/docs/iq/ Directory Listing



  • 1904-spearman.pdf: ⁠, Charles Spearman (1904-04-01; backlinks):

    Determined the connection between psychical tendencies and, that between ‘mental tests’ and psychical activities of greater generality and interest, on the basis of correlation. A critical review of previous and present studies showed that no conclusive results could be obtained. Experiments were confined to testing the sensory discrimination of hearing, sight and touch, using the monochord, a graduated series of colored cards, and a graduated series of weights constructed on Galton’s cartridge pattern, respectively, for the three conditioned. Five series of experiments were conducted involving varying number of Ss. The results indicated that all branches of intellectual activity possess in common one fundamental function, whereas the remaining or specific elements of the activity seem to be wholly different from that in all the others. In adult life no difference between the two sexes was observed.

  • 1906-terman.pdf

  • 1908-thorndike.pdf: ⁠, Edward L. Thorndike (1908-07-01; backlinks):

    Studied the amount, rate, progressive change of rate and the spread of improvement in the case of a purely intellectual function, using 33 subjects.

    After some training in multiplication of numbers the subjects mentally multiplied about 50 to 96 numbers. The reduction of the scores to one variable, the amount of improvement, the limits of practice effect, changes in the rate of improvement and the influence of equal practice upon individual differences were discussed.

    Implications for the improvement of human functioning have been suggested.

    [The author reports experiments in the mental multiplication of one 3-place number by another for the purpose of showing the amount of improvement, its rate, progressive change of rate, and spread. In studying the different influence of equal practice upon individuals it was found that high mental ability tended to go with high rate of improvement, thus showing that equal practice tended to increase rather than diminish individual differences. The author concludes with the opinion that students with greater original capacity gain as much or more from the same training. The conclusion seems to be, the better the student, the more he is able to profit by training, and, conversely, the greater the training, the greater the differences between those of higher and lower ability.]

  • 1917-goddard.pdf: “Mental Tests and the Immigrant”⁠, Henry H. Goddard

  • 1918-strong.pdf: ⁠, Edward K. Strong Junior (1918; backlinks):

    Discusses various functions of the Committee on Classification of Personnel in the Army:

    1. classifying personnel according to their military qualifications
    2. establishing the Trade-Tests division
    3. enlisting the occupational needs of units in a division
    4. extending the personnel work to staff corps troops
    5. establishing the Central Personnel Bureau
    6. appointing a committee on education and special training
    7. organizing the War Service Exchange
    8. rating the officers and candidates for commissions in the Officers Training Camps
    9. cooperating with the Provost Marshall General
    10. reducing the army paper work
    11. enlisting the intelligence ratings of army men and
    12. selecting aviators and navy men.
  • 1920-thorndike.pdf: “Intelligence and Its Uses”⁠, Edward L. Thorndike (backlinks)

  • 1925-gates.pdf (backlinks)

  • 1926-cox-theearlymentaltraitsof300geniuses.pdf (backlinks)

  • 1927-kelley-interpretationofeducationalmeasurements.pdf: ⁠, Truman Lee Kelley (1927; backlinks):

    [Historically notable for introducing Kelley’s paradox⁠, another fallacy related to regression to the mean⁠.] Among the outstanding contributions of the book are (1) the judgments of the relative excellence of assorted tests in some 70 fields of accomplishment, by Kelley, Franzen, Freeman, McCall, Otis, Trabue and Van Wagenen; (2) detailed and exact information on the statistical and other characteristics of the same tests, based on a questionnaire addressed to the text authors or (in the absence of reply) estimates by Kelley on the best data available; (3) a chapter of 47 pages condensing all the principal elementary statistical methods. In addition, there is constant emphasis upon the importance of the probable error, with some illustrative applications; for example, it is maintained that about 90% of the abilities measured by our best “intelligence” and “achievement” tests are (due chiefly to the size of the probable errors) the same ability. A chapter sets forth the analytical procedures which lead to this conclusion and to four others earlier enunciated. “Idiosyncrasy,” or inequality among abilities, which the author regards as highly valuable, is considered in two chapters; the remainder of the volume is devoted to a historical sketch of the mental test movement and a statement of the purposes of tests, the latter being illustrated by appropriate chapters.

  • 1927-spearman-theabilitiesofman.pdf

  • 1930-white.pdf: “Note on the Psychopathology of Genius”⁠, Ralph K. White

  • 1931-lawrence-investigationrelationbetweenintelligenceinheritance.pdf: “An investigation into the relation between intelligence and inheritance”⁠, Evelyn M. Lawrence (backlinks)

  • 1931-white.pdf: ⁠, Ralph K. White (1930-10-12):

    The purpose of this study is twofold : (a) to estimate the versatility of 300 eminent men, as an indication of the extent to which specialization is favorable or unfavorable to the attainment of eminence; and (b) to discover what kinds of special ability are associated with certain kinds of genius, as an indication of the vocational types to be kept in mind in the education and guidance of gifted children.

    …The first purpose of this study was “to estimate the versatility of three hundred eminent men, as an indication of the extent to which specialization is favorable or unfavorable to the attainment of eminence.” If bare figures told the whole story, the answer would be decisive. We could say, not only that these geniuses were not one-sided freaks, overdeveloped on one side of their natures and atrophied on all the rest, but that they were actually far more versatile than the average college graduate of today. They were judged superior to the average graduate in 2015 instances, and inferior in only 141. Even if 30% of the positive scores were disregarded because they represent abilities which contributed to eminence, and 40% more were disregarded because they represent activities which took up only a very small amount of time (these percentages are very unreliable), there would still remain 605 positive scores in contrast to the total of 141 negative scores. Positive scores would still be more than 80% of the total (746), and negative scores less than 20%.

  • 1933-nemzek.pdf (backlinks)

  • 1935-leahy.pdf: ⁠, Alice M. Leahy (1935-08-01):

    “The present study approaches the problem by a comparison of two groups of children living in approximately identical environments.” One group consists of adopted children and the other of “own” children. After surveying the records of 2449 children, 194 adopted children between the ages 5 and 14 (white, non-Jewish, north-European, and placed in their adoptive homes at the age of 6 months or younger) were matched with 194 own children whose sex was the same, whose age was within 6 months, whose fathers’ occupations belonged to the same group on the Minnesota Occupational Scale, whose fathers’ school attainments agreed within one school grade (mothers’ also), whose parents were white, non-Jewish, and north-European, and whose residence had been in communities of 1000 or more. The children of both groups were given the Stanford-Binet and the Woodworth-Mathews Personal Data Sheet; the parents were given the Otis Self-Administering Test and the Stanford-Binet vocabulary.

    “Variation in IQ is accounted for by variation in home environment to the extent of not more than 4%; 96% of the variation is accounted for by other factors… . Measurable environment does not shift the IQ by more than 3 to 5 points above or below the value it would have had under normal environmental conditions… . The nature or hereditary component in intelligence causes greater variation than does environment. When nature and nurture are operative, shifts in IQ as great as 20 points are observed with shifts in the cultural level of the home and neighborhood… . Variation in personality traits other than intelligence may be accounted for less by variation in heredity than by variation in environment.”

    Earlier studies are reviewed and 8 references are cited.

  • 1935-thorndike.pdf: ⁠, Robert Ladd Thorndike (1935-02-01; backlinks):

    The present study carries the current question as to the organization of behavior into the realm of comparative psychology.

    64 albino rats were given the following tests: revolving-wheel activity cage, Warner-Warden maze (2 patterns), elevated T maze (2 patterns), Jenkins circular problem box, latch problem box, Warner’s conditioned-response test, Columbia obstruction apparatus. Reliabilities of the scores were obtained as well as intercorrelations of scores. Thurstone’s center-of-gravity method of factor analysis was then applied. Corrected reliabilities, for the most part, ran from 0.70 to 0.95. Positive correlations were found in about 85% of the cases, although most of them were quite low.

    Thurstone’s center-of-gravity method of factor analysis revealed the following factors: (1) docility—maze-learning, intelligence, tameness; (2) transfer—distinguishing early from later tests; (3) a factor specific to the different conditioned-response scores.

    The bibliography contains 41 citations.

  • 1935-wechsler-rangeofhumancapacities.pdf: ⁠, David Wechsler (1935; backlinks):

    saw that the subjects who did well at the start of the training also improved faster as the training progressed compared with the subjects who began more slowly. “As a matter of fact,” ⁠, “in this experiment the larger individual differences increase with equal training, showing a positive correlation with high initial ability with ability to profit by training.” The passage from the Bible doesn’t quite capture Thorndike’s results accurately because every subject improved, but the rich got relatively richer. Everyone learned, but the learning rates were consistently different.

    When World War I erupted, Thorndike became a member of the Committee on Classification of Personnel, a group of psychologists commissioned by the U.S. Army to evaluate recruits [see ]. It was there that Thorndike rubbed off on a young man named ⁠, who had just finished his master’s degree in psychology. Wechsler, who would become a famous psychologist, developed a lifelong fascination with tracing the boundaries of humanity, from lower to upper limits.

    In 1935, Wechsler compiled essentially all of the credible data in the world he could find on human measurements. He scoured measures of everything from vertical jump to the duration of pregnancies to the weight of the human liver and the speeds at which card punchers at a factory could punch their cards. He organized it all in the first edition of a book with the aptly momentous title The Range of Human Capacities.

    Wechsler found that the ratio of the smallest to biggest, or best to worst, in just about any measure of humanity, from to hosiery looping [knitting], was between 2 to one and 3 to one. To Wechsler, the ratio appeared so consistent that he suggested it as a kind of universal rule of thumb.

    Phillip Ackerman, a Georgia Tech psychologist and skill acquisition expert, is a sort of modern-day Wechsler, having combed the world’s skill-acquisition studies in an effort to determine whether practice makes equal, and his conclusion is that it depends on the task. In simple tasks, practice brings people closer together, but in complex ones, it often pulls them apart. Ackerman has designed computer simulations used to test air traffic controllers, and he says that people converge on a similar skill level with practice on the easy tasks—like clicking buttons to get planes to take off in order—but for the more complex simulations that are used for real-life controllers, “the individual differences go up,” he says, not down, with practice. In other words, there’s a on skill acquisition.

    Even among simple motor skills, where practice decreases individual differences, it never drowns them entirely. “It’s true that doing more practice helps,” Ackerman says, “but there’s not a single study where variability between subjects disappears entirely.”

    “If you go to the grocery store,” he continues, “you can look at the checkout clerk, who is using mostly perceptual motor skill. On average, the people who’ve been doing it for 10 years will get through 10 customers in the time the new people get across one. But the fastest person with 10 years’ experience will still be about 3 times faster than the slowest person with 10 years’ experience.”

  • 1936-byrns.pdf (backlinks)

  • 1936-miles.pdf: ⁠, Catharine C. Miles, Lillian S. Wolfe (1936-01-01):

    The enigma of genius presents no more perplexing problems than those implied in the definition of its psychophysiological constitution. The health and more especially the mental health of men of genius has proved to be not only the most fascinating but also perhaps the most provocative question involved. Definitions of genius are generally of two kinds: in terms of intrinsic quality and in terms of extrinsic achievement. The question as to the qualifications for the highest human classification is still in the fascinatingly vague region of thought where subjective exploration attracts one to pleasant excursions without limiting effort in terms of a prescribed scientific goal. We perceive that the criterion of intrinsic quality is in an important sense more rigid than that of world recognition and we would prefer a definition which explicitly emphasizes both. Genius in the intrinsic sense demands not only “the highest conceivable form of original ability, something altogether extraordinary and beyond even supreme educational powers,” but also “inexplicable and unique endowment.” Genius in terms of achievement requires “the ability to create special values bearing a personal stamp; such values include novel ideas and forms of expression and the production of factors which initiate new historical efforts.” The studies of many investigators seem to show that a rigid definition of the intrinsic kind makes objective agreement regarding any considerable group of qualifying persons practically impossible. Results, in terms of the names of geniuses, selected with primary emphasis on qualitative divergences in endowment indicate that common agreement is not attainable for any very large number of persons in recent or in more remote centuries. It would perhaps prove more interesting and would seem to some also more profitable if there were in the qualitative sense of unique superiority a group of “certified geniuses” to whom study could be devoted. Because there is no recognized group of this kind, one must attempt either subjectively to select in terms of uniqueness of endowment as Lombroso, Lange-Eichbaum, and Nisbet have done, or else objectively to measure in terms of eminent achievement following the method of Galton, Ellis, and Cattell. For the present study we have followed the second course. This procedure implies what is perhaps a less rigorous definition of genius but it offers a more objective method, depending as it does upon the world’s cumulatively discriminating estimate with respect to eminence.

    …It is not essential that our scale agree with Olson’s at every point. The substantial finding in the comparison is, we believe the evidence which it gives that the mental health of 50 geniuses was on the average no less satisfactory than is shown by unselected children today. If there is a subtle relationship between genius and insanity it is not shown in the childhood records of this group of 50.

  • 1937-hollingworth.pdf (backlinks)

  • 1938-becker.pdf: “Grundsätze fur Auslese, Intelligenzprüfung und ihre praktische Verwirklichung [Principles for selection, intelligence measurement and its application”⁠, Friedrich Becker

  • 1938-cattell.pdf (backlinks)

  • 1938-jaensch.pdf: “Grundsätze für Auslese, Intelligenzprüfung und ihre praktische Verwirklichung [Principles for selection, intelligence measurement and its application]”⁠, E. R. Jaensch

  • 1938-woodrow.pdf: “The relation between abilities and improvement with practice”⁠, H. Woodrow

  • 1940-reymert.pdf: “The effect of a change to a relatively superior environment upon the IQs of one hundred children”⁠, Martin L. Reymert, Ralph T. Hinton Jr. (backlinks)

  • 1940-whipple-39thyearbooknationalsocietystudyeducation-intelligencenaturenurture-1-comparativecriticalexposition.pdf

  • 1940-whipple-39thyearbooknationalsocietystudyeducation-intelligencenaturenurture-2-originalstudiesexperiments.pdf

  • 1941-thurstone-factorialstudiesofintelligence.pdf: “Factorial Studies Of Intelligence”⁠, Louis L. Thurstone, Thelma G. Thurstone (backlinks)

  • 1943-burt.pdf: ⁠, Cyril Burt (1943-01-01; backlinks):

    The distribution of intelligence as measured by recognized scales supplemented by other information conforms closely to the normal curve of error, while that of personal income presents a highly skewed J-shaped curve. Reconciliation of this apparent discrepancy can be made by regarding income as dependent mainly on output, which in turn is related to the contributing abilities by some special function. Confirmation of this theory appears in the fact that in many intellectual fields the distribution of output approaches the J-shaped curve. The inequality in personal income is largely, though not entirely, an indirect effect of the inequality in innate intelligence. Yet mental output and achievement are undoubtedly influenced by differences in social and economic conditions. This is instanced by the fact that in assessing the influence of innate ability and parental income upon entrance to the universities, it appears from statistical analysis that of the ex-elementary (non-fee-paying) group about 40% of those possessing the necessary intelligence fail to obtain a university education. On the other hand, an equal number of children whose parents pay for their early instruction receive a university education for which their innate abilities alone scarcely equip them.

