GALTON AND THE COMING OF EMPIRICAL PSYCHOLOGY
All the early influences on differential psychology mentioned so far came
from philosophers. None was an empirical scientist. Darwin was, of course, but
Darwinian ideas were introduced into psychology by Herbert Spencer, a pro­
fessional philosopher. The empirical study of mental ability and individual dif­
ferences could not begin until someone took up the methods of empirical
science, that is, asking definite questions of nature and discovering the answers
through analysis of data based on systematic observation, objective measure­
ment, and experimentation. The first person to do this was the Victorian eccen­
tric, polymath, and genius Sir Francis Galton (1822-1911).3 Galton was Charles
Darwin’s younger half-cousin—half-cousin because they had only one grand­
parent in common, Erasmus Darwin, a noted physician, physiologist, naturalist,
and poet. Born into a prominent and wealthy family, Galton was a child prodigy,
who could read and write before the age of four. He intensely disliked school,
however, and his parents transferred him from one private boarding school to
another, each as boring and frustrating to him as the others, and he begged his
parents to let him quit. In his Memories o f My Life (1908), written when he was
86, he still complained of his unsatisfying school experience. At age fifteen, he
was sent away to college, which offered more challenge. To satisfy his parents’
ambition that he follow in his eminent grandfather’s footsteps and become a
physician, he entered medical school. There he soon discovered that the basic
sciences—physics, chemistry, biology, and physiology—were far more to his
liking than medical practice. So he left medical school for Cambridge Univer­
sity, there to major in mathematics in preparation for a career in science.

Soon after Galton graduated, at age twenty-one, his father died, and Galton
received a large inheritance that made him independently wealthy for the rest
of his very long life. It allowed him to pursue his extremely varied interests
freely in all things scientific. His enthusiastic and catholic curiosity about natural
phenomena drove him to became perhaps the greatest scientific dilettante of all
time. Because he was also a genius, he made original contributions to many
fields, some of them important enough to be accorded chapters in books on the
history of several fields: criminology, eugenics, genetics, meteorology, psy­
chology, and statistics. He first gained fame in geography, as an explorer, ex­
pertly describing, surveying, and mapping previously unexplored parts of Africa.
For this activity, his name is engraved on the granite facade of the Royal Ge­
ographical Society’s building in London, along with the names of the most
famous explorers in British history. (His fascinating book  The Art o f Travel
[1855] was a long-time best seller and went through nine editions.) He also
made contributions to meteorology, inventing isobar mapping, being the first to
write a daily newspaper weather report, and formulating a widely accepted the­
ory of the anticyclone. He made other original contributions to photography,
fingerprint classification, genetics, statistics, anthropology, and psychometrics.
His prolific achievements and publications brought worldwide recognition and
many honors, including knighthood, Fellow of the Royal Society, and several
gold medals awarded by scientific societies in England and Europe. As a famous
man in his own lifetime, Galton also had what Hollywood calls “ star quality.”

Biographies of Galton also reveal his charming eccentricities. His profuse
intellectual energy spilled over into lesser achievements or activities that often
seem trivial. He was almost obsessed with counting and measuring things (his
motto: “When you can, count!” ), and he devised mechanical counters and other
devices to help in counting and tabulating. He loved data. On his first visit to
a city, for example, he would walk around with a small, hand-held mechanical
counter and tally the number of people passing by, tabulating their character­
istics—tall, medium, short; blond, brunette, redhead—separately for males and
females, the latter also rated for attractiveness. To be able to manage all these
data while walking about, he had his tailor make a special vest with many little
pockets, each one for a particular tabulated characteristic. He could temporarily
store the data from his counters by putting into designated pockets the appro­
priate number of dried peas. Back in his hotel room, he counted the peas in
each pocket and entered the numerical results in his notebook for later statistical
calculations.

He devised an objective measure of the degree to which a lecturer bored the
audience, and tried it out at meetings of the Royal Society. It consisted of
counting the involuntary noises—coughs, feet shuffling, and the like—that is­
sued from the audience, and, with a specially rigged protractor, he measured the
angle that listeners’ heads were tilted from a vertical position during the lecture.
A score derived from the data obtained with this procedure showed that even
the most eloquently written lecture, if read verbatim, was more boring than an
extempore lecture, however rambling and inelegant.

He also invented a special whistle (now called a Galton whistle), which is
familiar to many dog owners. Its high-frequency pitch is beyond humans’ au­
dible range and can be heard only by dogs and certain other animals. Galton
made a series of these whistles, ranging widely in pitch, and used them to find
the upper limits of pitch that could be heard by humans of different ages. To
compare the results on humans with the auditory capacities of many species in
the London Zoo, he would attach the whistles to the end of a tube that could
be extended like a telescope, so it could reach into a cage and direct the sound
right at the animal’s ear. While quickly squeezing a rubber bulb attached to one
end of the long tube to force a standard puff of air through the whistle attached
to the other end, he would note whether or not the animal reacted to a particular
pitch.

In another amusing project, he used the mathematics of solid geometry to
figure out the optimal way to cut a cake of any particular shape and dimensions
into any given number of pieces to preserve the freshness of each piece. He
published his clever solution in a mathematics journal. There are many other
quaint anecdotes about Galton’s amazing scientific curiosity and originality, but
the several already mentioned should suffice to round out the picture of his
extraordinary personality.

Although he died (at age ninety) as long ago as 1911, his legacy remains
remarkably vivid. It comprises not only his many pioneering ideas and statistical
inventions, still in use, but also the important endowments, permitted by his
personal wealth, for advancing the kinds of research he thought would be of
greatest benefit to human welfare. He founded the Department of Eugenics (now
Genetics) at the University of London and endowed its Chair, which has been
occupied by such luminaries as Karl Pearson, Sir Ronald Fisher, and Lionel
Penrose; he furnished a psychological laboratory in University College, London;
he founded two prestigious journals that are still active,  Biometrika and  The
Annals o f Human Genetics’, and he founded (in 1904) the Eugenics Society
(recently renamed The Galton Institute), which maintains an extensive library,
publishes journals and books, and sponsors many symposia, all related to the
field now known as social biology.

THE TWO DISCIPLINES OF SCIENTIFIC PSYCHOLOGY

Galton’s position in the history of behavioral science is stellar. He is ac­
knowledged as one of the two founding fathers of empirical psychology, along
with Wilhelm Wundt (1832-1920), who established the first laboratory of ex­
perimental psychology in 1879 in Leipzig. As Wundt is recognized as the father
of experimental psychology, Galton can certainly be called the father of differ­
ential psychology, including psychometrics and behavioral genetics. Each is now
a major branch of modern behavioral science. The leading historian of experi­
mental psychology, Edwin G. Boring (1950), drew the following interesting
contrast between the scientific personalities of Galton and Wundt:

Wundt was erudite where Galton was original; Wundt overcame massive obstacles
by the weight of his attack; Galton dispatched a difficulty by a thrust of insight.
Wundt was forever armored by his system; Galton had no system. Wundt was
methodical; Galton was versatile. Wundt’s science was interpenetrated by his
philosophy; Galton’s science was discursive and unstructured. Wundt was
interminably arguing; Galton was forever observing. Wundt had a school, a formal
self-conscious school; Galton had friends, influence and effects only. Thus, Wundt
was personally intolerant and controversial, whereas Galton was tolerant and ready
to be convicted of error, (pp. 461-62)

Wundt and Galton were the progenitors of the two main branches of scientific
psychology—experimental (Wundt) and differential (Galton). These two disci­
plines have advanced along separate tracks throughout the history of psychology.
Their methodological and even philosophical differences run deep, although
both branches embrace the scientific tradition of objective testing of hypotheses.

Experimental psychology searches for general laws of behavior. Therefore, it
treats individual differences as unwanted variance, termed “ error variance,”
which must be minimized or averaged out to permit the discovery of universal
regularities in the relation between stimulus and response. The method of ex­
perimental psychology consists of controlling variables (or treatment conditions)
and randomizing the assignment of subjects to the different treatments. The
experimental conditions are intentionally manipulated to discover their average
effects, unconfounded by individual differences. In general, the stimulus pre­
sented to the subject is varied by the experimenter, while the subject’s responses
are recorded or measured. But the data of primary interest to the experimental
psychologist consist of the averaged performance of the many subjects randomly
assigned to each condition.

Differential psychology, on the other hand, seeks to classify, measure, and
then explain the variety and nature of both individual and group differences in
behavioral traits as phenomena worthy of investigation in their own right. It uses
statistical analysis, such as correlation, multiple regression, and factor analysis,
applied to data obtained under natural conditions, rather than the controlled
conditions of the laboratory. Obviously, when human characteristics are of in­
terest, individual differences and many other aspects of behavior cannot feasibly
or ethically be controlled or manipulated by the investigator. Therefore, scien­
tists must study human variation as it occurs under natural conditions. During
the latter half of this century, however, a rapprochement has begun between the
two disciplines. Both experimental and correlational methods are being used in
the study of cognition.

G al to n ’s Methodological Contributions. Galton made enduring contribu­
tions to the methodology of differential psychology. He was the first to devise
a precise quantitative index of the degree of relationship, or  co-relation (as he
called it) between any two metric variables obtained from the same individuals
(or relatives) in a given population. Examples are individuals’ height and weight
or the resemblance between parents and children, or between siblings, in a given
trait.

In 1896, Karl Pearson (1857-1936), a noted mathematician, who became a
Galton disciple and has been rightly called the “ father of statistics,” revamped
Galton’s formulation of co-relation, to make it mathematically more elegant and
enhance its general applicability. Pearson’s formula yields what now is called
“ the Pearson product-moment coefficient of correlation.” In the technical lit­
erature, however, the word  correlation, without a modifier, always signifies
Pearson’s coefficient.4 (The many other types of correlation coefficient are al­
ways specified, e.g.,  intraclass correlation,  rank-order correlation,  tetrachoric
correlation,  biserial correlation,  point-biserial correlation,  partial correlation,
semipartial correlation,  multiple correlation,  canonical correlation, correlation
ratio, phi coefficient,  contingency coefficient,  tau coefficient,  concordance co­
efficient, and  congruence coefficient. Each has its specialized use, depending on
the type of data.) Pearson’s correlation is the most generally used. Universally
symbolized by a lower-case italic  r (derived from Galton’s term  regression), it
is a ubiquitous tool in the biological and behavioral sciences. In differential
psychology, it is absolutely essential.

Galton invented many other statistical and psychometric concepts and meth­
ods familiar to all present-day researchers, including the bivariate scatter dia­
gram, regression (related to correlation), multiple regression and multiple
correlation (by which two or more different variables are used to predict another
variable), the conversion of measurements or ranks to percentiles, standardized
or scale-free measurements or scores, various types of rating scales, the use of
the now familiar normal or bell-shaped curve (originally formulated by the great
mathematician Karl Friedrich Gauss [1777-1855]) as a basis for quantifying
psychological traits on an equal-interval scale, and using either the median or
the geometric mean (instead of the arithmetic mean) as the indicator of central
tendency of measurements that have a markedly skewed frequency distribution.

In his  Inquiries into Human Faculty and Its Development (1883), Galton
described an odd assortment of clever tests and techniques, devised mostly by
himself, for measuring basic human capacities, particularly keenness of sensory
discrimination in the different modalities, imagery, and reaction times to audi­
tory and visual stimuli. Although Galton’s use of gadgetry has been disparaged
as “ brass instrument psychology,” it was a seminal innovation—the  objective
measurement of human capacities. Compared with modern technology, of
course, Galton’s methods were fairly crude, sometimes even inadequate for their
purpose. His intense interest in human variation and his passion for quantitative
data, however, led him to apply his “ brass instrument” techniques to almost
every physical and mental characteristic that could be counted, ranked, or mea­
sured.

Galton obtained many types of data on more than 9,000 persons who, from
1884 to 1890, went through his Anthropometric Laboratory in London’s South
Kensington Science Museum. Each had to pay threepence to serve as subjects
for these tests and measurements. Unfortunately, Galton lacked the powerful
tools of statistical inference that were later developed by Karl Pearson (1857-
1936) and Sir Ronald A. Fisher (1890-1962), and therefore he could only draw
much weaker conclusions than the quality of his massive data really warranted.
He was dismayed that the measurements of sensory discrimination and speed of
reaction appeared to show so little relationship to a person’s level of general
mental ability (as indicated by educational and occupational attainments). It soon
became a widely accepted and long-lasting conclusion that the simple functions
assessed by Galton are unrelated to individual differences in the higher mental
processes, or intelligence. Galton’s “ brass instrument” approach to the study
of human abilities, therefore, was abandoned for nearly a century.

Recently, Galton’s original data have been analyzed by modern methods of
statistical inference.151 It turned out that his original hypotheses were largely
correct after all. R. A. Fisher’s method known as analysis o f variance revealed
highly significant differences between groups differing in educational and oc­
cupational level on Galton’s discrimination and reaction-time tests. Galton’s
scientific intuitions were remarkably good, but the psychometric and statistical
methods then available were not always up to the task of validating them.

Galton Introduces Genetics into Psychology. Galton’s most famous work,
Hereditary Genius (1869), was the forerunner of behavior genetics, nearly a
century before either the term or the field of behavior genetics came into being.
Galton was especially interested in the inheritance of mental ability. Because
there was then no objective scale for measuring mental ability, he devised an­
other criterion of high-level ability:  eminence, based on illustrious achievements
that would justify published biographies, encyclopedia articles, and the like. By
this criterion, he selected many of the most famous intellects of the nineteenth
century, whom he classed as “ illustrious,” and he obtained information about
their ancestors, descendants, and other relatives. His extensive biographical and
genealogical research revealed that the relatives of his illustrious probands were
much more likely to attain eminence than would a random sample of the pop­
ulation with comparable social background. More telling, he noticed that the
probability of eminence in a relative of an illustrious person decreased in a
regular stepwise fashion as the degree of kinship was more remote. Galton
noticed that the same pattern was also true for physical stature and athletic
performance.

Galton made other observations that gave some indication of the power of
family background in producing eminence. In an earlier period of history, it was
customary for popes to adopt orphan boys and rear them like sons, with all the
advantages of culture and education that papal privilege could command. Galton
noted that far fewer of these adopted boys ever attained eminence than did the
natural sons of fathers whose eminence was comparable to a pope’s. From such
circumstantial evidence, Galton concluded that mental ability is inherited in
much the same manner, and to about the same degree, as physical traits.

Galton further concluded that what was inherited was essentially a  general
ability, because eminent relatives in the same family line were often famous in
quite different fields, such as literature, mathematics, and music. He supposed
that this hereditary general ability could be channeled by circumstance or interest
into different kinds of intellectual endeavor. He also recognized special abilities,
or talent, in fields like art and music, but considered them less important than
general ability in explaining outstanding accomplishment, because a high level
of general ability characterized all of his illustrious persons. (Galton noted that
they were also characterized by the unusual zeal and persistence they brought
to their endeavors.) He argued, for example, that the inborn musical gift of a
Beethoven could not have been expressed in works of genius were it not ac­
companied by superior general ability. In Hereditary Genius, he summarized his
concept of general ability in his typically quaint style: “ Numerous instances
recorded in this book show in how small a degree eminence can be considered
as due to purely special powers. People lay too much stress on apparent spe­
cialities, thinking that because a man is devoted to some particular pursuit he
would not have succeeded in anything else. They might as well say that, because
a youth has fallen in love with a brunette, he could not possibly have fallen in
love with a blonde. As likely as not the affair was mainly or wholly due to a
general amorousness” (p. 64).

