All you ever wanted to know about intelligence (but were too bright to ask) Part 1

 

There is a recently published Primer in Current Biology on Intelligence written  by Ian Deary, which is hidden behind a paywall, lest it be read by anybody other than a fully paid up current biologist. Strange world, the one in which scholars write things for nothing in order that other citizens should have to pay for the privilege of reading them. Such payments made some sense when publishing required printing, but rather less now, when the transmission of bytes is close to free.

Primer. Intelligence. Ian Deary. Current Biology Vol 23 No 16 R673  2013.

I will be using the article as a framework for a series of posts, taking one theme at a time, picking out some highlights and adding some extra bits. My target audience is bright people who don’t believe in intelligence. For a variety of reasons, they think it unseemly to acknowledge that they can think faster than others. This is not altogether stupid, because in many genocides it is the intelligent who get slaughtered. Excessive modesty may have some survival value.

“Some people are cleverer than others. It is a prominent and consistent way in which people differ from each other; the measurements we make of people’s cleverness produce scores that are correlated with important life outcomes; it is interesting to discover the mechanisms that produce these individual differences; and understanding these mechanisms might help to ameliorate those states in which cognitive function is low or declining.”

Deary distinguishes between cognitive psychologists who are trying to find out how the mind works and differential psychologists who mostly focus on how people differ in the workings of their minds. The latter try to show precisely the ways in which people differ, and try to discover the causes of those differences.  The two tribes don’t communicate very well. Cognitive psychologists, in my view, are missing a trick. A very brief vocabulary and/or digit span test or, with more time, a group intelligence test, would give them important data, and help place their results in the context of human differences.

Deary identifies four major sources of scepticism about intelligence:

1 The concept appears to be too general. People argue that they are better at some skills than others, and assume different modules are involved, such that we are all good at some specific mental skill.

2 Historical events in intelligence research which are discreditable. In the UK, the 11+ missed out people who later showed demonstrable talent; cases of probable fraud in reporting results; over use and over-interpretation of intelligence tests; controversies about intelligence differences between ethnic groups; or claims that “ordinary” intelligence has now been replaced by tests of “multiple” intelligence.

3 “It is possible that clever people develop a kind of cognitive noblesse oblige; they kind of know they have won the lottery on a valuable trait, but they think it is bad form to acknowledge it.”

4 They probably haven’t read good quality research on the topic.

I find that most of the hostility about intelligence comes from bright people, who keep up with the broad sweep of newspaper reports and popular books, but have not looked at good quality research. Despite this lack they are surprisingly vehement when they ridicule IQ.

So, it would appear that intelligence is most disparaged by the intelligent. “Define intelligence” they demand, with a knowing smile. Personally, I have found that the only answer is to show them a photo of George W. Bush. (But I am getting ahead of myself). There are three types of answer: a quip, an explanation, and a formula.

The Quip: “Intelligence is what you need when you don’t know what to do”. Carl Bereiter coined this elegant phrase. It captures the ultimate purpose of intelligence, which is to help you cope with the unknown. The best intelligence test is the puzzle to which no one knows the answer. For example, is there a detectable particle which gives objects mass?

The Explanation: “Intelligence is a very general mental capability that, among other things, involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly and learn from experience. It is not merely book learning, a narrow academic skill, or test-taking smarts. Rather, it reflects a broader and deeper capability for comprehending our surroundings — ‘catching on,’ ‘making sense’ of things, or ‘figuring out’ what to do.” Linda Gottfredson and 52 leading psychometricians agree with this explanation. http://www.udel.edu/educ/gottfredson/reprints/1997mainstream.pdf

The formula: g+group+specific skill+error, where g accounts for about 50% of the variance. (I have written this in English, but it should be displayed in eigenvalues).

 

So, let us look behind the formula (in English) “In 1904 Spearman found that people who perform well on one type of cognitive test tend to perform well on others. That is, if cognitive test scores are ordered so that better performance equals a higher score, the correlations between them are all positive. There is shared variation among all types of cognitive performance. Spearman called this shared/common variance g: an abbreviation for general intelligence. In the 100+ years since then, every study that has applied a diverse battery of cognitive tests to a decent-sized group of people with a mix of ability levels has re-discovered the same thing: there is some cognitive variance shared by all cognitive tests. Typically, if one applies principal components
analysis, just under half of the total test score variance is accounted for by the first unrotated principal component.”

This finding of 50% of the variance in ability being due to g is matched by another finding:  IQ-type test scores are highly reliable, and highly stable. For example, when the same intelligence test is taken at age 11 years and repeated at almost 80, about 50% of the variance is stable.

So, half of intelligence is due to a common factor, and half of the variance is stable throughout life.

Unfortunately, by this stage in the argument, we will have lost probably half of the intelligent readers. They are still smiling at the idea of anyone defining their intelligence. Can you please send them this link?

How illiterate is the OECD?

