My Thoughts On the Heritability of Intelligence and Eugenics

[Apollo]

Heritability increases from about 0.4 in childhood to 0.8 in later adulthood. The way these heritabilities are estimated is through numerous experiments on twins, adopted children, longitudinal studies, inbreeding depression research, etc. Nothing in science can be proven however. We know of gravity, but it is just a theory. We don't know what it is.

So what psychometricians are claiming is that the best evidence, based on similar research around the world, from thousands of studies, indicates that intelligence is highly heritable. In addition, very little evidence has been forthcoming showing that environment has much of an impact. Some data from nutrition, pathogens or diseases, etc. but very little real impact on intelligence has been shown so far.

SES also has very little impact on intelligence - numerous studies factor out the impact of SES on research results. It is quite easily controlled for. It is a matter of doing numerous types of studies that are peer reviewed, studies and assertions that can be falsified, and settling in on those theories that best fit the data. To date, it shows that intelligence or mental ability is very important, it is highly heritable, and it varies by individual and by races on average.

A child inherits ONE off TWO possible chromosomes from each parent's set of 23. 2 raised to the 23 power possible combinations. Some people get lucky and inherit far more smart genes than dumb ones; the next kid in the family can get unlucky and get mostly dumb genes from the parents. These emergent properties have been known to breeders for over 10,000 years - not how it works genetically but how to breed for the best emergent properties. Now we know how it is done. Eugenics takes the lucky kids and they have more offspring than the unlucky ones, just like dog breeders do. Except breeders may cull the least fit, just as our ancestors have been known to do (see Mother Nature by Hrdy).

The research on racial differences is also readily available from studying races around the world. The pattern is irrefutable and cannot be due to the environment. Average racial intelligences range from East Asians at about 106 to sub Saharan Blacks and Australian Aborigines at about 70. (See "The Scientific Study of General Intelligence" by numerous others, 2003.)

The question about how we can know heritability without knowing the genes is like asking how humans could have been breeding crops and animals for 10,000 years without knowing about genes. It is sophomoric. We study gravity, and yet it is still a theory. We don't know WHAT it is. It can't be proven. Yet we are all pretty sure it is what we think it is in terms of its repeatability. That is how intelligence is studied, using quantitative genetics, numerous studies, chronometric research on brain sizes, pH, glucose uptake, myelination, etc. Intelligence has been so thoroughly triangulated by so many methodologies that the social scientists have virtually given up trying to counter Jensenism with their own research. They have taken to mostly ignoring psychometrics, rather than challenge it. They have been routed and are on the run.

And as for apartheid because of racial differences, that is already the case. That is why Blacks deny intelligence testing, have moved to ban it, use quotas, etc. The tensions are already there because most people who already deal with Blacks on a day-to-day basis know they are less intelligent. Researchers note how Galton and Burt both had first hand knowledge of the less intelligent, while many elite academics do not. They can pretend that there are no real differences, because they do not rub shoulders with the underclass.

It is to be noted that no research has shown that intelligence is not highly heritable. That is, the naïve environmentalist position is dead in the water - it is moribund and going nowhere. Behavior geneticists have the only game in town, so one must accept the most parsimonious explanations with regards to intelligence and racial differences, or supply some data of their own that can overturn the Jensenism.

There is far more genetic variation within a breed of dog than there is between breeds. Now try taking a wolf over to a friend's house and ask if they can watch it for you for a while. Absurd of course. And yet, just a few genes determines the ferocity of a Wolf and the gentleness of Greyhound (not to mention the low IQ of Greyhounds compared to Border Collies). I believe they now have dog contests or shows that are "performance" in nature. From the couple I saw it looked to me that they were mostly Border Collies, the smartest of all breeds according to the book "The Intelligence of Dogs." So, the same rule applies to human breeds/races.

Race does not determine intelligence, evolution does. Many things impact different average intelligences within closely related races. Differential migration, cultural effects on breeding patterns, etc. Intelligence varies on many fronts within races such as rural versus cosmopolitan - the smart kids head for the city. For any group, whether race or some other criteria, average intelligences are based on past breeding patterns.

Studies on intelligence have been going on for over 100 years, and there is no indication that drug abuse, alcohol, or nutrition is a determinant of differences in average intelligence, of for individuals as far as that is concerned. There are damaged children from mothers, who are abusing drugs or alcohol, but they are a small minority and it occurs in every race. But also, it has nothing to do with genetics. A child could be intellectually damaged, say from a soccer head injury, but that debility is not passed onto the children. Intelligence is still primarily genetic. The naïve environmentalists have never shown that "pockets" of alcohol, drugs or nutrition can account for differences in average intelligence between races.

Nutrition does have a slight effect on intelligence, but not much. Just like stature, which is 90% genetic, but without adequate nutrition people will not develop. But today, there is no indication that lack of nutrition has any impact at all. Blacks in the US develop physically quite well, have no shortage of food, and studies have shown that their nutritional needs are about the same as Whites. The difference is genetic - no other naïve environmental cause has been found to explain the differences. Richard Lynn is the leading advocate of nutrition to increase IQ, but it has at best a small impact. Why do you think that nutrition is not promoted to close the gap between Whites and Blacks?

Actually, intelligence has high predictive validity with health. Intelligent people live longer, healthier lives. They understand diseases they may have, they can follow recommendations for taking medicine and following diets, etc., and they have far fewer accidents. Intelligence is the single most important determinate of numerous life outcomes, and they are all positive except for one - intelligent people live with the angst of knowing how stupid other people are.

Regarding evolution, when the races split, as they are constantly doing, different ecological niches select for different phenotypes, including behavioral traits and intelligence. There is no point in our history where "an intelligence" was selected for and when to fixation. Intelligence, unlike having five fingers, is highly variable by individuals and race: Ashkenazi Jews have an average IQ of about 108~115, while sub-Saharan Africans have and average IQ of 70. Each group has continued to evolve and is still evolving. Evolution never takes a break or ceases to operate on any organism. There is no teleological goal to evolution that states 'we have arrived, let's not change on iota from this point on.'

I am planning to research the databank at http://www.theoccidentalquarterly.com/ which appears to contain a large volume of scientific research on the topics of intelligence, personality, human interaction, race/ethnicity, and human evolution. If I come across any interesting data, I will post them here.

 

[selfAdjoint]

am planning to research the databank at http://www.theoccidentalquarterly.com/ which appears to contain a large volume of scientific research on the topics of intelligence, personality, human interaction, race/ethnicity, and human evolution. If I come across any interesting data, I will post them here

Cool. I'll be looking forward to them.

 

[peonyu]

Wow your asking to be flamed, coming out and saying blacks are less intelligent isn't a very popular thing to say.

Even if it does have some potential truth to it, its not a wise thing to say. So...myself I am not going to directly comment on it, but ill leave a little tidbit for you - In the animal kingdom different sub-species or 'races' of the same animal species have differing mental capabilities and areas that they excell at, this is well known and even different dog breeds have separate areas that they excell at. With some dog breeds excelling at sporting while others excell at leading the blind, which requires decent intelligence.

And of course in Science, there is no distinction between man and animal other than man being capable of reason. So make of that as you wish.

But if you are religous then the famous Bible verse of 'All men are created equal' should be good enough for you, as is denying Evolution...

 

[Nereid]

definition of 'race'?

Apollo,

In light of the growing body of data from the detailed study of variations in human DNA, why do you use the concept of 'race' without any definition?

Two examples which show that, at the very least, the ideas you present are flawed (in both cases the context makes it clear that you believe the groups you mention are 'races'):
1) you wrote: "sub-Saharan Africans have and average IQ of 70". IIRC, some parts of sub-Saharan Africa have a genetic variation far greater than anywhere else on Earth; for example, more variation in mitochondrial DNA in a typical Ethiopian village than in the whole of Europe. I'll post references later.
2) you wrote: "Average racial intelligences range from East Asians at about 106 [...]". In China alone there are >50 'nationalities'* most of which are just as much a 'race' as the 'Ashkenazi Jews'.

Peonyu's certainly correct to say that your post is highly inflamatory; if you do want a discussion based on the application of the scientific method, perhaps you could start with defining clearly what you mean by 'race'?

*an example (not a good one): http://www.asiarooms.com/china-travel-guide/nationalities/nationalities.html

 

[Nachtwolf]

Wow your asking to be flamed, coming out and saying blacks are less intelligent isn't a very popular thing to say.

Why flame someone for reporting well known facts? You have but to take a Psych 1 course to discover that it's true - U.S. blacks score around 85 on measures of IQ while whites score around 100. East Asians score somewhere above 100 (106 is the most commonly given figure).

Even if it does have some potential truth to it, its not a wise thing to say.

Ah! Now here is the interesting part - why is it "unwise" to say this, if it's so well established, and so widely known? The unfortunate fact is that in this day and age facts are shunted aside in favor of petty emotionalism and political expediency. History looks back at people like Gallileo, who spoke unpopular truths when it was "unwise" to do so, as great men. I think it better to allow principle to govern one's conduct rather than fear, even if it is "unwise."

the famous Bible verse of 'All men are created equal'

(That line is from the Constitution of the United States, not the Bible.)

you wrote: "sub-Saharan Africans have and average IQ of 70". IIRC, some parts of sub-Saharan Africa have a genetic variation far greater than anywhere else on Earth; for example, more variation in mitochondrial DNA in a typical Ethiopian village than in the whole of Europe. I'll post references later.

Both of these statements are, to the best of my knowledge, correct. Some African nations have IQs in the 60s; some in the high 70s. Equatorial Guinea has an average IQ measured at 59. So obviously there's a wide spread, there, but the average is still quite close to 70. These facts are reported in Lynn's IQ and the Wealth of Nations and I have his list of national IQs up at http://www.childrenofmillennium.org/science.htm

Average racial intelligences range from East Asians at about 106 [...]". In China alone there are >50 'nationalities'* most of which are just as much a 'race' as the 'Ashkenazi Jews'

"East Asian" is a technical term referring to a specific group of Asians (also called "Pacific Rim Asians"). China does indeed have a mix of non "East Asian" ethnicities, and this may account for the fact that the average IQ in China is 100, while the average IQ in Japan (a far more homogeneous nation) is 105.



--Mark

P.S. Nereid, in case you didn't read it yet, I sent you a private message a couple days ago.