Ga l to n ’s Anecdotal Report on Twins. The use of twins to study the inher­
itance of behavioral traits was another of Galton’s important “ firsts.” He noted
that there were two types of twins, judging from their degree of resemblance.
“ Identical” twins come from one egg (hence they are now called monozygotic,
or MZ, twins), which divides in two shortly after fertilization. Their genetic
makeup is identical; thus their genetic correlation is unity (r = 1). And they are
very alike in appearance. “ Fraternal” twins (now called dizygotic, or DZ) come
from two different fertilized eggs and have the same genetic relationship as
ordinary siblings, with a genetic correlation of about one-half (on average). That
is, DZ twins are, on average, about one-half as similar, genetically, as MZ twins.
DZ twins are no more alike in appearance than ordinary siblings when they are
compared at the same age.

Galton was interested in twins’ similarities and differences, especially in MZ
twins, as any difference would reflect only the influence of environment or
nongenetic factors. He located some eighty pairs of twins whose close physical
resemblance suggested they were MZ, and he collected anecdotal data on their
behavioral characteristics from their relatives and friends and from the twins
themselves. He concluded that since the twins were so strikingly similar in their
traits, compared to ordinary siblings, heredity was the predominant cause of
differences in individuals’ psychological characteristics.

Because Galton obtained no actual measurements, systematic observations, or
quantitative data, his conclusions are of course liable to the well-known short­
comings of all anecdotal reports. Later research, however, based on the more
precise methods of modern psychometrics and biometrical genetics, has largely
substantiated Galton’s surmise about the relative importance of heredity and
environment for individual differences in general mental ability. But Galton’s
research on heredity is cited nowadays only for its historical interest as the
prototype of the essential questions and methods that gave rise to modern be­
havioral genetics. It is a fact that most of the questions of present interest to
researchers in behavioral genetics and differential psychology were originally
thought of by Galton. His own answers to many of the questions, admittedly
based on inadequate evidence, have proved to be remarkably close to the con­
clusions of present-day researchers. In the history of science, of course, the
persons remembered as great pioneers are those who asked the fundamental
questions, thought of novel ways to find the answers, and, in retrospect, had
many correct and fruitful ideas. By these criteria, Galton unquestionably quali­
fies.

Ga l to n ’s Concept of Mental Ability. Galton seldom used the word  intelli­
gence and never offered a formal definition. From everything he wrote about
ability, however, we can well imagine that, if he had felt a definition necessary,
he would have said something like  innate, general, cognitive ability. The term
cognitive clearly distinguishes it from the two other attributes of Plato’s triarchic
conception of the mind, the affective and conative. Galton’s favored term, men­
tal ability, comprises both general ability and a number of special abilities—he
mentioned linguistic, mathematical, musical, artistic, and memorial. General
ability denotes a power of mind that affects (to some degree) the quality of
virtually everything a person does that requires more than simple sensory acuity
or sheer physical strength, endurance, dexterity, or coordination.

Analogizing from the normal, bell-shaped distribution of large-sample data
on physical features, such as stature, Galton assumed that the frequency distri­
bution of ability in the population would approximate the normal curve. He
divided the normal curve’s baseline into sixteen equal intervals (a purely arbi­
trary, but convenient, number) to create a scale for quantifying individual and
group differences in general ability. But Galton’s scale is no longer used. Ever
since Karl Pearson, in 1893, invented the  standard deviation, the baseline of
the normal distribution has been interval-scaled in units of the standard devia­
tion, symbolized by c (the lower-case Greek letter sigma). Simple calculation
shows that each interval of Galton’s scale is equal to 0.696o, which is equivalent
to 10.44 IQ points, when the o of IQ is 15 IQ points. Hence Galton’s scale of
mental ability, in terms of IQ, ranges from about 16 to 184.

Galton was unsuccessful, however, in actually  measuring individual differ­
ences in intelligence. We can easily see with hindsight that his particular battery
of simple tests was unsuited for assessing the higher mental processes that peo­
ple think of as “ intelligence.” Where did Galton go wrong? Like Herbert Spen­
cer, he was immensely impressed by Darwin’s theory of natural selection as the
mechanism of evolution. And hereditary individual variation is the raw material
on which natural selection works by, in Darwinian terms, “ selection of the fittest
in the struggle for survival.” Also, Galton was influenced by Locke’s teaching
that the mind’s content is originally gained through the avenue of the five senses,
which provide all the raw material for the association of impressions to form
ideas, knowledge, and intelligence. From Darwin’s and Locke’s theories, Galton
theorized that, in his words, “ the more perceptive the senses are of differences,
the larger is the field upon which our judgement and intelligence can act”
{Human Faculty, 1883, p. 19). Among many other factors that conferred advan­
tages in the competition for survival, individual variation in keenness of sensory
discrimination, as well as quickness of reaction to external stimuli, would have
been positively selected in the evolution of human intelligence.

It seemed to Galton a reasonable hypothesis, therefore, that tests of fine sen­
sory  discrimination (not just simple acuity) and of reaction time to visual and
auditory stimuli would provide objective measures of individual differences in
the elemental components of mental ability, unaffected by education, occupation,
or social status. The previously described battery of tests Galton devised for this
purpose, it turned out, yielded measurements that correlated so poorly with com-
monsense criteria of intellectual distinction (such as election to the Royal So­
ciety) as to be unconvincing as a measure of intelligence, much less having any
practical value. Statistical techniques were not then available to prove the the­
oretical significance, if any, of the slight relationship that existed between the
laboratory measures and independent estimates of ability. Galton had tested
thousands of subjects, and all of his data were carefully preserved. When re­
cently they were analyzed by modern statistical methods, highly significant (that
is, nonchance) differences were found between the  average scores obtained by
various groups of people aggregated by age, education, and occupation.151 This
finding lent considerable theoretical interest to Galton’s tests, although they
would have no practical validity for individual assessment.

Binet and the F irs t Practical Test of Intelligence. At the behest of the Paris
school system, Alfred Binet in 1905 invented the first valid and practically useful
test of intelligence. Influenced by Galton and aware of his disappointing results,
Binet (1857-1911) borrowed a few of Galton’s more promising tests (for ex­
ample, memory span for digits and the discrimination of weights) but also de­
vised new tests of much greater mental complexity so as to engage the higher
mental processes—reasoning, judgment, planning, verbal comprehension, and
acquisition of knowledge. Test scores scaled in units of mental age derived from
Binet’s battery proved to have practical value in identifying mentally retarded
children and in assessing children’s readiness for schoolwork. The story of Bi­
net’s practical ingenuity, clinical wisdom, and the lasting influence of his test
is deservedly well known to students of mental measurement.171 The reason that
Binet’s test worked so well, however, remained unexplained by Binet, except
in intuitive and commonsense terms. A truly theory-based explanation had to
wait for the British psychologist Charles Spearman (1863-1945), whose mo­
mentous contributions are reviewed in the next chapter.

Galton on Race Differences in Ability. The discussion of Galton’s work in
differential psychology would be incomplete without mentioning one other topic
that interested him—race differences in mental ability. The title itself of his
chapter on this subject in  Hereditary Genius would be extremely unacceptable
today: “ The Comparative Worth of Different Races.” But Galton’s style of
writing about race was common among nineteenth-century intellectuals, without
(he slightest implication that they were mean-spirited, unkindly, or at all un­
friendly toward people of another race. A style like Galton’s is seen in state­
ments about race made by even such democratic and humanitarian heroes as
Jefferson and Lincoln.

Galton had no tests for obtaining direct measurements of cognitive ability.
Yet he tried to estimate the mean levels of mental capacity possessed by different
racial and national groups on his interval scale of the normal curve. His esti­
mates—many would say guesses—were based on his observations of people of
different races encountered on his extensive travels in Europe and Africa, on
anecdotal reports of other travelers, on the number and quality of the inventions
and intellectual accomplishments of different racial groups, and on the percent­
age of eminent men in each group, culled from biographical sources. He ven­
tured that the level of ability among the ancient Athenian Greeks averaged “ two
grades” higher than that of the average Englishmen of his own day. (Two grades
on Galton’s scale is equivalent to 20.9 IQ points.) Obviously, there is no pos­
sibility of ever determining if Galton’s estimate was anywhere near correct. He
also estimated that African Negroes averaged “ at least two grades” (i.e., 1.39a,
or 20.9 IQ points) below the English average. This estimate appears remarkably
close to the results for phenotypic ability assessed by culture-reduced IQ tests.
Studies in sub-Saharan Africa indicate an average difference (on culture-reduced
nonverbal tests of reasoning) equivalent to 1.43a, or 21.5 IQ points between
blacks and whites.8 U.S. data from the Armed Forces Qualification Test (AFQT),
obtained in 1980 on large representative samples of black and white youths,
show an average difference of 1.36a (equivalent to 20.4 IQ points)—not far
from Galton’s estimate (1.39a, or 20.9 IQ points).9 But intuition and informed
guesses, though valuable in generating hypotheses, are never acceptable as ev­
idence in scientific research. Present-day scientists, therefore, properly dismiss
Galton’s opinions on race. Except as hypotheses, their interest is now purely
biographical and historical.

NOTE 3

3. The literature on Galton is extensive. The most accessible biography is by Forrest
(1974). Fancher (1985a) gives a shorter and highly readable account. A still briefer
account of Galton’s life and contributions to psychology is given in Jensen (1994a),
which also lists the principal biographical references to Galton. His own memoir (Galton,
1908) is good reading, but does not particularly detail his contributions to psychology,
a subject reviewed most thoroughly by Cyril Burt (1962). Galton’s activities in each of
the branches o f science to which he made original contributions are detailed in a collec­
tion o f essays, each by one o f fourteen experts in the relevant fields; the book also
includes a complete bibliography o f Galton’s published works, edited by Keynes (1993).
Fancher (1983a, 1983b, 1983c, 1984) has provided fascinating and probing essays about
quite specific but less well-known aspects o f Galton’s life and contributions to psychol­
ogy. Lewis M. Terman (1877-1956), who is responsible for the Stanford-Binet IQ test,
tried to estimate Galton’s IQ in childhood from a few of his remarkably precocious
achievements even long before he went to school. These are detailed in Terman’s (1917)
article, in which he concluded that Galton’s childhood IQ was “ not far from 200” (p.
212). One o f Galton’s biographers, Forrest (1974), however, has noted, “ Terman was
misled by Francis’ letter to [his sister] Adele which begins, ‘I am four years old.’ The
date shows that it was only one day short of his fifth birthday. The calculations should
therefore by emended to give an I.Q. of about 160” (p. 7). (Note: Terman estimated IQ
as 100  X  estimated Mental Age (MA)/Chronological Age (CA); he estimated Galton’s
MA as 8 years based on his purported capabilities at CA 5 years, so 100 x 8/5 = 160.)

(all from The g factor, the science of mental ability – Arthur R. Jensen,, chapter 1).

The Keynes book is: The Legacy of His Ideas  by Francis Galton; ed. Milo Keynes.

I found a review of it, here: Sir Francis Galton, FRS The legacy of his ideas. review

I was particular struck by this:

Some contributors  suggest  that  he spread  himself  too  thinly:  that  he did  too many
things and followed up too few. Perhaps  so, but many great  scientists have been
polymaths.  Could  it be something  more  insidious?  That  his major  work  has become
too politically incorrect  to mention?

I am much like Galton, except that im not that smart. I seem to be around 2.3sd above the white mean, but share his mental energy and diverse interests.

Why Women Have Orgasms An Evolutionary Analysis.1007_s10508-012-9967-x

apparently, female human orgasms are useful after all.

Abstract Whether women’s orgasmis an adaptation is argu-
ably the most contentious questioninthestudyoftheevolution
of human sexuality. Indeed, this question is a veritable litmus
test for adaptationism, separating those profoundly impressed
with the pervasive andmyriad correspondences between organ-
isms’ phenotypes and their conditions of life from those who
apply the ‘‘onerous concept’’ of adaptation with more caution,
skepticismor suspicion. Yet, the adaptedness of female orgasm
is a question whose answer will elucidate mating dynamics in
humans and nonhuman primates. There are two broad compet-
ing explanations for the evolution of orgasm in women: (1) the
mate-choice hypothesis, which states that female orgasm has
evolved to function in mate selection and (2) the byproduct
hypothesis,which states that female orgasmhas no evolutionary
function, existing only becausewomen share some early ontog-
eny with men, in whom orgasm is an adaptation. We review
evidence for these hypotheses and identify areaswhere relevant
evidence is lacking.Although additional research is needed
before firm conclusions can be drawn, we find that the mate-
choice hypothesis receives more support. Specifically, female
orgasm appears to have evolved to increase the probability of
fertilization from males whose genes would improve offspring
fitness.

Evolutionary Psychology and Feminism 2011

 

Abstract This article provides a historical context of

evolutionary psychology and feminism, and evaluates the

contributions to this special issue of Sex Roles within that

context. We briefly outline the basic tenets of evolutionary

psychology and articulate its meta-theory of the origins of

gender similarities and differences. The article then evaluates

the specific contributions: Sexual Strategies Theory and the

desire for sexual variety; evolved standards of beauty;

hypothesized adaptations to ovulation; the appeal of risk

taking in human mating; understanding the causes of sexual

victimization; and the role of studies of lesbian mate

preferences in evaluating the framework of evolutionary

psychology. Discussion focuses on the importance of social

and cultural context, human behavioral flexibility, and the

evidentiary status of specific evolutionary psychological

hypotheses. We conclude by examining the potential role of

evolutionary psychology in addressing social problems

identified by feminist agendas.

Keywords Evolutionary psychology . Feminism . Sexual

strategies . Gender differences

 

I came across this study while reading this article, which i think i will comment on later.

—

 

 

The fact that physical attractiveness is so highly valued

by men in mate selection, and contrary to conventional

social science wisdom is not arbitrarily socially constructed,

does not imply that the emphasis placed on it is not

destructive to women—a point about which many feminists

and evolutionary psychologists agree (e.g., Buss 1996;

Wolf 1991; Vandermassen 2005). Many feminist scholars,

evolutionary psychologists, and evolutionary feminists

concur that the value people place on female beauty is

likely a key cause of eating disorders, body image

problems, and potentially dangerous cosmetic surgery. As

Singh and Singh (2011) and others point out, it can lead to

the objectification of women as sex objects to the relative

neglect of other dimensions along which women vary, such

as talents, abilities, and personality characteristics. Finally,

in the modern environment, it seems clear that men’s

evolved standards of female beauty have contributed to a

kind of destructive run-away female-female competition in

the modern environment to embody the qualities men desire

(Buss, 2003; Schmitt and Buss 1996).

 

In our view, the key point is that feminist stances on the

destructiveness of the importance people place on female

attractiveness need not, and should not, rest on the faulty

assumption that standards of attractiveness are arbitrary

social constructions. Societal change, where change is

desired, is best accomplished by an accurate scientific

understanding of causes. The evolutionary psychological

foundations of attractiveness must be a starting point for

this analysis.

 

indeed, as is (nearly?) always the case: if one wants to change some state of affairs, then actually understanding WHY it is the way it is to begin with is of paramount importance.

 

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Adaptations to Ovulation

Ovulation attains special status within women’s reproduc-

tive biology because it provides the very brief window

(roughly 12–24 h) during women’s menstrual cycle during

which conception is possible. Conventional wisdom in the

field of human sexuality over the past century has been that

ovulation is cryptic or concealed, even from women

themselves (e.g., Symons 1979). Evolutionary psycholo-

gists over the past decade have begun to challenge this

conventional wisdom. The challenges have come in two

forms—hypothesized adaptations in men to detect ovula-

tion and hypothesized adaptations in women to adjust their

mating behavior around ovulation.