  • 1947-dubois-theclassificationprogram.pdf: “The Classification Program”⁠, Philip H. Dubois

  • 1947-terman-thegiftedchildgrowsup.pdf: “The Gifted Child Grows Up: Twenty-Five Years' Follow-Up of a Superior Group [Genetic Studies of Genius #4]”⁠, Lewis M. Terman, Melita H. Oden, Nancy Bayley, Helen Marshall, Quinn McNemar, Ellen B. Sullivan

  • 1947-terman.pdf: “Psychological Approaches To The Study Of Genius”⁠, Lewis M. Terman (backlinks)

  • 1949-michael.pdf: “Factor analyses of tests and criteria: A comparative study of two AAF pilot populations”⁠, William Burton Michael

  • 1949-skodak.pdf: “A Final Follow-Up Study of One Hundred Adopted Children”⁠, Marie Skodak, Harold M. Skeels (backlinks)

  • 1949-vernon-personnelselectioninthebritishforces.pdf: “Personnel Selection in the British Forces”⁠, Philip E. Vernon, John B. Parry

  • 1954-vernon.pdf (backlinks)

  • 1956-canter.pdf (backlinks)

  • 1956-chicagourbanleague-mcgurk.pdf: “A staff report on "A scientist\'s report on race differences" by Frank C. J. McGurk. Compiled by Chicago Urban League Research Dept”⁠, Chicago Urban League

  • 1957-honzik.pdf: “Developmental Studies of Parent-Child Resemblance in Intelligence”⁠, Marjorie P. Honzik

  • 1957-levinson.pdf (backlinks)

  • 1957-mccurdy.pdf: ⁠, Harold G. McCurdy (1957-11-01):

    In summary, the present survey of biographical information on a sample of 20 men of genius suggests that the typical developmental pattern includes as important aspects: (1) a high degree of attention focused upon the child by parents and other adults, expressed in intensive educational measures and, usually, abundant love; (2) isolation from other children, especially outside the family; and (3) a rich efflorescence of phantasy, as a reaction to the two preceding conditions. In stating these conclusions I by no means wish to imply that original endowment is an insignificant variable. On the contrary. Galton’s strong arguments on behalf of heredity appear to me to be well-founded; and in this particular sample the early promise of these very distinguished men cannot be dissociated from the unusual intellectual qualities evident in their parents and transmitted, one would suppose, genetically as well as socially to their offspring. It is upon a groundwork of inherited ability that I see the pattern operating. Whether the environmental phase of it summarized under (1) and (2) is actually causally important, and to what extent the environmental factors are related to the blossoming out of phantasy, are questions which could be examined experimentally, though obviously any thorough experiment would require both a great deal of money and a certain degree of audacity. It might be remarked that the mass education of our public school system is, in its way, a vast experiment on the effect of reducing all three of the above factors to minimal values, and should, accordingly, tend to suppress the occurrence of genius.

  • 1957-shockley.pdf: ⁠, William Shockley (1957; backlinks):

    It is well-known that some workers in scientific research laboratories are enormously more creative than others. If the number of scientific publications is used as a measure of productivity, it is found that some individuals create new science at a rate at least 50 times greater than others. Thus differences in rates of scientific production are much bigger than differences in the rates of performing simpler acts, such as the rate of running the mile, or the number of words a man can speak per minute. On the basis of statistical studies of rates of publication, it is found that it is more appropriate to consider not simply the rate of publication but its logarithm. The logarithm appears to have a normal distribution over the population of typical research laboratories. The existence of a “log-normal distribution” suggests that the logarithm of the rate of production is a manifestation of some fairly fundamental mental attribute. The great variation in rate of production from one individual to another can be explained on the basis of simplified models of the mental processes concerned. The common feature in the models is that a large number of factors are involved so that small changes in each, all in the same direction, may result in a very large [multiplicative] change in output. For example, the number of ideas a scientist can bring into awareness at one time may control his ability to make an invention and his rate of invention may increase very rapidly with this number.

  • 1957-super-scientificcareersandvocationaldevelopmenttheory.pdf: “Scientific Careers and Vocational Development Theory: A review, a critique and some recommendations”⁠, Donald E. Super, Paul B. Bachrach (backlinks)

  • 1959-mann.pdf (backlinks)

  • 1961-burt.pdf (backlinks)

  • 1962-hayes.pdf: “Genes, Drives, and Intellect”⁠, Keith J. Hayes

  • 1963-clark.pdf: “Educational stimulation of racially disadvantaged children”⁠, Kenneth B. Clark (backlinks)

  • 1963-erlenmeyerkimling.pdf

  • 1963-jensen-2.pdf

  • 1963-jensen-3.pdf

  • 1963-jensen.pdf

  • 1963-rosenthal.pdf (backlinks)

  • 1963-shaycoft-studentsofcompleteagegroupage15.pdf: “The Identification, Development, and Utilization of Human Talents: Studies of a Complete Age Group - Age 15 [Project Talent]”⁠, Marion F. Shaycoft, John T. Dailey, David B. Orr, Clinton A. Neyman, Jr., Stuart E. Sherman

  • 1964-mcnemar.pdf: ⁠, Quinn McNemar (1964-09-05):

    The “concept of general intelligence, despite being maligned by a few, regarded as a 2nd-order function by some, and discarded or ignored by others, still has a rightful place in the science of psychology and in the practical affairs of man.” “It is far from clear that tests of general intelligence have been outmoded by the multi-test batteries as the more useful predictors of school achievement.” In fact some evidence suggests that “better predictions are possible via old-fashioned general intelligence tests.” Discussion focuses on reasons for discarding the idea of general intelligence, factor theories of intelligence, and recent trends in the assessment of “general intelligence.” “By the criterion of social usefulness, the multiple aptitude batteries have been found wanting.” It is “time for the profession to establish a bureau of standards to test the tests.”

  • 1964-smith-spatialabilityitseducationalsocialsignificance.pdf: “Spatial Ability: Its Educational and Social Significance”⁠, I. Macfarlane Smith (backlinks)

  • 1964-wiseman-educationandenvironment.pdf

  • 1965-walkup.pdf: ⁠, Lewis E. Walkup (1965-08-01; backlinks):

    Editors’ note: Mr. Walkup, an electrical engineer by training but an applied physicist by experience, has worked 12 yr. in research on explosives and ballistics and 19 yr. in the technology of the graphic arts, especially on the electrostatic photographic process called xerography. In this latter field he has been a major contributor of inventive ideas; he holds 37 U. S. and 60 foreign patents. The present article is a result of his personal study of creativity in his co-workers in a large industrial research institute.

    Abstract: The fact that attempts to gain insight into the creative process have been so unsuccessful suggests that they have overlooked at least one basic ingredient in the process. This ingredient may lie in the nature or way the individual mind goes about remembering and manipulating data. The hypothesis is advanced that the creative persons appear to have stumbled onto and then developed to a high degree of perfection the ability to visualize—almost hallucinate—in the area in which they are creative. And their visualizations seem to be of a sort that lend themselves to easy manipulation in the thinking process. This is illustrated by reports from many of the great inventors of the past and it is easy to demonstrate that individuals differ enormously in the kind and degree of their ability to think in such manipulable visualizations. If correct, this aspect of creativity suggests many research attacks and many potential changes in education for creative activity.

    …It is interesting to ask a number of persons to solve a simple problem in mental arithmetic, say, to subtract 46 from 100, and then to ask them what went on in their heads as they solved the problem. I have found the following gamut of processes used. Some persons simply grope around with words, perhaps dividing the problem up into subtracting 6 from 10 and 4 from 10, which they do simply by remembering the words associated with these operations and then somehow combining these results to give the final answer. Others mentally write out 100 with 46 beneath it and picture the process of writing down the answer below the two. Finally, some individuals have specialized equipment for just this operation. They visualize two juxtaposed scales from zero to 100, one starting at the right and one at the left. With this mnemonic gadget the required subtraction involves simply finding 46 on one of the scales and reading off 54 on the other!

    …Another interesting example involves the ability to visualize combinations of cubes. Try asking a number of persons to visualize a large cube made up of 27 smaller cubes, that is, three on each edge of the composite cube. Then, ask him to imagine painting the entire outer surface of the large cube. Finally, ask him how many of the smaller cubes he has painted on zero, one, two, or three sides. After he gives the result, ask him to describe the mental process he used in arriving at the answer. A surprising variety of answers come from this simple test. Some persons, even some professionally engaged in science and art, simply are unable to solve this problem mentally because they cannot visualize a cube in any way! Others stumble around with crude visualizations of a cube and end up by guessing at the answer. Some can visualize an opaque cube fairly well but must infer from the one view what is on the other side. The most potent approach seems to be that of the person who can visualize a transparent cube and simply count the smaller cubes whose sides are covered with paint, a process something like counting one’s fingers with his hands held up in front of him.

    In still another provocative problem, persons may be asked co give verbal directions for driving a car from one location to another, and then asked what they visualized mentally as they were giving the directions. Again, a wide variety of mental processes will be disclosed. Surprisingly, many persons report seeing the route as from a low-flying helicopter. The fact that different persons use vastly different visualizations in thinking is suggested by some other informal reports. One person has declared that he dreams only in words, that he does not use any form of visualization in dream states. It has been claimed by some semanticists that the human being thinks only in words. This seems an utterly absurd statement to many of us who spend a large part of our waking hours in visualizing and thinking in pictorial representations. This, of course, does not deny the fact that it is quite possible that semanticists do, in fact, think only in words; it would be logical that “word thinkers” would be drawn to this specialized field.

    …This is well illustrated by the now famous visualization by Kekule, as reported by Beveridge, which led him to the discovery of the benzene ring through a vision of a series of linked atoms biting its tail like a snake. Michael Faraday was one of the first to “see” the electrical and magnetic lines of force that now are standard tools for physicists to visualize otherwise mysterious phenomena in this area. Albert Einstein apparently believed that thought consisted entirely of dealing with mechanical images and not at all of words. The mathematician that he thought exclusively in visual pictures. However, these men did not seem to realize the uniqueness of their ability to visualize in manipulable images. They seemed to assume that all persons had much the same ability. Inventors with whom I have talked report thinking visually about complex mechanisms and organic chemical molecules combining with other molecules. So, it appears that ideas which can be grasped when drawn on paper can be visualized without being put onto paper, perhaps with many shorthand approximations for unimportant parts. Also, the nature of the seeing or sensing is peculiar. It is almost a feeling like the object being visualized. One can feel the pressure of contacting objects, or the erosion of material by friction, or the flow of heat from one point to another, or the swing of the oscillating electrical circuit, or the bending of light as it passes from one medium to another, or the appropriateness of a well-designed structure co hold a maximum load, with every part equally strained in the process, or the eternal bouncing about of the molecules of a gas, or the almost physical transfer of energy from the gasoline, through the motor, transmission, and to the driving wheels of the automobile. It is as though one’s own kinesthetic sensing mechanisms were associated with the physical object and that he thus sensed directly what was going on in the external system. In highly-developed visualizers, this process probably is carried over for other than physical phenomena. Thus, poverty can be seen and felt as a pervading vapor that penetrates a house with its odors and depression, and history might be strung out along an imaginary line extending back as far as one wishes.

    …At least here is a positive lead that is so apparent to the creative persons with whom I am familiar that they never stopped to consider whether or not it is special. When asked if they use life-like visualizations when they are inventing, they are inclined to say, “Why yes. Doesn’t everybody?” [See also: typical mind fallacy]

  • 1966-burt.pdf

  • 1966-klausmeier-analysesofconceptlearning.pdf

  • 1966-shuey-thetestingofnegrointelligencevol1.pdf

  • 1967-hodges.pdf (backlinks)

  • 1968-deutsch-socialclassraceandpsychologicaldevelopment.pdf

  • 1968-nichols.pdf: “Heredity, Environment, and School Achievement”⁠, Robert C. Nichols (backlinks)

  • 1968-oden.pdf: “The Fulfillment of Promise: 40-Year Follow-up of the Terman Gifted Group”⁠, Melita H. Oden

  • 1968-schoenfeldt.pdf: “The hereditary components of the Project TALENT two-day test battery”⁠, Lyle F. Schoenfeldt

  • 1968-thorndike.pdf (backlinks)

  • 1969-anderson.pdf

  • 1969-bereiter.pdf

  • 1969-brazziel.pdf

  • 1969-centermagazine-vol2-issue5.pdf

  • 1969-cottle.pdf

  • 1969-cronbach.pdf

  • 1969-crow.pdf

  • 1969-deutsch.pdf

  • 1969-elkind.pdf

  • 1969-fehr.pdf

  • 1969-hunt.pdf

  • 1969-jensen-2.pdf

  • 1969-jensen-her.pdf: ⁠, Arthur R. Jensen (1969-05-01; backlinks):

    Arthur Jensen argues that the failure of recent compensatory education efforts to produce lasting effects on children’s IQ and achievement suggests that the premises on which these efforts have been based should be reexamined. He begins by questioning a central notion upon which these and other educational programs have recently been based: that IQ differences are almost entirely a result of environmental differences and the cultural bias of IQ tests. After tracing the history of IQ tests, Jensen carefully defines the concept of IQ, pointing out that it appears as a common factor in all tests that have been devised thus far to tap higher mental processes. Having defined the concept of intelligence and related it to other forms of mental ability, Jensen employs an analysis of variance model to explain how IQ can be separated into genetic and environmental components. He then discusses the concept of “heritability,” a statistical tool for assessing the degree to which individual differences in a trait like intelligence can be accounted for by genetic factors. He analyzes several lines of evidence which suggest that the heritability of intelligence is quite high (i.e., genetic factors are much more important than environmental factors in producing IQ differences). After arguing that environmental factors are not nearly as important in determining IQ as are genetic factors, Jensen proceeds to analyze the environmental influences which may be most critical in determining IQ. He concludes that prenatal influences may well contribute the largest environmental influence on IQ. He then discusses evidence which suggests that social class and racial variations in intelligence cannot be accounted for by differences in environment but must be attributed partially to genetic differences. After he has discussed the influence on the distribution of IQ in a society on its functioning, Jensen examines in detail the results of educational programs for young children, and finds that the changes in IQ produced by these programs are generally small. A basic conclusion of Jensen’s discussion of the influence of environment on IQ is that environment acts as a “threshold variable.” Extreme environmental deprivation can keep the child from performing up to his genetic potential, but an enriched educational program cannot push the child above that potential. Finally, Jensen examines other mental abilities that might be capitalized on in an educational program, discussing recent findings on diverse patterns of mental abilities between ethnic groups and his own studies of associative learning abilities that are independent of social class. He concludes that educational attempts to boost IQ have been misdirected and that the educational process should focus on teaching much more specific skills. He argues that this will be accomplished most effectively if educational methods are developed which are based on other mental abilities besides I.Q.

  • 1969-jensen.pdf

  • 1969-kagan.pdf

  • 1969-light.pdf

  • 1969-rohwer.pdf

  • 1969-snow.html (backlinks)

  • 1969-stinchcombe.pdf

  • 1969-thorndike.pdf (backlinks)

  • 1970-dockrell-onintelligence.pdf

  • 1970-jensen-2.pdf

  • 1970-jensen-3.pdf

  • 1970-jensen.pdf: “doi:10.1016/S0074-7750(08)60022-1”

  • 1970-ramsey.pdf: “Factorial Invariance and its Relation to Race, Sex, and IQ”⁠, Philip Hart Ramsey

  • 1971-albert.pdf: ⁠, Robert S. Albert (1971-01-01; backlinks):

    This paper reports an analysis of descriptions of children with IQs of 155 or better. It is suggested that these children be distinguished from gifted children by the label exceptionally gifted. The paper reports some important cognitive differences between the two groups as well as the high rate of early parental loss among historically famous highly intelligent persons. This finding is discussed in the light of how certain parent-child relationships might contribute to the development of cognitive giftedness into high level of creative behavior.

  • 1971-cancro-intelligencegeneticandenvironmentalinfluences.pdf

  • 1971-cattell-abilitiestheirstructuregrowthaction.pdf: “Abilities: Their Structure, Growth, and Action”⁠, Raymond B. Cattell

  • 1971-herrnstein.pdf

  • 1971-jensen-3.pdf

  • 1971-jensen.pdf: “The Phylogeny and Ontogeny of Intelligence”⁠, Arthur R. Jensen

  • 1971-seemanova.pdf

  • 1971-shockley.pdf

  • 1971-stanley.pdf

  • 1972-cronbach.pdf: “"Mastery Learning: Theory and Practice" by James H. Block [book review]”⁠, Lee J. Cronbach

  • 1972-gage-2.pdf

  • 1972-gage.pdf

  • 1972-jensen-2.pdf

  • 1972-jensen-3.pdf

  • 1972-jensen-4.pdf

  • 1972-jensen-5.pdf

  • 1972-jensen-6.pdf

  • 1972-jensen-7.pdf: “The Case for IQ Tests: Reply to McClelland”⁠, Arthur R. Jensen

  • 1972-jensen-8.pdf: “I.Q. and Race: Ethical Issues”⁠, Arthur R. Jensen

  • 1972-jensen.pdf

  • 1972-kamin.pdf: “You Cannot Kill An Idea By Force”⁠, Leon J. Kamin

  • 1972-matarazzo.pdf

  • 1972-mcclelland.pdf

  • 1972-page.pdf

  • 1972-saturdayeveningpost.pdf

  • 1972-scarrsalapatek.pdf

  • 1972-shockley-2.pdf

  • 1972-shockley.pdf

  • 1972-stevens.pdf

  • 1973-dewolff.pdf (backlinks)

  • 1973-eysenck-themeasurementofintelligence.pdf: “The Measurement of Intelligence”⁠, Hans J. Eysenck

  • 1973-herrnstein-iqinthemeritocracy.pdf (backlinks)

  • 1973-jensen-2.pdf

  • 1973-jensen-4.pdf: ⁠, Arthur R. Jensen (1973):

    The well-known study by Skodak & Skeels 1949⁠, in which 100 infants who were born to unwed mothers of below-average IQ and were adopted into superior foster homes and grew up to obtain Stanford-Binet IQs averaging 20 points higher than the IQs of their biological mothers, has frequently been interpreted as a contradiction of the evidence for the high heritability of intelligence.