 

[GCT]

Does intelligence correlate with repoductive success? If so "what kind of" intelligence are we referring to? IQ? It seems to me that IQ does not perfectly correlate with reproductive success. I would say that height, physiognomic features, atheltic ability correlate more strongly; and that the correlation between IQ and reproductive success would be relatively insignificant.

Intelligence to me, seems to be a form of working memory. Working memory, as you may know deals with executive functions; and in this sense I would have to agree that intelligence has a strong genetic etiology. However, I do not think that intelligence lies so much in an inherent neural efficiency; rather that this neural efficiency is shaped as a child ages. For instance, a child who possesses a reclusive, non-outgoing, shy personality may find comfort in intellectual persuit, and establishes an autonomy (reciprocal gene-environment theory).

I believe that the main difference in the IQ levels of whites v.s. blacks may be due to differences in executive functioning.

 

[Nachtwolf]

Does intelligence correlate with repoductive success?

Yes - inversely. The smart are being outbred by the stupid, and the consequent horror of this fact is impossible to exaggerate.

From a more academic standpoint, we know from inbreeding depression (the fact that the offspring of close relatives show decreased IQ) and heterosis (the fact that the offspring of mixed race individuals show increased IQ) that IQ-boosting genes are dominant. Without going too deeply into evolutionary explanations, this means that in our past, intelligence was favored by selection processes.

I would say that height, physiognomic features, atheltic ability correlate more strongly; and that the correlation between IQ and reproductive success would be relatively insignificant.

It seems to me that the best way to test this would be to look at the degree of inbreeding depression for height, athletic ability, and so forth, and compare that to the degree of inbreeding depression for IQ. Without knowing how these other traits would be depressed by inbreeding, I'd guess that IQ would win - inbreeding depression for just first cousins is around half a Standard Deviation.

Intelligence to me, seems to be a form of working memory.

Intelligence is best defined as psychometric g. Working memory correlates with this g rather well, however. (Incidentally, the best surrogate for psychometric g of which I am aware is, surprisingly, vocabulary.)

a child who possesses a reclusive, non-outgoing, shy personality may find comfort in intellectual persuit, and establishes an autonomy (reciprocal gene-environment theory

Whether what you just wrote is true or not, there is a link between Introversion and IQ. (I think this link is better explained by neural conductivity, but it does support your idea.)

I believe that the main difference in the IQ levels of whites v.s. blacks may be due to differences in executive functioning.

Spearman's Hypothesis was that the more highly g-loaded an intellectual task, the greater the black/white performance gap, and this hypothesis has been verified by a variety of means. In other words, the source of the difference between the IQ levels of whites and blacks is intelligence itself.

One of the ways this can be shown is by considering data from tests of digit span (that is, you read off numbers to a test subject and see how many he can repeat back). Blacks perform almost as well as whites on tests of raw digit span, but on tests of reverse-order digit span, white scores far surpass black scores. Reverse digit span is much more highly g-loaded than raw digit span.


--Mark

 

[selfAdjoint]

Nachtwolf, I think your "outbreeding" concerns are stil based on a naive view of genetic combination. Consider two pretty much reproductively isolated populations with different distributions of some trait. Population A has a lower mean of this traint that population B, but of course given a bell curve of occurrence, some members of B also have low values of this trait.

Now the outbreeding concern, for B, is that the curve for B will be moved "south" because of differential breeding by individuals with phenotypic low values, and only concerns members of B. A is irrelevant because of the near reproductive isolation.

But within the population B genetic mixing means that the values of a daughter generation are partly independent of those in a parent generation, so that regression on the mean happens, if only at a smaller than perfect level. The result is that very high values can occur in the subpopulation of low valued individuals even if they don't interbreed with the highs. Similarly the subpopulation of highs can produce children exhibiting low values.

Now to come down to cases, if the trait is Spearman's g and B is the population of US European-Americans, then extemely low-g individuals are generally prevented from reproducing and extremenly high-g individuals have a low reproductive rate, so what we're talking about is mix and match in the peak of the bell curve. And except for the Flynn effect, that can be taken as evolutionarily stable.

 

[Nachtwolf]

Nachtwolf, I think your "outbreeding" concerns are stil based on a naive view of genetic combination.

Yeah see I tell you people that I'm smart, and you must, like, disbelieve me. Reread what I said:

"The smart are being outbred by the stupid, and the consequent horror of this fact is impossible to exaggerate."

In this case "outbred" is like "outfought" or "outrun." What I meant was that smart people have low fertility and dumb people have high fertility, which is causing the genetic component to IQ to decrease in each human subgroup.

Mix them together? Keep them seperate? Either way, we're watching as genotypic intelligence decreases. This is the problem which eugenics attempts to solve, not by worrying about who marries whom, but by encouraging the brighter couples to have more offspring and the duller couples to have fewer.


--Mark

 

[hitssquad]

Originally posted by Nereid
perhaps you could start with defining clearly what you mean by 'race'?

Breeding populations with fuzzy boundaries.


See, below, the reproduced section on race definitions from Chapter 12 of Arthur Jensen's The g Factor.

Chapter 12 is available here for free:
http://home.comcast.net/~neoeugenics/jen12.htm

The entire book is available here for Questia subscribers:
http://www.questia.com/PM.qst?a=o&d=24373874


-Chris

_______________________________________
Before examining possible biological factors in racial differences in mental abilities, however, we should be conceptually clear about the biological meaning of the term “race.”


THE MEANING OF RACE
Nowadays one often reads in the popular press (and in some anthropology textbooks) that the concept of human races is a fiction (or, as one well-known anthropologist termed it, a “dangerous myth”), that races do not exist in reality, but are social constructions of politically and economically dominant groups for the purpose of maintaining their own status and power in a society. It naturally follows from this premise that, since races do not exist in any real, or biological, sense, it is meaningless even to inquire about the biological basis of any racial differences. I believe this line of argument has five main sources, none of them scientific:

• Heaping scorn on the concept of race is deemed an effective way of combating racism—here defined as the belief that individuals who visibly differ in certain characteristics deemed “racial” can be ordered on a dimension of “human worth” from inferior to superior, and that therefore various civil and political rights, as well as social privileges, should be granted or denied according to a person’s supposed racial origin.

• Neo-Marxist philosophy (which still has exponents in the social sciences and the popular media) demands that individual and group differences in psychologically and socially significant traits be wholly the result of economic inequality, class status, or the oppression of the working classes in a capitalist society. It therefore excludes consideration of genetic or biological factors (except those that are purely exogenous) from any part in explaining behavioral differences among humans. It views the concept of race as a social invention by those holding economic and political powers to justify the division and oppression of unprivileged classes.

• The view that claims that the concept of race (not just the misconceptions about it) is scientifically discredited is seen as a way to advance more harmonious relations among the groups in our society that are commonly perceived as “racially” different.

• The universal revulsion to the Holocaust, which grew out of the racist doctrines of Hitler’s Nazi regime, produced a reluctance on the part of democratic societies to sanction any inquiry into biological aspects of race in relation to any behavioral variables, least of all socially important ones.

• Frustration with the age-old popular wrong-headed conceptions about race has led some experts in population genetics to abandon the concept instead of attempting candidly to make the public aware of how the concept of race is viewed by most present-day scientists.


Wrong Conceptions of Race. The root of most wrong conceptions of race is the Platonic view of human races as distinct types, that is, discrete, mutually exclusive categories. According to this view, any observed variation among the members of a particular racial category merely represents individual deviations from the archetype, or ideal type, for that “race.” Since, according to this Platonic view of race, every person can be assigned to one or another racial category, it naturally follows that there is some definite number of races, each with its unique set of distinctive physical characteristics, such as skin color, hair texture, and facial features. The traditional number has been three: Caucasoid, Mongoloid, and Negroid, in part derived from the pre-Darwinian creationist view that “the races of mankind” could be traced back to the three sons of Noah—Shem, Ham, and Japheth.


The Cause of Biological Variation. All that is known today about the worldwide geographic distribution of differences in human physical characteristics can be understood in terms of the synthesis of Darwinian evolution and population genetics developed by R. A. Fisher, Sewall Wright, Theodosius Dobzhansky, and Ernst Mayr. Races are defined in this context as breeding populations that differ from one another in gene frequencies and that vary in a number of intercorrelated visible features that are highly heritable.

Racial differences are a product of the evolutionary process working on the human genome, which consists of about 100,000 polymorphic genes (that is, genes that contribute to genetic variation among members of a species) located in the twenty-three pairs of chromosomes that exist in every cell of the human body. The genes, each with its own locus (position) on a particular chromosome, contain all of the chemical information needed to create an organism. In addition to the polymorphic genes, there are also a great many other genes that are not polymorphic (that is, are the same in all individuals in the species) and hence do not contribute to the normal range of human variation. Those genes that do produce variation are called polymorphic genes, as they have two or more different forms called alleles, whose codes differ in their genetic information. Different alleles, therefore, produce different effects on the phenotypic characteristic determined by the gene at a particular chromosomal locus. Genes that do not have different alleles (and thus do not have variable phenotypic effects) are said to have gone to fixation; that is, alternative alleles, if any, have long since been eliminated by natural selection in the course of human or mammalian evolution. The physiological functions served by most basic “housekeeping” genes are so crucial for the organism’s development and viability that almost any mutation of them proves lethal to the individual who harbors it; hence only one form of the gene is possessed by all members of a species. A great many such essential genes are in fact shared by closely related species; the number of genes that are common to different species is inversely related to the evolutionary distance between them. For instance, the two living species closest to Homo sapiens in evolutionary distance, chimpanzees and gorillas, have at least 97 percent of their genes (or total genetic code) in common with present-day humans, scarcely less than chimps and gorillas have in common with each other. This means that even the very small percentage of genes (<3 percent) that differ between humans and the great apes is responsible for all the conspicuous and profound phenotypic differences observed between apes and humans. The genetic difference appears small only if viewed on the scale of differences among all animal species.

A particular gene’s genetic code is determined by the unique sequences of four chemical bases of the DNA, arranged in the familiar double-helix structure of the gene. A change in a gene’s code (one base pair), however slight, can produce a new or different allele that manifests a different phenotypic effect. (Many such mutations, however, have no phenotypic effect because of redundancy in the DNA.) Such changes in the DNA result from spontaneous mutation. Though mutations occur at random, some gene loci have much higher mutation rates than others, ranging for different loci from less than one per million to perhaps more than 500 per million sex cells—not a trivial number considering that each male ejaculation contains from 200 to 500 million sperm. While natural or spontaneous mutations have largely unknown causes, aptly referred to as biological “noise,” it has been shown experimentally that mutations can result from radiation (X-rays, gamma rays, cosmic rays, and ultraviolet radiation). Certain chemical substances are also mutagenic.

