Ethiopia, so one could actually run admixture studies here. I have not search this literature extensively, maybe something great exists waiting to be found by hereditarian-minded researchers.

To return to Kempthorne, the point is that if we can find such relationships between within group heritability-related statistics and between subspecies ones, this would imply that one can indeed derive relevant conclusions. Animal findings generalize to humans to some extent, though, perhaps not as much as we would hope. Given some level of generalizability (prior transfer, we might call it), we might be able to infer a likely range of between group heritability based on within group heritability in humans.

Per this, I shall coin the fallacy made by Kempthorne, which I shall term the deductivist’s fallacy. It is when a critic looks a relationship, finds that he cannot think of any strict formal i.e. necessary/logically necessary relationship between the premises and the conclusion, and then concludes that the premises can tell us nothing about the conclusion. This ignores the fact that the premises may have non-deductive/probabilistic relevance. To put it another way, the deductivist’s fallacy is when one criticizes an inductive argument for not being deductive enough. Many of the traditional fallacies in informal logic can be given a Bayesian reading this way and would no longer be fallacies. For instance, appeal to authority is surely relevant because statements about a topic from experts is more likely to be true than one from non-experts — unless it’s social science! There’s a few papers on this topic such as Korb 2004. Neven Sesardic also has a good discussion of the between/within group heritability reasoning in his excellent book Making sense of heritability.

Related meme

Language Science

Chomsky on postmodernism [repost]

This text used to be hosted at Shalizi‘s university website, but it was recently taken down for unknown reasons. However, Internet Archive saves us, and I repost it here because it’s interesting and so it doesn’t get lost.

This text has circulated quite a number of times on Usenet, and so far as I know is authentic. This version (less, of course, the HTML airs and graces) was posted by one to rec.arts.books, 13 Nov 1995 03:21:23 -0500, message-id 486v63$ Jenm289 wrote: “The following was written several months ago by Noam Chomsky in a discussion about po-mo and its contribution to activism et al. The discussion took place on LBBS, Z-Magazine’s Left On-Line Bulletin Board (contact to join).”

I’ve returned from travel-speaking, where I spend most of my life, and found a collection of messages extending the discussion about “theory” and “philosophy,” a debate that I find rather curious. A few reactions — though I concede, from the start, that I may simply not understand what is going on.

As far as I do think I understand it, the debate was initiated by the charge that I, Mike, and maybe others don’t have “theories” and therefore fail to give any explanation of why things are proceeding as they do. We must turn to “theory” and “philosophy” and “theoretical constructs” and the like to remedy this deficiency in our efforts to understand and address what is happening in the world. I won’t speak for Mike. My response so far has pretty much been to reiterate something I wrote 35 years ago, long before “postmodernism” had erupted in the literary intellectual culture: “if there is a body of theory, well tested and verified, that applies to the conduct of foreign affairs or the resolution of domestic or international conflict, its existence has been kept a well-guarded secret,” despite much “pseudo-scientific posturing.”

To my knowledge, the statement was accurate 35 years ago, and remains so; furthermore, it extends to the study of human affairs generally, and applies in spades to what has been produced since that time. What has changed in the interim, to my knowledge, is a huge explosion of self- and mutual-admiration among those who propound what they call “theory” and “philosophy,” but little that I can detect beyond “pseudo-scientific posturing.” That little is, as I wrote, sometimes quite interesting, but lacks consequences for the real world problems that occupy my time and energies (Rawls’s important work is the case I mentioned, in response to specific inquiry).

The latter fact has been noticed. One fine philosopher and social theorist (also activist), Alan Graubard, wrote an interesting review years ago of Robert Nozick’s “libertarian” response to Rawls, and of the reactions to it. He pointed out that reactions were very enthusiastic. Reviewer after reviewer extolled the power of the arguments, etc., but no one accepted any of the real-world conclusions (unless they had previously reached them). That’s correct, as were his observations on what it means.

The proponents of “theory” and “philosophy” have a very easy task if they want to make their case. Simply make known to me what was and remains a “secret” to me: I’ll be happy to look. I’ve asked many times before, and still await an answer, which should be easy to provide: simply give some examples of “a body of theory, well tested and verified, that applies to” the kinds of problems and issues that Mike, I, and many others (in fact, most of the world’s population, I think, outside of narrow and remarkably self-contained intellectual circles) are or should be concerned with: the problems and issues we speak and write about, for example, and others like them. To put it differently, show that the principles of the “theory” or “philosophy” that we are told to study and apply lead by valid argument to conclusions that we and others had not already reached on other (and better) grounds; these “others” include people lacking formal education, who typically seem to have no problem reaching these conclusions through mutual interactions that avoid the “theoretical” obscurities entirely, or often on their own.