 

The OECD is has conducted a study of adult skills in some of the wealthy countries, of the world and the UK papers are aghast at the results. The UK has done badly, with many heavily educated British youths knowing less than their more lightly educated elders. Cue for outrage, hurt feelings, and political posturing. If you look at the actual publication, you will find that the key OECD results have been written up in a corporate format: suitably uplifting photos of students staring intently at their homework lurk in the background as the Secretary General makes his opening remarks:

“If there is one central message emerging from this new survey, it is that what people know and what they do with what they know has a major impact on their life chances. The median hourly wage of workers who can make complex inferences
and evaluate subtle truth claims or arguments in written texts is more than 60% higher than for workers who can, at best, read relatively short texts to locate a single piece of information. Those with low literacy skills are also more than twice as likely
to be unemployed.”

http://skills.oecd.org/SkillsOutlook_2013_KeyFindings.pdf

Well, blow me down. Some people are brighter than others. This is the finding which has emerged from intelligence research over a century. Read Linda Gottfredson  “Why g Matters: The Complexity of Everyday Life” (1997) if only just page 117 for an explanation of the relationship between literacy, learning and intelligence.

http://www.udel.edu/educ/gottfredson/reprints/1997whygmatters.pdf

Then, for an explanation of the relationship between intelligence at 11 and scholastic attainment at 16 read Ian Deary:

http://emilkirkegaard.dk/en/wp-content/uploads/Intelligence-and-educational-achievement.pdf

Finally, for an explanation of the relationship between intelligence and the time taken to learn a skill to an adequate standard look at this summary, from Gottfredson: “Men of low ability (10th to 30th percentiles) took about 12 to 24 months to catch up with men of higher ability (above the 30th percentile) who had only 3 months’ experience on the job.” (Schmidt and Hunter (1998) The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings. Psychological Bulletin, Vol 124(2), Sep 1998, 262-274; Vineberg & Taylor, 1972,Performance in four army jobs by men at different aptitude (AFQT) levels p. 55-57). For this reason the US Army has always been allowed to use “ability” (intelligence) tests to selects its recruits and is allowed to reject low ability applicants simply because it will take too long to teach them necessary skills. The military are sitting on a treasure trove of data on how long it takes to train people at different levels of intelligence, and how much the recruits can think for themselves beyond their training, at various levels of intelligence. They go for the brightest recruits every time. The higher the rate of unemployment the better the class of recruit who present themselves to try to get into a well paid, if sometimes dangerous, job. The Army do not care what genetic group recruits come from. In that sense the military are race integrated because they are intelligence integrated. If you can make the grade you get the job. The US armed forces don’t talk too much about intelligence because they fear they might be prevented from using their best weapon: using IQ tests to get good quality people. They have government permission to use intelligence tests, and to reject those who are not intelligent enough, and they don’t want to lose that privilege, like many other public service employers have done. They keep their procedures very complicated and their results obscure.

Anyway, what else has been left out of the report, apart from human intelligence? The OECD view is that the problems arise from people not having the “skills”. Give them the skills and all will be well. That is true, but only given lots of time, patience and resources. As Gottfredson has pointed out, training skills in people of low ability is a very long drawn out process, and does not generalise easily to other skills. Her work on the Wonderlic personnel selection test (designed by researchers who did not believe in general intelligence) paradoxically is one of the best proofs of general intelligence. Training someone of low ability to do a particular task does not generalise very much at all to other tasks. You are better off getting someone who learns everything at a faster rate.

On the OECD results the UK is placed slightly below average in literacy. National results do not mean very much unless you analyse immigrants separately. PISA does this, and the scores show immigrants are lower than locals even in the second generation, although the second is usually better than the first generation. When the rate of immigration is high, national “skill” levels drop (except in countries with low intelligence levels who import brighter foreigners to run things).

The much repeated finding that UK youngsters are no better than their elders turns out to be a bit misleading. Both young and old in the UK are within measurement error of each other. It is simply that British youngsters have not shown the gains shown by Korean youths. Not surprising. The British 1870 Education Act ensured access to education long ago. Korea achieved it recently.

I turned to the full report. This shows that the samples in each country were initially assessed regardless of nationality. This includes immigrants. Later in the report they are studied separately, but not separating recent arrivals, nor identifying the immigrant groups in question despite their difference in ability, above or usually below the locals. As far as I can see, they regard immigrants as a fungible commodity. There are later analyses somewhere in which personal and parental education are mentioned, but finding the real data in this publication is difficult and time-consuming.

The following are excerpts from the summary which may surprise for their obtuseness:

“Most of the variation in skills proficiency is observed within, not between, countries.”  Bell curve? Mean differences always smaller than individual differences?

“In all but one participating country, at least one in ten adults is proficient only
at or below Level 1 in literacy or numeracy. In other words, significant numbers of adults do not possess the most basic information-processing skills considered necessary to succeed in today’s world.” Bell curve? Every distribution has a lower range?