    It is here shown that this is a misinterpretation of the Skodak and Skeels results, based on failure to consider the prediction made from a simple polygenic model of parent-offspring resemblance.

    The Skodak and Skeels data, when analyzed properly in terms of a quantitative-genetic model, are found to be not all improbable or contradictory of a broad heritability for IQ in the range of 0.70 to 0.80. Also, the common fallacy of generalizing the results of Skodak and Skeels as an environmental explanation of the cause of the approximately 1 σ mean white-Negro IQ difference is explicated from the standpoint of genetic theory.

  • 1973-mccall.pdf (backlinks)

  • 1973-mcclelland.pdf: ⁠, David C. McClelland (1973-01; backlinks):

    Argues that while traditional intelligence tests have been validated almost entirely against school performance, the evidence that they measure abilities which are essential to performing well in various life outcomes is weak. Most of the validity studies are correlational in nature and fail to control for the fact that social class might be a 3rd variable accounting for positive correlations between test scores and occupational success, and between level of schooling achieved and occupational success. It is suggested that better measures of competence might be derived by analysis of successful life outcomes and the competencies involved in them, criterion sampling, and assessment of communication skills.

  • 1973-white.pdf: “The Structure Of Intellect Model As A Basis For Cross-Cultural Analysis Of Tests”⁠, Herbert Leon White

  • 1974-jensen-3.pdf

  • 1974-jensen.pdf

  • 1974-krawiec-thepsychologistsvol2.pdf

  • 1974-walberg-evaluatingeducationalperformance.pdf

  • 1975-cronbach.pdf (backlinks)

  • 1975-keating.pdf: ⁠, Daniel P. Keating (1975-01-01):

    The data from Terman’s Genetic Studies of Genius (1925-1959) relating to sample size, mean IQ, and variance of IQ scores were analyzed in terms of their conformation to the theoretically projected statistics derived from a consideration of the normal curve. Deviations from the theoretical projections lead to the probable conclusion that the sample size was too small, with the IQ scores clustered more closely about a significantly higher mean than projected. Although the major findings of the “Genius” study are not cast into doubt by this analysis, caution is urged with respect to comparisons to a normal sample when the differences are not large.

  • 1975-kilgore.pdf: “Academic Values and the Jensen-Shockley Controversy”⁠, William J. Kilgore, Barbara Sullivan

  • 1975-seagoe-termanandthegifted.pdf: “Terman and the Gifted”⁠, Seagoe, May V. (May Violet), 1906

  • 1976-ashline-educationinequalityandnationalpolicy.pdf

  • 1976-brody-intelligence.pdf: “Intelligence: Nature, Determinants, and Consequences”⁠, Erness Bright Brody, Nathan Brody

  • 1976-jensen.pdf

  • 1976-montour.pdf: “Three Precocious Boys: What Happened To Them”⁠, Kathleen Montour

  • 1976-shayer.pdf

  • 1977-harwood.pdf: “The Race-Intelligence Controversy: A Sociological Approach II — 'External' Factors”⁠, Jonathan Harwood

  • 1977-jensen-2.pdf

  • 1977-jensen-3.pdf: “The nature of intelligence and its relation to learning”⁠, Arthur R. Jensen

  • 1977-jensen-4.pdf: ⁠, Arthur R. Jensen (1977-01-01):

    Internal evidence of cultural bias, in terms of various types of item analysis, was sought in the Wonderlic Personnel Test results in large, representative samples of Whites and Blacks totaling some 1,500 subjects. Essentially, the lack of any appreciable Race × Items interaction and the high interracial similarity in rank order of item difficulties lead to the conclusion that the Wonderlic shows very little evidence of cultural bias with respect to the present samples which, however, differ appreciably in mean scores. The items which account for the most variance within each racial group are, by and large, the same items that show the largest interracial discrimination.

  • 1977-jensen.pdf: “An Unfounded Conclusion In M.W. Smith'S Analysis Of Culture Bias In The Stanford-Binet Intelligence Scale”⁠, Relais Articlizer

  • 1977-kuse.pdf

  • 1977-montour.pdf: “William James Sidis, the broken twig”⁠, Kathleen Montour

  • 1977-smith.pdf

  • 1977-stickney.pdf (backlinks)

  • 1978-firkowska.pdf (backlinks)

  • 1978-jensen-2.pdf

  • 1978-jensen.pdf: “Sex linkage and race differences in spatial ability: A reply”

  • 1978-komm.pdf: “A Comparison Of The Black Intelligence Test Of Cultural Homogeneity With The Wechsler Intelligence Scale For Children (Revised), As Measured By A Conventional Achievement Test Within A Black Population At Different Social Class Levels”⁠, Richard Arnold Komm

  • 1978-last.pdf: “Genetical Aspects of Human Behaviour”⁠, Krystyna Last

  • 1978-scarr.pdf: “The Influence of 'Family Background' on Intellectual Attainment”⁠, Sandra Scarr, Richard A. Weinberg

  • 1978-walberg.pdf: ⁠, Herbert J. Walberg, Sue Pinzur Rasher, Keiko Hase (1978-06-01):

    Indicators of eminence derived from word and citation counts in primary biographical articles in encyclopedias published at the turn of the century, in 1935, and 1974 correlate positively 0.33 overall with IQ estimates made from biographical sources on a select sample of 282 philosophers, scientists, non-fiction and fiction writers, musicians, artists, religious leaders, statesmen, revolutionaries, and soldiers. These results are striking since the sample is restricted to the higher end of the eminence distribution; the mean estimated IQ for the total group is 158.9. Indicators of eminence for some fields—philosophers, musicians, and artists—vary from one period to the next. Individuals also shift in estimated eminence during the three time periods examined.

  • 1979-cox.pdf: ⁠, William F. Cox Jr, Thomas G. Dunn (1979):

    In spite of all its announced advantages, the implementation of mastery learning instruction often falls short of theoretical expectations. As discussed under the four major characteristics of mastery learning [systematic design of instruction/instructional correctives/ample time to learn/clear criterion of mastery], these implementation weaknesses pose serious problems for unsuspecting students, teachers, and instructional designers alike.

  • 1979-freedman.pdf: “Biological and Cultural Differences in Early Child Development”⁠, D G. Freedman, M. M DeBoer

  • 1979-humphreys.pdf: “Dimensions Involved in Differences among School Means of Cognitive Measures”⁠, Lloyd G. Humphreys, Charles K. Parsons, Randolph K. Park

  • 1979-jensen.pdf

  • 1979-lynn.pdf (backlinks)

  • 1979-needleman.pdf: ⁠, Needleman Herbert L., Gunnoe Charles, Leviton Alan, Reed Robert, Peresie Henry, Maher Cornelius, Barrett Peter (1979-03-29; backlinks):

    To measure the neuropsychological effects of unidentified childhood exposure to lead, the performance of 58 children with high and 100 with low dentine lead levels was compared. Children with high lead levels scored statistically-significantly less well on the Wechsler Intelligence Scale for Children (Revised) than those with low lead levels. This difference was also apparent on verbal subtests, on 3 other measures of auditory or speech processing and on a measure of attention. Analysis of variance showed that none of these differences could be explained by any of the 39 other variables studied.

    Also evaluated by a teachers’ questionnaire was the classroom behavior of all children (2146 in number) whose teeth were analyzed. The frequency of non-adaptive classroom behavior increased in a dose-related fashion to dentine lead level. Lead exposure, at doses below those producing symptoms severe enough to be diagnosed clinically, appears to be associated with neuropsychological deficits that may interfere with classroom performance. [See also ]

  • 1980-jensen-biasinmentaltesting.pdf (backlinks)

  • 1980-jensen-biasmentaltesting-iqcorrelates.pdf (backlinks)

  • 1980-jensen.pdf: “Correcting the bias against mental testing: A preponderance of peer agreement”⁠, Arthur R. Jensen

  • 1980-lewin.pdf: ⁠, Roger Lewin (1980-12-12; backlinks):

    …Lorber was not jesting totally when he addressed a conference of pediatricians with a paper entitled “Is your brain really necessary?” Lorber believes that his observations on a series of hydrocephalics who have severely reduced brain tissue throws into question many traditional notions about the brain, both in clinical and scientific terms.

    “There’s a young student at this university,” says Lorber, “who has an IQ of 126, has gained a first-class honors degree in mathematics, and is socially completely normal. And yet the boy has virtually no brain.” The student’s physician at the university noticed that the youth had a slightly larger than normal head, and so referred him to Lorber, simply out of interest. “When we did a brain scan on him,” Lorber recalls, “we saw that instead of the normal 4.5-centimeter thickness of brain tissue between the ventricles and the cortical surface, there was just a thin layer of mantle measuring a millimeter or so. His cranium is filled mainly with cerebrospinal fluid.”

    …In young children, whose skulls are still malleable, one obvious consequence can be a grossly enlarged head. Additionally, this physical assault from within leads to a real loss of brain matter. It is therefore not surprising that many hydrocephalics suffer intellectual and physical disabilities. What is surprising, however, is that a substantial proportion of patients appear to escape functional impairment in spite of grossly abnormal brain structure.

    “The spina bifida unit at the Children’s Hospital here in Sheffield is one of the largest in the world,” explains Lorber, “and this gives us an opportunity to make many observations. Since the introduction of the safe, noninvasive brain scanning technique just a few years ago we have done more than 600 scans on patients with hydrocephalus.” Lorber divides the subjects into four categories: those with minimally enlarged ventricles; those whose ventricles fill 50 to 70% of the cranium; those in which the ventricles fill between 70 and 90% of the intracranial space; and the most severe group, in which ventricle expansion fills 95% of the cranium. Many of the individuals in this last group, which forms just less than 10% of the total sample, are severely disabled, but half of them have IQ’s greater than 100. This group provides some of the most dramatic examples of apparently normal function against all odds.

    Commenting on Lorber’s work, Kenneth Till, a former neurosurgeon at the Great Ormond Street Hospital for Sick Children, London, has this to say: “Interpreting brain scans can be very tricky. There can be a great deal more brain tissue in the cranium than is immediately apparent.” Till echoes the cautions of many practitioners when he says, “Lorber may be being rather overdramatic when he says that someone has ‘virtually no brain.’” Lorber acknowledges the problem of interpretation of brain scans, and he counters Till’s remarks by insisting, “Of course these results are dramatic, but they’re not overdramatic. One would not make the claim if one did not have the evidence.”

    …Lorber concludes from these observations that “there must be a tremendous amount of redundancy or spare capacity in the brain, just as there is with kidney and liver.” He also contends that “the cortex probably is responsible for a great deal less than most people imagine.” These are two areas of considerable dispute in neurobiology. Wall lends support for this second point. “One reason why results such as Lorber’s have been neglected for so long is because of the implied attack on the predominance of the cerebral cortex,” suggests Wall. “For hundreds of years neurologists have assumed that all that is dear to them is performed by the cortex, but it may well be that the deep structures in the brain carry out many of the functions assumed to be the sole province of the cortex.” He likens the cortex to a “reference library” that may be consulted from time to time.

    On the question of the brain’s spare capacity there is equal contention. “To talk of redundancy in the brain is an intellectual cop-out to try to get round something you don’t understand,” states Wall. Geschwind agrees: “Certainly the brain has a remarkable capacity for reassigning functions following trauma, but you can usually pick up some kind of deficit with the right tests, even after apparently full recovery.” However, Colin Blakemore, professor of physiology at Oxford University, England, sees spare capacity as an important quality of the human brain. “The brain frequently has to cope with minor lesions and it’s crucial that it can overcome these readily,” he says; “there may be some reorganization of brain tissue, but mostly there’s a reallocation of function.”

    It is perhaps important that many of the instances in which gross enlargement of cerebral ventricles is compatible with normal life are cases where the condition develops slowly. Gross surgical lesions in rat brains are known to inflict severe functional disruption, but if the same damage is done bit by bit over a long period of time, the dysfunction can be minimal. Just as the rat brains appear to cope with a stepwise reduction of available hardware, so too do the human brains in some cases of hydrocephalus…The sparing of the gray matter even in severe hydrocephalus could go some way to explaining the remarkable retention of many normal functions in severely affected individuals….

  • 1980-lynn-2.pdf: “On the intelligence of the Japanese and other mongoloid peoples”⁠, Richard Lynn, Jenny Dziobon

  • 1980-lynn.pdf (backlinks)

  • 1980-mcclelland.pdf: ⁠, David C. McClelland, Richard E. Boyatzis (1980-01; backlinks):

    Innovations in testing emerging from the competency assessment movement offer counselors new capabilities in helping their clients to understand aspects of themselves and their problems, as well as to establish directions for development and improvement efforts. New types of tests and measures sample actual behavior more closely than testing instruments previously used: The characteristics they examine are closely linked to performance in a wide variety of jobs, and therefore provide increased focus of assessment on life outcomes. With this new degree of specificity and criterion referencing, implications for counseling, training, and development efforts emerge more clearly than with other forms of testing.

  • 1981-bouchard.pdf

  • 1981-hyde.pdf

  • 1981-lynn.pdf (backlinks)

  • 1982-detterman.pdf

  • 1982-garfinkle.pdf: ⁠, Arleen S. Garfinkle (1982-01):

    The classical twin study method was used to assess the relative contributions of genetic and environmental components to individual variation in several aspects of cognitive functioning. Tests of logico-mathematical concept formation, as well as vocabulary, nonverbal reasoning, and visual memory, were administered to 137 MZ and 72 DZ, same-sex white twin pairs. These children were individually tested on the Piagetian Mathematical Concepts Battery (PMCB), Peabody Picture Vocabulary Test (PPVT), Raven Coloured Progressive Matrices (PM), and a Visual Memory (VM) test. The Attitudes Toward Education (ATE) questionnaire and the Moos [63] Family Environment Scale (FES) were used to collect additional data from the parents. Twins were 4 to 8 years old, with a mean age of 71 months, and most were from middle-class and upper-middle-class families. Zygosity was determined from dermatoglyphic information and responses to a questionnaire asking mothers about twin similarities and confusion between the twins by others. These data were analyzed by a simple pair concordance procedure and by a discriminant function analysis. In addition, blood typing was done on 32 pairs for whom zygosity was not possible to determine by these methods.

    Previously reported patterns of intercorrelations among the 10 subscales of the FES, as well as the subscale structure, were verified by factor analysis. A factor analysis of the ATE yielded three factors: Basic Academic Education, Parental Participation, and General Utility of Education. These factors correlated statistically-significantly (p < 0.01) with various environmental indices (including father’s occupation and education, Achievement Orientation, Expressiveness, etc). A factor analysis of the PMCB tasks gave some support for the existence of Piaget’s underlying concepts of conservation of number, seriation, and classification.

    No sex differences were found for any of the specific cognitive abilities or any of the environmental variables. Correlations with age were substantial: 0.75 for PMCB, 0.70 for PPVT, 0.59 for PM, and 0.43 for VM. Because of the high correlations with age, the effect of age on these variables was partialed out in all further analyses. PMCB correlated most highly with PM (r = 0.41), and with PPVT (r = 0.36). Nonverbal reasoning and vocabulary were relatively independent of each other (r = 0.23). Correlations between visual memory and all other tests were low.

    MZ and DZ intraclass correlations for height and weight were similar to values reported in other studies. After correcting for test reliability, statistically-significant genetic variance (p < 0.01) was found for both PMCB and PPVT, and was suggested for VM. Genetic variance for PM was not statistically-significant (p > 0.05). Correction for reliability could not be employed in this case because an accurate estimate of the PM test-retest reliability is not available. There was no statistically-significant effect of age on the magnitude of the MZ or DZ intraclass correlations.

    A stepwise multiple regression on the environmental variables was performed for each cognitive test. The environmental variables considered were number of siblings, parental education and occupation, the 10 FES subscales, and the three ATE factors. Age was entered first in the regression equation for each test, and it accounted for 18% to 57% of the total variance in cognitive performance. Parental education accounted for 3% of the total variance in both PMCB and PPVT performance. This was considered as an environmental influence, but the possible confounding with a genetic element in parental IQ was discussed. Achievement Orientation exhibited a statistically-significant negative relationship (R2 = 0.02) with PM performance. Cohesion in the Family was positively related to PPVT performance (R2 = 0.02). In addition, Intellectual-Cultural Orientation predicted VM performance (R2 = 0.02). Overall, those environmental variables found to have a small effect suggest the value of a warm, stimulating, supportive (but not “pushy”) family environment for normal cognitive development in young children.