Again, those are simple requests. I’ve made them before, and remain in my state of ignorance. I also draw certain conclusions from the fact.

As for the “deconstruction” that is carried out (also mentioned in the debate), I can’t comment, because most of it seems to me gibberish. But if this is just another sign of my incapacity to recognize profundities, the course to follow is clear: just restate the results to me in plain words that I can understand, and show why they are different from, or better than, what others had been doing long before and and have continued to do since without three-syllable words, incoherent sentences, inflated rhetoric that (to me, at least) is largely meaningless, etc. That will cure my deficiencies — of course, if they are curable; maybe they aren’t, a possibility to which I’ll return.

These are very easy requests to fulfill, if there is any basis to the claims put forth with such fervor and indignation. But instead of trying to provide an answer to this simple requests, the response is cries of anger: to raise these questions shows “elitism,” “anti-intellectualism,” and other crimes — though apparently it is not “elitist” to stay within the self- and mutual-admiration societies of intellectuals who talk only to one another and (to my knowledge) don’t enter into the kind of world in which I’d prefer to live. As for that world, I can reel off my speaking and writing schedule to illustrate what I mean, though I presume that most people in this discussion know, or can easily find out; and somehow I never find the “theoreticians” there, nor do I go to their conferences and parties. In short, we seem to inhabit quite different worlds, and I find it hard to see why mine is “elitist,” not theirs. The opposite seems to be transparently the case, though I won’t amplify.

To add another facet, I am absolutely deluged with requests to speak and can’t possibly accept a fraction of the invitations I’d like to, so I suggest other people. But oddly, I never suggest those who propound “theories” and “philosophy,” nor do I come across them, or for that matter rarely even their names, in my own (fairly extensive) experience with popular and activist groups and organizations, general community, college, church, union, etc., audiences here and abroad, third world women, refugees, etc.; I can easily give examples. Why, I wonder.

The whole debate, then, is an odd one. On one side, angry charges and denunciations, on the other, the request for some evidence and argument to support them, to which the response is more angry charges — but, strikingly, no evidence or argument. Again, one is led to ask why.

It’s entirely possible that I’m simply missing something, or that I just lack the intellectual capacity to understand the profundities that have been unearthed in the past 20 years or so by Paris intellectuals and their followers. I’m perfectly open-minded about it, and have been for years, when similar charges have been made — but without any answer to my questions. Again, they are simple and should be easy to answer, if there is an answer: if I’m missing something, then show me what it is, in terms I can understand. Of course, if it’s all beyond my comprehension, which is possible, then I’m just a lost cause, and will be compelled to keep to things I do seem to be able to understand, and keep to association with the kinds of people who also seem to be interested in them and seem to understand them (which I’m perfectly happy to do, having no interest, now or ever, in the sectors of the intellectual culture that engage in these things, but apparently little else).

Since no one has succeeded in showing me what I’m missing, we’re left with the second option: I’m just incapable of understanding. I’m certainly willing to grant that it may be true, though I’m afraid I’ll have to remain suspicious, for what seem good reasons. There are lots of things I don’t understand — say, the latest debates over whether neutrinos have mass or the way that Fermat’s last theorem was (apparently) proven recently. But from 50 years in this game, I have learned two things: (1) I can ask friends who work in these areas to explain it to me at a level that I can understand, and they can do so, without particular difficulty; (2) if I’m interested, I can proceed to learn more so that I will come to understand it. Now Derrida, Lacan, Lyotard, Kristeva, etc. — even Foucault, whom I knew and liked, and who was somewhat different from the rest — write things that I also don’t understand, but (1) and (2) don’t hold: no one who says they do understand can explain it to me and I haven’t a clue as to how to proceed to overcome my failures. That leaves one of two possibilities: (a) some new advance in intellectual life has been made, perhaps some sudden genetic mutation, which has created a form of “theory” that is beyond quantum theory, topology, etc., in depth and profundity; or (b) … I won’t spell it out.