 

Ancestral men, in principle, could have benefited (in

reproductive currencies) if they could detect when women

ovulated. An ovulation-detection ability would afford men

the ability to selectively direct their sexual overtures toward

women when they are ovulating, as male chimpanzees do.

And already mated men might increase their mate-guarding

efforts when their partners are ovulating. Both strategies, in

principle, could have evolved in men. The key question is:

Did they?More than 20 years ago, Symons (1987) concluded

that such male adaptations to ovulation had not evolved:

“The most straightforward prediction I could have made,

based on simple reproductive logic and the study of

nonhuman animals, would have been that . . . men will be

able to detect when women are ovulating and will find

ovulating women most sexually attractive. Such adaptations

have been looked for in the human male and have never

been found . . .” (p. 133).

 

it seems to me that the authors need to learn more logic. the above case seems to be an example of an argument from ignorance, altho in a nonstraightforward way. heres how i interpret it:

 

1) Symons wrote that there is no evidence of such adaptations in humans.

2) thus, Symons thought that there is no evidence of such adaptations in humans.

3) thus, Symons thought that there are no such adaptations in humans.

 

(2) follows given normal conditions, that is, that he wasnt lying etc. it has a hidden premise stating that the conditions are normal, in a kind of default reasoning way.

(3) however attributes an argument from ignorance inference to Symons, which is not warranted. it may be that the adaptations are difficult to find and that science had per 1987 just missed them.

 

Symons might not have held the view the authors attribute to him.

 

-

 

[...] And no other framework suggests that adaptations to

ovulation might have evolved. Whatever the eventual

evidentiary status of the competing hypotheses, it is

reasonable to conclude that the search for adaptations to

ovulation has been a fertile one, yielding fascinating

empirical findings.

 

dat pun

 

-

 

The positive outcome for everyone is that evolutionary

psychological hypotheses, sex role/biosocial theory hy-

potheses, and gender-similarity hypotheses all share the

scientific virtue of making specific empirical predictions.

In this sense, we see this special issue of Sex Roles an

exceptionally positive sign that the discourse is beginning

to move beyond purely ideological stances and toward an

increasingly accurate scientific understanding of gender

psychology.

 

since evo psychs dont hav any ideological stance, this description is exceptionally nice to them. the only ones who need to move past any ideology are the marxist feminists.

 

-

 

 

The g factor, the science of mental ability – Arthur R. Jensen, ebook download pdf free

 

This is a very interesting book. Without a doubt the best about intelligence that i hav read so far. I definitely recommend reading it if one is interested in psychometrics. It can serve as a long, good, but a bit dated introduction to the subject. For shorter introductions, probably Gottfredson’s why g matters is better.

 

 

Quotes and comments below. Red text = quotes.

——-

 

Galton had no tests for obtaining direct measurements of cognitive ability.

Yet he tried to estimate the mean levels of mental capacity possessed by different

racial and national groups on his interval scale of the normal curve. His esti­

mates—many would say guesses—were based on his observations of people of

different races encountered on his extensive travels in Europe and Africa, on

anecdotal reports of other travelers, on the number and quality of the inventions

and intellectual accomplishments of different racial groups, and on the percent­

age of eminent men in each group, culled from biographical sources. He ven­

tured that the level of ability among the ancient Athenian Greeks averaged “ two

grades” higher than that of the average Englishmen of his own day. (Two grades

on Galton’s scale is equivalent to 20.9 IQ points.) Obviously, there is no pos­

sibility of ever determining if Galton’s estimate was anywhere near correct. He

also estimated that African Negroes averaged “ at least two grades” (i.e., 1.39a,

or 20.9 IQ points) below the English average. This estimate appears remarkably

close to the results for phenotypic ability assessed by culture-reduced IQ tests.

Studies in sub-Saharan Africa indicate an average difference (on culture-reduced
nonverbal tests of reasoning) equivalent to 1.43a, or 21.5 IQ points between

blacks and whites.8 U.S. data from the Armed Forces Qualification Test (AFQT),

obtained in 1980 on large representative samples of black and white youths,

show an average difference of 1.36a (equivalent to 20.4 IQ points)—not far

from Galton’s estimate (1.39a, or 20.9 IQ points).9 But intuition and informed

guesses, though valuable in generating hypotheses, are never acceptable as ev­

idence in scientific research. Present-day scientists, therefore, properly dismiss

Galton’s opinions on race. Except as hypotheses, their interest is now purely

biographical and historical.

 

yes there is. first, one can check the historical record to look for dysgenic effects. if the british are less smart than the ancient greeks, there wud probably hav been som dysgenic effects somwher in history. still, this is not a good method, since the population groups are somwhat different.

 

second, soon we will know the genes that cause different levels of intelligence. we can then analyze the remains of ancient greeks to see which genes they had. this shud giv a pretty good estimate, altho not perfect since, that 1) new mutations hav com by since then, 2) som gene variants hav perhaps disappeared, 3) the difficulty of getting a representativ sample of ancient greeks to test from, 4) the problems with getting good enuf quality DNA to run tests on. still, i dont think these are impossible to overcom, and i predict that som decent estimate can be made.

 

-

 

A General Factor Is Not Inevitable. Factor analysis is not by its nature

bound to produce a general factor regardless of the nature of the correlation

matrix that is analyzed. A general factor emerges from a hierarchical factor

analysis if, and only if, a general factor is truly latent in the particular correlation

matrix. A general factor derived from a hierarchical analysis should be based

on a matrix of positive correlations that has at least three latent roots (eigen­

values) greater than 1.

For proof that a general factor is not inevitable, one need only turn to studies

of personality. The myriad of inventories that measure various personality traits

have been subjected to every type of factor analysis, yet no general factor has

ever emerged in the personality domain. There are, however, a great many first-

order group factors and several clearly identified second-order group factors, or

“ superfactors” (e.g., introversion-extraversion, neuroticism, and psychoticism),

but no general factor. In the abilities domain, on the other hand, a general factor,

g, always emerges, provided the number and variety of mental tests are sufficient

to allow a proper factor analysis. The domain of body measurements (including

every externally measurable feature of anatomy) when factor analyzed also

shows a large general factor (besides several small group factors). Similarly, the

correlations among various measures of athletic ability show a substantial gen­

eral factor.

 

 

Jensen was wrong about this, altho the significance of that is disputed afaict. see:

How important is the General Factor of Personality? A General Critique (William Revelle and Joshua Wilt), PDF

 

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In jobs where assurance of competence is absolutely critical, however, such

as airline pilots and nuclear reactor operators, government agencies seem to have

recognized that specific skills, no matter how well trained, though essential for

job performance, are risky if they are not accompanied by a fairly high level of

g. For example, the TVA, a leader in the selection and training of reactor op­

erators, concluded that results of tests of mechanical aptitude and specific job

knowledge were inadequate for predicting an operator’s actual performance on

the job. A TVA task force on the selection and training of reactor operators

stated: “ intelligence will be stressed as one of the most important characteristics

of superior reactor operators.. . . intelligence distinguishes those who have

merely memorized a series of discrete manual operations from those who can

think through a problem and conceptualize solutions based on a fundamental

understanding of possible contingencies.” 161 This reminds one of Carl Bereiter’s

clever definition of “ intelligence” as “ what you use when you don’t know

what to do.”

 

funny and true

 

-

 

The causal underpinnings of mental development take place at the neurolog­

ical level even in the absence of any specific environmental inputs such as those

that could possibly explain mental growth in something like figure copying in

terms of transfer from prior learning. The well-known “ Case of Isabel” is a

classic example.181 From birth to age six, Isabel was totally confined to a dimly

lighted attic room, where she lived alone with her deaf-mute mother, who was

her only social contact. Except for food, shelter, and the presence of her mother,

Isabel was reared in what amounted to a totally deprived environment. There

were no toys, picture books, or gadgets of any kind for her to play with. When

found by the authorities, at age six, Isabel was tested and found to have a mental

age of one year and seven months and an IQ of about 30, which is barely at

the imbecile level. In many ways she behaved like a very young child; she had

no speech and made only croaking sounds. When handed toys or other unfa­

miliar objects, she would immediately put them in her mouth, as infants nor­

mally do. Yet as soon as she was exposed to educational experiences she

acquired speech, vocabulary, and syntax at an astonishing rate and gained six

years of tested mental age within just two years. By the age of eight, she had

come up to a mental age of eight, and her level of achievement in school was

on a par with her age-mates. This means that her rate of mental development—

gaining six years of mental age in only two years—was three times faster than

that of the average child. As she approached the age of eight, however, her

mental development and scholastic performance drastically slowed down and

proceeded thereafter at the rate of an average child. She graduated from high

school as an average student.

 

What all this means to the g controversy is that the neurological basis of

information processing continued developing autonomously throughout the six

years of Isabel’s environmental deprivation, so that as soon as she was exposed

to a normal environment she was able to learn those things for which she was

developmentally “ ready” at an extraordinarily fast rate, far beyond the rate for

typically reared children over the period of six years during which their mental

age normally increases from two to eight years. But the fast rate of manifest

mental development slowed down to an average rate at the point where the level

of mental development caught up with the level of neurological development.

Clearly, the rate of mental development during childhood is not just the result

of accumulating various learned skills that transfer to the acquisition of new

skills, but is largely based on the maturation of neural structures.

 

this reminds me of the person who suggested that we delay teaching math in schools for the same reason. it is simply more time-effective, and time is costly, both for the child who has limited freedom in the time spent in school, and for soceity becus that time cud hav been spent on teaching somthing else, or not spent at all and thus saved money on teachers.

 

the idea is that som math subjects takes very long to teach, say, 8 year olds, but can rapidly to taught to 12 year olds. so, using som invented numbers, the idea is that instead of spending 10 hours teaching long division to 8 year olds, we cud spend 2 hours teaching long division to 12 year olds, thus saving 8 eights that can be either used on somthing else that can be taught easily to 8 year olds, or simply freeing up the time for non-teaching activities.

 

see: www.inference.phy.cam.ac.uk/sanjoy/benezet/ for the original papers

 

-

 

Perhaps the most problematic test of overlapping neural elements posited by

the sampling theory would be to find two (or more) abilities, say, A and B, that

are highly correlated in the general population, and then find some individuals

in whom ability A is severely impaired without there being any impairment of

ability B. For example, looking back at Figure 5.2, which illustrates sampling

theory, we see a large area of overlap between the elements in Test A and the

elements in Test B. But if many of the elements in A are eliminated, some of

its elements that are shared with the correlated Test B will also be eliminated,

and so performance on Test B (and also on Test C in this diagram) will be

diminished accordingly. Yet it has been noted that there are cases of extreme

impairment in a particular ability due to brain damage, or sensory deprivation

due to blindness or deafness, or a failure in development of a certain ability due

to certain chromosomal anomalies, without any sign of a corresponding deficit

in other highly correlated abilities.22 On this point, behavioral geneticists Will-

erman and Bailey comment: “ Correlations between phenotypically different

mental tests may arise, not because of any causal connection among the mental

elements required for correct solutions or because of the physical sharing of

neural tissue, but because each test in part requires the same ‘qualities’ of brain

for successful performance. For example, the efficiency of neural conduction or

the extent of neuronal arborization may be correlated in different parts of the

brain because of a similar epigenetic matrix, not because of concurrent func­

tional overlap.” 22 A simple analogy to this would be two independent electric

motors (analogous to specific brain functions) that perform different functions

both running off the same battery (analogous to g). As the battery runs down,

both motors slow down at the same rate in performing their functions, which

are thus perfectly correlated although the motors themselves have no parts in

common. But a malfunction of one machine would have no effect on the other

machine, although a sampling theory would have predicted impaired perform­

ance for both machines.

 

i know its only an analogy, but whether ther ar one or two motors tapping from one battery might hav an effect on their speed. that depends on the setup, i think.

 

-

 

Gc is most highly loaded in tests based on scholastic knowledge and cultural

content where the relation-eduction demands of the items are fairly simple. Here

are two examples of verbal analogy problems, both of about equal difficulty in

terms of percentage of correct responses in the English-speaking general pop­

ulation, but the first is more highly loaded on G f and the second is more highly

loaded on Gc.

 

1. Temperature is to cold as Height is to

(a) hot (b) inches (c) size (d) tall (e) weight

2. Bizet is to Carmen as Verdi is to

(a) Aida (b) Elektra (c) Lakme (d) Manon (e) Tosca

 

first one, i wanted to answer <small>, since <cold> is on the bottum of the scale of temperature, so i wanted somthing that was on the bottom of the scale of height. but ther is no such option, but tall is also on the scale of height, just as cold is on the scale of temperature. with no other better option, i went with (d), which was correct.

 

second one, however, made no sense to me. i did look for patterns in spelling, vowels, length, etc., found nothing. i then googled it. its composers and their operas.

en.wikipedia.org/wiki/Georges_Bizet

en.wikipedia.org/wiki/Carmen

en.wikipedia.org/wiki/Giuseppe_Verdi

en.wikipedia.org/wiki/Aida

 

-

 

Another blood variable of interest is the amount of uric acid in the blood

(serum urate level). Many studies have shown it to have only a slight positive

correlation with IQ. But it is considerably more correlated with measures of

ambition and achievement. Uric acid, which has a chemical structure similar to

caffeine, seems to act as a brain stimulant, and its stimulating effect over the

course of the individual’s life span results in more notable achievements than

are seen in persons of comparable IQ, social and cultural background, and gen­

eral life-style, but who have a lower serum urate level. High school students

with elevated serum urate levels, for example, obtain higher grades than their

IQ-matched peers with an average or below-average serum urate level, and,

amusingly, one study found a positive correlation between university professors’

serum urate levels and their publication rates. The undesirable aspect of high

serum urate level is that it predisposes to gout. In fact, that is how the association

was originally discovered. The English scientist Havelock Ellis, in studying the

lives and accomplishments of the most famous Britishers, discovered that they

had a much higher incidence of gout than occurs in the general population.

Asthma and other allergies have a much-higher-than-average frequency in

children with higher IQs (over 130), particularly those who are mathematically

gifted, and this is an intrinsic relationship. The intellectually gifted show some

15 to 20 percent more allergies than their siblings and parents. The gifted are

also more apt to be left-handed, as are the mentally retarded; the reason seems

to be that the IQ variance of left-handed persons is slightly greater than that of

the right-handed, hence more of the left-handed are found in the lower and upper

extremes of the normal distribution of IQ.

 

Then there are also a number of odd and less-well-established physical cor­

relates of IQ that have each shown up in only one or two studies, such as vital

capacity (i.e., the amount of air that can be expelled from the lungs), handgrip

strength, symmetrical facial features, light hair color, light eye color, above-

average basic metabolic rate (all these are positively correlated with IQ), and

being unable to taste the synthetic chemical phenylthiocarbamide (nontasters are

higher both in g and in spatial ability than tasters; the two types do not differ

in tests of clerical speed and accuracy). The correlations are small and it is not

yet known whether any of them are within-family correlations. Therefore, no

causal connection with g has been established.

 

Finally, there is substantial evidence of a positive relation between g and

general health or physical well-being.[36] In a very large national sample of high

school students (about 10,000 of each sex) there was a correlation of +.381

between a forty-three-item health questionnaire and the composite score on a

large number of diverse mental tests, which is virtually a measure of g. By

comparison, the correlation between the health index and the students’ socio­

economic status (SES) was only +.222. Partialing out g leaves a very small

correlation ( + .076) between SES and health status. In contrast, the correlation

between health and g when SES is partialed out is +.326.