    Examination of the genetic and environmental results indicated that 49% of the variance in age-corrected PMCB performance was accounted for by the genetic variance (estimated from twin comparisons) and parental education. Similarly, variables identified in this investigation accounted for 60% of the variance in age-corrected PPVT performance, 29% of the age-corrected PM performance, and 32% of age-corrected VM performance.

    In conclusion, this was the first large twin study to find both genetic and environmental influences on the development of Piagetian logico-mathematical concepts and other specific cognitive abilities. The results illustrate the feasibility of investigating cognitive development in a theoretical framework such as Piaget’s.

  • 1982-jensen-2.pdf

  • 1982-jensen-3.pdf: “The Debunking of Scientific Fossils and Straw Persons”⁠, Arthur R. Jensen

  • 1982-jensen.pdf: “Bias in mental testing: A final word”⁠, Arthur R. Jensen

  • 1982-osborne-thetestingofnegrointelligencevol2.pdf

  • 1982-reed.pdf: “Parent-offspring correlations and regressions for IQ”⁠, Sheldon C. Reed, Stephen S. Rich

  • 1982-samelson.pdf

  • 1982-stanley.pdf

  • 1982-sternberg-advancespsychologyhumanintelligencevol1.pdf

  • 1983-ashton.pdf: “Mental Abilities of Children of Incross and Outcross Matings in Hawaii”⁠, Geoffrey C. Ashton, Ming-Pi Mi

  • 1983-cattell-intelligenceandnationalachievement.pdf (backlinks)

  • 1983-horn.pdf: “The Texas Adoption Project: Adopted Children and Their Intellectual Resemblance to Biological and Adoptive Parents”⁠, Joseph M. Horn

  • 1983-hunter.pdf: ⁠, J. E. Hunter (1983):

    Through a meta-analysis of 14 studies, Dr. Hunter investigates the relationships among three variables: ability, job knowledge and performance. Performance is measured in two ways, work sample tests and supervisory ratings. Two causal models are presented which depict the possible relationships among the three variables. The first model suggests a direct impact of ability on performance, on job knowledge, and on supervisor ratings. This implies that there is an indirect relationship impact of job knowledge on supervisory ratings. The alternative model suggests that job knowledge is directly related to supervisory ratings. The results of the path analysis provide support for the latter model.

    Dr. Guion states that Hunter’s findings provide evidence for the validity of ratings. However, the model is incomplete. He suggests that the model should be enlarged to include such exogenous variables as rater characteristics, ratee characteristics, and context factors.

  • 1983-jensen.pdf

  • 1984-gowan.pdf (backlinks)

  • 1984-hunter.pdf: ⁠, John Edward Hunter, Ronda F. Hunter (1984; backlinks):

    Meta-analysis of the cumulative research on various predictors of job performance shows that for entry-level jobs there is no predictor with validity equal to that of ability, which has a mean validity of 0.53. For selection on the basis of current job performance, the work sample test, with mean validity of 0.54, is slightly better. For federal entry-level jobs, substitution of an alternative predictor would cost from $9.32$3.121984 billion (job tryout) to $47.49$15.891984 billion per year (age). Hiring on ability has a utility of $46.65$15.611984 billion per year, but affects minority groups adversely. Hiring on ability by quotas would decrease this utility by 5%. A third strategy—using a low cutoff score—would decrease utility by 83%. Using other predictors in conjunction with ability tests might improve validity and reduce adverse impact, but there is as yet no data base for studying this possibility.

  • 1984-jensen-2.pdf

  • 1984-jensen-3.pdf

  • 1984-jensen-4.pdf

  • 1984-jensen-5.pdf

  • 1984-jensen-6.pdf

  • 1984-jensen-7.pdf

  • 1984-jensen-8.pdf

  • 1984-jensen-9.pdf

  • 1984-jensen.pdf

  • 1984-schmitt.pdf (backlinks)

  • 1984-selden.pdf

  • 1984-sternberg.pdf: “Mental speed and levels of analysis”⁠, Arthur R. Jensen

  • 1985-fancher-theintelligencemen.pdf: “The Intelligence Men: Makers of the IQ Controversy”⁠, Raymond E. Fancher

  • 1985-gagne.pdf (backlinks)

  • 1985-jensen.pdf

  • 1985-johnson.pdf: “Galton's data a century later”⁠, Ronald C. Johnson, Gerald E. McClearn, Sylvia Yuen, Craig T. Nagoshi, Frank M. Ahern, Robert E. Cole

  • 1985-thompson.pdf

  • 1985-wolman-handbookofintelligencetheoriesmeasurementsapplications.pdf: “Handbook of Intelligence: Theories, Measurements, And Applications”⁠, Wolman, Benjamin B

  • 1986-arvey.pdf: “General ability in employment: A discussion”⁠, Richard D. Arvey (backlinks)

  • 1986-avery.pdf: “Origins of and Reactions to the PTC conference on _The g Factor In Employment Testing_”⁠, Lillian Markos Avery (backlinks)

  • 1986-bower.pdf

  • 1986-gottfredson-2.pdf: “Validity versus utility of mental tests: Example of the SAT⁠, Linda S. Gottfredson, James Crouse (backlinks)

  • 1986-gottfredson-3.pdf: “Societal consequences of the g factor in employment”⁠, Linda S. Gottfredson (backlinks)

  • 1986-gottfredson.pdf: “The _g_ factor in employment”⁠, Linda S. Gottfredson (backlinks)

  • 1986-hawk.pdf: “Real world implications of g”⁠, John Hawk (backlinks)

  • 1986-humphreys.pdf: “Commentary [on 'The _g_ factor in employment special issue']”⁠, Lloyd G. Humphreys (backlinks)

  • 1986-hunter.pdf: “Cognitive ability, cognitive aptitudes, job knowledge, and job performance”⁠, John E. Hunter (backlinks)

  • 1986-jensen.pdf: “g: Artifact or Reality?”⁠, Arthur R. Jensen (backlinks)

  • 1986-linn.pdf: “Comments on the g factor in employment testing”⁠, Robert L. Linn (backlinks)

  • 1986-sears.pdf: “Catharine Cox Miles: 1890-1984”⁠, Robert R. Sears

  • 1986-spitz-theraisingofintelligence.pdf: “The Raising of Intelligence: A Selected History of Attempts To Raise Retarded Intelligence”⁠, H. H. Spitz

  • 1986-sternberg-whatisintelligence.pdf

  • 1986-thorndike.pdf: “The role of general ability in prediction”⁠, Robert L. Thorndike (backlinks)

  • 1986-tyler.pdf: “Back to Spearman?”⁠, Leona E. Tyler (backlinks)

  • 1987-cattell-intelligenceitsstructuregrowthaction.pdf

  • 1987-edwards.pdf: “Antecedents Of Academic Achievement Among Elementary School American Indians And Their Classmates”⁠, Karl Ormond Edwards

  • 1987-jensen.pdf

  • 1987-simonton.pdf: ⁠, Dean Keith Simonton (1987; backlinks):

    [Literature review of Simonton & other’s research into life history predictors of great accomplishment in the arts/sciences/politics/etc, particularly childhood: what variables seem to correlate with later eminence? Simonton discusses as predictors: 1. intelligence; 2. birth order (first-born); 3. extreme motivation/drive; 3. parental loss/orphanhood (!); 4. a previous generation of role models to imitate; 5. formal education (or lack thereof); 6. global circumstances/‘zeitgeist’.

    On nature-nurture, Simonton deprecates the role of genetics, arguing that genius counts fluctuate too much and are too sporadic over time to reflect primarily genetics, but see Lykken et al on ‘emergenesis’⁠, dysgenics, and tail effects in order statistics (especially the Lotka curve/log-normal distribution ‘leaky pipeline’ Simonton is so familiar with) for why this argument is weak.]

  • 1987-vernon-speedofinformationprocessingandintelligence.pdf

  • 1987-wineburg-2.pdf (backlinks)

  • 1987-wineburg.pdf (backlinks)

  • 1988-humphreys.pdf (backlinks)

  • 1988-janos.pdf

  • 1988-jensen.pdf

  • 1988-snyderman-theiqcontroversythemediaandpublicpolicy.pdf (backlinks)

  • 1989-buckhalt.pdf

  • 1989-carroll.pdf: ⁠, John B. Carroll (1989-01-01):

    The Model of School Learning, first published 25 years ago, has taken its place as a useful guide in research on teaching and learning in schools. The model accounts for variations in school learning with five classes of variables, three, of which can be expressed in terms of time, the other two in terms of achievement. Most aspects of the model have been confirmed, although details remain to be filled out by further research. Ways that the model might be used to address current problems in education are considered. The model’s emphasis on aptitude as a determinant of time needed for learning suggests that increased efforts be placed on predicting student potentialities and designing instruction appropriate to those potentialities, if ideals of equal opportunity to learn are to be achieved within a diversity of educational objectives.

  • 1989-jensen-2.pdf (backlinks)

  • 1989-jensen.pdf: “amp4450844.tif”

  • 1989-linn-intelligencemeasurementtheoryandpublicpolicy.pdf: “Intelligence: Measurement, Theory, and Public Policy (Proceedings of a Symposium in Honor of Lloyd G. Humphreys, Apr 30-May 2 1985)”⁠, Robert L. Linn

  • 1989-subotnik.pdf (backlinks)

  • 1990-benbow.pdf (backlinks)

  • 1990-bouchard.pdf: “Sources of Human Psychological Differences: The Minnesota Study of Twins Reared Apart”⁠, Thomas J. Bouchard, Jr., David T. Lykken, Matthew McGue, Nancy L. Segal, Auke Tellegen

  • 1990-hunter.pdf: “Individual Differences in Output Variability as a Function of Job Complexity”⁠, John E. Hunter, Frank L. Schmidt, Michael K. Judiesch (backlinks)

  • 1990-locurto.pdf: “The malleability of IQ as judged from adoption studies”⁠, Charles Locurto

  • 1990-silverman.pdf

  • 1990-thorndike-acenturyofabilitytesting.pdf: “A Century of Ability Testing”⁠, Robert M. Thorndike, David F. Lohman

  • 1990-welsh.pdf: ⁠, John R. Welsh, Susan K. Kucinkas, Linda T. Curran (1990-07-01):

    The purpose of this review was to integrate validity evidence relevant to the primary use of the Armed Services Vocational Aptitude Battery (ASVAB) as a selection and classification tool for military manpower, personnel, and training systems. The review covers the period from the first use of ASVAB Form 1 in 1966 in the DOD Student Testing Program to the latest reports of the validity for ASVAB Forms 11, 12, 13, and 14. The review presents the evidence for the construct, content, and criterion-related validity of the ASVAB. 172 studies from the military and civilian sectors and from the professional literature were reviewed and summarized to show averaged validity for military occupations. Reviewed studies established the validity of the ASVAB as a predictor of success in military technical training schools, and its validity for other criteria such as first-term attrition and job performance. Implications of the review for the military selection and classification systems are discussed.

    …This review discusses the validity of the ASVAB for a number of different types of criteria. Among them are final technical school training grade, time-to-completion for self-paced technical training courses, attrition from technical training, first-term attrition, and experimental job performance measures.

    The primary conclusion from the review of the literature is that the ASVAB aptitude composites and Armed Forces Qualification Test (AFQT) are valid predictors of final school grades, self-paced technical school completion times, first-term attrition, and job performance measures. The consistent finding from empirical, criterion-related studies shows that the five composites examined in this review (Mechanical-M, Administrative-A, General-G, Electronics-E and the AFQT) all predict final technical school grades with an order of magnitude between 0.55 and 0.60 (corrected for restriction in range). The validity coefficients of these five ASVAB composites against other criteria are lower, but still appreciable.

  • 1991-arthur.pdf: ⁠, Winfred Arthur, Gerald V. Barret, Ralph A. Alexander (1991; backlinks):

    Previous attempts to summarize the vehicular accident involvement literature have been non-quantitative. Outcomes of these reviews have also reflected the equivocalness of research in this area. In an attempt to synthesize the diverse research findings into a collective result, a meta-analysis procedure that controlled for sampling error was used.

    4 classes of variables were identified as predictors of vehicular accident involvement. These were information-processing, cognitive ability, personality, and demographic/biographical variables. Moderate-to-marginally favorable overall meta-analysis results were obtained for selective attention, regard for authority, locus of control, and cognitive ability as predictors of vehicular accident involvement.

    Suggestions and directions for future research are discussed.

  • 1991-barrett.pdf: ⁠, Gerald V. Barrett, Robert L. Depinet (1993; backlinks):

    David C. McClelland’s 1973 article has deeply influenced both professional and public opinion. In it, he presented 5 major themes: (1) Grades in school did not predict occupational success, (2) intelligence tests and aptitude tests did not predict occupational success or other important life outcomes, (3) tests and academic performance only predicted job performance because of an underlying relationship with social status, (4) such tests were unfair to minorities, and (5) “competencies” would be better able to predict important behaviors than would more traditional tests. Despite the pervasive influence of these assertions, this review of the literature showed only limited support for these claims.

  • 1991-gottfredson.pdf: “The Evaluation of Alternative Measures of Job Performance”⁠, Linda S. Gottfredson

  • 1991-jensen.pdf

  • 1991-johnson.pdf: “Biological factors and psychometric intelligence: A review”⁠, Fred W. Johnson

  • 1991-laurence-lowaptitudemeninthemilitary.pdf (backlinks)

  • 1991-pearson-raceintelligencebiasinacademe.pdf: “Race, Intelligence and Bias in Academe”⁠, Roger Pearson

  • 1991-simonton.pdf (backlinks)

  • 1992-bourhis.pdf: ⁠, John Bourhis, Mike Allen (1992; backlinks):

    Although numerous studies have examined the relationship between communication apprehension (CA) and cognitive performance (e.g., IQ grade point averages, course grades, assignment grades, and test scores), the findings are equivocal.

    One area of findings suggests that students in the traditional educational environment experiencing high CA are at a distinct disadvantage when compared to their low or moderate counterparts. A second area of findings suggests that no statistically-significant relationship exists. A third area indicates that the nature of the instructional environment is a statistically-significant mediating variable that moderates the effects of CA on cognitive performance.

    In the present study, a meta-analysis was conducted of 23 manuscripts containing information on 30 experiments that examined CA and cognitive performance. Results confirmed a statistically-significant negative correlation between CA and cognitive performance.

    Implications for future research and classroom instruction are discussed.

  • 1992-brody-intelligence.pdf: “Intelligence, Second Edition”

  • 1992-feingold.pdf (backlinks)

  • 1992-gustafsson-2.pdf

  • 1992-gustafsson.pdf

  • 1992-guttman.pdf

  • 1992-hollinger.pdf (backlinks)

  • 1992-jensen-2.pdf

  • 1992-jensen-4.pdf: “Henry Felix Kaiser (1927—1992). In Memoriam”⁠, Arthur R. Jensen, M. Wilson

  • 1992-jensen-5.pdf (backlinks)

  • 1992-jensen.pdf

  • 1992-loehlin-2.pdf

  • 1992-loehlin.pdf

  • 1992-mulaik.pdf

  • 1992-rhodes.pdf (backlinks)

  • 1992-roskam-2.pdf

  • 1992-roskam.pdf

  • 1992-schonemann-2.pdf

  • 1992-schonemann.pdf

  • 1992-shurkin-termanskids.pdf: “Terman's Kids: The Groundbreaking Study of How the Gifted Grow Up”⁠, Joel N. Shurkin

  • 1993-anderson.pdf: ⁠, Britt Anderson (1993-01-01):

    The data on a group of 22 rats, each measured for their speed of reasoning, accuracy of reasoning, response flexibility, and attention for novelty, were subjected to two different methods of factor analysis. By both methods, the correlation matrix of their performance was consistent with a single-factor model. In a second cohort of rats, where brain size was known, the score for this ‘general factor’ was computed. The regression for brain weight and the general factor was statistically-significant. [Keywords: intelligence, reasoning, rat, methylazoxymethanol, brain, mental retardation]

  • 1993-bock-theoriginanddevelopmentofhighability.pdf: “The Origins and Development of High Ability”⁠, Gregory R. Bock, Kate Ackrill, R. C. Atkinson, Robert J. Sternberg, Douglas K. Detterman, C. P. Benbow, David Lubinski, Robert Plomin, L. A. Thompson, M. J. A. Howe, J. Sloboda, J. C. Stanley, K. A. Heller, N. Colangelo, S. G. Assouline, B. Kerr, R. Huesman, D. Johnson, Howard Gardner, M. Csikszentmihalyi, I. S. Csikszentmihalyi, W. . Fowler, K. Ogston, G. Roberts-Fiati, A. Swenson, K. A. Ericsson, R. Th. Krampe, S. Heizmann, R. C. Atkinson (backlinks)

  • 1993-cahan.pdf

  • 1993-chubarikov.pdf (backlinks)

  • 1993-detterman.pdf: “The Case for the Prosecution: Transfer as an Epiphenomenon”⁠, Douglas K. Detterman

  • 1993-huitema.pdf: ⁠, Bradley E. Huitema, Cheri R. Stein (1993-02-01):

    Restriction of range is a frequently acknowledged issue in estimating the validity of predictors of academic performance in graduate school. Data obtained from a doctoral program in a psychology department where graduate students were admitted without regard to Graduate Record Examination (GRE) scores yielded essentially identical standard deviations on this test for the 204 applicants and 138 enrolled students. The GRE-Total validity coefficients obtained on subjects in the enrolled sample ranged from .55 through .70; these values are considerably higher than those typically reported. The data are congruent with the argument that uncorrected GRE validity coefficients yield biased estimates of the unknown validity in unrestricted applicant pools.