 

[hitssquad]

Originally posted by hitssquad
Breeding populations with fuzzy boundaries.

Reproduced section on race definitions from Chapter 12 of Arthur Jensen's The g Factor, continued.

Chapter 12 is available here for free:
http://home.comcast.net/~neoeugenics/jen12.htm

The entire book is available here for Questia subscribers:
http://www.questia.com/PM.qst?a=o&d=24373874


-Chris

_______________________________________
The creation of new alleles by spontaneous mutation along with the recombination of alleles in gametogenesis are essential conditions for the evolution of all forms of life. A new allele with phenotypic effects that decrease an individual’s fitness in a given environment, compared to the nonmutated allele that would normally occupy the same chromosomal locus, will be passed on to fewer descendants and will eventually go to extinction. The gene is driven out of existence, so to speak, by losing in the competition with other alleles that afford greater fitness. Biological fitness (also known as Darwinian fitness), as a technical term in evolutionary genetics, refers only to an individual’s reproductive success, often defined operationally as the number of surviving fertile progeny of that individual. (A horse mated with a donkey, for example, might produce many surviving offspring, but because they are all sterile, the horse and donkey in this mating have a fitness of zero.) The frequency of a particular gene in all of an individual’s relatives is termed the inclusive fitness of that gene. The inclusive fitness of a gene is a measure of its effect on the survival and reproductive success of both the individual bearing the gene and all of the individual’s relatives bearing the identical gene. Technically speaking, an individual’s biological fitness denotes nothing more than that individual’s genetic contribution to the next generation’s gene pool relative to the average for the population. The term does not necessarily imply any traits one may deem personally desirable, such as vigor, physical strength, or a beautiful body, although some such traits, to the extent that they are heritable, were undoubtedly genetically selected in the course of evolution only because, we know in retrospect, they enhanced individuals’ reproductive success in succeeding generations. The survival of any new allele and its rate of spreading through subsequent generations is wholly a function of the degree to which its phenotypic expression enhances the inclusive fitness of those who inherit the allele. An allele with any advantageous phenotypic effect, in this respect, spreads to an ever-larger part of the breeding population in each successive generation.

New alleles created by mutation are subject to natural selection according to the degree of fitness they confer in a particular environment. Changed environmental conditions can alter the selection pressure for a certain allele, depending on the nature of its phenotypic expression, thereby either increasing or decreasing its frequency in a breeding population. Depending on its fitness in a given environment, it may go to extinction in the population or it may go to fixation (with every member of the population eventually possessing the allele). Many polymorphic gene loci harbor one or another allele of a balanced polymorphism, wherein two or more alleles with comparable fitness values (in a particular environment) are maintained at equilibrium in the population. Thus spontaneous genetic mutation and recombination, along with differential selection of new alleles according to how their phenotypic expression affects inclusive fitness, are crucial mechanisms of the whole evolutionary process. The variation in all inherited human characteristics has resulted from this process, in combination with random changes caused by genetic drift and gene frequency changes caused by migration and intermarriage patterns.

Races as Breeding Populations with Fuzzy Boundaries. Most anthropologists and population geneticists today believe that the preponderance of evidence from both the dating of fossils and the analysis of the geographic distribution of many polymorphic genes in present-day indigenous populations argues that genus Homo originated in Africa. Estimates are that our direct distant hominid precursor split off from the great apes some four to six million years ago. The consensus of human paleontologists (as of 1997) accept the following basic scenario of human evolution.

Australopithecus afarensis was a small (about 3’6”), rather ape-like hominid that appears to have been ancestral to all later hominids. It was bipedal, walking more or less upright, and had a cranial capacity of 380 to 520 cm3 (about the same as that of the chimpanzee, but relatively larger for its overall body size). Branching from this species were at least two lineages, one of which led to a new genus, Homo.

Homo also had several branches (species). Those that were precursors of modern humans include Homo habilis, which lived about 2.5 to 1.5 million years ago. It used tools and even made tools, and had a cranial capacity of 510 to 750 cm3 (about half the size of modern humans). Homo erectus lived about 1.5 to 0.3 million years ago and had a cranial capacity of 850 to 1100 cm3 (about three-fourths the size of modern humans). The first hominid whose fossil remains have been found outside Africa, Homo erectus, migrated as far as the Middle East, Europe, and Western and Southeastern Asia. No Homo erectus remains have been found in Northern Asia, whose cold climate probably was too severe for their survival skills.

Homo sapiens branched off the Homo erectus line in Africa at least 100 thousand years ago. During a period from about seventy to ten thousand years ago they spread from Africa to the Middle East, Europe, all of Asia, Australia, and North and South America. To distinguish certain archaic subspecies of Homo sapiens (e.g., Neanderthal man) that became extinct during this period from their contemporaries who were anatomically modern humans, the latter are now referred to as Homo sapiens sapiens (or Homo s. sapiens); it is this line that branched off Homo erectus in Africa and spread to every continent during the last 70,000 years. These prehistoric humans survived as foragers living in small groups that frequently migrated in search of food.


GENETIC DISTANCE
As small populations of Homo s. sapiens separated and migrated further away from Africa, genetic mutations kept occurring at a constant rate, as occurs in all living creatures. Geographic separation and climatic differences, with their different challenges to survival, provided an increasingly wider basis for populations to become genetically differentiated through natural selection. Genetic mutations that occurred after each geographic separation of a population had taken place were differentially selected in each subpopulation according to the fitness the mutant gene conferred in the respective environments. A great many mutations and a lot of natural selection and genetic drift occurred over the course of the five or six thousand generations that humans were gradually spreading over the globe.

The extent of genetic difference, termed genetic distance, between separated populations provides an approximate measure of the amount of time since their separation and of the geographic distance between them. In addition to time and distance, natural geographic hindrances to gene flow (i.e., the interchange of genes between populations), such as mountain ranges, rivers, seas, and deserts, also restrict gene flow between populations. Such relatively isolated groups are termed breeding populations, because a much higher frequency of mating occurs between individuals who belong to the same population than occurs between individuals from different populations. (The ratio of the frequencies of within/between population matings for two breeding populations determines the degree of their genetic isolation from one another.) Hence the combined effects of geographic separation [or cultural separation], genetic mutation, genetic drift, and natural selection for fitness in different environments result in population differences in the frequencies of different alleles at many gene loci.

There are also other causes of relative genetic isolation resulting from language differences as well as from certain social, cultural, or religious sanctions against persons mating outside their own group. These restrictions of gene flow may occur even among populations that occupy the same territory. Over many generations these social forms of genetic isolation produce breeding populations (including certain ethnic groups) that evince relatively slight differences in allele frequencies from other groups living in the same locality.

When two or more populations differ markedly in allele frequencies at a great many gene loci whose phenotypic effects visibly distinguish them by a particular configuration of physical features, these populations are called subspecies. Virtually every living species on Earth has two or more subspecies. The human species is no exception, but in this case subspecies are called races. Like all other subspecies, human races are interfertile breeding populations whose individuals differ on average in distinguishable physical characteristics.

 

[hitssquad]

Originally posted by hitssquad
Breeding populations with fuzzy boundaries.

Reproduced section on race definitions from Chapter 12 of Arthur Jensen's The g Factor, continued further.

Chapter 12 is available here for free:
http://home.comcast.net/~neoeugenics/jen12.htm

The entire book is available here for Questia subscribers:
http://www.questia.com/PM.qst?a=o&d=24373874


-Chris

_______________________________________
Because all the distinguishable breeding populations of modern humans were derived from the same evolutionary branch of the genus Homo, namely, Homo s. sapiens, and because breeding populations have relatively permeable (non-biological) boundaries that allow gene flow between them, human races can be considered as genetic “fuzzy sets.” That is to say, a race is one of a number of statistically distinguishable groups in which individual membership is not mutually exclusive by any single criterion, and individuals in a given group differ only statistically from one another and from the group’s central tendency on each of the many imperfectly correlated genetic characteristics that distinguish between groups as such. The important point is that the average difference on all of these characteristics that differ among individuals within the group is less than the average difference between the groups on these genetic characteristics.

What is termed a cline results where groups overlap at their fuzzy boundaries in some characteristic, with intermediate gradations of the phenotypic characteristic, often making the classification of many individuals ambiguous or even impossible, unless they are classified by some arbitrary rule that ignores biology. The fact that there are intermediate gradations or blends between racial groups, however, does not contradict the genetic and statistical concept of race. The different colors of a rainbow do not consist of discrete bands but are a perfect continuum, yet we readily distinguish different regions of this continuum as blue, green, yellow, and red, and we effectively classify many things according to these colors. The validity of such distinctions and of the categories based on them obviously need not require that they form perfectly discrete Platonic categories.

It must be emphasized that the biological breeding populations called races can only be defined statistically, as populations that differ in the central tendency (or mean) on a large number of different characteristics that are under some degree of genetic control and that are correlated with each other through descent from common ancestors who are relatively recent in the time scale of evolution (i.e., those who lived about ten thousand years ago, at which time all of the continents and most of the major islands of the world were inhabited by relatively isolated breeding populations of Homo s. sapiens).

Of course, any rule concerning the number of gene loci that must show differences in allele frequencies (or any rule concerning the average size of differences in frequency) between different breeding populations for them to be considered races is necessarily arbitrary, because the distribution of average absolute differences in allele frequencies in the world’s total population is a perfectly continuous variable. Therefore, the number of different categories, or races, into which this continuum can be divided is, in principle, wholly arbitrary, depending on the degree of genetic difference a particular investigator chooses as the criterion for classification or the degree of confidence one is willing to accept with respect to correctly identifying the area of origin of one’s ancestors.

Some scientists have embraced all of Homo sapiens in as few as two racial categories, while others have claimed as many as seventy. These probably represent the most extreme positions in the “lumper” and “splitter” spectrum. Logically, we could go on splitting up groups of individuals on the basis of their genetic differences until we reach each pair of monozygotic twins, which are genetically identical. But as any pair of MZ twins are always of the same sex, they of course cannot constitute a breeding population. (If hypothetically they could, the average genetic correlation between all of the offspring of any pair of MZ twins would be 2/3; the average genetic correlation between the offspring of individuals paired at random in the total population is 1/2; the offspring of various forms of genetic relatedness, such as cousins [a preferred match in some parts of the world], falls somewhere between 2/3 and 1/2.) However, as I will explain shortly, certain multivariate statistical methods can provide objective criteria for deciding on the number and composition of different racial groups that can be reliably determined by the given genetic data or that may be useful for a particular scientific purpose. But one other source of genetic variation between populations must first be explained.