Again, I’ve lived for 50 years in these worlds, have done a fair amount of work of my own in fields called “philosophy” and “science,” as well as intellectual history, and have a fair amount of personal acquaintance with the intellectual culture in the sciences, humanities, social sciences, and the arts. That has left me with my own conclusions about intellectual life, which I won’t spell out. But for others, I would simply suggest that you ask those who tell you about the wonders of “theory” and “philosophy” to justify their claims — to do what people in physics, math, biology, linguistics, and other fields are happy to do when someone asks them, seriously, what are the principles of their theories, on what evidence are they based, what do they explain that wasn’t already obvious, etc. These are fair requests for anyone to make. If they can’t be met, then I’d suggest recourse to Hume’s advice in similar circumstances: to the flames.

Specific comment. Phetland asked who I’m referring to when I speak of “Paris school” and “postmodernist cults”: the above is a sample.

He then asks, reasonably, why I am “dismissive” of it. Take, say, Derrida. Let me begin by saying that I dislike making the kind of comments that follow without providing evidence, but I doubt that participants want a close analysis of de Saussure, say, in this forum, and I know that I’m not going to undertake it. I wouldn’t say this if I hadn’t been explicitly asked for my opinion — and if asked to back it up, I’m going to respond that I don’t think it merits the time to do so.

So take Derrida, one of the grand old men. I thought I ought to at least be able to understand his Grammatology, so tried to read it. I could make out some of it, for example, the critical analysis of classical texts that I knew very well and had written about years before. I found the scholarship appalling, based on pathetic misreading; and the argument, such as it was, failed to come close to the kinds of standards I’ve been familiar with since virtually childhood. Well, maybe I missed something: could be, but suspicions remain, as noted. Again, sorry to make unsupported comments, but I was asked, and therefore am answering.

Some of the people in these cults (which is what they look like to me) I’ve met: Foucault (we even have a several-hour discussion, which is in print, and spent quite a few hours in very pleasant conversation, on real issues, and using language that was perfectly comprehensible — he speaking French, me English); Lacan (who I met several times and considered an amusing and perfectly self-conscious charlatan, though his earlier work, pre-cult, was sensible and I’ve discussed it in print); Kristeva (who I met only briefly during the period when she was a fervent Maoist); and others. Many of them I haven’t met, because I am very remote from from these circles, by choice, preferring quite different and far broader ones — the kinds where I give talks, have interviews, take part in activities, write dozens of long letters every week, etc. I’ve dipped into what they write out of curiosity, but not very far, for reasons already mentioned: what I find is extremely pretentious, but on examination, a lot of it is simply illiterate, based on extraordinary misreading of texts that I know well (sometimes, that I have written), argument that is appalling in its casual lack of elementary self-criticism, lots of statements that are trivial (though dressed up in complicated verbiage) or false; and a good deal of plain gibberish. When I proceed as I do in other areas where I do not understand, I run into the problems mentioned in connection with (1) and (2) above. So that’s who I’m referring to, and why I don’t proceed very far. I can list a lot more names if it’s not obvious.

For those interested in a literary depiction that reflects pretty much the same perceptions (but from the inside), I’d suggest David Lodge. Pretty much on target, as far as I can judge.

Phetland also found it “particularly puzzling” that I am so “curtly dismissive” of these intellectual circles while I spend a lot of time “exposing the posturing and obfuscation of the New York Times.” So “why not give these guys the same treatment.” Fair question. There are also simple answers. What appears in the work I do address (NYT, journals of opinion, much of scholarship, etc.) is simply written in intelligible prose and has a great impact on the world, establishing the doctrinal framework within which thought and expression are supposed to be contained, and largely are, in successful doctrinal systems such as ours. That has a huge impact on what happens to suffering people throughout the world, the ones who concern me, as distinct from those who live in the world that Lodge depicts (accurately, I think). So this work should be dealt with seriously, at least if one cares about ordinary people and their problems. The work to which Phetland refers has none of these characteristics, as far as I’m aware. It certainly has none of the impact, since it is addressed only to other intellectuals in the same circles. Furthermore, there is no effort that I am aware of to make it intelligible to the great mass of the population (say, to the people I’m constantly speaking to, meeting with, and writing letters to, and have in mind when I write, and who seem to understand what I say without any particular difficulty, though they generally seem to have the same cognitive disability I do when facing the postmodern cults). And I’m also aware of no effort to show how it applies to anything in the world in the sense I mentioned earlier: grounding conclusions that weren’t already obvious. Since I don’t happen to be much interested in the ways that intellectuals inflate their reputations, gain privilege and prestige, and disengage themselves from actual participation in popular struggle, I don’t spend any time on it.