  • 1993-jensen.pdf (backlinks)

  • 1993-maier.pdf: “Military Aptitude Testing: The Past Fifty Years”⁠, Milton H. Maier

  • 1993-senior.pdf: “Canadian Native Intelligence Studies: A Brief Review”⁠, Sharon Senior

  • 1993-subotnik-geniusrevisited.pdf (backlinks)

  • 1993-thompson.pdf

  • 1993-vernon-biologicalapproachestudyhumanintelligence.pdf

  • 1994-barrett.pdf: ⁠, Gerald V. Barrett (1994-01; backlinks):

    Comments that after considering the responses of R. E. Boyatzis (see record 1994-27864-001) and D. C. McClelland (see record 1994-27871-001) and reviewing additional reports by these authors, the conclusions drawn by G. V. Barrett and R. L. Depinet’s (see record 1992-03797-001) article on competence testing are reinforced. If McClelland’s concept of competencies is to make a contribution to psychology, he must present empirical data to support his contention. Three sets of data are presented to illustrate this point.

    [Barrett points out that according to McClelland’s own analyses, his proposed screening methods barely predict job performance, are usually not even statistically-significant, would violate employment/discrimination law, and that McClelland’s claim that his methods don’t work because of the is an excuse.]

  • 1994-braden-deafnessdeprivationandiq.pdf

  • 1994-brody.pdf

  • 1994-carroll.pdf

  • 1994-ceci.pdf

  • 1994-detterman-currentopicshumanintelligence-4-theoriesofintelligence.pdf

  • 1994-detterman.pdf

  • 1994-flynn.pdf

  • 1994-humphreys-2.pdf

  • 1994-humphreys.pdf

  • 1994-jensen-2.pdf: “Guy Thomas Buswell. In Memoriam (1891-1994)”⁠, Arthur R. Jensen, Robert B. Ruddell

  • 1994-jensen-3.pdf

  • 1994-jensen-4.pdf

  • 1994-jensen-5.pdf

  • 1994-jensen-6.pdf

  • 1994-jensen-7.pdf

  • 1994-jensen.pdf

  • 1994-mcclelland.pdf: ⁠, David C. McClelland (1994; backlinks):

    Responds to the criticisms of regarding the author’s (1973) article on competence testing. D. C. McClelland agrees with Barrett and Depinet’s dismissal of competency testing as a poor alternative to ability testing. McClelland holds that well-designed competency-based tests could make an important contribution to selecting people who are better suited for certain jobs, but that these tests will not be developed until there is a strong commitment by psychologists to develop them and the necessary financial support is available.

  • 1994-rowe-2.pdf: “No More Than Skin Deep: Ethnic and Racial Similarity in Development Process”⁠, David C. Rowe, Alexander T. Vazsonyi, Daniel J. Flannery

  • 1994-rowe.pdf: “No More Than Skin Deep”⁠, David C. Rowe

  • 1994-schwartz.pdf: ⁠, J. Schwartz (1994-07-01; backlinks):

    While sophistication in public health research has been increasing substantially in the past few decades, sophistication in decision making about public health and environmental issues has not been increasing in parallel. Measures that are inexpensive tend to be implemented and measures that are expensive tend not to be implemented by makers of public policy. That is often independent of the degree of public health protection afforded by the measures. Understanding and addressing this pattern is crucial to the control of lead exposure of critical populations. People are still exposed to lead in our society not because anyone believes that exposure is good, but because reducing exposure costs money. Maintaining exposure also has its costs, however. It is more difficult to measure them, and they are often ignored in decision making—but they are not small, and attempts to measure them have been made. The high cost of reducing lead exposure of critical populations is the reason that progress in reducing lead-paint exposure has been minimal in the 18 years since the passage of the Lead-Based Paint Poisoning Prevention Act and that it took from the time of the initial proposal in 1973 until 1986 before lead was substantially eliminated from gasoline. In its 1986 rule making, the EPA estimated that the elimination of lead from gasoline would cost more than $1,349$5001986 million per year. Removing leaded paint is estimated to cost billions of dollars. The difference is that the EPA promulgated its rule of removing lead from gasoline, whereas HUD has had little success in removing leaded paint from housing. One reason that the EPA was successful in implementing such an expensive regulation was that it provided detailed estimates of the health and welfare benefits that would accrue and the monetary value of some of the benefits. The EPA cost-benefit analysis demonstrated that the monetary benefits of its regulation far exceeded the costs. That neutralized the cost issue and focused the debate over the regulation on questions of timing. A detailed benefit analysis of reducing lead in drinking water has caused the EPA to consider tighter water lead standards than initially envisioned. Despite years of concern about the consequences of leaded paint poisoning, children continue to be poisoned by leaded paint because it will cost billions of dollars to abate the hazard, and demand for these dollars has lost out to competing needs. As long as attention focuses on the costs of lead-paint abatement and ignores the costs of not abating and as long as people add up the costs of removing paint but not the costs of medical care, compensatory education, and school dropouts, substantial action is unlikely. It is possible that a detailed benefit analysis of lead-paint removal will not show that benefits exceed the costs, but we think it unlikely, given the large benefits estimated for other programs that reduce lead exposure, that a cost-beneficial removal strategy cannot be found. If no attempt is made to estimate the benefits, this strategy is less likely to be adopted. This paper cannot reasonably estimate the costs and benefits of the many measures that are available to reduce lead exposure of critical populations. It can, however, describe the methods that have been used and present a prototypical analysis that can readily be adapted to develop analyses specific to individual actions.

  • 1994-sternberg-encyclopediahumanintelligencevol1.pdf

  • 1994-sternberg-encyclopediahumanintelligencevol2.pdf

  • 1995-bouchard.pdf: ⁠, Thomas J. Bouchard (1995):

    The reviewer notes that this book (see record 1994-98748-000) has a simple but powerful thesis: There are substantial individual and group differences in intelligence; these differences profoundly influence the social structure and organization of work in modern industrial societies, and they defy easy remediation. In the current political milieu this book’s message is not merely controversial, it is incendiary. Commentators from across the political spectrum have documented the profound social changes that all industrialized societies are undergoing at the end of the 20th century—erosion of the middle class, loss of well-paying manufacturing jobs, and an emerging information age in which individual success will depend on brains not brawn. This book differs from other works by focusing on intelligence, rather than education or social class, as a causal variable. The authors argue that general cognitive ability is a major determiner of social status and that variance in general mental ability is largely attributable to genetic factors—propositions that are certainly endorsed by many experts in the field. The book explicitly disclaims, however, that general mental ability is the only determinant of social status.

  • 1995-cochrane-biologicallimitstoinformationprocessinginthebrain.html: ⁠, Peter Cochrane, C. S. Winter, A. Hardwick (1995; backlinks):

    The human brain is a product of Darwinian evolution and as such it has evolved from a set of underlying structures that constrain its ultimate potential. A combination of the physical size of the dendrites, axons and the associated blood vessels, and therefore their related signal space, limit the amount of information the brain can effectively store and process. By analysing the inter-relationship of the key constraints we have shown that:

    • The maximum effective diameter of the human brain is around 10–20cm.
    • The interconnectivity of neurons is dictated by thermal, volumetric, signal processing and transmission constraints, and is not, a priori, a key system parameter for intelligence.
    • Intelligent signal processing inflicts an order of magnitude time constraint on an optimised structure.

    Thus we contend that the human brain is at, or near, the capability limits that a neuron-based system allows. This implies that our future evolutionary potential is limited and that, as a species, Homo Sapiens may be near the pinnacle of achievable intelligence using current cellular carbon technology.

  • 1995-gal.pdf: “Personality and Intelligence in the Military: The Case of War Heroes”⁠, Reuven Gal

  • 1995-holahan-thegiftedgroupinlatermaturity.pdf: “The Gifted Group in Later Maturity [Genetic Studies of Genius #6]”⁠, Carole K. Holahan, Robert R. Sears, Lee J. Cronbach

  • 1995-jacoby-thebellcurvedebate.pdf

  • 1995-rowe.pdf: ⁠, David C. Rowe, Alexander T. Vazsonyi, Daniel J. Flannery (1995-01-01):

    Correlation matrices were computed on academic achievement and family environment measures using longitudinal data on siblings. The 8 × 8 correlation matrices were computed on Hispanics, blacks, and whites separately. When compared employing a LISREL method, the matrices were equal across these ethnic-racial groups. Hence, developmental processes influencing academic achievement may be similar in Hispanics, blacks, and whites. A structural equation model with 4 free parameters was fitted successfully to a correlation matrix pooled across groups. As a single structural equation model fitted all groups, the existence of minority-specific developmental processes was not supported.

  • 1995-snow.pdf (backlinks)

  • 1995-wilkinson.pdf: “For Whom The Bell Curve Tolls: A look at the controversy”⁠, Will Wilkinson

  • 1996-bouchard-2.pdf: “IQ similarity in twins reared apart: Findings and responses to critics”⁠, Thomas J. Bouchard, Jr.

  • 1996-bouchard.pdf: ⁠, Thomas J. Bouchard (1996-01-01):

    When asked whether he would discuss man in the Origins of the Species, Darwin replied, ‘I think I shall avoid the subject, as so surrounded with prejudices, though I fully admit it is the highest and most interesting problem for the naturalist’. Galton on the other hand replied to the same question, ‘I shall treat man and see what the theory of heredity of variations and the principles of natural selection mean when applied to man’ (Pearson, 1914–30, Vol. II, p. 86).

  • 1996-detterman-currenttopicshumanintelligence5environment.pdf

  • 1996-gendreau.pdf (backlinks)

  • 1996-jensen.pdf (backlinks)

  • 1996-schaie-intellectualdevelopmentinadulthood.pdf: “Intellectual development in adulthood: The Seattle Longitudinal Study”⁠, Schaie, K. Warner (Klaus Warner), 1928

  • 1997-cawley.pdf (backlinks)

  • 1997-cooper-processesindividualdifferences.pdf

  • 1997-gordon.pdf: ⁠, Robert A. Gordon (1997-01-01; backlinks):

    To show why the importance of intelligence is often misperceived, an analogy between single test items and single nontest actions in everyday life is drawn. 3 requirements of good test items are restated, and the analogy is employed to account for underrecognition of the importance of general intelligence in everyday actions, which often fail to meet the requirements and thus fail as intelligence measures for reasons that have little to do with their dependence on intelligence. A new perspective on the role of intelligence in nontest actions is introduced by considering its operation at 3 levels: that of the individual, that of the near context of the individual, and that of entire populations. Social scientists have misunderstood the operation and impact of IQ in populations by confining attention to the individual level. A population-IQ-outcome model is explained that tests for the pooled effects of intelligence at all 3 levels on differences between 2 populations in prevalences of certain outcomes. When the model fits, the difference between 2 populations in the outcome measured is found commensurate with the difference in their IQ or general intelligence distributions. The model is tested on and found to fit prevalences of juvenile delinquency, adult crime, single parenthood, HIV infection, poverty, belief in conspiracy rumors, and key opinions from polls about the O. J. Simpson trial and the earlier Tawana Brawley case. A deviance principle is extracted from empirical findings to indicate kinds of outcome the model will not fit. Implications for theories of practical and multiple intelligences are discussed. To understand the full policy implications of intelligence, such a fundamentally new perspective as that presented here will be needed.

  • 1997-gottfredson.pdf (backlinks)

  • 1997-horn.pdf: “On the mathematical relationship between factor or component coefficients and differences between means”⁠, John Horn

  • 1997-kingma-advances4-reflectionsconceptintelligence.pdf

  • 1997-lynn.pdf: “Direct Evidence for a Genetic Basis for Black-White Differences in IQ”⁠, Richard Lynn

  • 1997-mcclearn.pdf

  • 1997-neisser.pdf: “Never a Dull Moment”⁠, Ulric Neisser

  • 1997-pandolfi.pdf: “Assessment Of Factor Models Underlying The WISC-III In White, Black, And Hispanic Subgroups Of The Standardization Sample”⁠, Vincent Pandolfi

  • 1997-turkheimer.pdf: “The Search for a Psychometric Left”⁠, Eric Turkheimer

  • 1998-deneve.pdf (backlinks)

  • 1998-tempest.pdf: “Local Navajo Norms For The Wechsler Intelligence Scale For Children—Third Edition”⁠, Phyllis Tempest

  • 1999-flynn.pdf: “Evidence against Rushton: The genetic loading of WISC-R subtests and the causes of between-group IQ differences”⁠, James R. Flynn

  • 1999-rogers.pdf: ⁠, Karen B. Rogers (1999-07-01):

    An analysis of information collected from historical archives reveals a wealth of data on 30 female researchers who worked in various capacities with Dr. Lewis Terman in conducting his classic longitudinal study, Genetic Studies of Genius (1925), on 1,528 gifted children in California. The published and unpublished papers, memoranda, and research field notes of these researchers, their respective correspondence With Terman and each other, and some contacts with a living member of the research team and family members were used for this analysis. Although the information is incomplete on some of the women, most of them appeared to have had satisfying personal lives in addition to productive professional careers. Not only did they each contribute greatly to the actual work of carrying out Terman’s research conception, they also represent a continuum of life-long productivity. Personal responsibilities nay have had more to do with their subsequent levels of productivity than societal expectations or conventions.

  • 1999-rushton.pdf: “Secular gains in IQ not related to the _g_ factor and inbreeding depression - unlike Black-White differences: A reply to Flynn”⁠, J. Philippe Rushton

  • 1999-spitz.pdf: ⁠, Herman H. Spitz (1999-09; backlinks):

    The 1968 publication of the Rosenthal and Jacobson’s Pygmalion in the Classroom offered the optimistic message that raising teachers’ expectations of their pupils’ potentials would raise their pupils’ intelligence. This claim was, and still is, endorsed by many psychologists and educators. The original study, along with the scores of attempted replications and the acrimonious controversy that followed it, is reviewed, and its consequences discussed.

  • 1999-tonkin.pdf: “The comparative effects of education and the complexity of work on adult intellectual ability”⁠, Margaret (Peggy) Carol Tonkin

  • 2000-colquitt.pdf: ⁠, Jason A. Colquitt, Jeffrey A. LePine, Raymond A. Noe (2000-01-01; backlinks):

    This article meta-analytically summarizes the literature on training motivation, its antecedents, and its relationships with training outcomes such as declarative knowledge, skill acquisition, and transfer. statistically-significant predictors of training motivation and outcomes included individual characteristics (e.g., locus of control, conscientiousness, anxiety, age, cognitive ability, self-efficacy, valence, job involvement) and situational characteristics (e.g., climate). Moreover, training motivation explained incremental variance in training outcomes beyond the effects of cognitive ability. Meta-analytic path analyses further showed that the effects of personality, climate, and age on training outcomes were only partially mediated by self-efficacy, valence, and job involvement. These findings are discussed in terms of their practical importance and their implications for an integrative theory of training motivation.