Genetic Drift. In addition to mutation, natural selection, and migration, another means by which breeding population may differ in allele frequencies is through a purely stochastic (that is, random) process termed genetic drift. Drift is most consequential during the formation of new populations when their numbers are still quite small. Although drift occurs for all gene loci, Mendelian characters (i.e., phenotypic traits), which are controlled by a single gene locus, are more noticeably affected by drift than are polygenic traits (i.e., those caused by many genes). The reason is purely statistical.

Changes in a population’s allele frequencies attributable to genetic drift can be distinguished from changes due to natural selection for two reasons: (1) Many genes are neutral in the sense that their allele frequencies have remained unaffected by natural selection, because they neither increase nor decrease fitness; over time they move across the permeable boundaries of different breeding populations. (2) When a small band of individuals emigrates from the breeding population of origin to found a new breeding population, it carries with it only a random sample of all of the alleles, including neutral alleles, that existed in the entire original population. That is, the allele frequencies at all gene loci in the migrating band will not exactly match the allele frequencies in the original population. The band of emigrants, and of course all its descendants (who may eventually form a large and stable breeding population), therefore differs genetically from its parent population as the result of a purely random process. This random process is called founder effect. It applies to all gene loci. All during the time that genetic drift was occurring, gene mutations steadily continued, and natural selection continued to produce changes in allele frequencies at many loci. Thus the combined effects of genetic drift, mutation, and natural selection ensure that a good many alleles are maintained at different frequencies in various relatively isolated breeding populations. This process did not happen all at once and then cease. It is still going on, but it takes place too slowly to be perceived in the short time span of a few generations.

It should be noted that the phenotypic differences between populations that were due to genetic drift are considerably smaller than the differences in those phenotypic characteristics that were strongly subject to natural selection, especially those traits that reflect adaptations to markedly different climatic conditions, such as darker skin color (thought to have evolved as protection from the tropical sun’s rays that can cause skin cancer and to protect against folate decomposition by sunlight), light skin color (to admit more of the ultraviolet rays needed for the skin’s formation of vitamin D in northern regions; also because clothing in northern latitudes made dark skin irrelevant selectively and it was lost through random mutation and drift), and globular versus elongated body shape and head shape (better to conserve or dissipate body heat in cold or hot climates, respectively).

Since the genetic drift of neutral genes is a purely random process, and given a fairly constant rate of drift, the differing allele frequencies of many neutral genes in various contemporary populations can be used as a genetic clock to determine the approximate time of their divergence. The same method has been used to estimate the extent of genetic separation, termed genetic distance, between populations.

 

[hitssquad]

Originally posted by hitssquad
Breeding populations with fuzzy boundaries.

Reproduced section on race definitions from Chapter 12 of Arthur Jensen's The g Factor, continued further, again.

Chapter 12 is available here for free:
http://home.comcast.net/~neoeugenics/jen12.htm

The entire book is available here for Questia subscribers:
http://www.questia.com/PM.qst?a=o&d=24373874


-Chris

_______________________________________
Measurement and Analysis of Genetic Distance Between Groups. Modern genetic technology makes it possible to measure the genetic distance between different populations objectively with considerable precision, or statistical reliability. This measurement is based on a large number of genetic polymorphisms for what are thought to be relatively neutral genes, that is, genes whose allele frequencies therefore differ across populations more because of mutations and genetic drift than because of natural selection. Population allele frequencies can be as low as zero or as high as 1.0 (as there are certain alleles that have large frequencies in some populations but are not found at all in other populations). Neutral genes are preferred in this work because they provide a more stable and accurate evolutionary “clock” than do genes whose phenotypic characters have been subjected to the kinds of diverse external conditions that are the basis for natural selection. Although neutral genes provide a more accurate estimate of populations’ divergence times, it should be noted that, by definition, they do not fully reflect the magnitude of genetic differences between populations that are mainly attributable to natural selection.

The technical rationale and formulas for calculating genetic distance are fully explicated elsewhere. For present purposes, the genetic distance, D, between two groups can be thought of here simply as the average difference in allele frequencies between two populations, with D scaled to range from zero (i.e., no allele differences) to one (i.e., differences in all alleles). One can also think of D as the complement of the correlation coefficient r (i.e., D= 1- r, and r=1- D). This conversion of D to r is especially useful, because many of the same objective multivariate statistical methods that were originally devised to analyze large correlation matrices (e.g., principal components analysis, factor analysis, hierarchical cluster analysis, multidimensional scaling) can also be used to analyze the total matrix of genetic distances (after they are converted to correlations) between a large number of populations with known allele frequencies based on some large number of genes.

The most comprehensive study of population differences in allele frequencies to date is that of the Stanford University geneticist Luigi Luca Cavalli-Sforza and his coworkers. Their recent 1,046-page book reporting the detailed results of their study is a major contribution to the science of population genetics. The main analysis was based on blood and tissue specimens obtained from representative samples of forty-two populations, from every continent (and the Pacific islands) in the world. All the individuals in these samples were aboriginal or indigenous to the areas in which they were selected samples; their ancestors have lived in the same geographic area since no later than 1492, a familiar date that generally marks the beginning of extensive worldwide European explorations and the consequent major population movements. In each of the Stanford study’s population samples, the allele frequencies of 120 alleles at forty-nine gene loci were determined. Most of these genes determine various blood groups, enzymes, and proteins involved in the immune system, such as human lymphocyte antigens (HLA) and immunoglobulins. These data were then used to calculate the genetic distance (D) between each group and every other group. (DNA sequencing was also used in separate analyses of some groups; it yields finer genetic discrimination between certain groups than can the genetic polymorphisms used in the main analysis.) From the total matrix of (42 X 41)/2 = 861 D values, Cavalli-Sforza et al. constructed a genetic linkage tree. The D value between any two groups is represented graphically by the total length of the line that connects the groups in the branching tree. (See Figure 12.1.)

The greatest genetic distance, that is, the largest D, is between the five African groups (listed at the top of Figure 12.1) and all the other groups. The next largest D is between the Australian + New Guinean groups and the remaining other groups; the next largest split is between the South Asians + Pacific Islanders and all the remaining groups, and so on. The clusters at the lowest level (i.e., at far right in Figure 12.1) can also be clustered to show the D values between larger groupings, as in Figure 12.2. Note that these clusters produce much the same picture as the traditional racial classifications that were based on skeletal characteristics and the many visible physical features by which non-specialists distinguish “races.”

It is noteworthy, but perhaps not too surprising, that the grouping of various human populations in terms of invisible genetic polymorphisms for many relatively neutral genes yields results that are highly similar to the classic methods of racial classification based on directly observable anatomical features.

Another notable feature of the Stanford study is that the geographic distances between the locations of the groups that are less than 5,000 miles apart are highly correlated (r ~.95) with the respective genetic distances between these groups. This argues that genetic distance provides a fairly good measure of the rate of gene flow between populations that were in place before A.D. 1492.

None of the 120 alleles used in this study has equal frequencies across all of the forty-two populations. This attests to the ubiquity of genetic variation among the world’s populations and subpopulations.

All of the modern human population studies based on genetic analysis (including analyses based on DNA markers and sequences) are in close agreement in showing that the earliest, and by far the greatest, genetic divergence within the human species is that between Africans and non-Africans (see Figures 12.1 and 12.2).

Cavalli-Sforza et al. transformed the distance matrix to a correlation matrix consisting of 861 correlation coefficients among the forty-two populations, so they could apply principal components (PC) analysis to their genetic data. (PC analysis is similar to factor analysis; the essential distinction between them is explained in Chapter 3, Note 13.) PC analysis is a wholly objective mathematical procedure. It requires no decisions or judgments on anyone’s part and yields identical results for everyone who does the calculations correctly. (Nowadays the calculations are performed by a computer program specifically designed for PC analysis.) The important point is that if the various populations were fairly homogeneous in genetic composition, differing no more genetically than could be attributable only to random variation, a PC analysis would not be able to cluster the populations into a number of groups according to their genetic propinquity. In fact, a PC analysis shows that most of the forty-two populations fall very distinctly into the quadrants formed by using the first and second principal components as axes (see Figure 12.3). They form quite widely separated clusters of the various populations that resemble the “classic” major racial groups—Caucasians in the upper right, Negroids in the lower right, Northeast Asians in the upper left, and Southeast Asians (including South Chinese) and Pacific Islanders in the lower left. The first component (which accounts for 27 percent of the total genetic variation) corresponds roughly to the geographic migration distances (or therefore time since divergence) from sub-Saharan Africa, reflecting to some extent the differences in allele frequencies that are due to genetic drift. The second component (which accounts for 16 percent of the variation) appears to separate the groups climatically, as the groups’ positions on PC2 are quite highly correlated with the degrees latitude of their geographic locations. This suggests that not all of the genes used to determine genetic distances are entirely neutral, but at least some of them differ in allele frequencies to some extent because of natural selection for different climatic conditions. I have tried other objective methods of clustering on the same data (varimax rotation of the principal components, common factor analysis, and hierarchical cluster analysis). All of these types of analysis yield essentially the same picture and identify the same major racial groupings.

 

[hitssquad]

Originally posted by hitssquad
Breeding populations with fuzzy boundaries.

Reproduced section on race definitions from Chapter 12 of Arthur Jensen's The g Factor, continued further, and yet again.

Chapter 12 is available here for free:
http://home.comcast.net/~neoeugenics/jen12.htm

The entire book is available here for Questia subscribers:
http://www.questia.com/PM.qst?a=o&d=24373874


-Chris

_______________________________________
African-Americans. The first Africans arrived in North America in 1619 and for more than two centuries thereafter, mostly between 1700 and 1800, the majority of Africans were brought to America as slaves. The end to this involuntary migration came between 1863 and 1865, with the Emancipation Proclamation. Nearly all of the Africans who were enslaved came from sub-Saharan West Africa, specifically the coastal region from Senegal to Angola. The populations in this area are often called West African or North West and Central West Bantu.