Phetland suggests starting with Foucault — who, as I’ve written repeatedly, is somewhat apart from the others, for two reasons: I find at least some of what he writes intelligible, though generally not very interesting; second, he was not personally disengaged and did not restrict himself to interactions with others within the same highly privileged elite circles. Phetland then does exactly what I requested: he gives some illustrations of why he thinks Foucault’s work is important. That’s exactly the right way to proceed, and I think it helps understand why I take such a “dismissive” attitude towards all of this — in fact, pay no attention to it.

What Phetland describes, accurately I’m sure, seems to me unimportant, because everyone always knew it — apart from details of social and intellectual history, and about these, I’d suggest caution: some of these are areas I happen to have worked on fairly extensively myself, and I know that Foucault’s scholarship is just not trustworthy here, so I don’t trust it, without independent investigation, in areas that I don’t know — this comes up a bit in the discussion from 1972 that is in print. I think there is much better scholarship on the 17th and 18th century, and I keep to that, and my own research. But let’s put aside the other historical work, and turn to the “theoretical constructs” and the explanations: that there has been “a great change from harsh mechanisms of repression to more subtle mechanisms by which people come to do” what the powerful want, even enthusiastically. That’s true enough, in fact, utter truism. If that’s a “theory,” then all the criticisms of me are wrong: I have a “theory” too, since I’ve been saying exactly that for years, and also giving the reasons and historical background, but without describing it as a theory (because it merits no such term), and without obfuscatory rhetoric (because it’s so simple-minded), and without claiming that it is new (because it’s a truism). It’s been fully recognized for a long time that as the power to control and coerce has declined, it’s more necessary to resort to what practitioners in the PR industry early in this century — who understood all of this well — called “controlling the public mind.” The reasons, as observed by Hume in the 18th century, are that “the implicit submission with which men resign their own sentiments and passions to those of their rulers” relies ultimately on control of opinion and attitudes. Why these truisms should suddenly become “a theory” or “philosophy,” others will have to explain; Hume would have laughed.

Some of Foucault’s particular examples (say, about 18th century techniques of punishment) look interesting, and worth investigating as to their accuracy. But the “theory” is merely an extremely complex and inflated restatement of what many others have put very simply, and without any pretense that anything deep is involved. There’s nothing in what Phetland describes that I haven’t been writing about myself for 35 years, also giving plenty of documentation to show that it was always obvious, and indeed hardly departs from truism. What’s interesting about these trivialities is not the principle, which is transparent, but the demonstration of how it works itself out in specific detail to cases that are important to people: like intervention and aggression, exploitation and terror, “free market” scams, and so on. That I don’t find in Foucault, though I find plenty of it by people who seem to be able to write sentences I can understand and who aren’t placed in the intellectual firmament as “theoreticians.”

To make myself clear, Phetland is doing exactly the right thing: presenting what he sees as “important insights and theoretical constructs” that he finds in Foucault. My problem is that the “insights” seem to me familiar and there are no “theoretical constructs,” except in that simple and familiar ideas have been dressed up in complicated and pretentious rhetoric. Phetland asks whether I think this is “wrong, useless, or posturing.” No. The historical parts look interesting sometimes, though they have to be treated with caution and independent verification is even more worth undertaking than it usually is. The parts that restate what has long been obvious and put in much simpler terms are not “useless,” but indeed useful, which is why I and others have always made the very same points. As to “posturing,” a lot of it is that, in my opinion, though I don’t particularly blame Foucault for it: it’s such a deeply rooted part of the corrupt intellectual culture of Paris that he fell into it pretty naturally, though to his credit, he distanced himself from it. As for the “corruption” of this culture particularly since World War II, that’s another topic, which I’ve discussed elsewhere and won’t go into here. Frankly, I don’t see why people in this forum should be much interested, just as I am not. There are more important things to do, in my opinion, than to inquire into the traits of elite intellectuals engaged in various careerist and other pursuits in their narrow and (to me, at least) pretty unininteresting circles. That’s a broad brush, and I stress again that it is unfair to make such comments without proving them: but I’ve been asked, and have answered the only specific point that I find raised. When asked about my general opinion, I can only give it, or if something more specific is posed, address that. I’m not going to undertake an essay on topics that don’t interest me.