  • 2000-lutter.pdf: “Valuing Children's Health: A Reassessment of the Benefits of Lower Lead Levels”⁠, Randall Lutter (backlinks)

  • 2000-reed.pdf: “An investigation of measurement invariance in the WISC III: Examining a sample of referred African American and Caucasian students”⁠, Cametra Latecia Reed

  • 2000-shindelman.pdf: “Generalizability of the Factor Structure of the Wisc-III From Standardization Samples to African American Students With Learning Disabilities”⁠, Sharon Anne Shindelman

  • 2000-swiatek.pdf

  • 2001-collis-intelligenceandpersonality.pdf: “Intelligence and Personality: Bridging the Gap in Theory and Measurement”⁠, Janet M. Collis, Samuel Messick (edt)

  • 2001-kaplan.pdf

  • 2001-nyborg.pdf: “PII: S0160-2896(00)00042-8” (backlinks)

  • 2001-sternberg.pdf (backlinks)

  • 2002-firkowska-mankiewicz.pdf (backlinks)

  • 2002-hauser.pdf: “Meritocracy, Cognitive Ability, and the Sources of Occupational Success”⁠, Robert M. Hauser (backlinks)

  • 2002-murray.pdf (backlinks)

  • 2002-templer.pdf: “Mean Graduate Record Examination (GRE) score and gender distribution as function of academic discipline”⁠, Donald I. Templer, Marie E. Tomeo

  • 2003-barrett.pdf: ⁠, Gerald V. Barrett, Alissa J. Kramen, Sarah B. Lueke (2003; backlinks):

    In the 1920s and 1930s basic theories of intellectual ability were developed along with operational tests which proved effective in predicting job performance (Spearman 1927; Thorndike 1936). In a series of studies and meta-analyses throughout the 1970s and 1980s, Schmidt and Hunter showed that cognitive ability was the best overall predictor of job performance (Hunter & Hunter 1984; Hunter 1986; Schmidt & Hunter 1981). Partially in reaction to the meta-analytic findings, research to expand on the definitions of competencies continued. The development of competencies by McClelland (1973) was followed by a discussion of tacit knowledge (Wagner & Sternberg 1985), practical intelligence (Sternberg & Wagner 1986), and multiple intelligence (Gardner 1999). In the 1990s, emotional intelligence became the intelligence of interest (Feist & Barron 1996; Goleman 1995, 1998a, 1998b; Graves 1999; Mayer et al 1990).

    All these new theories and proposed measurement instruments pose a challenge to traditional cognitive ability tests since it is claimed that these tests are more valid and have lower adverse impact. It is our contention that many of these tests are nothing more than pop psychology. It is distressing to see such books (i.e. Goleman 1998b) quoted as if they had some merit. We will review the themes present throughout all of these “creative” concepts and examine whether they have practical implications and can withhold legal scrutiny in the public and private sector.

  • 2003-brody.pdf: “What Sternberg should have concluded”⁠, Elsevier Science

  • 2003-der.pdf: ⁠, Geoff Der, Ian J. Deary (2003-09-01):

    Associations between reaction times and mental ability test scores have been widely reported in the literature on the information processing theories of psychometric intelligence. There have been varying estimates of the strength of these associations, which are typically reported in terms of correlation coefficients.

    In a previous article, we reported correlations between scores on Part 1 of the Alice Heim 4 and simple and 4-choice reaction time of −0.31 and −0.49, respectively, derived from a population based sample of 900 residents of the West of Scotland aged 56. The use of the Pearson, or product moment, correlation coefficient to summarise the association between reaction time and mental test ability assumes that they jointly have a bivariate normal distribution and that the relationship between them is linear. The differentiation hypothesis can be construed as implying that the relationship should be nonlinear with a stronger relationship at lower levels of mental ability.

    We examined in detail the relationships underlying these correlations to assess whether they adequately represented the strength of the association and to test for any departure from linearity. For 4-choice reaction time, the correlation is a good summary of the relation to AH4 score. However, the relation of AH4 and simple reaction time is more complex and nonlinear

  • 2003-gottfredson.pdf (backlinks)

  • 2003-nelson.pdf: “Learner Characteristics that Influence the Treatment Effectiveness of Early Literacy Interventions: A Meta-Analytic Review” (backlinks)

  • 2003-owen.pdf: “The wealth of nations is mapped by their IQ”⁠, Aspose Ltd.

  • 2004-deary.pdf (backlinks)

  • 2004-frey.pdf: “Scholastic Assessment or g? The Relationship Between the Scholastic Assessment Test (SAT) and General Cognitive Ability”⁠, Meredith C. Frey, Douglas K. Detterman (backlinks)

  • 2004-gottfredson.pdf: “2004fundamentalcause.pdf”⁠, gottfredson (backlinks)

  • 2004-van-hiel.pdf (backlinks)

  • 2004-wicherts.pdf (backlinks)

  • 2005-escorial.pdf

  • 2005-johnson-2.pdf: ⁠, Wendy Johnson, Thomas J. Bouchard Jr. (2005-07-01; backlinks):

    In a heterogeneous sample of 436 adult individuals who completed 42 mental ability tests, we evaluated the relative statistical performance of 3 major psychometric models of human intelligence—the Cattell-Horn fluid-crystallized model, Vernon’s verbal-perceptual model, and Carroll’s 3-strata model.

    The verbal-perceptual model fit statistically-significantly better than the other 2. We improved it by adding memory and higher-order image rotation factors. The results provide evidence for a 4-stratum model with a g factor and 3 third-stratum factors.

    The model is consistent with the idea of coordination of function across brain regions and with the known importance of brain laterality in intellectual performance. We argue that this model is theoretically superior to the fluid-crystallized model and highlight the importance of image rotation in human intellectual function. [Keywords: g factor, fluid and crystallized intelligence, verbal and perceptual abilities, mental rotation, spatial visualization, VPR theory]

  • 2005-johnson.pdf: ⁠, Wendy Johnson, Thomas J. Bouchard Jr. (2005-07-01; backlinks):

    We recently evaluated the relative statistical performance of the Cattell-Horn fluid-crystallized model and the Vernon verbal-perceptual model of the structure of human intelligence in a sample of 436 adults heterogeneous for age, place of origin, and educational background who completed 42 separate tests of mental ability from 3 test batteries.

    We concluded that the Vernon model’s performance was substantively superior but could be substantially improved. In so doing, we proposed a 4-stratum model with a g factor at the top of the hierarchy and 3 factors at the third stratum. We termed this the Verbal-Perceptual-Image Rotation (VPR) model.

    In this study, we constructively replicated the model comparisons and development of the VPR model using the data matrix published by Thurstone and Thurstone (1941) [Thurstone & Thurstone 1941, Factorial studies of intelligence]. The data matrix was generated by scores of 710 Chicago 8th graders on 60 tests of mental ability. [Keywords: g factor, fluid and crystallized intelligence, verbal and perceptual abilities, mental rotation, spatial visualization, VPR theory]

  • 2005-viswesvaran.pdf: ⁠, Chockalingam Viswesvaran, Deniz S. Ones (2005-01-01):

    An important construct in Industrial, Work and Organizational (IWO) psychology, organizational behavior, and human resources management (personnel selection, training, and performance evaluation) in general, and personnel selection in particular, is the construct of job performance. Job performance is the most important dependent variable in IWO psychology. A general definition of the construct of job performance reflects behaviors (both visually observable and non-observable) that can be evaluated. In other words, job performance refers to scalable actions, behaviors, and outcomes that employees engage in or bring about that are linked with and contribute to organizational goals. To date, most researchers focusing on the construct of job performance have confined themselves to particular situations and settings with no attempt to generalize their findings. Also, there has been an emphasis on prediction and practical application rather than explanation and theory building. The consequence of these two trends has been a proliferation of the various measures of job performance in the extant literature. Virtually every measurable individual differences dimension thought to be relevant to the productivity, efficiency, or profitability of the unit or organization has been used as a measure of job performance. Absenteeism, productivity ratings, violence on the job, and teamwork ratings are some examples of the variety of measures used to measure job performance.

  • 2006-dickerson.pdf (backlinks)

  • 2006-jones.pdf: ⁠, Garett Jones, William Joel Schneider (2006; backlinks):

    Human capital plays an important role in the theory of economic growth, but it has been difficult to measure this abstract concept. We survey the psychological literature on cross-cultural IQ tests and conclude that intelligence tests provide one useful measure of human capital. Using a new database of national average IQ, we show that in growth regressions that include only robust control variables, IQ is statistically-significant in 99.8% of these 1330 regressions, easily passing a Bayesian model-averaging robustness test. A 1 point increase in a nation’s average IQ is associated with a persistent 0.11% annual increase in GDP per capita.

  • 2006-mcdaniel.pdf (backlinks)

  • 2007-berry.pdf: ⁠, Christopher M. Berry, Paul R. Sackett, Richard N. Landers (2007-11-13; backlinks):

    This study revisits the relationship between interviews and cognitive ability tests, finding lower magnitudes of correlation than have previous meta-analyses; a finding that has implications for both the construct and incremental validity of the interview. Our lower estimates of this relationship than previous meta-analyses were mainly due to (a) an updated set of studies, (b) exclusion of samples in which interviewers potentially had access to applicants’ cognitive test scores, and (c) attention to specific range restriction mechanisms that allowed us to identify a sizable subset of studies for which range restriction could be accurately accounted. Moderator analysis results were similar to previous meta-analyses, but magnitudes of correlation were generally lower than in previous meta-analyses. Findings have implications for the construct and incremental validity of interviews, and meta-analytic methodology in general.

  • 2007-feuillet.pdf: ⁠, Lionel Feuillet, Henry Dufour, Jean Pelletier (2007-07-21; backlinks):

    [Very brief case study.] On neuropsychological testing, he proved to have an intelligence quotient (IQ) of 75: his verbal IQ was 84, and his performance IQ 70. CT showed severe dilatation of the lateral ventricles (figure); MRI revealed massive enlargement of the lateral, third, and fourth ventricles, a very thin cortical mantle and a posterior fossa cyst. We diagnosed a non-communicating hydrocephalus…after a ventriculoperitoneal shunt was inserted, the findings on neurological examination became normal within a few weeks. The findings on neuropsychological testing and CT did not change.

  • 2007-johnson-2.pdf: ⁠, Wendy Johnson, Thomas J. Bouchard Jr., Matt McGue, Nancy L. Segal, Auke Tellegen, Margaret Keyes, Irving I. Gottesman (2007-11-01):

    In previous papers [] [] we have proposed the Verbal, perceptual, and image rotation (VPR) model of the structure of mental abilities. The VPR model is hierarchical, with a g factor that contributes strongly to broad verbal, perceptual, and image rotation abilities, which in turn contribute to 8 more specialized abilities. The verbal and perceptual abilities, though separable, are highly correlated, as are the perceptual and mental rotation abilities. The verbal and mental rotation abilities are much less correlated.

    In this study we used the twin sample in the Minnesota Study of Twins Reared Apart to estimate the genetic and environmental influences and the correlations among them at each order of the VPR model. Genetic influences accounted for 67–79% of the variance throughout the model, with the exception of the second-stratum Content Memory factor, which showed 33% genetic influence. These influences could not be attributed to assessed similarity of rearing environment. Genetic correlations closely mirrored the phenotypic correlations.

    Together, these findings substantiate the theory that the entire structure of mental abilities is strongly influenced by genes. [Keywords: genetic and environmental influences, genetic and environmental correlations, verbal and image rotation abilities, intelligence, VPR model, g factor, twin study]

  • 2007-johnson.pdf: ⁠, Wendy Johnson, Thomas J. Bouchard Jr. (2007-01-01):

    Empirical data suggest that there is at most a very small sex difference in general mental ability, but men clearly perform better on visuospatial tasks while women clearly perform better on tests of verbal usage and perceptual speed. In this study, we integrated these overall findings with predictions based on the Verbal-Perceptual-Rotation (VPR) model ([Johnson, W., and Bouchard, T. J. (2005a). “Constructive replication of the visual-perceptual-image rotation (VPR) model in Thurstone’s (1941) battery of 60 tests of mental ability”. Intelligence, 33, 417–430.; Johnson, W., and Bouchard, T. J. (2005b). “The structure of human intelligence: It’s verbal, perceptual, and image rotation (VPR), not fluid and crystallized”. Intelligence, 33. 393–416.]) of the structure of mental abilities. We examined the structure of abilities after removing the effects of general intelligence, identifying three underlying dimensions termed rotation-verbal, focus-diffusion, and memory. Substantial sex differences appeared to lie along all three dimensions, with men more likely to be positioned towards the rotation and focus poles of those dimensions, and women displaying generally greater memory. At the level of specific ability tests, there were greater sex differences in residual than full test scores, providing evidence that general intelligence serves as an all-purpose problem solving ability that masks sex differences in more specialized abilities. The residual ability factors we identified showed strong genetic influences comparable to those for full abilities, indicating that the residual abilities have some basis in brain structure and function. [Keywords:, Sex differences, Residual mental abilities, Verbal and spatial abilities, General intelligence, VPR theory, Genetic and environmental influences]

  • 2007-jung.pdf: ⁠, Andreas Demetriou, Antigoni Mouyi (2007-01-01; backlinks):

    “Is there a biology of intelligence which is characteristic of the normal human nervous system?” Here we review 37 modern neuroimaging studies in an attempt to address this question posed by Halstead (1947) as he and other icons of the last century endeavored to understand how brain and behavior are linked through the expression of intelligence and reason. Reviewing studies from functional (i.e., functional magnetic resonance imaging, positron emission tomography) and structural (i.e., magnetic resonance spectroscopy, diffusion tensor imaging, voxel-based morphometry) neuroimaging paradigms, we report a striking consensus suggesting that variations in a distributed network predict individual differences found on intelligence and reasoning tasks. We describe this network as theParieto-Frontal Integration Theory(P-FIT). The P-FIT model includes, by Brodmann areas (BAs): the dorsolateral prefrontal cortex (BAs 6, 9, 10, 45, 46, 47), the inferior (BAs 39, 40) and superior (BA 7) parietal lobule, the anterior cingulate (BA 32), and regions within the temporal (BAs 21, 37) and occipital (BAs 18, 19) lobes. White matter regions (i.e., arcuate fasciculus) are also implicated. The P-FIT is examined in light of findings from human lesion studies, including missile wounds, frontal lobotomy/leukotomy, temporal lobectomy, and lesions resulting in damage to the language network (e.g., aphasia), as well as findings from imaging research identifying brain regions under significant genetic control. Overall, we conclude that modern neuroimaging techniques are beginning to articulate a biology of intelligence. We propose that the P-FIT provides a parsimonious account for many of the empirical observations, to date, which relate individual differences in intelligence test scores to variations in brain structure and function. Moreover, the model provides a framework for testing new hypotheses in future experimental designs.

  • 2007-kuncel.pdf: “Standardized Tests Predict Graduate Students' Success”⁠, Nathan R. Kuncel, Sarah A. Hezlett (backlinks)

  • 2007-strenze.pdf (backlinks)

  • 2007-tenijenhuis.pdf (backlinks)

  • 2007-zagorsky.pdf (backlinks)

  • 2008-hanushek.pdf: ⁠, Eric A. Hanushek, Ludger Woessmann (2008-09-01):

    The role of improved schooling, a central part of most development strategies, has become controversial because expansion of school attainment has not guaranteed improved economic conditions. This paper reviews the role of cognitive skills in promoting economic well-being, with a particular focus on the role of school quality and quantity. It concludes that there is strong evidence that the cognitive skills of the population—rather than mere school attainment—are powerfully related to individual earnings, to the distribution of income, and to economic growth. New empirical results show the importance of both minimal and high level skills, the complementarity of skills and the quality of economic institutions, and the robustness of the relationship between skills and growth. International comparisons incorporating expanded data on cognitive skills reveal much larger skill deficits in developing countries than generally derived from just school enrollment and attainment. The magnitude of change needed makes clear that closing the economic gap with developed countries will require major structural changes in schooling institutions.

  • 2008-kemmelmeier.pdf (backlinks)

  • 2008-machin.pdf: “Science Magazine”

  • 2008-reeve.pdf: “Survey of opinions on the primacy of g and social consequences of ability testing: A comparison of expert and non-expert views”⁠, Charlie L. Reeve, Jennifer E. Charles

  • 2009-richwine.pdf: “IQ and Immigration Policy”⁠, jason.richwine (backlinks)

  • 2009-shikishima.pdf: ⁠, Chizuru Shikishima, Kai Hiraishi, Shinji Yamagata, Yutaro Sugimoto, Ryo Takemura, Koken Ozaki, Mitsuhiro Okada, Tatsushi Toda, Juko Ando (2009-05-01):

    Using a behavioral genetic approach, we examined the validity of the hypothesis concerning the singularity of human general intelligence, the g theory, by analyzing data from 2 tests: the first consisted of 100 syllogism problems and the second a full-scale intelligence test.