 

how very curius!

 

-

 

Certainly psychometric tests were never constructed with the intention of

measuring inbreeding depression. Yet they most certainly do. At least fourteen

studies of the effects of inbreeding on mental ability test scores—mostly IQ—

have been reported in the literature.132′ Without exception, all of the studies show

inbreeding depression both of IQ and of IQ-correlated variables such as scho­

lastic achievement. As predicted by genetic theory, the IQ variance of the inbred

is greater than that of the noninbred samples. Moreover, the degree to which

IQ is depressed is an increasing monotonic function of the coefficient of in-

breeding. The severest effects are seen in the offspring of first-degree incestuous

matings (e.g., father-daughter, brother-sister); the effect is much less for first-

cousin matings and still less for second-cousin matings. The degree of IQ de­

pression for first cousins is about half a standard deviation (seven or eight IQ

points).

 

In most of these studies, social class and other environmental factors are well

controlled. Studies in Muslim populations in the Middle East and India are

especially pertinent. Cousin marriages there are more prevalent in the higher

social classes, as a means of keeping wealth in family lines, so inbreeding and

high SES would tend to have opposite and canceling effects. The observed effect

of inbreeding depression on IQ in the studies conducted in these groups,

therefore, cannot be attributed to the environmental effects of SES that are often

claimed to explain IQ differences between socioeconomically advantaged and

disadvantaged groups.

 

These studies unquestionably show inbreeding depression for IQ and other

single measures of mental ability. The next question, then, concerns the extent

to which g itself is affected by inbreeding. Inbreeding depression could be

mainly manifested in factors other than g, possibly even in each test’s specificity.

To answer this question, we can apply the method of correlated vectors to in-

breeding data based on a suitable battery of diverse tests from which g can be

extracted in a hierarchical factor analysis. I performed these analyses1331 for the

several large samples of children born to first-and second-cousin matings in

Japan, for whom the effects of inbreeding were intensively studied by geneticists

William Schull and James Neel (1965). All of the inbred children and compa­

rable control groups of noninbred children were tested on the Japanese version

of the Wechsler Intelligence Scale for Children (WISC). The correlations among

the eleven subtests of the WISC were subjected to a hierarchical factor analysis,

separately for boys and girls, and for different age groups, and the overall av­

erage g loadings were obtained as the most reliable estimates of g for each

subtest. The analysis revealed the typical factor structure of the WISC—a large

g factor and two significant group factors: Verbal and Spatial (Performance).

(The Memory factor could not emerge because the Digit Span subtest was not

used.) Schull and Neel had determined an index of inbreeding depression on

each of the subtests. In each subject sample, the column vector of the eleven

subtests’ g loadings was correlated with the column vector of the subtests’ index

of inbreeding depression (ID). (Subtest reliabilities were partialed out of these

correlations.) The resulting rank-order correlation between subtests’ g loadings

and their degree of inbreeding depression was + .79 (p < .025). The correlation

of ID with the Verbal factor loadings (independent of g) was +.50 and with the

Spatial (or Performance) factor the correlation was —.46. (The latter two cor­

relations are nonsignificant, each with p < .05.) Although this negative corre­

lation of ID with the spatial factor (independent of g) falls short of significance,

the negative correlation was found in all four independent samples. Moreover,

it is consistent with the hypothesis that spatial visualization ability is affected

by an X-linked recessive allele.34 Therefore, it is probably not a fluke.

 

A more recent study1351 of inbreeding depression, performed in India, was

based entirely on the male offspring of first-cousin parents and a control group

of the male offspring of genetically unrelated parents. Because no children of

second-cousin marriages were included, the degree of inbreeding depression was

considerably greater than in the previous study, which included offspring of

second-cousin marriages. The average inbreeding effect on the WISC-R Full

Scale IQ was about ten points, or about two-third of a standard deviation.1361

The inbreeding index was reported for the ten subtests of the WISC-R used in

this study. To apply the method of correlated vectors, however, the correlations

among the subtests for this sample are needed to calculate their g loadings.

Because these correlations were not reported, I have used the g loadings obtained

from a hierarchical factor analysis of the 1,868 white subjects in the WISC-R

standardization sample.1371 The column vector of these g loadings and the column

vector of the ID index have a rank-order correlation (with the tests’ reliability

coefficients partialed out) of +.83 (p < .01), which is only slightly larger than

the corresponding correlation between the g and ID vectors in the Japanese

study.

 

In sum, then, the g factor significantly predicts the degree to which perform­

ance on various mental tests is affected by inbreeding depression, a theoretically

predictable effect for traits that manifest genetic dominance. The larger a test’s

g loading, the greater is the depression of the test scores of the inbred offspring

of consanguineous parents, as compared with the scores of noninbred persons.

The evidence in these studies of inbreeding rules out environmental variables

as contributing to the observed depression of test scores. Environmental differ­

ences were controlled statistically, or by matching the inbred and noninbred

groups on relevant indices of environmental advantage.

 

pretty large effects. the footnote with the 14 studies mentioned is:

 

Adams & Neel, 1967; Afzal, 1988; Afzal & Sinha, 1984; Agrawal et al., 1984;

Badaruddoza & Afzil, 1993; Bashi, 1977; Book, 1957; Carter, 1967; Cohen et al., 1963;

Inbaraj & Rao, 1978; Neel, et al., 1970; Schull & Neel, 1965; Seemanova, 1971; Slatis

& Hoene, 1961.

 

-

 

Semantic Verification Test. The SVT uses the binary response console (Fig­

ure 8.3) and a computer display screen. Following the preparatory “ beep,” a

simple statement appears on the screen. The statement involves the relative

positions of the three letters A, B, C as they may appear (equally spaced) in a

horizontal array. Each trial uses one of the six possible permutations of these

three letters chosen at random. The statement appears on the screen for three

seconds, allowing more than enough time for the subject to read it. There are

fourteen possible statements of the following types: “ A after B,” “ C before

A,” “ A between B and C,” “ B first,” “ B last,” “ C before A and B,” “ C

after B and A” ; and the negative form of each of these statements, for instance,

“ A not after B.” Following the three-second appearance of one of these state­

ments, the screen goes blank for one second and then one of the permutations

of the letters A B C appears. The subject responds by pressing either the TRUE

or FALSE button, depending on whether the positions of the letters does or does

not agree with the immediately previous statement.

 

Although the SVT is the most complex of the many ECTs that have been

tried in my lab, the average RT for university students is still less than 1 second.

The various “ problems” differ widely in difficulty, with average RTs ranging

from 650 msec to 1,400 msec. Negative statements take about 200 msec longer

than the corresponding positive statements. MT, on the other hand, is virtually

constant across conditions, indicating that it represents something other than

speed of information processing.

 

The overall median RT and RTSD as measured in the SVT each correlates

about —.50 with scores on the Raven’s Advanced Progressive Matrices given

without time limit. The average RT on the SVT also shows large differences

between Navy recruits and university students,1201 and between academically

gifted children and their less gifted siblings.1211 The fact that there is a within-

families correlation between RT and IQ indicates that these variables are intrin­

sically and functionally related.

 

One study20 reveals that the average processing time for each of the fourteen

types of SVT statements in university students predicts the difficulty level of

the statements (in terms of error responses) in children (third-graders) who were

given the SVT as a nonspeeded paper-and-pencil test. While the SVT is of such

trivial difficulty for college students that individual differences are much more

reliably reflected by RT rather than by errors, the SVT items are relatively

difficult for young children. Even when they take the SVT as a nonspeeded

paper-and-pencil test, young children make errors on about 20 percent of the

trials. (The few university students who made even a single error under these

conditions, given as a pretest, were screened out.) The fact that the rank order

of the children’s error rates on the various types of SVT statements closely

corresponds to the rank order of the college students’ average RTs on the same

statements indicates that item difficulty is related to speed of processing, even

when the test is nonspeeded.

 

It appears that if information exceeds a critical level of complexity for the in­

dividual, the individual’s speed of processing is too slow to handle the infor­

mation all at once; the system becomes overloaded and processing breaks

down, with resulting errors, even for nonspeeded tests on which subjects are

told to take all the time they need. There are some items in Raven’s Advanced

Matrices, for example, that the majority of college students cannot solve with

greater than chance success, even when given any amount of time, although the

problems do not call for the retrieval of any particular knowledge. As already

noted, the scores on such nonspeeded tests are correlated with the speed of in­

formation processing in simple ECTs that are easily performed by all subjects

in the study.

 

interesting test. the threshold hypothesis is also interesting for makers of IQ tests.

 

-

 

There are many other kinds of simple tasks that do not resemble the con­

tents of conventional psychometric tests but that have significant correlations

with IQ. Many studies have confirmed Spearman’s finding that pitch discrim­

ination is g-loaded, and other musical discriminations, in duration, timbre,

rhythmic pattern, pitch interval, and harmony, are correlated with IQ, indepen­

dently of musical training.28 The strength of certain optical illusions is also

significantly related to IQ.1291 Surprisingly, higher-IQ subjects experience cer­

tain illusions more strongly than subjects with lower IQ, probably because

seeing the illusion implies a greater amount of mental transformation of the

stimulus, and tasks that involve transformation of information (e.g., backward

digit span) are typically more g loaded than tasks involving less transforma­

tion of the input (e.g., forward digit span). The positive correlation between

IQ and susceptibility to illusions is consistent with the fact that susceptibility

to optical illusions also increases with age, from childhood to maturity, and

then decreases in old age—the same trajectory we see for raw-score perform­

ance on IQ tests and for speed and intraindividual consistency of RT in ECTs.

The speed and consistency of information processing generally show an in­

verted U curve across the life span.

 

interesting.

 

-

 

Jensen mentions the en.wikipedia.org/wiki/Yerkes-Dodson_law

interesting. i link to Wikipedia since i think its explanation of the law is better than Jensens, who just briefly mentions it.

 

-

 

[...Localized damage to the brain

areas that normally subserve one of these group factors can leave the person

severely impaired in the expression of the abilities loaded on the group factor,

but with little or no impairment of abilities that are loaded on other group factors

or on g.]

 

A classic example of this is females who are born with a chromosomal anom­

aly known as Turner’s syndrome.1701 Instead of having the two normal female

sex chromosomes (designated XX), they lack one X chromosome (hence are

designated XO). Provided no spatial visualization tests are included in the IQ

battery, the IQs of these women (and presumably their levels of g) are normally

distributed and virtually indistinguishable from that of the general population.

Yet their performance on all tests that are highly loaded on the spatial-

visualization factor is extremely low, typically borderline retarded, even in

Turner’s syndrome women with verbal IQs above 130. It is as if their level of

g is almost totally unreflected in their level of performance on spatial tasks.

 

It is much harder to imagine the behavior of persons who are especially

deficient in all abilities involving g and all of the major group factors, but have

only one group factor that remains intact. In our everyday experience, persons

who are highly verbal, fluent, articulate, and use a highly varied vocabulary,

speaking with perfect syntax and appropriate expression, are judged to be of at

least average or probably superior IQ. But there is a rare and, until recently,

little-known genetic anomaly, Williams syndrome,1711 in which the above-listed

characteristics of high verbal ability are present in persons who are otherwise

severely mentally deficient, with IQs averaging about 50. In most ways, Wil­

liams syndrome persons appear to behave with no more general capability of

getting along in the world than most other persons with similarly low IQs. As

adults, they display only the most rudimentary scholastic skills and must live

under supervision. Only their spoken verbal ability has been spared by this

genetic defect. But their verbal ability appears to be “ hollow” with respect to

g. They speak in complete, often complex, sentences, with good syntax, and

even use unusual words appropriately. (They do surprisingly well on the Pea­

body Picture Vocabulary Test.) In response to a series of pictures, they can tell

a connected and fully elaborated story, accompanied by appropriate, if somewhat

exaggerated, emotional expression. Yet they have exceedingly little ability to

reason, or to explain or summarize the meaning of what they say. On most

spatial ability tests they generally perform on a par with Down syndrome persons

of comparable IQ, but they also differ markedly from Down persons in peculiar

ways. Williams syndrome subjects are more handicapped than IQ-matched

Down subjects in figure copying and block designs.

 

Comparing Turner’s syndrome with Williams syndrome obviously suggests

the generalization that a severe deficiency of one group factor in the presence

of an average level of g is far less a handicap than an intact group factor in the

presence of a very low level of g.

 

never heard of Williams syndrome befor.

 

en.wikipedia.org/wiki/Williams_syndrome

 

-

 

The correlation of IQ with grades and achievement test scores is highest (.60

to .70) in elementary school, which includes virtually the entire child population

and hence the full range of mental ability. At each more advanced educational

level, more and more pupils from the lower end of the IQ distribution drop out,

thereby restricting the range of IQs. The average validity coefficients decrease

accordingly: high school (.50 to .60), college (.40 to .50), graduate school (.30

to .40). All of these are quite high, as validity coefficients go, but they permit

far less than accurate prediction of a specific individual. (The standard error of

estimate is quite large for validity coefficients in this range.)

 

interesting. one thing that i hav been thinking about is that my GPA thruout my life has always been a bit abov average, but not close to the top. given that the intelligence requirement for each new step on the way thru the school system increases, one wud hav expected a drop in GPA, but no such thing happened. in fact, its the other way around. my GPA is the danish elementary school is 9.3 (9th grade) the average is ~8.1. this includes grades from non-intellectual subjects such as the ‘subject’ of having a nice hand-writing (yes seriusly). in 10th grade my average was 8.7, and the average is ~6.6. the max is 13 in all cases, altho normally grades abov 11 wer not given.

 

in gymnasiet (high school equiv.ish), my GPA was 7.8 and the average is 7.0. the slightly slower grades is becus the system was changed from a 13-step to a 7-step scale. and for comparison reasons, one can note that i went to HTX which has lower grades. the percentile level is 65th.

 

my university grades befor dropping out of filosofy were rather good, lots of 10′s, but i dont know the average, so cant compare. i suspect they were abov average again.

 

-

 

Unless an individual has made the transition from word reading to reading

comprehension of sentences and paragraphs, reading is neither pleasurable nor

practically useful. Few adults with an IQ of eighty (the tenth percentile of the

overall population norm) ever make the transition from word reading skill to

reading comprehension. The problem of adult illiteracy (defined as less than a

fourth-grade level of reading comprehension) in a society that provides an ele­

mentary school education to virtually its entire population is therefore largely a

problem of the lower segment of the population distribution of g. In the vast

majority of people with low reading comprehension, the problem is not word

reading per se, but lack of comprehension. These individuals score about the

same on tests of reading comprehension even if the test paragraphs are read

aloud to them by the examiner. In other words, individual differences in oral

comprehension and in reading comprehension are highly correlated.12’1

 

80.. but the american black average is only about 85. is it really true that ~37% of them ar too dull to learn to read properly? compared with ~10% of whites.

 

-

 

Virtually every type of work calls for behavior that is guided by cognitive

processes. As all such processes reflect g to some extent, work proficiency is g

loaded. The degree depends on the level of novelty and cognitive complexity

the job demands. No job is so simple as to be totally without a cognitive com­

ponent. Several decades of empirical studies have shown thousands of correla­

tions of various mental tests with work proficiency. One of the most important

conclusions that can be drawn from all this research is that mental ability tests

in general have a higher success rate in predicting job performance than any

other variables that have been researched in this context, including (in descend­

ing order of average predictive validity) skill testing, reference checks, class

rank or grade-point average, experience, interview, education, and interest meas­

ures.1221 In recent years, one personality constellation, characterized as “ consci­

entiousness,” has emerged near the top of the list (just after general mental

ability) as a predictor of occupational success.