Steadily over time, the real, but relatively low frequency of cross-mating between blacks and whites produced an infusion of Caucasoid genes into the black gene pool. As a result, the present-day population of black Americans is genetically different from the African populations from whom they descended. Virtually 100 percent of contemporary black Americans have some Caucasian ancestry. Most of the Caucasian genes in the present-day gene pool of black Americans entered the black gene pool during the period of slavery.

Estimates of the proportion of Caucasoid genes in American blacks are based on a number genetic polymorphisms that have fairly high allele frequencies in the European population but zero or near-zero frequencies in the West African population, or vice versa. For any given allele, the estimated proportion (M) of white European ancestry in American blacks is obtained by the formula M =(qB-qAf)/qW-qAf) where qB is the given allele’s frequency in the black American population, qAf is its frequency in the African population, and qW is its frequency in the white European population. The average value of M is obtained over each of twenty or so genes with alleles that are unique either to Africans or to Europeans. The largest studies, which yield estimates with the greatest precision, give mean values of M close to 25 percent, with a standard error of about 3 percent. This is probably the best estimate for the African-American population overall. However, M varies across different regions of the United States, being as low as 4 percent to 10 percent in some southeastern States and spreading out in a fan-shaped gradient toward the north and the west to reach over 40 percent in some northeastern and northwestern states. Among the most typical and precise estimates of M are those for Oakland, California (22.0 percent) and Pittsburgh, Pennsylvania (25.2 percent). This regional variation in M reflects the pattern of selective migration of blacks from the Deep South since the mid-nineteenth century. Gene flow, of course, goes in both directions. In every generation there has been a small percentage of persons who have some African ancestry but whose ancestry is predominantly Caucasian and who permanently “pass as white.” The white American gene pool therefore contains some genes that can be traced to Africans who were brought over as slaves (estimated by analyses of genetic polymorphisms to be less than 1 percent).


Genetic Distance and Population Differences in g. The preceding discourse on the genetics of populations is germane to any discussion of population differences in g. The differences in gene frequencies that originally created different breeding populations largely explain the physical phenotypic differences observed between populations called races. Most of these differences in visible phenotypic characteristics are the result of natural selection working over the course of human evolution. Selection changes gene frequencies in a population by acting directly on any genetically based phenotypic variation that affects Darwinian fitness for a given environment. This applies not only to physical characteristics, but also to behavioral capacities, which are necessarily to some degree a function of underlying physical structures. Structure and function are intimately related, as their evolutionary origins are inseparable.

The behavioral capacities or traits that demonstrate genetic variation can also be viewed from an evolutionary perspective. Given the variation in allele frequencies between populations for virtually every known polymorphic gene, it is exceedingly improbable that populations do not differ in the alleles that affect the structural and functional basis of heritable behavioral traits. The empirical generalization that every polygenic physical characteristic that shows differences between individuals also shows mean differences between populations applies to behavioral as well as physical characteristics. Given the relative genetic distances between the major racial populations, one might expect some behavioral differences between Asians and Europeans to be of lesser magnitude than those between these groups and sub-Saharan Africans.

The behavioral, psychological, or mental characteristics that show the highest g loadings are the most heritable and have the most biological correlates (see Chapter 6) and are therefore the most likely to show genetic population differences. Because of the relative genetic distances, they are also the most likely to show such differences between Africans (including predominantly African descendants) and Caucasians or Asians.

Of the approximately 100,000 human polymorphic genes, about 50,000 are functional in the brain and about 30,000 are unique to brain functions. The brain is by far the structurally and functionally most complex organ in the human body and the greater part of this complexity resides in the neural structures of the cerebral hemispheres, which, in humans, are much larger relative to total brain size than in any other species. A general principle of neural organization states that, within a given species, the size and complexity of a structure reflect the behavioral importance of that structure. The reason, again, is that structure and function have evolved conjointly as an integrated adaptive mechanism. But as there are only some 50,000 genes involved in the brain’s development and there are at least 200 billion neurons and trillions of synaptic connections in the brain, it is clear that any single gene must influence some huge number of neurons—not just any neurons selected at random, but complex systems of neurons organized to serve special functions related to behavioral capacities.

It is extremely improbable that the evolution of racial differences since the advent of Homo sapiens excluded allelic changes only in those 50,000 genes that are involved with the brain.

Brain size has increased almost threefold during the course of human evolution, from about 500 cm3 in the australopithecenes to about 1,350 cm3 (the present estimated worldwide average) in Homo sapiens. Nearly all of this increase in brain volume has occurred in connection with those parts of the cerebral hemispheres associated with cognitive processes, particularly the prefrontal lobes and the posterior association areas, which control foresight, planning, goal-directed behavior, and the integration of sensory information required for higher levels of information processing. The parts of the brain involved in vegetative and sensorimotor functions per se differ much less in size, relative to total brain size, even between humans and chimpanzees than do the parts of the brain that subserve cognitive functions. Moreover, most of the evolutionary increase in brain volume has resulted not from a uniform increase in the total number of cortical neurons per Se, but from a much greater increase in the number and complexity of the interconnections between neurons, making possible a higher level of interneuronal communication on which complex information processing depends. Although the human brain is three times larger than the chimpanzee brain, it has only 1.25 times as many neurons; the much greater difference is in their degree of arborization, that is, their number of synapses and interconnecting branches.

No other organ system has evolved as rapidly as the brain of Homo sapiens, a species that is unprecedented in this respect. Although in hominid evolution there was also an increase in general body size, it was not nearly as great as the increase in brain size. In humans, the correlation between individual differences in brain size and in stature is only about + .20. One minus the square of this relatively small correlation, which is .96, reflects the proportion of the total variance in brain size that cannot be accounted for by variation in overall body size. Much of this residual variance in brain size presumably involves cognitive functions.

 

[Nereid]

Nachtwolf wrote:"East Asian" is a technical term referring to a specific group of Asians (also called "Pacific Rim Asians"). China does indeed have a mix of non "East Asian" ethnicities, and this may account for the fact that the average IQ in China is 100, while the average IQ in Japan (a far more homogeneous nation) is 105.

Please give a complete list of east asian races.

]Nachtwolf wrote:Some African nations have IQs in the 60s; some in the high 70s. Equatorial Guinea has an average IQ measured at 59. So obviously there's a wide spread, there, but the average is still quite close to 70.

Is the population distribution of IQ (g etc) about the mean (median?), for the North American standard group, the East Asian races, and the various sub-Saharan countries, all normal/Gaussian? If not, what is the distribution? What are the standard deviations of the population means you quote? What sample selections processes were used for chosing the people to give tests to? Where are the tests and detailed test data reproduced (not summaries)? What measured were instituted to control for factors such as sexual maturity, native language, and literacy?

 

[selfAdjoint]

I think Nachtwolf is quoting from the Flyn book "IQ and the Wealth of Nations". There's a lot of misinformation about this book, such as he did his own tests, used Raven Matrices, etc. Actually it was all done off of published data with little or no attention to different methodologies in different countries.


You ask if the distributions are normal. Well not even the best studied populations have been proved to have normal curves. They are TREATED as normal, and described with just the two parameters, but there is evidence they have significantly fatter tails, at least on the upside, than normal distributions do.

 

[hitssquad]

Sexual maturity, native language, and literacy

Originally posted by Nereid
What measured were instituted to control for factors such as sexual maturity, native language, and literacy?

Langauge and literacy were accounted for by

1. using non-verbal tests such as Raven's Progressive Matrices (Standard Progressive Matrices; and Coloured Progressive Matrices); the Cattell Culture Fair Test; and the Draw-a-Man Test;

and

2. Translated verbal or part-verbal tests such as the WISC, WISC-R. In the special case of Morrocan imigrants to the Netherlands being administered the Dutch General Intelligence Battery, the vocabulary subtest score (69) was disregarded because of poor knowledge of Dutch by the Morrocans. They otherwise did much better (84 compared to a Dutch mean of 100).


The reliability of these measures was

quantified by the correlation between two measures taken from a number of countries. In the sample of 81 nations, there are 45 for which there are two or more measures of IQ. There are also 15 countrues for which there are two or more measures and for these we have used the two extreme values. The correlation between the two measures of national IQ is .939. This high correlation establishes that the measure of national IQ has high reliability.

(Lynn, R, and Vanhanen, T. IQ and the Wealth of Nations. p64.)


The validity of national IQ measures was quantified by comparing IQ test results with popular assessments in those nations of bright and dull. It turns out that assessment of bright and dull is universal among all human cultures and that these assessments have strong correlations with IQ test results.

This has been shown to be true in Turkey (Kagitcibasi and Savasir, 1988) for Ugandans, Eskimos, and Native American Indians (Hakstian and Vandenberg, 1979) and for Blacks as well as Whites in South Africa (Kendall, Verster, and von Mollendorf, 1988).

(IQ and the Wealth of Nations. p65.)

Two other national IQ validity assessments consisted of comparisons with reaction time scores and comparisons of national education attainments. For the reaction time comparisions, r scores ranged from .73 to .96, with the higher r scores corresponding with higher statistical significance. For the education attainment comparisions

The correlation between national IQs and mathematics achievement scores is .881 (N-38) and between national IQs and science achievement scores .868 (N=38)... All countries are relatively close to the regression line which indicates a very strong correspondence between national IQs and national differences in school achievements.

(IQ and the Wealth of Nations. p71.)


Sexual maturity is not accounted for. Because of this, sub-Saharan African scores may tend to come out exaggeratedly high and caucasian and especially East Asian scores correspondingly may tend to come out depressed (sub-Saharan Africans mature most quickly; East Asians mature least quickly; and caucasians mature at an in-between rate closer to that of East Asians than that of Africans).


-Chris

 

[Nereid]

Nereid wrote: Is the population distribution of IQ (g etc) about the mean (median?), for the North American standard group, the East Asian races, and the various sub-Saharan countries, all normal/Gaussian? If not, what is the distribution? What are the standard deviations of the population means you quote? What sample selections processes were used for chosing the people to give tests to? Where are the tests and detailed test data reproduced (not summaries)? What measured were instituted to control for factors such as sexual maturity, native language, and literacy?

hitssquad gave some quotes, but none seem to have answered my questions (thank you SelfAdjoint, that was an answer to one of my questions).