The authors seem incapable of understanding the normal distribution of human abilities. I decided to skip their carefully crafted presentation, and have a look at the methods section. Here are some scattered findings on the way: the Russian sample omits Moscow; some countries have over-sampled minorities; sample sizes range from 4,500 to 27,000 so the authors are right to say we need to pay close attention to the standard errors of the estimates. In fact, I found out much later in the Readers Companion that all countries were at the 4 to 6 thousand sample size, which is OK but not great, and only Canada managed 27,000. Deary’s work on IQ and scholastic attainment included 70,000 children and that was for just one academic paper. Basically, these researchers do not appear to have used entirely proper epidemiological samples, though they certainly used national registers. It is hard to find a single table which compares sample characteristics with population characteristics, let alone a chi-square to identify discrepancies.

The correlation between proficiency in literacy and numeracy at the individual level for the entire sample is 0.87 (see Figure 2.9). This strongly suggests a common factor, but this is not discussed. Why not show a correlation of the main cognitive variables and do a principal components analysis? Numeracy, they say, has a stronger relationship to wages than does literacy. Yes, it is a better measure of intelligence because it is more demanding. These authors tend to list their results rather than try to understand them, and all the important matters are strung out in a series of addenda.

There are no mentions of “intelligence” in the text, but the word can be found in two of the references. Presumably the censor missed those, or simply had to concede that some researchers use the term. No mention of “genetics”. 76 uses of “ability”. 68 uses of “cognitive”. Note these code words for your corporate survival. You may have ability, you may even have cognitive ability, but woe betide you if you have intelligence.

“Across the countries involved in the study, between 4.9% and 27.7% of adults are proficient at the lowest levels in literacy and 8.1% to 31.7% are proficient at the lowest levels in numeracy. At these levels, adults can regularly complete tasks that involve very few steps, limited amounts of information presented in familiar contexts with little distracting information present, and that involve basic cognitive operations, such as locating a single piece of information in a text or performing basic arithmetic operations, but have difficulty with more complex tasks.”

That, in a nutshell, is the problem of the normal distribution of skills. You can shift the distribution downwards or upwards. The shape will change somewhat depending on what sort of factors are keeping people back (disease, malnutrition, social restrictions). You cannot get rid of variation. However you define the levels, and wherever you set the cut-offs, you will find a distribution of abilities. How you deal with such disparities is a social issue. Pretending you can educate people out of showing individual differences is not possible, not if you are honest about displaying the result. So, if you do not want “any child left behind” you will have to prevent all children from working at their own pace. The slowest pace will have to be imposed upon all. Finally, although the authors do not intend it, the description they give in the above paragraph is a good explanation of what it means that one person is more intelligent than another.

More gems: “Foreign-language immigrants with low levels of education tend to have low skills proficiency. Immigrants with a foreign-language background have significantly lower proficiency in literacy, numeracy and problem solving in technology-rich environments than native-born adults, whose first or second language learned as a child was the same as that of the assessment, even after other factors are taken into account. In some countries, the time elapsed since arrival in the receiving country appears to make little difference to the proficiency of immigrants, suggesting either that the incentives to learn the language of the receiving country are not strong or that policies that encourage learning the language of the receiving country are of limited effectiveness.”  Note that the differences in skills are thought to be due to language, and that lack of ability is a matter of incentives and policies and, most of all, that any intellectual differences are due to language alone.  Language may be part of the picture, but the authors do not consider that ability levels may vary between immigrants and locals regardless of language.

Dissatisfied, I turned as a last resort to the Reader’s Companion. http://www.oecd.org/site/piaac/Skills%20(vol%202)-Reader%20companion--full%20v6%20eBook%20(Press%20quality)-27%2009%200213.pdf 

“Read this one first”, I thought, but it was a disappointment. Finally, I realised I needed to read the Technical Report. At this stage I gave up, fearing, dear reader, that you would have lost interest long ago. For all I know, there are secret messages in the repetitive slabs of tabulated data. I could not find a humble table of correlation coefficient between the main measures, let alone a factor analysis. There are some regression lines for country data, which are most welcome. Otherwise, it is death by a thousand tabulations.

Frankly, this is less well described than the average social science paper, and that is saying something. The whole thing is back to front: policy implications and conclusions are proclaimed first, then more conclusions are trumpeted, then some findings are picked out, and then finally, way in the background, they reveal some of the things you need to know to figure out if they have got it right, or even vaguely right. Perhaps our standard sequence in academic papers makes sense after all: explain the problem, explain the subjects and the methods, describe the results, discuss them including explaining why they may be wrong. And avoid having anything to do with the production of corporate brochures.

This lump of a report is not all bad. One can compare one country with another, which is the sort of thing governments like doing. I really believe that somewhere in the mass of the extended report there may be good things. On a broader matter, I am in favour of people measuring skills. That makes sense, because employers need a skilled workforce, and economies prosper if skilled people are moved to where they can contribute most. The report contains descriptions of skill levels, and that is a good thing. Skills make sense, and if you say that someone has the skill to drive a car, but not the skill to service a car, (another Gottfredson quip) that immediately makes sense to most people. We can distinguish between a driver and a mechanic. We can also understand that someone who can only handle one concept at a time should not be given the task of integrating disparate conceptual inputs. That cuts out being in the control room of most industrial processes. In does not preclude employment as a university teacher, where to manage one concept may lead to a successful career.