 

reminds me that i ought to look into this field of psychology. its called I/O psychology. som time back i talked with a phd (i think) on 4chan who studied that area. he said that if he had his way, he wud just rely on g alone to predict job performance, training etc. he recommended me a textbook, which i found on the internet.

 

Psychology Applied to Work, An Introduction to Industrial and Organizational Psychology – Paul M. Muchinsky

 

it seems decent.

 

-

 

A person cannot perform a job successfully without the specific knowledge

required by the job. Possibly such job knowledge could be acquired on the job

after a long period of trial-and-error learning. For all but the very simplest jobs,

however, trial-and-error learning is simply too costly, both in time and in errors.

Job training inculcates the basic knowledge much more efficiently, provided that

later on-the-job experience further enhances the knowledge or skills acquired in

prior job training. Because knowledge and skill acquisition depend on learning,

and because the rate of learning is related to g, it is a reasonable hypothesis that

g should be an effective predictor of individuals’ relative success in any specific

training program.

 

The best studies for testing this hypothesis have been performed in the armed

forces. Many thousands of recruits have been selected for entering different

training programs for dozens of highly specialized jobs based on their perform­

ance on a variety of mental tests. As the amount of time for training is limited,

efficiency dictates assigning military personnel to the various training schools

so as to maximize the number who can complete the training successfully and

minimize the number who fail in any given specialized school. When a failed

trainee must be rerouted to a different training school better suited to his apti­

tude, it wastes time and money. Because the various schools make quite differing

demands on cognitive abilities, the armed services employ psychometric re­

searchers to develop and validate tests to best predict an individual’s probability

of success in one or another of the various specialized schools.

 

 

one is tempted to say ”common sense”, but apparently, only the military dares to do such things.

 

-

 

A rough analogy may help to make the essential point. Suppose that for some

reason it was impossible to measure persons’ heights directly in the usual way,

with a measuring stick. However, we still could accurately measure the length

of the shadow cast by each person when the person is standing outdoors in the

sunlight. Provided everyone’s shadow is measured at the same time of day, at

the same day of the year, and at the same latitude on the earth’s surface, the

shadow measurements would show exactly the same correlations with persons’

weight, shoe size, suit or dress size, as if we had measured everyone directly

with a yardstick; and the shadow measurements could be used to predict per­

fectly whether or not a given person had to stoop when walking through a door

that is only 5 ‘/2 -feet high. However, if one group of persons’ shadows were

measured at 9:00 a .m . and another group’s at 10:00 a .m ., the pooled measure­

ments would show a much smaller correlation with weight and other factors

than if they were all measured at the same time, date, and place, and the meas­

urements would have poor validity for predicting which persons could walk

through a 5 ‘/2 -foot door without stooping. We would say, correctly, that these

measurements are biased. In order to make them usefully accurate as predictors

of a person’s weight and so forth, we would have to know the time the person’s

shadow was measured and could then add or subtract a value that would adjust

the measurement so as to make it commensurate with measurements obtained

at some other specific time, date, and location. This procedure would permit the

standardized shadow measurements of height, which in principle would be as

good as the measurements obtained directly with a measuring stick.

 

Standardized IQs are somewhat analogous to the standardized shadow meas­

urements of height, while the raw scores on IQ tests are more analogous to the

raw measurements of the shadows themselves. If we naively remain unaware

that the shadow measurements vary with the time of day, the day of the year,

and the degrees of latitude, our raw measurements would prove practically

worthless for comparing individuals or groups tested at different times, dates,

or places. Correlations and predictions could be accurate only within each unique

group of persons whose shadows were measured at the same time, date, and

place. Since psychologists do not yet have the equivalent of a yardstick for

measuring mental ability directly, their vehicles of mental measurement—IQ

scores—are necessarily “ shadow” measurements, as in our height analogy, al­

beit with amply demonstrated practical predictive validity and construct validity

within certain temporal and cultural limits.

 

 

interesting. however, biologically based tests shud allow for absolut measurement, say tests based on RT in ECTs, or tests based on the amount of mylianation in the brain, or brain ph levels, brain size via brain imaging scans if we can make them better measurements of g, etc.

 

-

 

Many possible factors determine whether a person passes or fails a particular

test item. Does the person understand the item at all (e.g., “What is the sum of

all the latent roots of a 7 X 7 R matrix?” )? Has the person acquired the specific

knowledge called for by the item (e.g., “Who wrote Faust?”), or perhaps has

he acquired it in the past and has since forgotten it? Did the person really know

the answer, but just couldn’t recall it at the moment of being tested? Does the

item call for a cognitive skill the person either never acquired or has forgotten

through disuse (e.g., “ How much of a whole apple is two-thirds of one-half of

the apple?” )? Does the person understand the problem and know how to solve

it, but is unable to do it within the allotted time limit (e.g., substituting the

corresponding letter of the alphabet for each of the numbers from one to twenty-

six listed in a random order in one minute)? Or even when there is a liberal

time limit does the person give up on the item or just guess at the answer

prematurely, perhaps because the item looks too complicated at first glance (e.g.,

“ If it takes six garden hoses, all running for three hours and thirty minutes to

fill a tank, how many additional hoses would be needed to fill the tank in thirty

minutes?” )?

 

1) dunno

2) Goethe

3) 2/3*1/2=4/6*3/6=12/36=1/3

4) #hose*time=tank size

6*3.5=21

21 is the size of the tank

21=0.5*#hose, solve #hose

42=#hose

42-6=36

36 more hoses

 

-

 

The only study I have found that investigated whether there has been a secular

change (over thirty years) in the heritability of g-loaded test scores concluded

that “ the results revealed no unambiguous evidence for secular trends in the

heritability of intelligence test scores.” 1351 However, the heritability coefficients

(based on twenty-two same-age cohort samples of MZ and DZ male twins born

in Norway between 1930 and 1960) showed some statistically reliable nonlinear

trends over the thirty-year period, as shown in Figure 10.2. The overall trend

line goes equally down-up-down-up with heritability coefficients ranging from

slightly above .80 to slightly below .40. The heritability coefficient was the same

for the cohort born in 1930 as for the cohort born in 1960 (for both, h2 = .80).

The authors offer only weak ad hoc speculations about possible causes of this

erratic fluctuation of h2 across 22 points in time.

 

the hole is the german occupation of norway. the data from the 30s make sense to me, the depression wud result in civil unrest and the changing up of society. after a period of such, heritabilities shud stabilize again, as seen in the after war period. i dont understand the 50s down swing in heritability.

 

so, i thought it might be somthing economic. i gathered GDP data, and looked at the data. nope, not true.

 

www.norges-bank.no/pages/77409/p1_c6.xlsx

 

data from 1901 to 2000 looks like this:

gdp norway 50s

 

doesnt fit with the GDP hypothesis at all, except for missing data in the war.

 

i dunno, perhaps www.newsinenglish.no/2010/06/16/the-50s-in-norway-werent-so-nifty/

 

the authors of the study that found the drop in heritability also dont know ”We are, however, quite at a loss in explaining the dip from about 1950 to 1954. Thus, we feel that the best strategy at present is to leave the issue of secular trends open. ”

On the question of secular trends in the heritability of intelligence scores A study of Norwegian twins

-

 

Head Start. The federal preschool intervention known as Head Start, which

has been in continual existence now since 1964, is undoubtedly the largest-

scale, though not the most intensive, educational intervention program ever un­

dertaken, with an annual expenditure over $2 billion. The program is aimed at

improving the health status and the learning and social skills of preschoolers

from poor backgrounds so they can begin regular school more on a par with

children from more privileged backgrounds. The intervention is typically short­

term, with various programs lasting anywhere from a few months to two years.

 

The general conclusion of the hundreds of studies based on Head Start data

is that the program has little, if any, effect on IQ or scholastic achievement that

endures beyond more than two to three years after exposure to Head Start. The

program does, however, have some potential health benefits, such as inoculations

of enrollees against common childhood diseases and improved nutrition (by

school-provided breakfast or lunch). The documented behavioral effects are less

retention-in-grade and lower dropout rates. The cause(s) of these effects are

uncertain. Because eligible children were not randomly enrolled in Head Start,

but were selected by parents and program administrators, these scholastic cor­

relates of Head Start are uninterpretable from a causal standpoint. Selection,

rather than direct causation by the educational intervention itself, could be the

explanation of Head Start’s beneficial outcomes.

 

crazy amount of money spent for som slight health benefits. perhaps ther is a cheaper way to get such benefits.

 

-

 

The Milwaukee Project. Aside from Head Start, this is the most highly

publicized of all intervention experiments. It was the most intensive and exten­

sive educational intervention ever conducted for which the final results have

been published.55 It was also the most costly single experiment in the history of

psychology and education—over $14 million. In terms of the highest peak of

IQ gains for the seventeen children in the treatment condition (before the gains

began to vanish), the cost was an estimated $23,000 per IQ point per child.

 

holy shit. even tho i think iv seen this figur befor (in The g Factor by Chris Brand).

 

Jensen also doesnt mention the end of the project, but Wikipedia does:

en.wikipedia.org/wiki/Milwaukee_Project

 

The Milwaukee Project’s claimed success was celebrated in the popular media and by famous psychologists. However, later in the project Rick Heber, the principal investigator, was discharged from the University of Wisconsin–Madison and convicted and imprisoned for large-scale abuse of federal funding for private gain. Two of Heber’s colleagues in the project were also convicted for similar abuses. The project’s results were not published in any refereed scientific journals, and Heber did not respond to requests from colleagues for raw data and technical details of the study. Consequently, even the existence of the project as described by Heber has been called into question. Nevertheless, many college textbooks in psychology and education have uncritically reported the project’s results.[3][4]

 

this reminds me why open data is necessary in science.

 

-

 

[The Abecedarian Early Intervention Project.]

Both the T and C groups (each with about fifty subjects) were given age-

appropriate mental tests (Bayley, Stanford-Binet, McCarthy, WPPSI) at

six-month intervals from age six months to sixty months. The important com­

parisons here are the mean T-C differences at each testing. (Because the test

scores do not have the same factor composition across this wide age range,

the absolute scores of the T group alone are not as informative of the efficacy

of the intervention as are the mean T-C differences.) At every testing from six

months to five years of age, the T group outperformed the C group, and the

overall average T-C difference (103.3 — 95.5 = 7.8 IQ points) was highly

significant (p < .001). Peculiarly, however, the largest T-C differences (aver­

aging fifteen IQ points) occurred between eighteen and thirty-six months of

age and then declined during the last two years of intervention. At sixty

months, the average T-C difference was 7.5 IQ points. This decrease might

simply reflect the fact that with the children’s increasing age the tests become

increasingly more g-Ioaded. The tests used before two or three years of age

measure mainly perceptual-motor functions that have relatively little g satura­

tion. Only later does g becomes the predominant component of variance in

IQ. In follow-up studies at eight and twelve years of age, the T-C difference

on the WISC-R was about five IQ points,1571 a difference that has remained up

to age fifteen. At the last reported testing, the T-C difference was 4.6 IQ

points, or a difference of 0.35ct. Scholastic achievement test scores showed a

somewhat larger effect of the intervention up to age fifteen.1571 The interven­

tion effect on other criteria of the project’s success was demonstrated by the

decreased percentage of children who repeated at least one grade by age

twelve (T = 28 percent, C = 55 percent) and the percentage of children with

borderline or retarded intelligence (IQ < 85) (T = 12.8 percent, C = 44.2

percent).1561

 

Thus this five-year program of intensive intervention beginning in early in­

fancy increased IQ (at age fifteen years) by about five points. Judging from a

comparable gain in scholastic achievement, the effect had broad transfer, sug­

gesting that it probably raised the level of g to some extent. The finding that

the T subjects did better than the C subjects on a battery of Piaget’s tests of

conservation, which reflect important stages in mental development, is further

evidence. The Piagetian tests are not only very different in task demands from

anything in the conventional IQ tests used in the conventional assessments, but

are also highly g loaded.1571 The mean T-C difference on the Piagetian conser­

vation tests was equal to 0.33a (equivalent to five IQ points). Assuming that

the instructional materials in the intervention program did not closely resemble

Piaget’s tests, it is a warranted conclusion that the intervention appreciably

raised the Level of g.

 

im still skeptical as to the g effects. id like to see the data about them as adults, and a larger sample size.

 

again, Wikipedia has mor on the issue, both positiv and negativ:

en.wikipedia.org/wiki/Abecedarian_Early_Intervention_Project

Significant findings

Follow-up assessment of the participants involved in the project has been ongoing. So far, outcomes have been measured at ages 3, 4, 5, 6.5, 8, 12, 15, 21, and 30.[5] The areas covered were cognitive functioning, academic skills, educational attainment, employment, parenthood, and social adjustment. The significant findings of the experiment were as follows:[6][7]

Impact of child care/preschool on reading and math achievement, and cognitive ability, at age 21:

• An increase of 1.8 grade levels in reading achievement
• An increase of 1.3 grade levels in math achievement
• A modest increase in Full-Scale IQ (4.4 points), and in Verbal IQ (4.2 points).

Impact of child care/preschool on life outcomes at age 21:

• Completion of a half-year more of education
• Much higher percentage enrolled in school at age 21 (42 percent vs. 20 percent)
• Much higher percentage attended, or still attending, a 4-year college (36 percent vs. 14 percent)
• Much higher percentage engaged in skilled jobs (47 percent vs. 27 percent)
• Much lower percentage of teen-aged parents (26 percent vs. 45 percent)
• Reduction of criminal activity

Statistically significant outcomes at age 30:

• Four times more likely to have graduated from a four-year college (23 percent vs. 6 percent)
• More likely to have been employed consistently over the previous two years (74 percent vs. 53 percent)
• Five times less likely to have used public assistance in the previous seven years (4 percent vs. 20 percent)
• Delayed becoming parents by average of almost two years

(Most recent information from Developmental Psychology, January 18, 2012, cited in uncnews.unc.edu, January 19, 2012)

The project concluded that high quality, educational child care from early infancy was therefore of utmost importance.

Other, less intensive programs, notably the Head Start Program, but also others, have not been as successful. It may be that they provided too little too late compared with the Abecedarian program.[4]

Criticisms

Some researchers have advised caution about the reported positive results of the project. Among other things, they have pointed out analytical discrepancies in published reports, including unexplained changes in sample sizes between different assessments and publications. It has also been noted that the intervention group’s reported 4.6 point advantage in mean IQ at age 15 was not statistically significant. Herman Spitz has noted that a mean IQ difference of similar magnitude to the final difference between the intervention and control groups was apparent already at age six months, indicating that “4 1/2 years of massive intervention ended with virtually no effect.” Spitz has suggested that the IQ difference between the intervention and control groups may have been present from the outset due to faulty randomization.[8]

 

not quite sure what to think. the sample sizes ar still kind small, and if Spitz is right in his criticism, the studies hav not shown much.

 

the reason that im skeptical to begin with is that the modern twin studies show, that shared environment, which is what these studies change to a large degree, has no effect on adult IQ.

 

in any case, if it requires so expensiv spendings to get slightly less dumb kids, its hard to justify as a public policy. at the very least, id like to see the calculation that finds that this has a net positiv benefit for society. it is possible, for instance, becus crime rates ar (supposedly) down, and job retention up which leads to mor taxes being paid, and so on.