Unless someone can answer the simple questions that immediately arise in the mind of any reasonable person when claims about “theory” and “philosophy” are raised, I’ll keep to work that seems to me sensible and enlightening, and to people who are interested in understanding and changing the world.

Johnb made the point that “plain language is not enough when the frame of reference is not available to the listener”; correct and important. But the right reaction is not to resort to obscure and needlessly complex verbiage and posturing about non-existent “theories.” Rather, it is to ask the listener to question the frame of reference that he/she is accepting, and to suggest alternatives that might be considered, all in plain language. I’ve never found that a problem when I speak to people lacking much or sometimes any formal education, though it’s true that it tends to become harder as you move up the educational ladder, so that indoctrination is much deeper, and the self-selection for obedience that is a good part of elite education has taken its toll. Johnb says that outside of circles like this forum, “to the rest of the country, he’s incomprehensible” (“he” being me). That’s absolutely counter to my rather ample experience, with all sorts of audiences. Rather, my experience is what I just described. The incomprehensibility roughly corresponds to the educational level. Take, say, talk radio. I’m on a fair amount, and it’s usually pretty easy to guess from accents, etc., what kind of audience it is. I’ve repeatedly found that when the audience is mostly poor and less educated, I can skip lots of the background and “frame of reference” issues because it’s already obvious and taken for granted by everyone, and can proceed to matters that occupy all of us. With more educated audiences, that’s much harder; it’s necessary to disentangle lots of ideological constructions.

It’s certainly true that lots of people can’t read the books I write. That’s not because the ideas or language are complicated — we have no problems in informal discussion on exactly the same points, and even in the same words. The reasons are different, maybe partly the fault of my writing style, partly the result of the need (which I feel, at least) to present pretty heavy documentation, which makes it tough reading. For these reasons, a number of people have taken pretty much the same material, often the very same words, and put them in pamphlet form and the like. No one seems to have much problem — though again, reviewers in the Times Literary Supplement or professional academic journals don’t have a clue as to what it’s about, quite commonly; sometimes it’s pretty comical.

A final point, something I’ve written about elsewhere (e.g., in a discussion in Z papers, and the last chapter of Year 501). There has been a striking change in the behavior of the intellectual class in recent years. The left intellectuals who 60 years ago would have been teaching in working class schools, writing books like “mathematics for the millions” (which made mathematics intelligible to millions of people), participating in and speaking for popular organizations, etc., are now largely disengaged from such activities, and although quick to tell us that they are far more radical than thou, are not to be found, it seems, when there is such an obvious and growing need and even explicit request for the work they could do out there in the world of people with live problems and concerns. That’s not a small problem. This country, right now, is in a very strange and ominous state. People are frightened, angry, disillusioned, skeptical, confused. That’s an organizer’s dream, as I once heard Mike say. It’s also fertile ground for demagogues and fanatics, who can (and in fact already do) rally substantial popular support with messages that are not unfamiliar from their predecessors in somewhat similar circumstances. We know where it has led in the past; it could again. There’s a huge gap that once was at least partially filled by left intellectuals willing to engage with the general public and their problems. It has ominous implications, in my opinion.

End of Reply, and (to be frank) of my personal interest in the matter, unless the obvious questions are answered.

Book review Economics Government form Politics Science Sociology

Austrian economics: worse than expected — Review of Democracy, the God that failed (Hoppe)

After reading a book defending limitations to free trade/protectionism, it was time for something completely different.

So I looked around after any current, well-regarded (in their circles) Austrian libertarian economist. Because I know many ancap people, I just picked one of those they often mentioned: Hans-Hermann Hoppe. Looking over his Wikipedia profile, you’d probably get the general idea. We combine a Kantian synthetic a priori approach with economics and a natural law theory of morality. As our foundational principle of the moral system, we choose some kind of self-ownership property etc. principle (not the non-aggression one apparently). Then we try to derive everything in morality and economics from these principles per deduction. Sounds crazy? Sure. As mentioned in the previous post, humans really aren’t that consistent, self-interested, knowledgeable, rational etc. for these kinds of deductions to make correct predictions. What does Hoppe say when faced with incorrect predictions? Naturally, he correctly deduces that:

And in accordance with common sense, too, I would regard someone who wanted to “test” these propositions, or who reported “facts” contradicting or deviating from them, as con- fused. A priori theory trumps and corrects experience (and logic overrules observation), and not vice-versa.

So, from that perspective, things are quite simple. We establish (to our satisfaction) some principles of economics and morality, then we just deduce the rest from there. We don’t need to care about any actual sciencing involving data. These merely serve as illustrations of the deductive results (when in agreement) or ??? when not.