The problem with the “skills only” approach is that it strongly implies that is it only a matter of getting the right teacher, and the right attitude, and you can master all tasks.  If only the OECD could help me with structural equation modelling! Even a small grant would make all the difference.

If you want to say anything useful at all about why people don’t have the required skills you have to have a measure of their ability on the one hand, and a measure of the effectiveness of teaching on the other. (In that way you can judge to what extent and for which pupils teaching makes a difference).  Absent either of those measures, you have an interpretive problem. Absent both, you have a muddle.

80 years on: classical and operant conditioning: the genetics

No sooner do I admit that I find it hard to relinquish any idea I have put on a slide and lectured upon more than three times, a message comes through about an ancient debate about the differences between classical and operant conditioning.

Naturally, I always had a slide which compared the visceral nervous system, high emotional tone, basic appetitive focus of classical Pavlovian conditioning with the lower emotional tone, higher cognitive focus of operant Skinnerian conditioning. Classical effects accounted for trauma, operant effects for ordinary learning. So, I had attempted a very crude differentiation, but was aware that deeper work was going on,  calling into question this particular divide, and looking at what was happening from an expectations perspective, grounded in the thought that the animals were trying to work out the contingencies in both and all cases.

Now Björn Brembs, Professor of Neurogenetics at Universität Regensburg says that, having stuck with this issue whilst most other had abandoned it, he has come up with a unifying explanation, backed up by genetics. He says:

“Operant and classical processes can be genetically separated, using the right behavioral experiments. What made these processes different was not how the animal was learning (i.e., operantly or classically), but what it learned (i.e., about external stimuli, e.g. Pavlov’s bell, or about their own behavior, e.g. pressing the lever in a Skinner box). Thus, in order to avoid confusion between the procedures (operant vs. classical) and the mechanisms, we had to come up with descriptive terms for the learning mechanisms. We arrived at ‘world-learning’ for the mechanism that detects and processes relationships in the external world and at ‘self-learning’ for the mechanism that detects and processes the consequences of an animal’s own behavior.”

Part of the resolution of the problem lay in realising that the response key in the Skinner box was acting as a Pavlovian conditioned stimulus for food, thus thoroughly confusing the picture. I am sure I gave the learning theory lecture at least fifteen times, and never thought of that, though I often had difficulty working through how the concepts mapped onto the broad range of human and animal learning.

I cannot give you more details, because the paper will be presented at the Winter Conference on Animal Learning and Behavior next February 2014. More details here. http://bjoern.brembs.net/2013/10/operant-and-classical-conditioning/ However, when the paper comes out, I will be the experimental animal. Will I embrace the new finding, or hold fast to my old slide (which I cannot find at the moment).

I have written this note for two main reasons.

1 I often wonder if anyone follows up on old psychology dilemmas. We should be a progressive discipline. We won’t advance as a science if we just abandon difficult issues, so this is a very welcome finding, and very much worth a look.

2 On a somewhat disconsolate note, Björn Brembs accepts that he will be speaking to a few dozen people at most, those being the few who are still interested in the issue and have survived long enough to hear about a potential solution. Perhaps you can drum up some people for the conference.

Now, sit back and relax while I place you in the experimental box.

Loci and genetic groups: The Keyhole Problem

 

It may be to belabour a point, but some errors take on a life of their own, and are resistant to disproof. Presumably they meet some need, personal or social. We all have favourite arguments and treasured ideas. We tend to abandon such positions reluctantly. It takes an open mind to go with the evidence, particularly as it sways to and fro. The scientific ideal of enthusiastic open-mindedness to new ideas and then the dispassionate evaluation of those notions is hard for all of us to achieve. In my case I am reluctant to abandon any position which I have depicted in a complicated slide and lectured on more than three times. Call it the Powerpoint Theory of Perverse Persistence.

At present people still argue that there cannot be real genetic groups similar to traditional races, because there is more variance within races (85%) than there is between races (15%). This is an argument put forward by Lewontin in 1972 so the fact that is is being discussed shows it has stayed in popular consciousness for 41 years. I should like to believe that some of my arguments might remain interesting for 41 weeks but Lewontin’s is a meme which has survived with a vengeance.

Let us try to understand this statement by considering the traditional racial classifications of Black Pigmies and White European. If the statement about variation is to be taken seriously, it means that there is more variability within Black Pigmies then there is between Black Pigmies and White Europeans. This is an odd assertion. Both groups have things in common which make it easy to distinguish one from another. Skin colour, for one thing. This is why we refer to “white” Europeans and “black” Pigmies. So, is there more variation in skin pigmentation within whites than between Europeans and Pigmies? No. This simple point was raised by G. Cochran, and should have been enough to dispose of the matter. However, it is possible that followers of Lewontin might argue that skin is a special case, and they are referring to other human characteristics. This is a significant concession. Presumably it means that skin must be considered part of the 15% which varies between groups more than it varies within groups. Perhaps the 15% contains most of the socially significant traits such as personality and intelligence.