Let me ask again:
1) what are the mean "IQs" (Nachtwolf's term) for all the "sub-Saharan African" races? Please list them individually.
2) what are the distributions around the mean? For each of the races.
3) what are the standard deviations of the distributions? Again, for each of the races.
4) What sample selection processes were used to choose people to give the tests to? For each of the races
5) Where are the tests and detailed test results published (not summaries)? for each of the races
6) How was literacy and native language accounted for in a) giving the tests, and b) interpreting the results? For example, the use of French and English (for example, in Benin and Nigeria respectively) vs the native language of those tested. For each of the races
7) [new question] How was the state of health of those tested accounted for in the analysis? What I am interested in here is how the results Nachtwolf quoted have been analysed to account for the fact that a) your health at the time of doing a test (any test) has a big influence on your performance in that test, and b) people in developing countries are generally less healthy than those in the US (for example).

 

[hitssquad]

Tire low; check for nails

Originally posted by Nereid
1) what are the mean "IQs" (Nachtwolf's term) for all the "sub-Saharan African" races? Please list them individually.

What races are you referring to?

5) Where are the tests and detailed test results published (not summaries)? for each of the races

For the national IQ data used in IQ and the Wealth of Nations, Lynn has the sources for 80 nations listed here...
http://www.rlynn.co.uk/pages/article_intelligence/7-a1.htm

...and their publication information listed here:
http://www.rlynn.co.uk/pages/article_intelligence/9.htm

For other nations used in the final regression analysis, national IQs were estimated by such methods as taking an average of neighboring nations, and using IQ data from racially similar populations (correcting for racial proportion in the latter case).

6) How was literacy and native language accounted for in a) giving the tests, and b) interpreting the results? For example, the use of French and English (for example, in Benin and Nigeria respectively) vs the native language of those tested. For each of the races

If the answer to this question already provided above is not sufficient, you will have to explain what you mean and/or your assumptions. For example, do you not know what a non-verbal test is? We can provide you with samples of test items, if that is what you are looking for. Here is what Raven's Matrices look like:
http://www.wilderdom.com/intelligence/IQExampleTests.html

This test is very similar to the Raven tests:
http://www.queendom.com/tests/iq/culture_fair_iq_r_access.html

7) [new question] How was the state of health of those tested accounted for in the analysis? What I am interested in here is how the results Nachtwolf quoted have been analysed to account for the fact that a) your health at the time of doing a test (any test) has a big influence on your performance in that test, and b) people in developing countries are generally less healthy than those in the US (for example).

Testing a nonrepresentative sample of the population might bias the results, so, of course, what you are proposing here was not done. Perhaps you do not understand the purpose of, in general, testing things and analysing the results. Perhaps, also, you do not understand the purpose of the IQ tests and their analyses. As to the latter, the point of testing IQs is to ascertain relative levels of functioning of general mental ability. If population conglomerates of these results are different from results found in other populations, that clue can be used as a raison d'être for further inquiry. Purposely making the results not appear, as you propose, would seem to be counterproductive to the end of establishing grounds for action -- such action as, say, distribution of IQ-boosting nutritional and pharmacological aid to low-IQ nations.

It has come to light through medical research -- especially that within the last decade -- that anti-senescence efforts, heavy-metal chelation, and anti-oxidant supplementation would have dramatic effects on the average IQ of the general population of the United States, and especially of the older members of that population. We could perhaps raise the average IQ of the US 20 points through modest efforts in these areas. The fact that we can do this does not imply that researchers should be ading 20 points to either the individual or collective IQ results of this population. This is because, again, the point of testing is to establish what really is there.

Since one tire may leak a bit more than another -- perhaps it simply came off the assembly line that way; perhaps the rim or valve is not sealed correctly; perhaps there is a nail stuck in the tread -- do you add compensating PSI points to your flatter tire's PSI scores when you check their pressure levels? I submit that if you did this, you would bias the results and make them quite useless to you as a vehicle owner.


-Chris

 

[Nereid]

no answers to simple questions -> flawed work (1)?

This is what I originally wrote, re Apollo's post at the head of this thread: "In light of the growing body of data from the detailed study of variations in human DNA, why do you use the concept of 'race' without any definition?

Two examples which show that, at the very least, the ideas you present are flawed (in both cases the context makes it clear that you believe the groups you mention are 'races'):
1) you wrote: "sub-Saharan Africans have and average IQ of 70". IIRC, some parts of sub-Saharan Africa have a genetic variation far greater than anywhere else on Earth; for example, more variation in mitochondrial DNA in a typical Ethiopian village than in the whole of Europe. I'll post references later.
2) you wrote: "Average racial intelligences range from East Asians at about 106 [...]". In China alone there are >50 'nationalities'* most of which are just as much a 'race' as the 'Ashkenazi Jews'."

Nachtwolf replied, as follows: "Both of these statements are, to the best of my knowledge, correct. Some African nations have IQs in the 60s; some in the high 70s. Equatorial Guinea has an average IQ measured at 59. So obviously there's a wide spread, there, but the average is still quite close to 70. [...] "East Asian" is a technical term referring to a specific group of Asians (also called "Pacific Rim Asians"). China does indeed have a mix of non "East Asian" ethnicities, and this may account for the fact that the average IQ in China is 100, while the average IQ in Japan (a far more homogeneous nation) is 105.."

In answer to my question "what is a 'race'?", hitssquad replied: "Breeding populations with fuzzy boundaries.", and posted material from a book by Jensen.

Later hitssquad referred to a book by Lynn which gives data on the IQ of nations, not races.

I'm still waiting for the list of (east) Asian races, and a similar list of sub-Saharan races, together with data on their mean IQs, standard deviations, distributions around the mean, and references (preferrably to peer-reviewed papers) to sources.

Without this I can't see how we can have a sensible discussion of Apollo's (and hitssquad's? and Nachtwolf's?) statements.

 

[Nereid]

no answer to simple questions -> flawed work (2)?

Twice now I have asked for data on the observed distributions about the quoted means, and measures of those distributions, standard deviations in particular.

SelfAdjoint: "I think Nachtwolf is quoting from the Flyn book "IQ and the Wealth of Nations". There's a lot of misinformation about this book, such as he did his own tests, used Raven Matrices, etc. Actually it was all done off of published data with little or no attention to different methodologies in different countries.

Neither Apollo, nor Nachtwolf, nor hitssquad have provided any data other than that in Lynn's book, nor offered a counter to SelfAdjoint's characterisation of that book.

In fact, from a link which hitssquad provided, Lynn seems to have merely collected studies done between 1952 and 2000, on subjects whose ages ranged from 3 to "Adults", with sample sizes ranging from 88 to over 43,000, by a number of different authors.

Apollo, Nachtwolf, hitssquad: if you want PF members and guests to take what you post seriously, please do us the courtesy of answering simple, basic questions about the research on which your assertions appear to rest.

 

[Nereid]

Apollo <-> hitssquad contradiction

Apollo: "So what psychometricians are claiming is that the best evidence, based on similar research around the world, from thousands of studies, indicates that intelligence is highly heritable. In addition, very little evidence has been forthcoming showing that environment has much of an impact. Some data from nutrition, pathogens or diseases, etc. but very little real impact on intelligence has been shown so far. [...] Nutrition does have a slight effect on intelligence, but not much. Just like stature, which is 90% genetic, but without adequate nutrition people will not develop. But today, there is no indication that lack of nutrition has any impact at all."

hitssquad: "*SNIP the point of testing IQs is to ascertain relative levels of functioning of general mental ability. If population conglomerates of these results are different from results found in other populations, that clue can be used as a raison d'être for further inquiry. Purposely making the results not appear, as you propose, would seem to be counterproductive to the end of establishing grounds for action -- such action as, say, distribution of IQ-boosting nutritional and pharmacological aid to low-IQ nations.
It has come to light through medical research -- especially that within the last decade -- that anti-senescence efforts, heavy-metal chelation, and anti-oxidant supplementation would have dramatic effects on the average IQ of the general population of the United States, and especially of the older members of that population. We could perhaps raise the average IQ of the US 20 points through modest efforts in these areas.

So what is it guys? IQ, as measured in a test, can be heavily influenced by environmental factors - how well you felt that day, how much anti-oxidant supplementation you've been taking - or not?

 

[Nereid]

test protocol

Suppose you do not speak, or understand Cantonese. Suppose a Chinese-looking gent comes to your playground one day, accompanied by a local policeman. The Chinese-looking gent pulls out a bunch of funny cards with triangles and circles on them, and speaks for 15 minutes in Cantonese. The policeman says that you have to answer his questions. You respect the policeman, and do your best, but you really don't understand what it's all about, and the policeman clearly doesn't much understand Cantonese either.

You've just completed a "Raven Standard Progressive Matrices" test, and your IQ has been scored as 30.

Now, when Laroche did his SPM work in Congo (Zaire) in 1959 (or before; 1959 is when the work was published), and got an average IQ for his 222 subjects of 68, to what extent was the test performed in a manner resembling the parody above?

The test may be a perfectly fine instrument; without information on the test protocol, we cannot use the test results.

 

[hitssquad]

Originally posted by Nereid
The test may be a perfectly fine instrument; without information on the test protocol, we cannot use the test results.

Without information on the test protocol, we cannot use the test results to do what?

Any single sampling is necessarily noisy, in a statistical sense. If it happens to get near a "right" answer, it is just by chance that it does, and is therefore still a noisy sample. Lynn's and Vanhanen's work can be considered a single sample. The data they used can be considered samples. If the results of Lynn's and Vanhanen's work is intriguing, it may serve as an impetus for further study of

1. the same data and using the same techniques as published by Lynn and Vanhanen;

and

2. different data.


With higher data volume, we will have more statistical power with which to draw inferences.


New data is coming in all the time. You can look at the abstracts at sciencedirect.com and see if the national IQ results are different or if papers are being published that lend new insight into why certain phenomena have been showning up in studies, or why certain phenomena haven't been showing up, or why some studies may have produced vastly different results than others.


It is not necessary to know how someone really performed sampling for scientific progress to occur. If he did not follow the protocols he said he did, then someone else following his published protocols will get data that differ from his. Methods and results that are not repeatable are assigned low probabilities of reliability.