Hoppe gives some examples of a priori propositions:

Examples of what I mean by a priori theory are: No material thing can be at two places at once. No two objects can occupy the same place. A straight line is the shortest line between two points. No two straight lines can enclose a space. Whatever object is red all over cannot be green (blue, yellow, etc.) all over. Whatever object is colored is also extended. Whatever object has shape has also size. If A is a part of Band B is a part of C, then A is a part of C. 4 = 3 +1. 6 = 2 (33-30).

None of them concern politics, but we might already see some problems. Some material things are in two places at once, like galaxies, which are distributed objects kept together by gravity (in fact, atoms, molecules etc. are the same way). A straight line is not always the shortest between two points: it depends on the geometry in question. It just so happens that reality is not actually Euclidian per general relativity theory, so this statement is actually empirically false. The same is true for the next. Black holes, which have no extension, might send out light of certain wave lengths (Hawking radiation). I’m not sure.

Hoppe then goes on to mention some social science ones:

More importantly, examples of a priori theory also abound in the social sciences, in particular in the fields of political economy and philosophy: Human action is an actor’s purposeful pursuit of valued ends with scarce means. No one can purposefully not act. Every action is aimed at improving the actor’s subjective well-being above what it otherwise would have been. A larger quantity of a good is valued more highly than a smaller quantity of the same good. Satisfaction earlier is preferred over satisfaction later. Production must precede consumption. What is consumed now cannot be consumed again in the future. If the price of a good is lowered, either the same quantity or more will be bought than otherwise. Prices fixed below market clearing prices will lead to lasting shortages. Without private property in factors of production there can be no factor prices, and without factor prices cost-accounting is impossible. Taxes are an imposition on producers and/ or wealth owners and reduce production and/ or wealth below what it otherwise would have been. Interpersonal conflict is possible only if and insofar as things are scarce. No thing or part of a thing can be owned exclusively by more than one person at a time. Democracy (majority rule) is incompatible with private property (individual ownership and rule). No form of taxation can be uniform (equal), but every taxation involves the creation of two distinct and unequal classes of taxpayers versus tax-receiver consumers. Property and property titles are distinct entities, and an increase of the latter without a corresponding increase of the former does not raise social wealth but leads to a redistribution of existing wealth.

For an empiricist, propositions such as these must be interpreted as either stating nothing empirical at all and being mere speech conventions, or as forever testable and tentative hypotheses. To us, as to common sense, they are neither. In fact, it strikes us as utterly disingenuous to portray these propositions as having no empirical content. Clearly, they state something about “real” things and events! And it seems similarly disingenuous to regard these propositions as hypotheses. Hypothetical propositions, as commonly understood, are statements such as these: Children prefer McDonald’s over Burger King. The worldwide’ ratio of beef to pork spending is 2:1. Germans prefer Spain over Greece as a vacation destination. Longer education in public schools will lead to higher wages. The volume of shopping shortly before Christmas exceeds that of shortly after Christmas. Catholics vote predominantly “Democratic.” Japanese save a quarter of their disposable income. Ger- mans drink more beer than Frenchmen. The United States produces more computers than any other country. Most inhabitants of the U.S. are white and of European descent. Propositions such as these require the collection of historical data to be validated. And they must be continually reevaluated, because the asserted relationships are not necessary (but “contingent”) ones; that is, because there is nothing inherently impossible, inconceivable, or plain wrong in assuming the opposite of the above: e.g., that children prefer Burger King to McDonald’s, or Germans Greece to Spain, etc. This, however, is not the case with the former, theoretical propositions. To negate these propositions and assume, for in- stance, that a smaller quantity of a good might be preferred to a larger one of the same good, that what is being consumed now can possibly be consumed again in the future, or that cost-accounting could be accomplished also without factor prices, strikes one as absurd; and anyone engaged in “empirical research” and “testing” to determine which one of two contradictory propositions such as these does or does not hold appears to be either a fool or a fraud.

Where to begin? Actually many or even most of these are open to question. E.g Human action is an actor’s purposeful pursuit of valued ends with scarce means. Are we defining ‘human action’ this way, or trying to state something true about the world? Well, unless they have odd definition of ‘action’ in mind, then not all human actions are purposeful. There’s an entire category of such non-purposeful actions, like sneezing, hiccups, most coughing, and knee jerks. The remaining statements have similar problems.