However, Cochran goes on to wonder whether Lewontin’s argument might apply to height, which is brought about by very many small genetic effects, rather than just a few genes as in the case of pigmentation. Not so. Pigmies are all short, and neighbouring Bantus are as tall as Europeans.  In a mixed population, part Bantu part Pigmy, height is determined by the proportion of Bantu ancestry. The Lewontin variance approach is found wanting.

In some exasperation Cochran writes: “So Lewontin’s argument does not work.  You can’t predict group differences in trait values from the distribution of genetic variation – except in the limiting case where all of the variation is within-group, which means that the two populations are genetically identical.  You know you can’t apply it to other traits, whether they are influenced by a few genes or by many.  It’s not essential to know _why_ it doesn’t work – the mere fact that its predictions don’t come true is reason enough to discard it.”

So, why don’t people discard the “more variation within races” argument? Why don’t all commentators discard it? Cochran continues:

“We do know why, though. Selection generates correlated genetic differences. Selection for increased height causes changes in the frequency of many alleles, in principle at all loci that influence height, although that is still a small subset of the genome.   What matter is the difference in that subset: the overall distribution of genetic variation tells you nothing.  Moreover, imagine that in the ancestral population, there were two alleles for each of those loci – a short allele with a frequency of 0.7 and a tall allele with a frequency of 0.3. Suppose that after selection for height, the frequency of each short allele was 0.3 and the frequency of the tall allele was 0.7.   This could significantly increase height. In that subset of the genome, about 85% of the variation between those two population is within-group  while 15% is between-group.”

http://westhunt.wordpress.com/2012/01/26/lewontins-argument/

In the words of the song, not the technical terminology of geneticists, it is a case of “You got the Right Key, but the wrong Key Hole”. By a process of selection the frequency distribution of Long Keys has changed, but the overall number of keys and locks has not changed. The change has come about because there are now more functional links between Long Keys and Key Holes, resulting in generations getting taller and taller.

Evidently, since the 85-15 variance argument persists, this explanation needs to be given several times in different forms. Imagine you are in charge of a jail, and hold the key to each cell. You are told that the inmates are of different races, or different religions, or have different view on the relative contributions of nature and nurture, or just vary considerably in height. Whatever the reason, they tend to assault each other during exercise periods. Your task is to let the inmates get exercise without rioting. Using one selection of keys you release only one set of prisoners. Perhaps it is the short prisoners. They exercise, in their short way. Once they are back in their cells you release the tall ones, and they exercise in their lofty way. Neither the number of keys nor the number of locks has altered, but anyone closely observing the exercise yard would notice a significant difference in the two sets of prisoners. It is the subset of activated key/lock combinations which has caused the changes in the prison population.

Can you please find someone who still believes the Lewontin argument, and try my version out on them?  I may need to find yet further ways to explain it.

Group differences and within group variation

Consider the following problem. You are searching the Atlantic Ocean for a nuclear submarine which is about to launch 16 ballistic missiles, capable of destroying 32 cities. There is nothing to be seen on the surface of the ocean other than waves. However, the fast moving submarine creates a tiny pressure wave which can be detected by satellite sensing. It shows locations in which you are very likely to find the submarine. Would you turn down this information because the waves caused by the submarine are an infinitesimal fragment of the total number of waves on the ocean?

Now consider the human genome. You are searching for your close cousins, by which you mean all those who are your first and second cousins. You assume that such persons will all have the usual apportionment of legs and arms and digestive processes and inner organs, but you are mostly interested in those aspects of character which may make them distinctive as individuals, and somewhat like you: personality, attitudes, intellect. Only some parts of the genome will be of interest to you. A few hundred genetic variants, or a few thousand at most, in particular combinations (the correlation of correlations) suffice for you to track down your cousins. You can confirm their identity through the usual documentary channels of birth certificates and surnames. By this this genetic analysis you may be able to recognise even those relatives who have lost their official papers. Should you turn this down because only a small part of the genetic code was required to confirm their identity? I think most people would say that if the technique works accurately enough then those small signals are worth studying for their discriminative value.

Now consider a less happy scenario. You come upon a grizzly murder scene whic contains some scraps of human flesh. There is very little other material which leads you to guess the identity of the victim. You extract DNA from the mortal remains, and find different DNA on the paper in which the flesh was wrapped. Would you like to know as much as possible about the victim and the putative murderer? Would it help to track down the missing person, and the last person who touched them, if you knew the races of the persons concerned?

The first scenario is entirely hypothetical, or at least, I assume it is. The second is where we are currently on population genetics. The third is where we are with genetic forensics. In the latter case finding the general geographic origin of the missing person or perpetrator is relatively easy. More detailed work allows guesses about membership of more precise geographic subgroupings, but with a higher error term. Population genetics allows the reconstruction of a genetic tree and can identify who your first and second cousins are.

So, that’s it in practice. We are able to use principal component analysis, factor analysis, cluster analysis and discriminant function analysis on genetic data. We can classify people by their relatedness, and determine group membership from fragments of DNA. Now, as the French say, we have to see if it works in theory.