 

-

 

Error distractors in multiple-choice answers are of interest as a method of

discovering bias. When a person fails to select the correct answer but instead

chooses one of the alternative erroneous responses (called “ distractors” ) offered

for an item in a multiple-choice test, the person’s incorrect choice is not random,

but is about as reliable as is the choice of the correct answer. In other words,

error responses, like correct responses, are not just a matter of chance, but reflect

certain information processes (or the failure of certain crucial steps in infor­

mation processing) that lead the person to choose not just any distractor, but a

particular one. Some types of errors result from a solution strategy that is more

naive or less sophisticated than other types of errors. For example, consider the

following test item:

 

If you mix a pint of water at 50° temperature with two pints of water at 80°

measured on the same thermometer, what will be the temperature of the mix­

ture? (a) 65°, (b) 70°, (c) 90°, (d) 130°, (e) Can’t say without knowing

whether the temperatures are Centigrade or Fahrenheit.

 

We see that the four distractors differ in the level of sophistication in mental

processing that would lead to their choice. The most naive distractor, for ex­

ample, is D, which is arrived at by simple addition of 50° and 80°. The answer

A at least shows that the subject realized the necessity for averaging the tem­

peratures. The answer 90° is the most sophisticated distractor, as it reveals that

the subject had a glimmer of the necessity for a weighted average (i.e., 50° +

8072 = 90°) but didn’t know how to go about calculating it. (The correct

answer, of course, is B, because the weighted average is [1 pint X 50° + 2

pints X 80°]/3 pints = 70°.) Preference for selecting different distractors changes

across age groups, with younger children being attracted to the less sophisticated

type of distractor, as indicated by comparing the percentage of children in dif­

ferent age groups that select each distractor. The kinds of errors made, therefore,

appear to reflect something about the children’s level of cognitive development.

 

interesting.

 

-

 

What is termed a cline results where groups overlap at their fuzzy boundaries

in some characteristic, with intermediate gradations of the phenotypic charac­

teristic, 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 cat­

egories.

 

while the rainbow analogy works to som extent, it is not that good. the reason is that with rainbows, all the colors (groups) ar on a continuum in such a way that ther isnt a blend between every two colors (groups). this is not how races work, as ther is always the possibility of a blend between any two groups, even odd groups such as amerindians and aboriginals.

 

-

 

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.[12] 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.

 

the same point was made, altho less technically, in Hjernevask. ther is no good apriori reason to think that natural selection for som reason only worked on non-brain, non-behavioral genes. it simply makes no sense at all to suppose that.

 

-

 

Bear in mind that, from the standpoint of natural selection, a larger brain

size (and its corresponding larger head size) is in many ways decidedly disad­

vantageous. A large brain is metabolically very expensive, requiring a high-

calorie diet. Though the human brain is less than 2 percent of total body weight,

it accounts for some 20 percent of the body’s basal metabolic rate (BMR). In

other primates, the brain accounts for about 10 percent of the BMR, and for

most carnivores, less than 5 percent. A larger head also greatly increases the

difficulty of giving birth and incurs much greater risk of perinatal trauma or

even fetal death, which are much more frequent in humans than in any other

animal species. A larger head also puts a greater strain on the skeletal and

muscular support. Further, it increases the chances of being fatally hit by an

enemy’s club or missile. Despite such disadvantages of larger head size, the

human brain, in fact, evolved markedly in size, with its cortical layer accom­

modating to a relatively lesser increase in head size by becoming highly con­

voluted in the endocranial vault. In the evolution of the brain, the effects of

natural selection had to have reflected the net selective pressures that made an

increase in brain size disadvantageous versus those that were advantageous. The

advantages obviously outweighed the disadvantages to some degree or the in­

crease in hominid brain size would not have occurred.

 

this brain must hav been very useful for somthing. if som of this use has to do with non-social things, like environment, one wud expect to see different levels of ‘brain adaptation’ due to the relative differences in selection pressure in populations that evolved in different environments.

 

-

 

How then can the default hypothesis be tested empirically? It is tested exactly

as is any other scientific hypothesis; no hypothesis is regarded as scientific unless

predictions derived from it are capable of risking refutation by an empirical test.

Certain predictions can be made from the default hypothesis that are capable of

empirical test. I f the observed result differs significantly from the prediction, the

hypothesis is considered disproved, unless it can be shown that the tested pre­

diction was an incorrect deduction from the hypothesis, or that there are artifacts

in the data or methodological flaws in their analysis that could account for the

observed result. If the observed result does in fact accord with the prediction,

the hypothesis survives, although it cannot be said to be proven. This is because

it is logically impossible to prove the null hypothesis, which states that there is

no difference between the predicted and the observed result. If there is an al­

ternative hypothesis, it can also be tested against the same observed result.

 

For example, if we hypothesize that no tiger is living in the Sherwood Forest

and a hundred people searching the forest fail to find a tiger, we have not proved

the null hypothesis, because the searchers might have failed to look in the right

places. I f someone actually found a tiger in the forest, however, the hypothesis

is absolutely disproved. The alternative hypothesis is that a tiger does live in

the forest; finding a tiger clearly proves the hypothesis. The failure of searchers

to find the tiger decreases the probability of its existence, and the more search­

ing, the lower is the probability, but it can never prove the tiger’s nonexistence.

 

Similarly, the default hypothesis predicts certain outcomes under specified

conditions. If the observed outcome does not differ significantly from the pre­

dicted outcomes, the default hypothesis is upheld but not proved. If the predic­

tion differs significantly from the observed result, the hypothesis must be

rejected. Typically, it is modified to accord better with the existing evidence,

and then its modified predictions are empirically tested with new data. If it

survives numerous tests, it conventionally becomes a “ fact.” In this sense, for

example, it is a “ fact” that the earth revolves around the sun, and it is a “ fact”

that all present-day organisms have evolved from primitive forms.

 

meh, mediocre or bad filosofy of science.

 

-

 

 

 

the problem with this data is that the women were not don having children. the data is from women aged 34. since especially smart women (and so mor whites) hav children later than that age, their fertility estimates ar spuriusly low. see also the data in Intelligence: A Unifying Construct for the Social Sciences (Richard Lynn and Tatu Vanhanen, 2012).

 

-

 

Whites perform significantly better than blacks on the subtests called Com­

prehension, Block Design, Object Assembly, and Mazes. The latter three tests

are loaded on the spatial visualization factor of the WISC-R. Blacks perform

significantly better than whites on Arithmetic and Digit Span. Both of these tests

are loaded on the short-term memory factor of the WISC-R. (As the test of

arithmetic reasoning is given orally, the subject must remember the key elements

of the problem long enough to solve it.) It is noteworthy that Vocabulary is the

one test that shows zero W-B difference when g is removed. Along with Infor­

mation and Similarities, which even show a slight (but nonsignificant) advantage

for blacks, these are the subtests most often claimed to be culturally biased

against blacks. The same profile differences on the WISC-R were found in

another study|8lbl based on 270 whites and 270 blacks who were perfectly

matched on Full Scale IQ.

 

seems inconsistent with typical environment only theories.

 

-

 

 

The 10000 year explosion – Gregory Cochran and Henry Harpending, download, free, ebook, pdf

 

This is a nontechnical overall introduction to how human evolution has happened. it mentions a lot of stuff i didnt know. i wud have liked more references. the book is openly race realist, and i was waiting for it to mention that the reason Africa is so backwards is that africans are so dumb, but it was only hinted at. instead, the authors focused the last chapter on a higher than average group, the jews. this is probably a smart move. once it has been acknowledged that the asians and jews are smarter than whites, one cannot shrug off other racial differences as being due to white racism, white supremacy, biased IQ tests, and so on.

 

Quotes and comments below.

 

There’s been no biological change in humans in 40,000 or

50,000 years. Everything we call culture and civilization

we’ve built with the same body and brain.

—Stephen Jay Gould

 

wat. even supposing that natural selection (lack of reproduction due to death/injury) was set out of motion (as it nearly is in todays welfare states), there wud still be sexual selection.

 

but it does fit with Goulds punctuated equilibrium ideas.

 

-

 

Their behavior has changed as well: Dogs are good at read­

ing human voice and gestures, while wolves can’t understand us

at all. Male wolves pair-bond with females and put a lot of ef­

fort into helping raise their pups, but male dogs—well, call

them irresponsible. There have been substantial changes in dogs

in just the past couple of centuries: Most of the breeds we know

today are no older than that.

 

In an extreme example, the Russian scientist Dmitri Belyaev

succeeded in developing a domesticated fox in only forty years.5

In each generation he selected for tameness (and only tame­

ness); this eventually resulted in foxes that were friendly and

enjoyed human contact, in strong contrast to wild foxes. This

strain of tame foxes also changed in other ways: Their coat color

lightened, their skulls became rounder, and some of them were

born with floppy ears. It seems that some of the genes influenc­

ing behavior (tameness in this case) also affect other traits—so

when Belyaev selected for tameness, he automatically got changes

in those other traits as well. Many of these changes have occurred

as side effects of domestication in a number of species—possibly

including humans, as we shall see.

 

very cool. more here: en.wikipedia.org/wiki/Tame_Silver_Fox

 

-

 

Changes in domesticated plants can be just as impressive.

Corn, or maize, which is derived from a wild grass named

teosinte, has changed wildly in only 7,000 years. I t ’s hard to be­

lieve that maize and teosinte are closely related.

Such dramatic responses to selection aren’t isolated cases—

they’ve occurred in many domesticated species and continue to

occur today. Evolutionary genetics predicts that substantial

change in almost any trait is possible in a few tens of genera­

tions, and those predictions are confirmed every day. Selection is

used routinely in many kinds of agriculture, and it works: It

grows more corn, lots more. You can’t argue with corn.

chuckle

 

-

 

While there has probably not been enough time for dogs to

develop wholly new complex adaptations, there has certainly

been enough time to lose some, sometimes in all breeds, but

other times only in a subset of dog breeds. Wolf bitches dig

birthing dens; a few breeds of dogs still do, but most do not.

Wolves go into season in a predictable way, at a fixed time of the

year; a few dog breeds do, but most do not. Wolves regurgitate

food for weaned cubs, but dogs no longer do so. Male wolves

help care for their offspring, but male dogs do not. Any adapta­

tion, whether physical or behavioral, that loses its utility in a

new environment can be lost rapidly, especially if it has any no­

ticeable cost. Fish in lightless caves lose their sight over a few

thousand years at most—much less time than it took for eyes to

evolve in the first place.

 

In some sense these are evolutionarily shallow changes,

mostly involving loss of function or exaggerations and redirec­

tions of function. Although such changes will not produce gills

or sonar, they can accomplish amazing things. Dogs are all one

species, but as we have noted, they vary more in morphology

than any other mammal and have developed many odd abilities,

including learning abilities: Dog breeds vary greatly in learning

speed and capacity. The number of repetitions required to learn

a new command can vary by factors of ten or more from one

breed to another. The typical Border collie can learn a new com­

mand after 5 repetitions and respond correctly 95 percent of

the time, whereas a basset hound takes 80-100 repetitions to

achieve a 25 percent accuracy rate.

 

very interesting! see also:

en.wikipedia.org/wiki/Border_Collie

en.wikipedia.org/wiki/Dog_intelligence

en.wikipedia.org/wiki/The_Intelligence_of_Dogs

 

im definitely going to add the last book to my to read list: Coren, Stanley (1995). The Intelligence of Dogs: A Guide To The Thoughts, Emotions, And Inner Lives Of Our Canine Companions. New York: Bantam Books. ISBN 0-553-37452-4.

 

as for the rankings listed in the third article above. it seems obvious that they shud be compared for cranium and brain size (measured by brain scans) and see if that correlates with their intelligence rankings. ill bet that it does, just like for both between and within human populations.

 

-

 

But even then, we knew from our experience with animal

and plant breeding, along with observation of many examples of

rapid evolution in nature, that there could be significant evolu­

tionary change in 10,000 years or less. It was also clear that

modest genetic differences between groups could cause big trait

differences. Indeed, entirely divergent life strategies can be

caused by differences in a single gene, as we see in fire ants,

where ants with one version of a pheromone receptor live in in­

dependent colonies, each having a single queen, while those

with the other version live in a sprawling metacolony with many

queens.17 Well before the revolution in genomics, it was clear

enough that there could be significant differences between human

populations in almost any trait, despite recent common ancestry.

It was clear that this was entirely compatible with what we knew

of genetics, and it was also clear that at least some such differ­

ences existed in skin color, size, morphology, and metabolism.

 

Very cool. the cite given is: Laurent Keller and Kenneth G. Ross, “Selfish Genes: A Green

Beard in the Red Fire Ant,” Nature 394 (1998): 573; Michael J. B.

Krieger and Kenneth G. Ross, “Identification of a Major Gene Regulat­

ing Complex Social Behavior,” Science 295, no. 5553 (2002): 328-332.

 

-

 

BUT I DON’T WANT TO BE PART NEANDERTHAL!

There is often a visceral reaction to the idea that we carry some

Neanderthal genes. Probably this is due to the general impres­

sion that Neanderthals were backward and apelike. Neanderthals

weren’t really apelike, although they were behind the times—but

since it looks, in any case, as if we’ve absorbed only their best

(most useful) traits, we can be happy about our Neanderthal

ancestry, proud even. At any rate, it could be worse: We could

have picked up genes from a virus. In fact, it is worse: We have.

Most viruses (which are basically just bags full of DNA or

RNA) slip into cells and then take over, making copies of them­

selves and usually killing the host cells in the process. But some

RNA viruses (retroviruses, like HIV) copy their RNA into

DNA and then, sometimes, integrate that DNA into the host

cell’s genome. I f the retrovirus happens to occupy a reproduc­

tive cell, one that makes sperm or eggs, the retroviral genes can

actually become part of the next generation’s genome. This has

happened in the past: Humans have many genetic remnants of

retroviruses that at one time inserted copies of themselves into

the human genome. Most do not seem to have any real func­

tion, but a few do. For example, both humans and apes have

syncytin, derived from a retroviral envelope protein that our an­

cestors picked up roughly 30 million years ago. It plays a role in

the development of the placenta—in particular, the process that

leads to the development of a fused cell layer. Anyone who’s

overly worried about possible Neanderthal ancestry should re­

member that we’re certainly descended from viruses. As usual,

the facts don’t care about our feelings.

 

thats cool

 

-

 

When you think about it, the whole process is rather

strange: Northern Europeans and some sub-Saharan Africans

have become “mampires,” mutants that live off the milk of an­

other species. We think lactose-tolerance mutations played an

important role in history, a subject we will treat at some length

in Chapter 6.

 

i hav often thought the same.

 

-

 

Science as we know it got its official start in Europe in the

sixteenth century with the publication of Copernicus’s work De

revolutionibus in 1543. The closest thing to modern science seen

before that would have been the protoscience practiced by the

Greek and, later, Arab civilizations—but they’re not that close.

The productivity and intensity of modern science far outshines

earlier efforts. Some of the most important European scien­

tists, such as Isaac Newton, James Clerk Maxwell, and Charles

Darwin, made larger intellectual contributions as individuals

than other entire civilizations did over a period of centuries.

 

true, but kinda mean. think about it!