Anyway, so Hoppe does not seem to get this. Instead he treats his derivations based on such principles as matter of fact, for morality and policy. Everything that doesn’t agree is then morally dubious or doesn’t understand the facts, or is deluded that empirical data can overrule logic. Actually, Hoppe doesn’t actually formally deduce anything (i.e. with symbols or rigid prose), presumably because he lacks actual knowledge of logic, so why should we trust his informal, hand-waving arguments?

The rest of the book is essentially his speculations and moral condemnations of non-anarchists. The culty nature of things is revealed in the extreme reliance on a select few authors. Searching the book for Rothbard yields 170 mentions and von Mises 144 in a book with 330 pages (I removed the use of the latter in cases where it referred to the publisher).

This book is not recommended unless you have a particular interest in this breed of pseudoscience (praxeology). Among pseudosciences, it is surprisingly rarely mentioned, especially considering how anti-left wing it is (for exceptions, see here and here).

Differential psychology/psychometrics Metascience Science

On scientific consensus

In reply to: Scott Alexander’s Learning To Love Scientific Consensus. Actually, I have planned (in my mind) a somewhat longer post on my take on the ‘correct contrarian cluster’, or how to make up your mind of what to believe on controversial topics. But I certainly don’t have time to write that now, so instead you get this post.

Regarding historical examples, this list collected by The Alternative Hypothesis is much better than the various top 10 lists you can find. Maybe somewhat with more time and knowledge of science history than me should go over it.

In so far as their examples hold up, they make a smarter argument. Instead of doing only “consensus was X, and X was wrong” arguments, which can always be attacked on the grounds that “X wasn’t really wrong”, they do arguments of “consensus was X, then consensus was Y, and now it’s X or Z”. For this argument, one does not need to agree on the truth of the matter, only the expert consensus status. If consensus changed, then no matter what the truth really is, consensus was not always in agreement with it.

A more sophisticated version of the consensus-is-right position is to argue that the consensus may not be the truth, but it follows the evidence base as a whole (slowly and wiggly). Sometimes the evidence base may point towards a falsehood for extended periods of time. Not necessarily due to any particular political or religious bias, but just due to the difficulty of some scientific questions, lack of good quality relevant data, stochastic processes among humans etc. This view is harder to attack, but also harder to positively argue for because it is really hard to show track of what the total evidence base pointed towards in, say, 1955 re., say, plate tectonics theory. Finding out requires doing a lot of reading on old material and painstakingly avoiding anachronisms. This is far beyond what most people are willing and capable of doing, and generally only a few science historians take this route (bless them!).

It is of course often hard to know what the expert consensus is. Aside from controversial topics (evolution, global warming, IQ, GMO etc., see below), scientists don’t routinely conduct large surveys of expert beliefs (they should!). So instead people rely on their general impressions of what experts believe. If they don’t read the scientific literature, what other source to rely on than the media? This gives rise a likely* media bias effect as the media tends to present experts that believe things media people believe in, and not necessarily what the experts generally believe in. So, lots of space to, say, “10,000 hours of training” researchers and lots of space to “the next early intervention will fix inequality, promise!” researchers. And then people get the impression that the consensus is something else than it really is. I wish the media would adopt public high score tables for ‘science pundits’ and give preferential treatment (attention) to those who tend to make correct predictions (an idea proposed by John Pressman here). The media and scientists should team up to make pre-registered experiments and predictions in the hostile collaboration style.

For the record, I don’t think of myself as a revolutionary scientist (or a ‘universal genius’ as a journalist recently made up). To put it in horse terms, my view is that essentially I’m betting on an winning horse early, and that this horse has a bad reputation, but that in 10 years or so, there will be widespread open acknowledgement that this is a good horse nonetheless (yes, I am talking about race and IQ). As the surveys show, experts generally do agree with me on this topic, altho I’m surely more towards the genetic side than the median. (But it does depend on who counts as an expert. Presumably most experts surveyed on this question have not studied it in depth.) Scott does not like my presentation style of these ideas because it makes it harder for nice people like Steven Pinker to work on the public image of the ideas. I understand accept this argument, but I would like to point out that when people with my views don’t speak candidly about them, the media bias effect gets stronger. Personally, I think scientific should discuss their ideas openly and frankly. In general, I think the long-term consequences of suppression of unpopular findings is a net native outcome. I think it also applies in this case, i.e. the harms of ignoring scientific findings about what works with regards to social inequality is likely to have much larger negative consequences than the alternative. Frankly, I don’t think Nazi-style totalitarian governments that target specific races/ethnicities/religions have any large chance of coming back in Western countries (as long as these are run by Europeans).