Loci number and group difference

A sharp eyed reader, Stuart Ritchie, who on forensic examination will be revealed as a member of the Deary gang, has drawn my attention to a paper entitled: “Genetic Similarities Within and Between Human Populations” by D. J. Witherspoon, S. Wooding, A. R. Rogers,E. E. Marchani, W. S. Watkins, M. A. Batzer and L. B. Jorde
(2007) Genetics Society of America. DOI: 10.1534/genetics.106.067355  http://www.genetics.org/content/176/1/351.full.pdf+html

This paper shows that the debate about “variation within races is bigger than variation between races” depends largely on the number of loci being analysed, and the assumptions being made about the significance of the revealed differences. They concentrate “on the frequency, v, with which a pair of random individuals from two different populations is genetically more similar than a pair of individuals randomly selected from any single population. We compare v to the error rates of several classification methods, using data sets that vary in number of loci, average allele frequency, populations sampled, and polymorphism ascertainment strategy. We demonstrate that classification methods achieve higher discriminatory power
than v because of their use of aggregate properties of populations. The number of loci analyzed is the most critical variable: with 100 polymorphisms, accurate classification is possible, but v remains sizable, even when using populations as distinct as sub-Saharan Africans and Europeans. Phenotypes controlled by
a dozen or fewer loci can therefore be expected to show substantial overlap between human populations. This provides empirical justification for caution when using population labels in biomedical settings, with broad implications for personalized medicine, pharmacogenetics, and the meaning of race.

I have abstracted the key distribution shown above. It seems to me a balanced presentation of the issue, and the heated debate may revolve round “it depends what you mean about race” as well as “it depends how good your data are when carrying out a discriminant function analysis”.

The ethics of taboo genetics

Nature, which calls itself the International weekly journal of science, and is known to all researchers just as Nature (pause, deep respect) has published a news feature  by Erika Check Hayden entitled “Ethics: Taboo genetics”. http://www.nature.com/news/ethics-taboo-genetics-1.13858 The strapline is: “Probing the biological basis of certain traits ignites controversy. But some scientists choose to cross the red line anyway.”

It begins with Stephen Hsu’s work on the genetics of very high ability, and reports “scientific qualms over the value of his work”. Checking this reference leads to a Nature news article by Ed Yong which reveals that a few interviewed geneticists think that Hsu and Robert Plomin will fail because their sample size is too small and intelligence is too complex. They may be right, but frankly neither Hsu or Plomin nor the other geneticists know if the analysis of this unique sample will come up with anything until the DNA has been analysed to death. Not only is this the biggest sample of high intelligence people ever sequenced, but sequencing power is increasing and costs are falling. So the scientific qualms are that the enterprise might not work. That is true, and also true of much of science. In my view it would be premature to give up just as we are beginning to learn how difficult it is to obtain replicable results.

The Hayden article continues: “At the root of this caution is the widespread but antiquated idea that genetics is destiny — that someone's genes can accurately predict complex behaviours and traits regardless of their environment. The public and many scientists have continued to misinterpret modern findings on the basis of this — fearing that the work will lead to a new age of eugenics, pre-emptive imprisonment and discrimination against already marginalized groups.”

She continues: “But trying to forestall such poor choices by drawing red lines around certain areas subverts science, says Christopher Chabris of Union College in Schenectady, New York. Funding for research in some areas dries up and researchers are dissuaded from entering promising fields. “Any time there's a taboo or norm against studying something for anything other than good scientific reasons, it distorts researchers' priorities and can harm the understanding of related topics,” he says. “It's not just that we've ripped this page out of the book of science; it causes mistakes and distortions to appear in other areas as well.”

Nature then goes on to look at “four controversial areas of behavioural genetics to find out why each field has been a flashpoint, and whether there are sound scientific reasons for pursuing such studies.” It may be just a matter of words, but this seems to put the onus on the scientists who want to carry out the studies. Usually scientists in free societies pursue the studies that interest them, and it is those who would ban those studies who have to justify themselves.

Intelligence is the first controversial area to be looked at, and is rated High Taboo. The objections given are not scientific but social and historical: feared selection for intelligent babies by totalitarian governments; and forced sterilization of people deemed mentally inferior. A more “scientific” concern is that intelligence is a “slippery” concept which does not measure wholly innate ability, though it is conceded that 50% of variability in intelligence seems to be inherited. In my view intelligence researchers would not say that intelligence was slippery, but that it measures mental abilities with significant reliability and validity, yet always contains an error term. Of course, an ability measure does not of itself provide any evidence about the heritability of the trait: those estimates come from heritability studies using various measures of relatedness.

Next to be looked at is Race which is rated Very High Taboo and the most heavily policed. “This is due mostly to suspicion about what motivates the study. There is broad consensus across the social and biological sciences that groups of humans typically referred to as races are not very different from one another. Two individuals from the same race could have more genetic variation between them than individuals from different races. Race is therefore not a particularly useful category to use when searching for the genetics of biological traits or even medical vulnerabilities, despite widespread assumptions.” Hayden then discusses Bruce Lahn, who was bullied into laying off further investigating his micro-cephalic linked genes result. I can remember being at the Amsterdam meeting where Danielle Posthuma found that on larger sample the link disappeared. Those who most avidly prohibit research on racial genetics are the most convinced that research will come up with results! Some times it may, some times not. At this stage in genetic research we can expect lots of null results and failed replications.