 

-

 

Technical and social factors must have been important in

increasing social connectivity: Better transportation, regular

mail services, and the printing press, for example, played essen­

tial roles. Although inventions such as the printing press were

undoubtedly important, they seem to have been necessary rather

than sufficient, since science either does not exist or is appallingly

feeble in the majority of the world’s populations, even among

those that have access to those favorable technological factors. If

a region or population produces major advances in knowledge,

science there is real and alive, otherwise not. By that standard,

science does not exist in sub-Saharan Africa or in the Islamic

world today. As Pervez Hoodbhoy (head of the physics depart­

ment in Islamabad) has written, “No major invention or discov­

ery has emerged from the Muslim world for well over seven

centuries now.”30

 

the reference is presumably this: islamicvoice.com/January2008/Islam&Science/index.php

its worth a read. try f.i.:

 

Let us look at the state of science in the current Islamic world. A study by academics at the International Islamic University, Malaysia, showed that OIC countries have 8.5 scientists, engineers, and technicians per 1,000 population, compared with a world average of 40.7, and 139.3 for countries of the Organisation for Economic Co-operation and Development. Forty-six Muslim countries contributed 1.17 per cent of the world’s science literature, whereas 1.66 per cent came from India alone and 1.48 per cent from Spain. Twenty Arab countries contributed 0.55 per cent, compared with 0.89 per cent by Israel alone. Of the 28 lowest producers of scientific articles in 2003, half belong to the OIC.

 

-

 

Every selective sweep starts out as a change in the DNA of a

sperm or egg. Such changes can be caused by chemicals, radia­

tion, or just random jostling of molecules—but what matters to

us is that such changes do occur. Mutations favorable enough

to initiate a sweep are extremely rare. One set of human DNA

has about 3 billion nucleotides, and an average person has about

100 new mutations. Most of those changes are in DNA that ap­

parently does nothing at all—only 2 percent of our DNA does

anything (as far as we know)—but on average, two or three of

those mutations affect functional DNA. Still, they do not usu­

ally make a significant difference, either in a positive or a nega­

tive way.

 

hasnt this simplistic notion of junk DNA been disproven?

en.wikipedia.org/wiki/Junk_DNA

 

see especially www.sciencemag.org/content/337/6099/1159

 

This week, 30 research papers, including six in Nature and additional papers published online by Science, sound the death knell for the idea that our DNA is mostly littered with useless bases. A decade-long project, the Encyclopedia of DNA Elements (ENCODE), has found that 80% of the human genome serves some purpose, biochemically speaking. Beyond defining proteins, the DNA bases highlighted by ENCODE specify landing spots for proteins that influence gene activity, strands of RNA with myriad roles, or simply places where chemical modifications serve to silence stretches of our chromosomes.

 

that the authors apparently do not know this raises some doubts about their other knowledge of genetics. they also dont provide a source for their claim, indicating that they think it is common knowledge. well, it was common belief but it turned out to be wrong (so it wasnt knowledge at all).

 

a very favorable reading of their claim wud take it that they were simply refering to non-coding DNA, for which the 98% number holds true. but being non-coding (for proteins) does not exactly imply that it “does nothing at all”.

 

-

 

the authors mention the interesting case of en.wikipedia.org/wiki/ApoA-1_Milano

 

-

 

 

Richard Lynn was so kind to send me a signed copy of his latest book. i immediately paused the reading of another book to read this one. some comments and quotes are below. quotes are from the ebook version of the book which i found on the internet.

Richard Lynn, Tatu Vanhanan – Intelligence, a A Unifying Construct for the Social Sciences, 2012

Review

Some general conclusions about the book. All in all this is a typical Richard Lynn book. It has a very dry style, and is somewhat repetitive. On the other hand, it is not overly long at 400 pages. Many of these are long lists of tables, so are not normally read except if one wants to look up specific countries. It would perhaps have been a good idea to just publish them on the internet for the curious and other researchers. The book contains a wealth of citations revealing a very impressive scholarship. The areas investigated on a global level are many, and the results interesting. The people who think that national IQs are “meaningless” and that human races do not exist or are social constructions (whatever that means, if anything) have the difficult job of explaining why, if these numbers are meaningless, do they fare so well in predicting things on a global level? In other words, why do they have so high validity for a multitude of things? One cannot just regard IQ as “academic intelligence” or some such thing if one can effectively use national IQs to predict things like the lack of proper sanitation. Most often national IQs are found to be better predictors than various non-IQ variables. Although one some occasions I would have liked the authors to use some more variables to see whether they made an impact. I think the authors are sometimes a bit too pessimistic about the possibilities of changing the situation for the low-IQ countries, but I agree with them that one should not expect many of these correlations to change drastically in the near future.

 

Thoughts and comments to various things

The introduction of the book neatly and shortly explains what the book is about:

The physical sciences are unified by a few common theoretical
constructs, such as mass, energy, pressure, atoms, molecules and
momentum, that are defined and measured in the same ways and
explain a wide range of phenomena in physics, astrophysics,
chemistry and biochemistry. This has been beneficial for the
development of the physical sciences, because it has allowed the
transfer of concepts from one field to others. It has allowed
interface subjects like chemical physics and biochemistry to
develop their own insights and concepts on the basis of those
already developed in their parent fields. Physics is the most basic
of the natural sciences, because the phenomena of the others can
be explained by the laws of physics. For this reason, physics has
been called the queen of the physical sciences.

Hitherto, the social sciences have lacked common unifying
constructs of this kind. The disciplines of the social sciences,
comprising psychology, economics, political science,
demography, sociology, criminology, anthropology and
epidemiology are largely isolated from one another, each with
their own vocabulary and theoretical constructs.
Psychology can be considered the most basic of the social
sciences because it is concerned with differences between
individuals, while the other social sciences are principally
concerned with differences between groups such as socio-
economic classes, ethnic and racial populations, regions within
countries, and nations. These groups are aggregates of
individuals, so the laws that have been established in psychology
should be applicable to the group phenomena that are the concern
of the other social sciences.
Our objective in this book is to develop the case that the
psychological construct of intelligence can be a unifying
explanatory construct for the social sciences. Intelligence is
measured by the intelligence test that was constructed by Alfred
Binet in 1905. During the succeeding century it has been shown
that intelligence, measured as the IQ (the intelligence quotient),
is a determinant of many important social phenomena,
including educational attainment, earnings, socio-economic
status, crime and health. Our theme is that the explanatory value
of intelligence that has been established for individuals can be
extended to the explanation of the differences between groups,
that have been found in the other social sciences, and in
particular to the explanation of the differences between nations.
Thus, we propose that psychology is potentially the queen of
the social sciences, analogous to the position of physics as the
queen of the physical sciences. (p. 1-2)

It is difficult to disagree with this.

-

one of the things that bother me with the Health chapter is that it doesnt try to compare with and adjoin with the data from The Spirit Level. The authors of SPL contend that many of the things that Lynn&Vanhanan (LV) thinks is due to intelligence, is really due to economic (in)equality. unfortunately, LV does not try to control for this. it wud be interesting to see if the effects of high econ. equality goes away if one controls for intelligence. in other words, that the effects of econ. equality is really just intelligence working thru it.

For a video introduction to the SPL, see this:

-

one annoying thing about this book, is that it is full of data tables, and the data from these cannot easily be copied into something useful. at least, i have failed to do it in any easy way. it requires a lot of fiddling to get the formatting right in calc/excel. hopefully, LV will make data tables available on their websites where they can easily be downloaded so that others can test out other hypotheses.

many of the tables span two pages but are not that big and cud easily fit into a single table on one page. unfortunately, having to use the image now requires that one either zooms out a lot to fit it all into one screen before taking a screenshot and hence makes the text small, or take two screenshots and edit them together in an image editor. it wud be very nice if they were made available on the website for free use.

-

a recurrent thing about the book is that the editor did quite a poor job. there are a lot of easily visible typografical mistakes that are a bit annoying. they dont distract too much from the reading of the book, except in the rare cases where a missing word makes interpretation necessary. for instance, on p. 83-84 table 4.5, the 10th line is missing the prefix “in” which makes it appear as if the data presented varies wildly from a positive 0.61 correlation to three other strong negative correlations between -.52 and -0.60.

there was also another place where a “not” was missing and this left me confused for a few seconds.

as for formatting, look at table 7.1, line 1, the word “All” is strangely located in a line below the other information. look also to lines 10-11 and notice how the two “F” are floating to the left.

these mistakes shud be fixed and a new online edition released. this cant be too difficult to do.

-

notice how low the dysgenic effects are. i was under the impression that they were stronger. also keep in mind that the lines 14-17 are those with the best data. the reason for that is that:

Rows 2, 3 and 4 give negative correlations between
intelligence and fertility based on a nationally representative
American sample showing that the negative correlation is higher
for white women than for white men, and higher for white
women than for black women. This study is not wholly
satisfactory because the age of the sample was 25 to 34 years and
many of them would not have completed their fertility.

To overcome this problem, Vining (1995) published data on
the fertility of his female sample of the ages between 35 and 44,
which can be regarded as close to completed fertility. The results
are given in rows 4 and 5 for white and black women and show
that the correlations between intelligence and fertility are still
significantly negative and are higher for black women (-0.226)
than for white women (-0.062). These correlations are probably
underestimates because the samples excluded high-school
dropouts, who were about 14 per cent of whites and 26 per cent
of blacks at this time, and who likely had low IQs and high
average fertility. (p. 201-2)

which is to say that if one gathers the data before women are done having children, one will miss out some older women who get children late. since such women are especially likely to be well-educated (and hence, smart), this is an important bias.

still given that there are some consistent negative correlations, then there is a dysgenic effect – its just smaller than i had imagined. at least on a within population basis.

-

It would be interesting to explore to what extent differences
in geographical circumstances and water resources affect the
access to clean water, but unfortunately it is difficult to find
appropriate indicators of geographical factors. However, there is
one indicator for this purpose.WDI-09 (Table 3.5) includes data
on renewable internal freshwater resources per capita in cubic
metres in 2007 (Freshwater). It measures internal renewable
resources (internal river flows and groundwater from rainfall) in
the country. It is noted that these “estimates are based on different
sources and refer to different years, so cross-country
comparisons should be made with caution” (WDI-09, p. 153). It
could be assumed that freshwater resources per capita are
negatively correlated with Water-08, but in fact there is no
correlation between these variables (0.050, N=139). The
correlation between national IQ and Freshwater is also in zero
(0.014, N=147). Access to clean water seems to be completely
independent from freshwater resources, whereas it is
significantly dependent on national IQ (39%) and several
environmental variables. Therefore, it is interesting to see how
well national IQ explains the variation in Water-08 at the level of
single countries and what kinds of countries deviate most from
the regression line. Figure 8.1 summarizes the results of the
regression analysis of Water-08 on national IQ in the group of
166 countries. Detailed results for single countries are reported in
Table 8.3. (p. 246)

Very interesting! Is this a direct disproof of Jared Diamond (1997)‘s environment theory regarding access to water?

Figure 8.1 shows that the relationship between national IQ
and Water-08 is linear as hypothesized, but many highly
deviating countries weaken the relationship. In the countries
above the regression line, the percentage of people without
access to improved water services is higher than expected on the
basis of the regression equation, and in the countries below the
regression line it is lower than expected. In all countries above
the national IQ level of 90, the percentage of the population
without access to clean water is zero or near zero, except in
Cambodia, China and Mongolia, whereas this percentage varies
greatly in the countries below the national IQ level of 85.
National IQ is not able to explain the great variation in Water-08
in the group of countries with low national IQs. Most of that
variation seems to be due to some environmental and local
factors, perhaps also to measurement errors. ( p. 247-8)

in the case of China it seems very unhelpful to category it as one country. it is a HUGE place. it wud be better to split it up into provinces, and calculate these instead. en.wikipedia.org/wiki/Provinces_of_the_People%27s_Republic_of_China altho this will result in many of them having no data. i doubt that there is IQ data for all the regions of China. perhaps those in the regions away from the ocean are not quite as clever as those near the ocean, and near Japan. but surely there is data about Hong Kong, Macau, and some other city or city-like states.

-

one thing that bothers me a bit is that when LV discuss outliers to their correlation, they use some seemingly arbitrarily picked number. heres a random example (p. 258):

Table 8.3 shows the countries which deviate most from the
regression line and for which positive or negative residuals are
large. An interesting question is whether some systematic
differences between large positive and negative outliers could
help to explain their deviations from the regression line. Let us
regard as large outliers countries whose residuals are ±15 or
higher (one standard deviation is 13).

they note that the sd is 13, but instead opt to use 15 without an explanation. this is the same every time they adopt such an analysis, which do they every chapter. normally, they choose some number slightly larger than 1sd. in p. 155 sd = 1.7, and they use 2. in p. 146 they use 11 while sd = 10.1. in p. 103 they use 12 while the sd is 12.017. the general rule seems to be: choose an arbitrary but nicely looking number just a bit larger than the sd. i dont think this skews the analysis much, but i wud have prefered just if they used 1sd as the border for counting as an outlier.

-

one odd thing is that when LV finds that a relationship between national IQs and some other variable is curvilinear, they still go on to use the linear model in their explanation. they do this time and time again. it results in some bad points of analysis, for instance:

It is remarkable that this group does not include any
economically highly developed countries, Caribbean tourist
countries, Latin American countries, or oil exporting countries.
Most of them are poor sub-Saharan African countries (17). China
is not really a large positive outlier for the reason that its
predicted value of Water-08 is negative -6. The other eight
positive outliers are poor Asian and Oceanian countries. Most of
them (especially Afghanistan, Cambodia, Myanmar and Timor-
Leste) have suffered from serious civil wars, which have
hampered socio-economic development. (p.259)

if they had made a proper model, one where negative values are impossible, then they wud have avoided such details. its not that LV doesnt know this, as they discuss on page. 79:

Rows 13 through 18 give six correlations between national
IQs and various measures of per capita income reported. The
author analyzed further the relationship by fitting linear, quadratic
and exponential curves to the data for 81 and 185 nations and
found that fitting exponential curves gave the best results. His
interpretation was that “a given increment in IQ, anywhere along
the IQ scale, results in a given percentage in GDP, rather than a
given dollar increase as linear fitting would predict” (Dickerson,
2006, p. 291). He suggests that

exponential fitting of GDP to IQ is logically
meaningful as well as mathematically valid. It is
inherently reasonable that a given increment of IQ
should improve GDP by the same proportional ratio,
not the same number of dollars. An increase of GDP
from $500 to $600 is a much more significant change
than is a linear increase from $20,000 to $20,100. The
same proportional change would increase $20,000 to
$24,000. These data tell us that the influence of
increasing IQ is a proportional effect, not an absolute
one (p. 294).

heres as example of a plot where LV acknowledges that it is curvilinear:

i wud replicate this plot myself and fit an exponential function to it, and then look for outliers, but i wud need the raw data for that in a useable form. see the previous point about how it is difficult to extract the data from the PDF and the need to publish it in some other format, preferably excel/calc.

-

Some systematic differences in the characteristics of large
positive and negative outliers provide partial explanations for
their large residuals. Most countries with large negative residuals
have benefitted from investments, technologies, and
management from countries of higher national IQs, whereas
most countries with large positive residuals have received much
less such foreign help. (p.260)

tourism is not the only way to receive money from the rich countries. it wud be interesting to look at the effects of foreign aid to poor countries. is there any discernible effect of it? perhaps it has had effects on water supply, for instance.

-

Table 8.4 shows that the indicators of sanitation are a little
more strongly correlated with national IQ than the indicators of
water (cf. Table 8.2). The explained part of variation varies from
41 to 60 percent. Differences between the three groups of
countries are relatively small, although the correlations are
strongest in the group of countries with more than one million
inhabitants. It should be noted that the correlations between
national IQ and Sanitation-08 are negative because Sanitation-08
concerns the percentage of the population without access to
improved sanitation services (see section 2). (p. 261)

i understand their wish to stay true to the sources numbers, but i wud have prefered if they had multiplied the numbers by -1 to make them fit with the direction of the other numbers.