Since history repeats itself, here’s Jensen in 1969 (How much can we boost IQ and scholastic achievement?):

The question of race differences in intelligence comes up not when we deal with individuals as individuals, but when certain identifiable groups or subcultures within the society are brought into comparison with one another as groups or populations. It is only when the groups are disproportionately represented in what are commonly perceived as the most desirable and the least desirable social and occupational roles in a society that the question arises concerning average differences among groups. Since much of the current thinking behind civil rights, fair employment, and equality of educational opportunity appeals to the fact that there is a disproportionate representation of different racial groups in the various levels of the educational, occupational, and socioeconomic hierarchy, we are forced to examine all the possible reasons for this inequality among racial groups in the attainments and rewards generally valued by all groups within our society.

To what extent can such inequalities be attributed to unfairness in society’s multiple selection processes? (‘Unfair’ meaning that selection is influenced by intrinsically irrelevant criteria, such as skin color, racial or national origin, etc.) And to what extent are these inequalities attributable to really relevant selection criteria which apply equally to all individuals but at the same time select disproportionately between some racial groups because there exist, in fact, real average differences among the groups – differences in the population distributions of those characteristics which are indisputably relevant to educational and occupational performance? This is certainly one of the most important questions confronting our nation today. The answer, which can be found only through unfettered research, has enormous consequences for the welfare of all, particularly of minorities whose plight is now in the foreground of public attention. A preordained, doctrinaire stance with regard to this issue hinders the achievement of a scientific understanding of the problem. To rule out of court, so to speak, any reasonable hypotheses on purely ideological grounds is to argue that static ignorance is preferable to increasing our knowledge of reality. I strongly disagree with those who believe in searching for the truth by scientific means only under certain circumstances and eschew this course in favor of ignorance under other circumstances, or who believe that the results of inquiry on some subjects cannot be entrusted to the public but should be kept the guarded possession of a scientific elite. Such attitudes, in my opinion, represent a danger to free inquiry and, consequently, in the long run, work to the disadvantage of society’s general welfare. ‘No holds barred’ is the formula for scientific inquiry. One does not decree beforehand which phenomena cannot be studied or which questions cannot be answered.

And in 1973 (Educability and group differences):

The scientific task is to get at the facts and properly verifiable explanations. Recommendations for dealing with specific problems in educational practice, and in social action in general, are mainly a social problem. But would anyone argue that educational and social policies should ignore the actual nature of the problems with which they must deal? The real danger is ignorance, and not that further research will result eventually in one or another hypothesis becoming generally accepted by the scientific community. In the sphere of social action, any theory, true or false, can be twisted to serve bad intentions. But good intentions are impotent unless based on reality. Posing and testing alternative hypotheses are necessary stepping stones toward a knowledge of reality in the scientific sense. To liken this process to screaming ‘FIRE . . . I think’ in a crowded theatre (an analogy drawn by Scarr-Salapatek, 1971b, p. 1228) is thus quite mistaken, it seems to me. A much more subtle and complete expression of a similar attitude came to me by way of the comments of one of the several anonymous reviewers whose judgments on the draft of this book were solicited by the publishers. It summarizes so well the feelings of a good number of scientists that it deserves to be quoted at length.

* I’d like to see some more quantitative evidence as ‘general impressions’ are a low form of evidence. There was that study (n=40) of economists (Kardashian’s index) showing that those who received the most media attention has lower research output/citations, which is sorta in the right direction. Another example of this is famed scientific Neil Degrasse Tyson, who seems to have little research output. I did not check to see if there have been more of these studies, but they should be ‘fairly easy’** to conduct using Google Scholar. Maybe we should survey journalists on science topics, see which beliefs they really have, and consequently, which topics we should be attentive to bias about. See also the 2015 survey of AAAS scientists on various issues as compared with the general population.

** Nothing in science is ever as easy or fast to do as it sounds (planning fallacy). I know because I have 100 unfinished projects in my projects folder. Most of these were started on the basis of “Oh, I’ll just do this quick, easy and worthwhile study of X”. Often I do most of the data collection and analysis, but never submit it for publication. I don’t seem to learn, and recently started another 5 or so projects in a similar vein… Oh well!