“Some argue that Lahn should have been more cautious. “Science always plays out in a certain socio-political context, and you have to look at the consequences of how the science might play out,” says John Horgan, a journalist who has written widely on the societal implications of science. “Research on race and intelligence is much more prone to supporting racist ideas about the inferiority of certain groups, which plays into racist policies.” Horgan says that institutional review boards should ban or seriously question proposed studies on race and IQ.”

Third area examined: Genetics of violence. Mild taboo.

Fourth area examined: Genetics of sexuality: Mild taboo.

In conclusion, Hayden says the highest taboo is on the genetics of race. However, apart from the difficulties currently experienced in relating the genetic code to any behaviour, the objections are mostly about feared abuses of knowledge. There are also some ancient arguments about whether genetic variance within races prevents any study of genetic group differences. I do not rank any of these arguments very highly, and Hayden probably does not either, but the views of those that do are given proper coverage. She leaves the final word to someone standing up for scientific enquiry: “You hear this refrain in lots of areas of science, that because people will misuse science we shouldn't engage in scientific inquiry. I think that gets it backwards. If we're worried that people will misuse it, we need to create safeguards — and an open public dialogue that ensures responsible use.”

Hayden ends saying “That, (open public dialogue) rather than censoring science or ignoring its implications, is perhaps the only way that…researchers will get their wish: to do their work in peace.”

It is a bit depressing to see a science journal not looking at the scientific debates in more detail, particularly when genetic analysis is becoming increasingly powerful. Essentially, this paper follows Lewontin 1972 without reference to Edwards 2003  and ignores Richard Dawkin’s elegant summary: "However small the racial partition of the total variation may be, if such racial characteristics as there are highly correlate with other racial characteristics, they are by definition informative, and therefore of taxonomic significance." On the broader front, geneticists have now organised themselves to provide extremely large samples of human genomes (125,000 in the most recent publication) and technology is racing to increase the speed and particularly the power of gene analysis. In strategic terms they have more data points in terms of people, and more data points in terms of analytic comparisons within the genome. It seems odd to give up the quest now. To use an old analogy, it would be like trying to break the Enigma code by using a punched tape reading machine, finding that the process was slow, cumbersome, and error prone, resulting in long periods in which the enemy code could not be read, and therefore deciding to give up trying.  In such circumstances Bletchley Park increased the numbers of code breaking machines and invented the computer age.

By the way, after an essay on science, Nature allows you to vote on each of the four topics, without recording who you are, or how many times you vote. As Steve Sailer wryly notes over at iSteve “Vote early and often”. However, no reader of this blog would participate in flawed science. Here is the link again: http://www.nature.com/news/ethics-taboo-genetics-1.13858

Post-script. Nature has written an editorial about the Hayden paper entitled “Dangerous work” which includes the following admonition: “Researchers should design studies on the basis of sound scientific reasoning. For instance, in light of increasing evidence that race is biologically meaningless, research into genetic traits that underlie differences in intelligence between races, or that predispose some races to act more aggressively than others, will produce little.”

I will try to comment about that at some later stage, once I have worked out whether I am a patient of black African descent, in which case my “eGFR must be corrected (multiplied by 1.2)”. Will let you know how that goes.

Government, death and taxes

 

Americans are currently conducting a controlled study on the utility of having a government. Belgium has led the way in showing that they are not strictly necessary. Independent law courts, and other independent providers may be able to perform useful quasi-governmental functions to higher standards at lower cost. However, establishing metrics to prove the case is a tricky business, but I thought it interesting to consult that standby, the frequency with which words are used in books.

Specifically, will usage of the word government rise or fall in the years following the shutdown? To prepare the ground, we have to look back at the usage of that word, and other related words over the past two centuries.

The results are quite startling: government was used at a perfectly steady rate of 0.032% from 1800 to 1855 and then fell significantly to 1870, probably as a consequence of the Civil War. Citizens are not fools, and regard cousins killing other cousins as a failure of good government. Use of the word remains subdued till the Second World War, and rises to a gentle peak in 1968, the peak of Counterculture. Perhaps it only records citizens saying “Down with the Government”. After 1990 it begins to decline again. Despite the current dramas, people are slightly losing interest in it.

On the cheery grounds that nothing is certain except death and taxes, I have looked at both those words. On purely actuarial grounds, all men being mortal, I expected that death would be depressingly and consistently lodged in our language. Not so. Stable from 1800 to 1860 it then shows a linear decline to 1940 and stays at that low level thereafter.

As to tax it rises from the 1900 but only very slightly. I assumed it would have risen more sharply, but we talk more about death than tax.