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Row 7 gives a low but statistically significant positive
correlation of 0.18 between national IQ and son preference. This
may be a surprising result, because it might be expected that
liberal and more modern populations would not have such a
strong preference for sons as more traditional peoples. (p. 273)

surprising indeed.

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Consistent with Frazer’s analysis, it has been found in a
number of studies of individuals within nations that there is a
negative relationship between intelligence and religious belief.
This negative relationship was first reported in the United States
in the 1920s by Howells (1928) and Sinclair (1928), who both
reported studies showing negative correlations between
intelligence and religious belief among college students of -0.27
to -0.36 (using different measures of religious belief). A number
of subsequent studies confirmed these early results, and a review
of 43 of these studies by Bell (2002) found that all but four found
a negative correlation. To these can be added a study in the
Netherlands of a nationally representative sample (total N=1,538)
that reported that agnostics scored 4 IQs higher than believers
(Verhage, 1964). In a more recent study Kanazawa (2010) has
analyzed the data of the American National Longitudinal Study of
Adolescent Health, a national sample initially tested for
intelligence with the PPVT (Peabody Picture Vocabulary Test) as
adolescents and interviewed as young adults in 2001-2
(N=14,277). At this interview they were asked: “To what extent
are you a religious person?” The responses were coded “not
religious at all”, “slightly religious”, “moderately religious”, and
“very religious”. The results showed that the “not religious at all”
group had the highest IQ (103.09), followed in descending order
by the other three groups (IQs = 99.34, 98.28, 97.14). The
negative relationship between IQ and religious belief is highly
statistically significant. (p. 278)

the Bell article sounds interesting, but after spending some time trying to locate it, i failed. it seems that im not the only one having such problems.

regardless of that, there was a similar article: “The Effect of Intelligence on Religious Faith,” Free Inquiry, Spring 1986: (1). There is an online parafrase of it here.

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one of the interesting datasets that id love to see a nonlinear function fitted to. i want to know how much we need to boost intelligence to almost remove religiousness. perhaps one can discover this from using high-IQ samples. at which IQ are there <5% religious people?

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another of those tables that have problems with the direction. Legatum and Newsweek shud be positive with each other, right? since they are measuring in the same direction, that is, the one opposite of HDI and IHC (which correlate positively).

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LV mention the 2008 study by Kanazawa: Temperature and evolutionary novelty as forces behind the evolution of general intelligence. The interesting thing about this study is that it sort of tests my idea that i wrote about earlier. Kanazawa goes on with his novelty hypothesis using distance from Africa to predict national IQs. However, compared with Ashraf and Galor (2012) paper, he just uses bird distance instead of actual travel distance (humans are not birds, after all!, nor did they just sail straight from Africa to populate America). So im not really sure what his computed r’s are useful for. It wud be interesting to add together the data from the Ashraf and Galor (2012) paper about distances, and genetic diversity to the climate model. LV does mention at one point that lack of genetic diversity make evolution slower:

A further
anomaly is that the Australian Aborigines inhabit a relatively
warm region but have small brain sizes and low IQs. The
explanation for this anomaly is that these were a small isolated
population numbering only around 300,000 at the time of
European colonization, so the mutant alleles for higher IQs did
not appear in them. (p. 381)

consider also the criticism of Kanazawa’s paper in Why national IQs do not support evolutionary theories of intelligence, Wicherts et al (2009):

5. Migration and geographic distance
Kanazawa (2008) was concerned with the relation between lev-
els of general intelligence, as they were distributed geographically
thousands of years ago, and the degree of ‘‘evolutionary novelty” of
the relevant geographic locations. Lacking data regarding evolu-
tionary novelty, Kanazawa proposed, as a measure of evolutionary
novelty, the geographic distance to the EEA, i.e., a large region of
sub-Saharan Africa. The idea is that the greater the distance from
the EEA, the more evolutionarily novel the corresponding environ-
ment. There are several problems with this operationalization.
First, Kanazawa operationalized geographic distance using
Pythagoras’ first theorem (a²+ b²= c²). However, Pythagoras’ theo-
rem applies to Euclidian space, not to the surface of a sphere. Sec-
ond, even if these calculations were accurate, distances as traveled
on foot do not in general correspond to distances ‘‘as the crow flies”
(Kanazawa 2008, p. 102). According to most theories, ancestors of
the indigenous people in Australia (i.e., the Aborigines) moved out
of Africa on foot. They probably crossed the Red Sea from Africa to
present day Saudi Arabia, went on to India, and then through Indo-
nesia to Australia. Thus the distance covered on foot must have
been much larger than the distances computed by Kanazawa. This
suggests that the real distances covered by humans to reach a gi-
ven location, i.e., data of central interest to Kanazawa, are likely
to differ appreciably from the distances as the crow flies. One
can avoid this problem by using maps that exist of the probable
routes that humans followed in their exodus from Africa, and esti-
mating the distances between the cradle of humankind and various
other locations accordingly (Relethford, 2004).
Third, it is not obvious that locations farther removed from the
African Savannah are geographically and ecologically more dissim-
ilar than locations closer to the African Savannah. For instance, the
rainforests of central Africa or the mountain ranges of Morocco are
relatively close to the Savannah, but arguably are more dissimilar
to it than the great plains of North America or the steppes of Mon-
golia. In addition, some parts of the world were quite similar to the
African savannas during the relevant period of evolution (e.g., Ray
& Adams, 2001). Clearly, there is no strict correspondence between
evolutionary novelty and geographic distance. This leaves the use
of distances in need of theoretical justification. It is also notewor-
thy that given the time span of evolutionary theories, it is hardly
useful to speak of environmental effects as if these were fixed at
a certain geographical location.
People migrate, and have done so extensively in the time since
the evolutionarily period relevant to the evolutionary theories by
Kanazawa and others. A simple, yet imperfect, solution to this
problem is to use data solely from countries that have predomi-
nantly indigenous inhabitants (Templer, 2008; Templer & Arika-
wa, 2006). However, Kanazawa used national IQs of all
countries in Lynn and Vanhanen’s survey, including Australia
and the United States. This casts further doubt on the relevance
of Kanazawa’s data vis-à-vis the evolutionary theories that he
set out to test. Given persistent migration, it is likely that many
of the people, whose test scores Lynn and Vanhanen used to cal-
culate national IQs, are genetically unrelated to the original
inhabitants of their respective countries. In at least 50 of the
192 countries in Kanazawa’s (2008) study, the indigenous people
represent the ethnic minority.

Via Steve Sailer.

The Out of Africa Hypothesis, Human Genetic Diversity, and Comparative Economic Development

Quamrul Ashraf and Oded Galor

Abstract
This research advances and empirically establishes the hypothesis that, in the course of the prehistoric exodus of Homo sapiens out of Africa, variation in migratory distance to various settlements across the globe affected genetic diversity and has had a long-lasting hump-shaped effect on comparative economic development, reáecting the trade-offs between the beneficial and the detrimental effects of diversity on productivity. While intermediate levels of genetic diversity prevalent among Asian and European populations have been conducive for development, the high diversity of African populations and the low diversity of Native American populations have been detrimental for the development of these regions.

A very interesting paper. As can be seen in the link, it receives the usual backlash of dumbness.

The interesting thing about this that wasnt explored – even if it screamed to be explored – is how it works together with Lynn’s world wide IQ data. Lynn’s theory of cold climate has difficulties explaining why the arctic people are not smarter than they are. They are by no means dumb like africans, but they shud be smarter than they are going by the latitude theory and climate theory. I suggested that this might be due to inbreeding due to small populations. Perhaps. Perhaps its due to less genetic variation. It shud be possible to run a multiple regression analysis, and see how these two together explain IQ and income per capita.

The theory behind this is: First humans were in Africa, then they migrated out to live in other places. These other places differed in environment by coldness among other things. Those that lived in colder places were under (stronger) selection pressure for intelligence. How fast this adaptation happens is controlled by population size and genetic variation in the populations.

Very strange that the paper does not even cite Lynn, or mentioned IQ anywhere. These seem obvious to explain differences in income per capita.

I have had this on my computer for 6 months now, but i can’t get myself to work on it. Basically just need to insert some references and look thru some studies. Perhaps the theory is bunk. I did try to find data on kinsey scale ratings vs. number of children, but didnt find anything.

Since it is of not much use to me lying on my hard drive, i will publish it now. The theory was invented by me with input from Samuel Mossberg.

PDF: An evolutionary theory of the origin of same-sex sexual acts based on social bonding

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An evolutionary theory of the origin of same-sex sexual acts based on social bonding

Emil Kirkegaard, Department of Linguistics, Aarhus University

Samuel Mossberg, Department of Mathematics, Linköping University

Introduction

Homsexuality in humans and other animals [get some refs from wikipedia] is a mystery [ref to Buss's textbook]. The mystery goes like this: homosexualiy seems so obviously bad for inclusive fitness that it very strange that evolution has not filtered it out. The reason that it is bad, is that homosexuals do not have children. This is not correct [insert studies with data about sexuality and number of children], and the misleadingly simple terms “homosexual”, “bisexual” and “heterosexual” make it harder. It is better to use a Kinsey scale of sexuality [cites, perhaps grab some from Wiki]. Using such a scale, one would expect that people that score more towards the homosexual end have fewer children. [look for studies about this]. But people with scores toward the low end of the Kinsey scale are here and data from research on people’s ability to detect people that are ‘homosexual’ (popularly called the gaydar) suggests that humans have evolved the ability to pretty reliably detect people that have sexual interest in the same sex as themselves. [cite some of the studies mentioned on Wikipedia].

In this paper we propose an evolutionary explanation of sexual interest in the same sex. This theory is one among many theories that attempt to explain the evolutionary origins of same-sex sex acts. Some of these theories work via kin selection, and are called ‘good uncle’ theories. The idea is that even though a ‘homosexual’ family member may have reduced fitness, he conves fitness indirectly by helping his relatives. Another interesting theory is that same-sex sexual behavior is due to sexual antagonism which is when genes that improve fitness in the one sex, reduce it in the other and but are positive on balance. Such genes can be selected for and a recent study by [mentioned on Wikipedia page] supports this theory. [use Wikipedia for more cites]

The theory

The theory is based on three assumptions:

1. Having an interest in both sexes is good for fitness, i.e., scoring somewhere between 1-5 on the scale

2. Sexual preferences follow a normal distribution or a skewed Gaussian distribution that is skewed towards the heterosexual end of the Kinsey scale

3. Exclusive homosexuality is bad, i.e. scoring 6 on the scale

The reasoning for these hypotheses is as following.

1. Having an interest in both sexes is good for fitness, i.e., scoring somewhere between 1-5 on the scale

The support is based on social bonding betwen same-sex people. The idea is that having sex helps create bonds between two animals, including humans. This idea works for humans and non-human animals alike. It is known from animal sexuality research that males tend to engage in same-sex sex acts for bonding purposes [cites]. Having stronger bonding with members of the same sex is potentially useful for (surviving) warfare and social hierarchy purposes. These things have over evolutionary time been more important for the human male. So, this effect is stronger for males and would thus skew the distribution more towards homosexuality for men more than for women. This is indeed the case. There are more men than women that rate themselves 6 on the scale. [cites and illustrations for each sex].

Testing this hypothesis in industrialized humans seems hard as there is no longer much of a struggle for survival (natural selection is almost completely without force). In fact, we are probably living in the least violent time ever in evolutionary history (Pinker 2011). But it should be possible to test it in the surviving traditional societies spread around the world. One way to do that is to do a longditutional study of the survival rates for people and their Kinsey scale ratings. If the hypothesis is correct, there should be a slight positive effect on survival rates for the people that are more bisexual, especially for men. This effect may not appear if the society is very hostile to same-sex sexual acts. For this reason, one would need a larger sample than one society to disprove the hypothesis. We are not aware of any studies that have done this [look for such studies].

2. Sexual preferences follow a normal distribution or a skewed Gaussian distribution that is skewed towards the heterosexual end of the Kinsey scale

For this theory to work, sexuality has to be either normally distributed or skewed to the one end. If there were more people at the extreme ends of the scale, this theory would not work. But sexuality does follow a skewed Gaussian distribution. [cites and illustration]

3. Exclusive homosexuality is bad, i.e. scoring 6 on the scale

This is the usual mystery. People that score towards the homosexual end of the scale have fewer (non-adopted) children than those that are in the middle or towards the heterosexual end. [need data but i think this is true]

Selection preasures

The selection preasure for bisexuality, i.e., scale 1-5 moves the sexuality average towards the middle area, while the selection against exclusive homosexuality, i.e. scale 6 moves the sexuality average away from 6. If the theory is correct, then these preasures move the sexuality average to some midway between 0 (furtherst away from 6) and 1-5 (whatever is optimal). Without data about how strong the hypothesized extra strength of bonding with same sex persons is worth, there is no way to deduce from this theory where on the scale the optimal point is for bisexuality. Perhaps the occassional same-sex sexual act is strong enough to maximize the effect (this would favor scale 1-2), perhaps more regular or very regular same-sex acts are necessary (this would favor scale 3-5).

Conclusion

We have proposed a theory to explain the origin of homosexual behavior (exclusive or not) in humans and other animals. Some research seems to support it but more decisive empirical tests are necessary, including ones in traditional societies.

References

Pinker, Steven (2011). The Better Angels of Our Nature: Why Violence Has Declined. Viking Adult.

racialreality.blogspot.com/2010/03/richard-lynn-on-italian-iq.html

Apparently sometimes either a sloppy or an intellectually dishonest writer. Check the links about manipulating data, and the cases of choice with samples seems doubtful.

Still, there is no doubt in my mind that there are genetic differences between the races. It is simply evolutionarily unthinkable. However, they might not be just as large as Lynn posits. If anything, this is a good thing! Especially if he is still right about the relationship between IQ and wealth of nations. This means that there is more hope for Africa. :)

This is about the kontroversy that hapened after Dawkins published his The Selfish Gene book.

I was reeding Dennett’s Darwin’s Dangerous Idea wen i saw a referens to the kontroversy (p. 362). Having diskused it befor (with the mod on FRDB with the unrememberable name that begins with A), i resently diskovered that i hav akses thru my university to akademik papers. I used that akses to download the relevant papers and reed them. Il post them here in kase anyone els in interested/kurius about that kontroversy.

The outline is this:

• 1975: R. Dawkins publishes The Selfish Gene.
• 1978: J. L. Mackie publishes a paper in the journal Philosophy in wich he diskuses sertain elements from Dawkins’ book. The Law of the Jungle: Moral Alternatives and Principles of Evolution.
• 1979: M. Migley publishes a paper that is extreemly harsh and very kritikal of Dawkins’ book. Gene-Juggling.
• 1981: R. Dawkins publishes a paper in respons to Migley’s paper. In Defence of Selfish Genes.

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It is interesting to note that the komonly used frase “the law of the jungle” (DA “jungleloven”), was aktualy populaized as meening somthing els than wat we use it to meen today. Mackie mentions this, but see also Wikipedia:

en.wikipedia.org/wiki/The_Law_of_the_Jungle

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A benefit of reeding the texts of this kontroversy (i red Dawkins’ book years ago), was to (re-)diskover this nise quote about metafors:

“At times, gene language gets a bit tedious, and for brevity and vividness we shall lapse into metaphor. But we shall always keep a sceptical eye on our metaphors, to make sure they can be translated back into gene language if necessary.” (p. 45 in The Selfish Gene)