    The participants were 448 Japanese young adult twins (167 pairs of identical and 53 pairs of fraternal twins). Data were analyzed for their fit to 2 kinds of multivariate genetic models: a common pathway model, in which a higher-order latent variable, g, was postulated as an entity; and an independent pathway model, in which the higher-order latent variable was not posited. These analyses revealed that the common pathway model which included additive genetic and nonshared environmental factors best accounted for the 3 distinct mental abilities: syllogistic logical deductive reasoning, verbal, and spatial.

    Both the substantial g-loading for syllogism-solving, historically recognized as the symbol of human intelligence, and the emergence of g as an entity at an etiological level, that is, at the genetic and environmental factor level, provide further support for the g theory. [Keywords: g factor, syllogism, twin study, multivariate genetic analysis, common pathway model, independent pathway model]

  • 2010-beraldo.pdf: “Do differences in IQ predict Italian north–south differences in income? A methodological critique to Lynn”⁠, Sergio Beraldo (backlinks)

  • 2010-calvin.pdf: ⁠, Catherine M. Calvin, Cres Fernandes, Pauline Smith, Peter M. Visscher, Ian J. Deary (2020-07-01):

    General cognitive ability (g) does not explain sex differences in academic test performance by the end of compulsory education. Instead, individual differences in specific reasoning abilities, after removing the effects of g, may contribute to the observed gender gaps. Associations between general or specific cognitive abilities, sex, and educational attainments were analysed in a cross-sectional study of 11-year-olds (M = 133.5 months, SD = 3.5), at an age before substantive gender-related selection-bias occurred. The 178,599 pupils (89,545 girls and 89,054 boys) attending English state schools represented 93% of the UK’s local education authorities. In 2004 each student completed the Cognitive Abilities Test—Third Edition (CAT3), assessing verbal, quantitative, and nonverbal reasoning abilities. These data were linked to each child’s attainment scores on national Key Stage 2 tests in English, mathematics and science. A sex difference in g, favoring girls, was statistically-significant but of negligible effect size (Cohen’s d = 0.01). Girls scored 26% of a SD higher than boys on a verbal residual factor, and boys scored 28% of a SD higher than girls on a quantitative residual factor, with negligible sex differences on a nonverbal residual factor (1% of a SD). In education, 10% more girls than boys achieved UK government targets in English. In mathematics and science, sex differences were less apparent at the government target grade (Level 4), although a 5% greater proportion of boys than girls performed at the highest level in mathematics (Level 5). General cognitive ability (g) was strongly related to an educational factor score (r = 0.83) as expected, and did not explain sex differences in academic performance. In general linear models, a verbal residual factor explained up to 29% of girls’ higher English attainment, and better quantitative skills among boys explained 50% of their higher attainment in mathematics. Besides the substantial contributions of specific cognitive abilities to gender differences in English and mathematics, there remains substantive variance of the educational gender gap left to explain. [Keywords: Sex, Intelligence, Education, Cognitive Abilities Test, Key Stage 2]

  • 2010-campbell.pdf: ⁠, John P. Campbell, Deirdre J. Knapp (2010-01-01):

    Origins of Project A · Enabling of Project A · Specific Research Objectives · Overall Research Design · Research Instrument Development: Predictors · Job Analyses and Criterion Development · Modeling the Latent Structure of Performance · Correlations of Past Performance With Future Performance · Criterion-Related Validation · Some Broader Implications · Conclusions · References

    This chapter 1 is about personnel selection and classification research on a scale never before attempted in terms of (a) the types and variety of information collected, (b) the number of jobs that were considered simultaneously, (c) the size of the samples, and (d) the length of time that individuals were followed as they progressed through the organization.

    The effort, commonly known as Project A, was sponsored by the U.S. Army Research Institute for the Behavioral and Social Sciences (ARI). For contract management reasons the research program was conducted as two sequential projects: Project A (1982–1989) and Career Force (1990–1994), which worked from a single overall design (described subsequently).

    Collectively, these projects attempted to evaluate the selection validity and classification efficiency of systematically sampled domains of prediction information for different selection and classification goals for the entire enlisted personnel system of the U.S. Army, using various alternative decision rules (i.e., “models”). Pursuing such ambitious objectives required the development of a comprehensive battery of new tests and inventories, the development of a wide variety of training and job performance measures for each job in the sample, four major worldwide data collections involving thousands of Army enlisted job incumbents for one to two days each, and the design and maintenance of the resulting database.

    The truly difficult part was the never-ending need to develop a consensus among all of the project participants regarding literally hundreds of choices among measurement procedures, analysis methods, and data collection design strategies. Although many such decisions were made in the original design stage, many more occurred continuously as the projects moved forward, driven by the target dates for the major data collections, which absolutely could not be missed. The fact that all major parts of the projects were completed within the prescribed time frames and according to the specified research design was a source of wonder for all who participated.

  • 2010-cornoldi.pdf: “The mean Southern Italian children IQ is not particularly low: A reply to R. Lynn (2010)”⁠, Cesare Cornoldi, Carmen Belacchi, David Giofrè, Angela Martini, Patrizio Tressoldi (backlinks)

  • 2010-drasgow.pdf: “Factor Structure of the Air Force Officer Qualifying Test Form S: Analysis and Comparison with Previous Forms”⁠, Fritz Drasgow, Christopher D. Nye, Thomas R. Carretta, Malcolm James Ree

  • 2010-kuncel.pdf: ⁠, Nathan R. Kuncel, Sarah A. Hezlett (2010-12-14):

    Standardized measures of intelligence, ability, or achievement are all measures of acquired knowledge and skill and have consistent relationships with multiple facets of success in life, including academic and job performance.

    Five persistent beliefs about ability tests have developed, including:

    1. that there is no relationship with important outcomes like creativity or leadership,
    2. that there is predictive bias,
    3. that there is a lack of predictive independence from socioeconomic status,
    4. that there are thresholds beyond which scores cease to matter, and
    5. that other characteristics, like personality, matter as well.

    We present the evidence and conclude that of these 5 beliefs, only the importance of personality is a fact; the other 4 are fiction. [Keywords: standardized tests, intelligence, cognitive ability, admissions tests, test bias, job performance, academic success]

  • 2010-lopez.pdf (backlinks)

  • 2010-lynn.pdf (backlinks)

  • 2010-meyer.pdf: ⁠, Christine Sandra Meyer, Priska Hagmann-von Arx, Sakari Lemola, Alexander Grob (2010-01-13):

    For more than a century the veracity of Spearman’s postulate that there is a nearly perfect correspondence between general intelligence and general sensory discrimination has remained unresolved. Most studies have found significant albeit small correlations. However, this can be used neither to confirm nor dismiss Spearman’s postulate, a major weakness of previous research being that only single discrimination capacities were considered rather than general discrimination. The present study examines Spearman’s hypothesis with a sample of 1,330 5- to 10-year-old children, using structural equation modeling. The results support Spearman’s hypothesis with a strong correlation (r = 0.78). Results are discussed in terms of the validity of the general sensory discrimination factor. In addition, age-group-specific analyses explored the age differentiation hypothesis.

  • 2010-sabbah.pdf: “The relationships between cognitive ability and dental status in a national sample of USA adults”⁠, Wael Sabbah, Aubrey Sheiham (backlinks)

  • 2010-sellman.pdf: ⁠, Wayne S. Sellman, Dana H. Born, William J. Strickland, Jason J. Ross (2010-01-01):

    Military Personnel System · Indicators of Recruit Quality · Need for Military Selection · Short History of Military Personnel Testing (Pre-All Volunteer Force) · Moving to an All-Volunteer Force · ASVAB Misnorming and Job Performance Measurement Project · Enlisted Selection and Classification in Today’s Military · Enlistment Process · Recruit Quality Benchmarks and Enlistment Standards · Selection for Officer Commissioning Programs · Officer Retention and Attrition · Officer Executive Development · Command Selection and Career Broadening Experiences · Defense Transformation in Military Selection · Conclusions · References

  • 2010-sturgis.pdf: “Does intelligence foster generalized trust? An empirical test using the UK birth cohort studies”⁠, Patrick Sturgis, Sanna Read, Nick Allum (backlinks)

  • 2010-subotnik.pdf: “Should eminence based on outstanding innovation be the goal of gifted education and talent development? Implications for policy and research”⁠, Rena F. Subotnik, Rochelle Rickoff (backlinks)

  • 2010-wennerstad.pdf: “Associations between IQ and cigarette smoking among Swedish male twins”⁠, Karin Modig Wennerstad, Karri Silventoinen, Per Tynelius, Lars Bergman, Jaakko Kaprio, Finn Rasmussen (backlinks)

  • 2010-wicherts.pdf: “Why national IQs do not support evolutionary theories of intelligence”⁠, Jelte M. Wicherts, Denny Borsboom, Conor V. Dolan (backlinks)

  • 2011-almeida.pdf (backlinks)

  • 2011-barnett.pdf

  • 2011-beaver.pdf: “The association between county-level IQ and county-level crime rates”⁠, Kevin M. Beaver, John Paul Wright (backlinks)

  • 2011-daniele.pdf (backlinks)

  • 2011-felice.pdf: “Myth and reality: A response to Lynn on the determinants of Italy's North–South imbalances”⁠, Emanuele Felice, Ferdinando Giugliano (backlinks)

  • 2011-gensowski.pdf: ⁠, Miriam Gensowski, James Heckman, Peter Savelyev (2011-01-24; backlinks):

    [Preprint version of ]

    This paper estimates the internal rate of return (IRR) to education for men and women of the Terman sample, a 70-year long prospective cohort study of high-ability individuals. The Terman data is unique in that it not only provides full working-life earnings histories of the participants, but it also includes detailed profiles of each subject, including IQ and measures of latent personality traits. Having information on latent personality traits is important as it allows us to measure the importance of personality on educational attainment and lifetime earnings.

    Our analysis addresses two problems of the literature on returns to education: First, we establish causality of the treatment effect of education on earnings by implementing generalized matching on a full set of observable individual characteristics and unobserved personality traits. Second, since we observe lifetime earnings data, our estimates of the IRR are direct and do not depend on the assumptions that are usually made in order to justify the interpretation of regression coefficients as rates of return.

    For the males, the returns to education beyond high school are sizeable. For example, the IRR for obtaining a bachelor’s degree over a high school diploma is 11.1%, and for a doctoral degree over a bachelor’s degree it is 6.7%. These results are unique because they highlight the returns to high-ability and high-education individuals, who are not well-represented in regular data sets.

    Our results highlight the importance of personality and intelligence on our outcome variables. We find that personality traits similar to the Big Five personality traits are statistically-significant factors that help determine educational attainment and lifetime earnings. Even holding the level of education constant, measures of personality traits have statistically-significant effects on earnings. Similarly, IQ is rewarded in the labor market, independently of education. Most of the effect of personality and IQ on life-time earnings arise late in life, during the prime working years. Therefore, estimates from samples with shorter durations underestimate the treatment effects.

  • 2011-johnson-supplementarytables.txt

  • 2011-meisenberg.pdf: “JSPES 36 - 4 contents and editorial page”⁠, RupertPearson (backlinks)

  • 2011-rindermann.pdf (backlinks)

  • 2012-chang.pdf

  • 2012-damico.pdf (backlinks)

  • 2012-deary.pdf: ⁠, Ian J. Deary (2011-09-19; backlinks):

    Individual differences in human intelligence are of interest to a wide range of psychologists and to many people outside the discipline. This overview of contributions to intelligence research covers the first decade of the twenty-first century. There is a survey of some of the major books that appeared since 2000, at different levels of expertise and from different points of view.

    Contributions to the phenotype of intelligence differences are discussed, as well as some contributions to causes and consequences of intelligence differences. The major causal issues covered concern the environment and genetics, and how intelligence differences are being mapped to brain differences. The major outcomes discussed are health, education, and socioeconomic status. Aging and intelligence are discussed, as are sex differences in intelligence and whether twins and singletons differ in intelligence.

    More generally, the degree to which intelligence has become a part of broader research in neuroscience, health, and social science is discussed. [Keywords: IQ, cognitive ability, psychometrics, behavior genetics, cognitive epidemiology, twins, education, health]

  • 2012-grinblatt.pdf: ⁠, Mark Grinblatt, Matti Keloharju, Juhani T. Linnainmaa (2012-05; backlinks):

    We analyze whether IQ influences trading behavior, performance, and transaction costs. The analysis combines equity return, trade, and limit order book data with two decades of scores from an intelligence (IQ) test administered to nearly every Finnish male of draft age. Controlling for a variety of factors, we find that high-IQ investors are less subject to the disposition effect, more aggressive about tax-loss trading, and more likely to supply liquidity when stocks experience a one-month high. High-IQ investors also exhibit superior market timing, stock-picking skill, and trade execution.

    Figure 1: Cumulative distribution of the cross-section of investors’ annualized portfolio returns. This figure plots the cumulative distribution  of the cross-section of investors’ annualized returns for subgroups of investors sorted by IQ (stanines 1–4 or stanine 9). The sample excludes investors who held stocks for fewer than 252 trading days in the sample period. Returns for each investor are annualized from the average daily portfolio returns computed over days the investor held stocks. The daily portfolio return is the portfolio-weighted average of the portfolio’s daily stock returns. The latter are close-to-close returns unless a trade takes place in the stock, in which case execution prices replace closing prices in the calculation. The returns are adjusted for dividends, stock splits, and mergers. IQ data [n = 87,914] are from  to  Remaining data are from
  • 2012-hooghe.pdf: “The cognitive basis of trust”⁠, Sofie (backlinks)

  • 2012-lynn.pdf: “MQ LII 3&4 editorial page”⁠, RupertPearson (backlinks)

  • 2012-rindermann-supplement.doc (backlinks)

  • 2012-rindermann.pdf: “Intellectual classes, technological progress and economic development: The rise of cognitive capitalism”⁠, Heiner Rindermann (backlinks)

  • 2013-barnes.pdf (backlinks)

  • 2013-bouchard.pdf (backlinks)

  • 2013-boutwell.pdf (backlinks)

  • 2013-cornoldi.pdf (backlinks)

  • 2013-floyd.pdf

  • 2013-lee.pdf: ⁠, Christine S. Lee, David J. Therriault (2013-09-01):

    • The relationships among intelligence, working memory, and creative thinking
    • Testing structural equation models of cognitive abilities and creative processes
    • Associative fluency predicted both divergent thinking and convergent thinking.
    • Intelligence and working memory also predicted three distinct creative processes.
    • Results support an executive interpretation of creative thinking.

    The field of creativity has largely focused on individual differences in divergent thinking abilities. Recently, contemporary creativity researchers have shown that intelligence and executive functions play an important role in divergent thought, opening new lines of research to examine how higher-order cognitive mechanisms may uniquely contribute to creative thinking. The present study extends previous research on the intelligence and divergent thinking link by systematically examining the relationships among intelligence, working memory, and three fundamental creative processes: associative fluency, divergent thinking, and convergent thinking.

    265 participants were recruited to complete a battery of tasks that assessed a range of elementary to higher-order cognitive processes related to intelligence and creativity. Results provide evidence for an associative basis in two distinct creative processes: divergent thinking and convergent thinking. Findings also supported recent work suggesting that intelligence statistically-significantly influences creative thinking. Finally, working memory played a statistically-significant role in creative thinking processes.

    Recasting creativity as a construct consisting of distinct higher-order cognitive processes has important implications for future approaches to studying creativity within an individual differences framework.