Anyway, what is the US government shutdown about? I would characterise it thus: “Can we increase the limit on our credit card?” At the core of this debate is a concept which will determine the outcome.  What is the word that English speaking peoples have rarely used over the last two centuries, in good times or bad, the one concept they don’t like talking about?

 

 

Debt.

US Government Shutdown

 

In my last post on “Ipsative Lives” I talked about the value of natural experiments in testing the impacts of forced life-choices. Such is the power of this little blog that the US Government immediately shut down, and obligingly afforded us a test case. There is no need for a detailed explanation. One faction believes in slightly larger government and the other in smaller government. The factions must agree on the management of the national debt, and whether to extend further credit to themselves, which first of all requires admitting that they are overdrawn.

From a psychological point of view this presents some interesting possibilities. Each faction has a significant preference for a particular explanation about the importance of government and the significance of national debt. Those conflicting views can now be tested. The temporary withdrawal of some governments services, brief as this interruption might be, should have some tangible effects. Another 15 days of shutdown, regrettable or desirable as it may be depending on political stances, should afford a measurable impact.

Belgium survived 589 days without a government in 2010-2011, and we can only hope/regret that it takes that long in the US case so as to provide a proper basis for data collection. It might be argued that the case of Belgium should be sufficient for even the most exacting of statisticians, but Belgium constitutes a special case which it would be too unkind to spell out in detail. The Grand Place is one of the beautiful public spaces in Europe, the neighbouring streets have excellent beer and chocolates, but after that one goes to France or Holland.

What will be interesting to see is whether the opposed US factions are able to draw any agreed conclusions after the event. I assume that if nothing much happens, and the country is not perceptibly affected by the shutdown, this should favour the smaller government faction. I suppose that the pro-government faction could argue that many aspects of government have carried on as usual (I assume that tax collection and benefits and so on continue, as does the Federal Reserve) and that there were accumulated benefits deriving from government which have slowly run down during the shutdown. Perhaps. The stronger argument, as any full blooded British journalist will tell you, is bodies piling up in the mortuary. There must be some photographable failure to drive citizens back into the hands of the legislators. When it happens, it can usher in significant attitude change.

My understanding of the situation is that if the US really goes for many days without spending money on government services, then they will certainly be richer in terms of their bank balances, but might actually be poorer if the government provides them with services they cannot provide themselves at comparable cost. Economists should have a field day determining the true balance sheet.

In terms of attitude change, I doubt whether anything short of a dramatic national failure will have any impact on political points of view. My bet is that those preferences will survive, whichever way the evidence goes.

Britain is currently unable to organise a government shutdown, but from time to time the fire service goes on strike. It is claimed, though I have never seen the evidence, that in those circumstances the number of reported fires goes down. This seems strange, until you realise that the majority of fires are due to some form of carelessness. Knowing that the brave fire fighters were not on call, citizens took more care to stub out their cigarettes properly.

I wait with interest for the first paper to show the effects of the government shutdown on ……. something.

Ipsative lives

Footfalls echo in the memory
Down the passage which we did not take
Towards the door we never opened
Into the rose-garden.

T.S.Eliot  Burnt Norton

Eliot, who was born 125 years ago this week, and thus merits remembrance, was a master of regret. The sparse, well-chosen and well placed words say it all. This brief addendum is only about the implications for psychology. In more prosaic terms: Life is not a pure experimental design. 

As Stephen Hawking put it: “It seems that there is a Chronology Protection Agency which prevents the appearance of closed time-like curves and so makes the universe safe for historians.” We cannot live two lives in parallel so as to judge which is the better one, and then return to the point of choice. We cannot wind back life, nor judge what we would have been like if we had been spared the errors, mischances, hazards, losses and defeats of our particular lives.  Lives are ipsative, in the sense that one has to chose one thing or another, and then a door closes. Opportunity cost, the economists call it.

For that very reason, popular scepticism about psychological research is in some ways well founded: group results apply to us all, but only partly. We still retain the ability to make choices and note, if only in retrospect, how those choices have changed our lives.

For example, most of us are the product of choices. Two adults made a decision, and we are the result. Those adults chose our food, clothes, books, and schools. We were not entirely passive, and sometimes spat out the food, rejected the clothes, ignored the books, and ran away from school. Nonetheless, choices were made for us in our early lives, until we started making choices for ourselves. Thereafter, “the terrible ifs” accumulate: there are the “if then” ifs, and the “if only” ifs. Forced and not so forced choices begin to determine our fate. 

This presents behavioural science with a dilemma: it cannot be a true science, if by that is meant a fully experimental science, with random allocation to living conditions. Hence the interest in natural experiments: looking at life before and after the raising of the Iron Curtain; first generation immigrants versus the second generation; measuring crime in towns which did and did not receive television broadcasts; comparing the effects of different health services, different diets, and different patterns of breast feeding. 

These natural experiments help us understand the causes of group differences, but they probably don’t satisfy the personal need to look back on crucial life choices. Possibly only identical twins can do that. They can see how, despite being as similar as it is possible to be, certain extraneous events can have a big influence. Perhaps the answer to Eliot’s dilemma is to study discrepancies between identical twins.

Or one could just continue regretting things.