-Chris

 

[hitssquad]

Originally posted by Nereid
Apollo: "So what psychometricians are claiming is that the best evidence, based on similar research around the world, from thousands of studies, indicates that intelligence is highly heritable. In addition, very little evidence has been forthcoming showing that environment has much of an impact. Some data from nutrition, pathogens or diseases, etc. but very little real impact on intelligence has been shown so far. [...] Nutrition does have a slight effect on intelligence, but not much. Just like stature, which is 90% genetic, but without adequate nutrition people will not develop. But today, there is no indication that lack of nutrition has any impact at all."

hitssquad: "*SNIP the point of testing IQs is to ascertain relative levels of functioning of general mental ability. If population conglomerates of these results are different from results found in other populations, that clue can be used as a raison d'être for further inquiry. Purposely making the results not appear, as you propose, would seem to be counterproductive to the end of establishing grounds for action -- such action as, say, distribution of IQ-boosting nutritional and pharmacological aid to low-IQ nations.
It has come to light through medical research -- especially that within the last decade -- that anti-senescence efforts, heavy-metal chelation, and anti-oxidant supplementation would have dramatic effects on the average IQ of the general population of the United States, and especially of the older members of that population. We could perhaps raise the average IQ of the US 20 points through modest efforts in these areas.

So what is it guys? IQ, as measured in a test, can be heavily influenced by environmental factors - how well you felt that day, how much anti-oxidant supplementation you've been taking - or not?

In a statistical worldview, IQ variance, or any outcome variance, can be virtually 100% acountable for by any single potential source of variance.

The point of using sizable numbers of samples is to increase statistical power, or signal to noise ratio. The more samples you gather, the more the signals in your collection of samples will tend to rise above noise.

There is published trend data for how much tested IQ tends to vary in individuals. This variance has been attributed to things like tiredness, distraction, anxiety, blood-sugar levels, inumerable squishy bloody cellular type happenings inside the skull, etc. I don't recall if anyone has managed to quantify yet things like tiredness specifically or its power as a source of variance on test outcome.

If you had a sample population that had spread among its members a certain distribution of tiredness at any given time, and you tested this population for anything -- IQ, physical fitness, whatever -- the noise of tiredness would tend to drop compared to the strength of signal as a function of the size of your sample population. In other words, yes, things can matter to any degree imaginable and beyond in individuals, but they don't tend to matter much in large populations, and furthermore there are ways of checking that this is reliably so.

And similarly to what I wrote in another message, if a population tends to be tired -- as with a tire that, perhaps unbeknownst to you, has a nail in it and tends to leak air fast -- and this tiredness affects IQ levels, and it is IQ levels you are looking for since you perhaps want to determine how much variance IQ levels account for in economic variance, then -- as with the air-pressure of the tire -- you would want the level of IQ as it comes from whatever sources of IQ variance the population is afflicted with, not absent them.


As for Appolo's statement "evidence ... indicates that intelligence is highly heritable," heritability as a statistical phenomenon, just as with any other statistical phenomenon, in a statistical worldview, is, by definition, contingent upon specifics of sampling parameters; e.g., which population at what time and under what conditions of variance and variance effect. It's like a stock price quote. There is no such thing as a listed price of a stock. Many sources will quote prices, but they are all contingent. They are all, by definition, derived, since they are all, by definition, statistical. The statistical power can go up -- as in a heavily traded stock -- or down -- as in a lightly traded stock -- but it can never, in a statistical worldview, reach a point of certainty.

So when Appolo says that "evidence ... indicates that intelligence is highly heritable," in a statistical worldview this would be taken to mean that evidence indicates intelligence is highly heritable within a certain population immersed in an environment with a particular variance. If the variance of the environment increases, provided this does not kill the population (as in, perhaps a widely varying environment might come in the form of temperature swings from 4 degrees kelvin to 2000 degrees kelvin everyday), then the amount of IQ variance attributable to environment might increase, and the amount attributable to genetics might decrease.

As far as populations in the United States, present environmental variance accounts for very little variance in IQ, as long as we control for age. Taking this statistical pseudoreality and injecting it into the real world, not much, as far as the present author can tell, is doable to raise the IQs of young adults; but more than a standard deviation of difference can be made in the IQs of older adults provided that brain-decay prevention starts when they are young adults. Furthermore things can be done at any point in the process of age-related brain tissue -- or other types of senescence that might effect IQ, such as low hormone levels -- decay, but it depends on the characterstics of the decay. In the case of hormone levels causing thinning of myelin (the insulative-protective covering on nerve axons) and subsequent lowering of IQ, hormone therapy is known to permanently raise tested IQ several standard deviations in a matter of weeks.


-Chris

 

[hitssquad]

Originally posted by Nereid
SelfAdjoint: "I think Nachtwolf is quoting from the Flyn book "IQ and the Wealth of Nations". There's a lot of misinformation about this book, such as he did his own tests, used Raven Matrices, etc. Actually it was all done off of published data with little or no attention to different methodologies in different countries.

Neither Apollo, nor Nachtwolf, nor hitssquad have provided any data other than that in Lynn's book, nor offered a counter to SelfAdjoint's characterisation of that book.

The point, from a statistical worldview, is not whether Lynn personally produced the national IQ data, but whether there was enough of that data available to develop quantifiably reliable and statistical trends, and whether major contingencies have been named and statistically quantified. Both the reliability and validity of the data were quantified and the relevance of those quantification further rest upon the contingencies of their own reliabilities and validities. The fact that statistical tools allow us to quantify both reliability and validity of data means that we can develop statistical inferences of the meaning of what Lynn and Vanhanen have brought to us, without having to go frame-by-frame over Zapruder-type films of the original data collection procedures, and without collecting things like standard deviations of the raw scores in each original IQ data collection academic article.

Quoting a previous message in this thread by hitssquad
The reliability of these measures was

quantified by the correlation between two measures taken from a number of countries. In the sample of 81 nations, there are 45 for which there are two or more measures of IQ. There are also 15 countrues for which there are two or more measures and for these we have used the two extreme values. The correlation between the two measures of national IQ is .939. This high correlation establishes that the measure of national IQ has high reliability.

(Lynn, R, and Vanhanen, T. IQ and the Wealth of Nations. p64.)

The validity was quantified.

The validity of national IQ measures was quantified by comparing IQ test results with popular assessments in those nations of bright and dull. It turns out that assessment of bright and dull is universal among all human cultures and that these assessments have strong correlations with IQ test results.

This has been shown to be true in Turkey (Kagitcibasi and Savasir, 1988) for Ugandans, Eskimos, and Native American Indians (Hakstian and Vandenberg, 1979) and for Blacks as well as Whites in South Africa (Kendall, Verster, and von Mollendorf, 1988).

(IQ and the Wealth of Nations. p65.)


Two other national IQ validity assessments consisted of comparisons with reaction time scores and comparisons of national education attainments. For the reaction time comparisions, r scores ranged from .73 to .96, with the higher r scores corresponding with higher statistical significance. For the education attainment comparisions

The correlation between national IQs and mathematics achievement scores is .881 (N-38) and between national IQs and science achievement scores .868 (N=38)... All countries are relatively close to the regression line which indicates a very strong correspondence between national IQs and national differences in school achievements.

(IQ and the Wealth of Nations. p71.)

In a statistical worldview, statistical reliability and statistical validity matter. These things are focused on as important.

Originally posted by Nereid
Apollo, Nachtwolf, hitssquad: if you want PF members and guests to take what you post seriously, please do us the courtesy of answering simple, basic questions about the research on which your assertions appear to rest.

Some of the specifics you have been asking about do not seem to be relevant in a statistical sense. Whether or not Lynn's IQ regression line is flawed, in a statistical sense, is quantifiable by measures of reliability and validity. Lynn and Vanhanen provided a reliability figure of .939; and validity figures of reaction time correlation with IQ r values from .73 to .96, a national mathematics achievement score correlation with IQ r value of .881, and a national science achievement score correlation with IQ r value of .868.

From the perspective of a statistical worldview, the reliability and validity of Lynn's and Vanhanen's IQ/Wealth regression correlation work is contingent upon the reliability and validity of those reliability and validity measures.


-Chris

 

[selfAdjoint]

There are also 15 countrues for which there are two or more measures and for these we have used the two extreme values. The correlation between the two measures of national IQ is .939. This high correlation establishes that the measure of national IQ has high reliability.

No, it just shows the same causes produced both values. If those causes were systematically skewed, the same high correlation would result. BTW, which countries were those 15?

 

[Nereid]

hitssquad wrote: Without information on the test protocol, we cannot use the test results to do what?

To eliminate systematic errors (N tests may yield similar results, with high correlations; if all tests suffer from the same systematic error, conclusions drawn from the correlations may be wrong); to address challenges to the validity of the test results; to rule out the null hypothesis.

In short, to conduct a study based on the scientific method.

 

[Nereid]

hitssquad wrote: *SNIP And similarly to what I wrote in another message, if a population tends to be tired -- as with a tire that, perhaps unbeknownst to you, has a nail in it and tends to leak air fast -- and this tiredness affects IQ levels, and it is IQ levels you are looking for since you perhaps want to determine how much variance IQ levels account for in economic variance, then -- as with the air-pressure of the tire -- you would want the level of IQ as it comes from whatever sources of IQ variance the population is afflicted with, not absent them.

Or, in other words, the sub-Saharan African nations' average IQ of 70 may be due to general, population-wide malnutrition; endemic disease; colonial repression (many of the tests Lynn appears to have used were taken during post-WW II independence struggles); or a dozen other factors as yet undetermined ... and NOT RACE [?] [?] [?]

And why is this? Because Lynn et al appear to have not even tried to determine the size (or even the existence) of these potential systematic effects.

 

[Nereid]

hitssquad,

You have made a number of statements concerning the power of statistical analyses, and how conclusions can validly be drawn using such analyses. You use such common statistical terms as 'correlation', 'variance', 'regression', 'significance'. You quote from Lynn, giving values for r, and (sometimes) sample sizes.

Yet on two fundamental aspects - standard deviation and observed distribution about the mean - you have remained silent.

Perhaps the social sciences are different from physics and astronomy, chemistry and engineering? In the latter disciplines, AFAIK, any serious work which involves statistical analysis must include at least consideration of the observed distribution and the standard deviation. You may read that the Hubble constant is 70 km/sec/Mpc, and that a careful analysis of the errors (which includes the observed distribution about the mean and the standard deviation) gives 1-sigma values about this value of 70 of -12 and +15.

Results quoted by you, Apollo, and Nachtwolf have been given as two digits, e.g. 68, 80; or three, e.g. 100, 106. From this one could guess that the errors - however defined - are approx 1% to 5%. However, a proper statistical analysis of the errors may show that the numbers quoted are +/- 12, or 25, or 46 (Nachtwolf, in one of his posts, hints that a difference of 2 is within the precision of the study, but that 6 is significant). From what you (and Apollo, and Nachtwolf) have posted, it is not possible to say whether even the simple statements you make appear reasonable, let alone do our own analyses to confirm or contradict your assertions.

Can we have some standard deviations and observed distributions about the (stated) means please?

Nereid

 

[hitssquad]

Reliability vs validity

Originally posted by selfAdjoint

hitssquad wrote
There are also 15 countrues for which there are two or more measures and for these we have used the two extreme values. The correlation between the two measures of national IQ is .939. This high correlation establishes that the measure of national IQ has high reliability.

No, it just shows the same causes produced both values.

In a statistical sense, there can be neither a determinable thing as a cause, nor production, of an event.

You seem to be answering here something that was not stated, selfAdjoint. Relative validity was not claimed here; relative reliability was.

If those causes were systematically skewed, the same high correlation would result.

...Which would make the results reliable. This essentially what Lynn wrote. Here it is again: "This high correlation establishes that the measure of national IQ has high reliability." Whatever is causing this skew, as far as our statistical methods have statistical power, appears to be relatively consistent. In a statistical sense, that is all that reliability establishes.

Do you know, in a statistical sense, what reliability is, selfAdjoint? Here's a hint: it is not validity.

BTW, which countries were those 15?

Sorry, my quote from the Lynn book was a typo. After Lynn says there are 45 nations from which there are two or more IQ measures, he says, "There are also 15 countries for which there are more than two measures" (emphasis mine). So, if you want only these 15 nations from which we have more than two measures (as listed in the book IQ and the Wealth of Nations, they are:

Australia
Belgium
Brazil (4 measures)
China
Congo (Zaire)
France
Germany (9 measures)
Hong Kong (5 measures)
India (4 measures)
Japan (10 measures)
Mexico
The Netherlands
South Africa (4 measures)
Switzerland
Taiwan (4 measures)
United States (4 measures)

(If not stated, then the number of measures for a particular nation is three.)


As you can see, I counted 16 nations. I think that perhaps Lynn was not including South Africa since the measures used tended to be racially restricted and the ultimate IQ of South Africa for Lynn's book was an average based on these results and the approximated racial distribution of the society.


-Chris

 

[Nereid]

hitssquad wrote (re conclusions from Lynn's statements re the relative reliability of multiple datasets for the one country): In a statistical sense, there can be neither a determinable thing as a cause, nor production, of an event.

So, in contradiction to what both Apollo and Nachtwolf wrote, you assert that Lynn et al's work merely demonstrates a correlation, but is silent on any causal relationships?

Further, unless and until there is solid work which goes beyond 'a statistical worldview', no hypotheses - including the null hypothesis - can be shown to be inconsistent with the data?

Nachtwolf, for avoidance of doubt, please note these are questions.

 

[selfAdjoint]

...Which would make the results reliable. This essentially what Lynn wrote. Here it is again: "This high correlation establishes that the measure of national IQ has high reliability." Whatever is causing this skew, as far as our statistical methods have statistical power, appears to be relatively consistent. In a statistical sense, that is all that reliability establishes.

Do you know, in a statistical sense, what reliability is, selfAdjoint? Here's a hint: it is not validity.

Show me a text where reliability is defined to include effects of systematic bias.

There is (we used to say in the service) precision, and there is accuracy. Precision is when you shoot a two inch circle. Accuracy is when that circle intersects the bull's eye.

 

[hitssquad]

Coexistence or otherwise of bias and reliability

Originally posted by selfAdjoint
...Which would make the results reliable. This essentially what Lynn wrote. Here it is again: "This high correlation establishes that the measure of national IQ has high reliability." Whatever is causing this skew, as far as our statistical methods have statistical power, appears to be relatively consistent. In a statistical sense, that is all that reliability establishes.

Do you know, in a statistical sense, what reliability is, selfAdjoint? Here's a hint: it is not validity.

Show me a text where reliability is defined to include effects of systematic bias.

First of all, we have as a text your very own quote, reproduced below, which defines reliability as including effects of bias:

There is (we used to say in the service) precision, and there is accuracy. Precision is when you shoot a two inch circle. Accuracy is when that circle intersects the bull's eye.

A non-bull's-eye-intersecting shot group is by statistical definition biased. Precision is reliability is measurement error -- the difference between a tight shot group and a widely-scattered shot group; e.g., how close one might be able to expect a single given shot to conform to the statiostical mean of the shot group -- and accuracy is validity -- e.g., how close that statistical mean gets to the theoretical target.

Precision/reliability, to be an internally-consistent statistical concept, necessarily would have to refer to the relative typical conformity of individual shots to a biased mean of a given shot group of which those individual shots are considered members.

Accuracy/validity, to be an internally-consistent statistical concept, necessarily would have to refer to the relative amount of bias incorporated in the shot group and quantifiable by the relative distance of that shot group's biased mean from any given "nonbiased" bull's-eye.


Arthur Jensen's The g Factor (1998) features the word "reliability" on 83 of its 652 pages. I haven't checked all of those uses of the word within that book, but I would predict that every one of those uses would be consistent with a definition of statistical reliability that assumes that the shot-group mean about which individual shots are judged for relative reliable incorporates an inherent non-zero bias.

Let's look, in The g Factor, at the first instance of use by Jensen of the word reliability:

Spearman noted that the Galtonian measures had poor reliability; that is, the same subject obtained different scores when the test was repeated. Besides measuring what they were intended to measure and appeared to measure, therefore, the Galtonian tests also contained a lot of measurement error. Spearman drew the analogy of firing a gun repeatedly while aiming at a mark on a target. The bullets scatter randomly around the mark, more of them hitting nearer the mark than farther away from it, and the more shots that are fired, the greater is the number of bullets that hit the mark. The scatter of bullets around the mark is analogous to measurement error. It is a part of every kind of measurement, to a greater or lesser degree, depending on the nature of the measuring instrument, the thing being measured, and how hard the experimenter works to reduce measurement error.

Neither Galton nor anyone else working on the measurement of mental abilities had taken into account the reliability of their measurements. Measurement error necessarily diminishes (the technical term is attenuates) the correlation coefficient. The larger the error (that is, the lower the reliability) in either one or both of the correlated variables, the lower will be the possible obtained correlation between them, because the measurement errors are by definition random and therefore uncorrelated. Even two variables that theoretically are perfectly correlated, such as the diameter and the circumference of circles, will not show a perfect correlation (i.e., r = +1.00) unless both variables are measured with perfect accuracy. Yet perfect accuracy of measurement is a pure abstraction never attained by any actual measurement. Actual measurements of any kind always have some "margin of error."

Spearman's formalization of this idea with respect to test scores is the basic postulate of what is now called classic test theory. It states that any and every actual (also termed obtained) score (or measurement), call it X, is composed of two elements--a true score, t, and a random error of measurement, e. (Neither t nor e can be directly observed.) Thus X = t + e. Because e can have either a positive or a negative sign and because it is random, its value tends toward zero as we average more and more of the measurements of X. Theoretically, the average of an infinite number of Xs contains zero error; it will consist purely of t. The way, then, to reduce measurement error is to average a number of repeated measurements of the thing being measured, and to include in the average as many repeated measurements as necessary to achieve the desired degree of accuracy, or, as it is termed, reliability, of the composite measure. The t (which is systematic) is repeatedly averaged in, while the e (which is random) is increasingly averaged out.

In other words, "reliability" is simply an inverse measure of the volume of a stack of bias so complex and individually generally orthogonal to each other that the net sum of those biases is zero with respect to. And, again, the mean of that reliability would consistently, in a statistical sense, have to itself be subject to a non-zero bias. (In other words, the statistical noise of which reliability is categorically and wholly an inverse measure is bias itself, though bias that cancels itself out. Any bias which does not cancel itself out is systematic bias and therefore causes a mean of a shot group to deviate {unlike "noise" bias which merely effects individual shot but not the overall meam of the shot group}.)

So, the "pure noise" bias of which reliability is an inverse measure is simply bias that does not systematically result in deviation from a given golden standard. Out of that "pure noise" bias -- which is to say statistically self-cancelling bias -- we rate with another inverse measure known as validity the relative strength of any non-pure-noise bias.

In short, the mean of any shot group of any amount of reliability necessarily always incorporates a non-zero level of bias which causes a consistent drift from a given golden (ideal; by definition, non-biased) standard.


*edit: format fixed*


-Chris

 

[Nereid]

hitssquad wrote: Sorry, my quote from the Lynn book was a typo. After Lynn says there are 45 nations from which there are two or more IQ measures, he says, "There are also 15 countries for which there are more than two measures" (emphasis mine). So, if you want only these 15 nations from which we have more than two measures (as listed in the book IQ and the Wealth of Nations, they are:
Australia
Belgium
Brazil (4 measures)
China
Congo (Zaire)
France
Germany (9 measures)
Hong Kong (5 measures)
India (4 measures)
Japan (10 measures)
Mexico
The Netherlands
South Africa (4 measures)
Switzerland
Taiwan (4 measures)
United States (4 measures)

If this is so, he does not use all the data in his analysis. Specifically, the appendix contains only the following (I simply clicked on your link):
Australia (2)
Belgium (1)
Brazil (4)
China (1); unless you count Hong Kong and Taiwan as China (which would be sensible, but Lynn doesn't seem to have done this)
Congo (Zaire) (1)
France (1)
Germany (2)
Hong Kong (3)
India (3)
Japan (1)
Mexico (3) YES!
The Netherlands (2)
South Africa (1)
Switzerland (2)
Taiwan (2)
US (1)

It would be interesting to know if he has introduced even more systematic errors than I have already identified by selective inclusion of data! I'll check when I have more time.

[Edit: I just noticed this quote; hitssquad of Lynn (my emphasis): "quantified by the correlation between two measures taken from a number of countries. In the sample of 81 nations, there are 45 for which there are two or more measures of IQ. There are also 15 countrues for which there are two or more measures and for these we have used the two extreme values. The correlation between the two measures of national IQ is .939. This high correlation establishes that the measure of national IQ has high reliability." Strong contradiction between the two sets of Lynn quotes, for six countries (Belgium, China, France, Japan, South Africa, US); slightly less strong for another four (Brazil, Hong Kong, India, Mexico).]