  • 2013-lynn.pdf: “Differences in intelligence across thirty-one regions of China and their economic and demographic correlates”⁠, Richard Lynn, Helen Cheng (backlinks)

  • 2013-rietveld-supplementary-revision2.pdf (backlinks)

  • 2013-rietveld.pdf: ⁠, Cornelius A. Rietveld, Sarah E. Medland, Jaime Derringer, Jian Yang, Tõnu Esko, Nicolas W. Martin, Harm-Jan Westra, Konstantin Shakhbazov, Abdel Abdellaoui, Arpana Agrawal, Eva Albrecht, Behrooz Z. Alizadeh, Najaf Amin, John Barnard, Sebastian E. Baumeister, Kelly S. Benke, Lawrence F. Bielak, Jeffrey A. Boatman, Patricia A. Boyle, Gail Davies, Christiaan de Leeuw, Niina Eklund, Daniel S. Evans, Rudolf Ferhmann, Krista Fischer, Christian Gieger, Håkon K. Gjessing, Sara Hägg, Jennifer R. Harris, Caroline Hayward, Christina Holzapfel, Carla A. Ibrahim-Verbaas, Erik Ingelsson, Bo Jacobsson, Peter K. Joshi, Astanand Jugessur, Marika Kaakinen, Stavroula Kanoni, Juha Karjalainen, Ivana Kolcic, Kati Kristiansson, Zoltán Kutalik, Jari Lahti, Sang H. Lee, Peng Lin, Penelope A. Lind, Yongmei Liu, Kurt Lohman, Marisa Loitfelder, George McMahon, Pedro Marques Vidal, Osorio Meirelles, Lili Milani, Ronny Myhre, Marja-Liisa Nuotio, Christopher J. Oldmeadow, Katja E. Petrovic, Wouter J. Peyrot, Ozren Polašek, Lydia Quaye, Eva Reinmaa, John P. Rice, Thais S. Rizzi, Helena Schmidt, Reinhold Schmidt, Albert V. Smith, Jennifer A. Smith, Toshiko Tanaka, Antonio Terracciano, Matthijs J. H. M. van der Loos, Veronique Vitart, Henry Völzke, Jürgen Wellmann, Lei Yu, Wei Zhao, Jüri Allik, John R. Attia, Stefania Bandinelli, François Bastardot, Jonathan Beauchamp, David A. Bennett, Klaus Berger, Laura J. Bierut, Dorret I. Boomsma, Ute Bültmann, Harry Campbell, Christopher F. Chabris, Lynn Cherkas, Mina K. Chung, Francesco Cucca, Mariza de Andrade, Philip L. De Jager, Jan-Emmanuel De Neve, Ian J. Deary, George V. Dedoussis, Panos Deloukas, Maria Dimitriou, Guðný Eiríksdóttir, Martin F. Elderson, Johan G. Eriksson, David M. Evans, Jessica D. Faul, Luigi Ferrucci, Melissa E. Garcia, Henrik Grönberg, Vilmundur Guðnason, Per Hall, Juliette M. Harris, Tamara B. Harris, Nicholas D. Hastie, Andrew C. Heath, Dena G. Hernandez, Wolfgang Hoffmann, Adriaan Hofman, Rolf Holle, Elizabeth G. Holliday, Jouke-Jan Hottenga, William G. Iacono, Thomas Illig, Marjo-Riitta Järvelin, Mika Kähönen, Jaakko Kaprio, Robert M. Kirkpatrick, Matthew Kowgier, Antti Latvala, Lenore J. Launer, Debbie A. Lawlor, Terho Lehtimäki, Jingmei Li, Paul Lichtenstein, Peter Lichtner, David C. Liewald, Pamela A. Madden, Patrik K. E. Magnusson, Tomi E. Mäkinen, Marco Masala, Matt McGue, Andres Metspalu, Andreas Mielck, Michael B. Miller, Grant W. Montgomery, Sutapa Mukherjee, Dale R. Nyholt, Ben A. Oostra, Lyle J. Palmer, Aarno Palotie, Brenda W. J. H. Penninx, Markus Perola, Patricia A. Peyser, Martin Preisig, Katri Räikkönen, Olli T. Raitakari, Anu Realo, Susan M. Ring, Samuli Ripatti, Fernando Rivadeneira, Igor Rudan, Aldo Rustichini, Veikko Salomaa, Antti-Pekka Sarin, David Schlessinger, Rodney J. Scott, Harold Snieder, Beate St Pourcain, John M. Starr, Jae Hoon Sul, Ida Surakka, Rauli Svento, Alexander Teumer, The LifeLines Cohort Study, Henning Tiemeier, Frank J. A. van Rooij, David R. Van Wagoner, Erkki Vartiainen, Jorma Viikari, Peter Vollenweider, Judith M. Vonk, Gérard Waeber, David R. Weir, H.-Erich Wichmann, Elisabeth Widen, Gonneke Willemsen, James F. Wilson, Alan F. Wright, Dalton Conley, George Davey-Smith, Lude Franke, Patrick J. F. Groenen, Albert Hofman, Magnus Johannesson, Sharon L. R. Kardia, Robert F. Krueger, David Laibson, Nicholas G. Martin, Michelle N. Meyer, Danielle Posthuma, A. Roy Thurik, Nicholas J. Timpson, André G. Uitterlinden, Cornelia M. van Duijn, Peter M. Visscher, Daniel J. Benjamin, David Cesarini, Philipp D. Koellinger (2013-06-21; backlinks):

    A genome-wide association study (GWAS) of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent single-nucleotide polymorphisms (SNPs) are genome-wide statistically-significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (coefficient of determination R2 ≈ 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for ≈2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.

    [A landmark study in behavioral genetics and intelligence: the first well-powered GWAS to detect genetic variants for intelligence and education which replicate out of sample and are proven to be causal in a between-sibling study.]

  • 2013-trzaskowski.pdf (backlinks)

  • 2013-zuckerman.pdf (backlinks)

  • 2014-abdulkadiroglu.pdf: ⁠, Atila Abdulkadiroğlu, Joshua Angrist, Parag Pathak (2014-02-05; backlinks):

    Parents gauge school quality in part by the level of student achievement and a school’s racial and socioeconomic mix. The importance of school characteristics in the housing market can be seen in the jump in house prices at school district boundaries where peer characteristics change. The question of whether schools with more attractive peers are really better in a value-added sense remains open, however. This paper uses a fuzzy regression-discontinuity design to evaluate the causal effects of peer characteristics. Our design exploits admissions cutoffs at Boston and New York City’s heavily over-subscribed exam schools. Successful applicants near admissions cutoffs for the least selective of these schools move from schools with scores near the bottom of the state SAT score distribution to schools with scores near the median. Successful applicants near admissions cutoffs for the most selective of these schools move from above-average schools to schools with students whose scores fall in the extreme upper tail. Exam school students can also expect to study with fewer nonwhite classmates than unsuccessful applicants. Our estimates suggest that the marked changes in peer characteristics at exam school admissions cutoffs have little causal effect on test scores or college quality.

  • 2014-baten.pdf: “Back to the ‘Normal’ Level of Human-Capital Driven Growth”⁠, user (backlinks)

  • 2014-beaujean.pdf: ⁠, Alexander Beaujean, Yanyan Sheng (2014-01-01):

    The current study examined the Flynn Effect (i.e., the increase in IQ scores over time) across all editions of the Wechsler Adult Intelligence Scale (WAIS), Wechsler Intelligence Scale for Children (WISC), and Wechsler Preschool and Primary Scale of Intelligence (WPPSI). By reverse engineering the correlation and scale score transformations from each Wechsler edition’s technical manual, we made a mean and covariance matrix using the subtests and age groups that were in common for all editions of a given instrument. The results indicated that when aggregated, there was a FE of 0.44 IQ points/year. This Wechsler instrument used, however, moderates the FE, with the WISC showing the largest FE (0.73 IQ points/year) and the WAIS showing a smallest FE (0.30 IQ points/year). Moreover, this study found that the amount of invariant indicators across instruments and age groups varied substantially, ranging from 51.53% in the WISC for the 7-year-old group to 10.00% in the WPPSI for the 5- and 5.5-year-old age groups. Last, we discuss future direction for FE research based on these results.

  • 2014-beaver.pdf (backlinks)

  • 2014-benyamin.pdf: ⁠, B. Benyamin, B. St Pourcain, O. S. Davis, G. Davies, N. K. Hansell, M-J. A. Brion, R. M. Kirkpatrick, R.A. M. Cents, S. Franić, M. B. Miller, C.M. A. Haworth, E. Meaburn, T. S. Price, D. M. Evans, N. Timpson, J. Kemp, S. Ring, W. McArdle, S. E. Medland, J. Yang, S. E. Harris, D. C. Liewald, P. Scheet, X. Xiao, J. J. Hudziak, E.J.C. de Geus, Wellcome Trust Case Control Consortium 2 (WTCCC2), V.W. V. Jaddoe, J. M. Starr, F. C. Verhulst, C. Pennell, H. Tiemeier, W. G. Iacono, L. J. Palmer, G. W. Montgomery, N. G. Martin, D. I. Boomsma, D. Posthuma, M. McGue, M. J. Wright, G. Davey Smith, I. J. Deary, R. Plomin, P. M. Visscher (2013-01-29; backlinks):

    Intelligence in childhood, as measured by psychometric cognitive tests, is a strong predictor of many important life outcomes, including educational attainment, income, health and lifespan. Results from twin, family and adoption studies are consistent with general intelligence being highly heritable and genetically stable throughout the life course. No robustly associated genetic loci or variants for childhood intelligence have been reported. Here, we report the first genome-wide association study (GWAS) on childhood intelligence (age range 6–18 years) from 17 989 individuals in six discovery and three replication samples. Although no individual single-nucleotide polymorphisms (SNPs) were detected with genome-wide statistical-significance, we show that the aggregate effects of common SNPs explain 22–46% of phenotypic variation in childhood intelligence in the three largest cohorts (p = 3.9×10-15, 0.014 and 0.028). FNBP1L, previously reported to be the most statistically-significantly associated gene for adult intelligence, was also statistically-significantly associated with childhood intelligence (p = 0.003). Polygenic prediction analyses resulted in a statistically-significant correlation between predictor and outcome in all replication cohorts. The proportion of childhood intelligence explained by the predictor reached 1.2% (p = 6×10-5), 3.5% (p = 10-3) and 0.5% (p = 6×10-5) in three independent validation cohorts. Given the sample sizes, these genetic prediction results are consistent with expectations if the genetic architecture of childhood intelligence is like that of body mass index or height. Our study provides molecular support for the heritability and polygenic nature of childhood intelligence. Larger sample sizes will be required to detect individual variants with genome-wide statistical-significance.

  • 2014-bergman.pdf: “High IQ in Early Adolescence and Career Success in Adulthood: Findings from a Swedish Longitudinal Study”⁠, Lars R. Bergman, Jelena Corovic, Laura Ferrer-Wreder, Karin Modig

  • 2014-bouchard.pdf (backlinks)

  • 2014-carl.pdf: “Verbal intelligence is correlated with socially and economically liberal beliefs”⁠, Noah Carl (backlinks)

  • 2014-castex.pdf: ⁠, Gonzalo Castex, Evgenia Kogan Dechter (2014-10-01; backlinks):

    This study examines changes in returns to formal education and cognitive skills over the past 20 years using the 1979 and 1997 waves of the National Longitudinal Survey of Youth. We show that cognitive skills had a 30%–50% larger effect on wages in the 1980s than in the 2000s. Returns to education were higher in the 2000s. These developments are not explained by changing distributions of workers’ observable characteristics or by changing labor market structure. We show that the decline in returns to ability can be attributed to differences in the growth rate of technology between the 1980s and 2000s.

  • 2014-dobbie.pdf: ⁠, Will Dobbie, Roland G. Fryer Jr. (2014-07; backlinks):

    This paper uses data from three prominent exam high schools in New York City to estimate the impact of attending a school with high-achieving peers on college enrollment and graduation. Our identification strategy exploits sharp discontinuities in the admissions process. Applicants just eligible for an exam school have peers that score 0.17 to 0.36 standard deviations higher on eighth grade state tests and that are 6.4 to 9.5 percentage points less likely to be black or Hispanic. However, exposure to these higher-achieving and more homogeneous peers has little impact on college enrollment, college graduation, or college quality.

  • 2014-dutton.pdf: “MQ (54) LIV 3&4 contents”⁠, RupertPearson (backlinks)

  • 2014-fletcher.pdf: “Friends or family? Revisiting the effects of high school popularity on adult earnings”⁠, Jason Fletcher (backlinks)

  • 2014-haier.pdf: “A comment on”Fractionating Intelligence" and the peer review process"⁠, Richard J. Haier, Sherif Karama, Roberto Colom, Rex Jung, Wendy Johnson

  • 2014-hyde.pdf

  • 2014-johnson.pdf: ⁠, Wendy Johnson, Thomas J. Bouchard Jr. (2014; backlinks):

    [Behavioral genetics discussion of eminence/genius: intelligence, developmental processes, psychopathology, and creativity scales all contribute to accomplishment but leave much unexplained, in particular, the odd pattern of inheritance where genius runs in families but highly sporadically and not following any standard Mendelian or polygenic inheritance pattern. The authors refer to the concept of ‘emergenesis’⁠, where emergenic traits are not additive combinations of subtraits (as is strongly the case for traits like intelligence) but rather are multiplicative combinations, which are epistatic at the genetic level. Because all subtraits must be present to have a chance of producing the overall trait, emergenic traits can be highly genetically influenced yet still rare and sporadically appearing within families. (The Wiley Handbook of Genius 2014, chapter 14)]

  • 2014-shulman.pdf (backlinks)

  • 2014-tenijenhuis-supplement.doc (backlinks)

  • 2014-tenijenhuis.pdf: “Are Headstart gains on the g factor? A meta-analysis”⁠, Jan te Nijenhuis, Birthe Jongeneel-Grimen, Emil O. W. Kirkegaard (backlinks)

  • 2014-toro.pdf (backlinks)

  • 2014-valerius.pdf: ⁠, Sonja Valerius, Jörn R. Sparfeldt (2014-01-01):

    • We analyzed data of n = 562 students who took 26 ability tests from 3 batteries.
    • Higher-order factor, nested-factor & general-factor models fitted at least acceptably.
    • Test-battery-specific g-factors in nested-factor models correlated highly (r ≥ .91).
    • Verbal content & numerical content factors evidenced convergent–divergent validity.

    Concerning the correlational structure of intelligence, there is a broad consensus regarding hierarchical models with a general factor at the apex (g), and less consensus regarding the number, content, and structure of more specific ability-factors hierarchically below g. Previous studies revealed very high correlations of test-battery-specific g-factors, whereas the consistency of more specific ability-factors has been neglected.

    In order to investigate this, current data stemming from n = 562 high school students who took 26 mental ability tests from independently developed test-batteries were analyzed. Regarding the intelligence-structure, nested-factor models revealed a (relatively) better fit than higher-order models and general-factor-models. The test-battery-specific g-factors of the nested-factor models were substantially correlated (r ≥ .91); the correlations of the test-battery-specific verbal and numerical factors evidenced convergent and discriminant validity (convergent correlations: verbal—r = 0.83; numerical—r = 0.46; figural—r = 0.22).

    These results provided evidence that some group factors (besides the g-factors) of different test-batteries are largely similar. [Keywords: intelligence, g-factor, domain-specific ability, confirmatory factor analysis, nested-factor modeling]

  • 2014-warne.pdf: “Exploring the Various Interpretations of 'Test Bias'”⁠, Russell T. Warne, Myeongsun Yoon, Chris J. Price

  • 2015-carl.pdf (backlinks)

  • 2015-cofnas.pdf (backlinks)

  • 2015-daniele.pdf (backlinks)

  • 2015-hofman.pdf: ⁠, Michel A. Hofman (2015; backlinks):

    Design principles and operational modes are explored that underlie the information processing capacity of the human brain. The hypothesis is put forward that in higher organisms, especially in primates, the complexity of the neural circuitry of the cerebral cortex is the neural correlate of the brain’s coherence and predictive power, and, thus, a measure of intelligence. It will be argued that with the evolution of the human brain we have nearly reached the limits of biological intelligence. [Keywords: Biological intelligence, Cognition, Consciousness, Cerebral cortex, Primates, Information processing, Neural networks, Cortical design, Human brain evolution]

  • 2015-johnson.pdf (backlinks)

  • 2015-lynn.pdf: “Differences in cognitive ability, per capita income, infant mortality, fertility and latitude across the states of India”⁠, Richard Lynn, Prateek Yadav (backlinks)

  • 2015-mcgue.pdf (backlinks)

  • 2015-mosing.pdf (backlinks)

  • 2015-piffer.pdf: “A review of intelligence GWAS hits: Their relationship to country IQ and the issue of spatial autocorrelation”⁠, Davide Piffer (backlinks)

  • 2015-protzko.pdf: “The environment in raising early intelligence: A meta-analysis of the fadeout effect”⁠, John Protzko (backlinks)

  • 2015-roth.pdf: “Intelligence and school grades: A meta-analysis”⁠, Bettina Roth, Nicolas Becker, Sara Romeyke, Sarah Schäfer, Florian Domnick, Frank M. Spinath

  • 2015-schaefer.pdf (backlinks)

  • 2015-scheiber.pdf: “Do the Kaufman Tests of Cognitive Ability and Academic Achievement Display Ethnic Bias for Students in Grades 1 through 12?”⁠, Caroline Scheiber

  • 2015-strenze.pdf (backlinks)

  • 2015-tenijenhuis.pdf: “Are adoption gains on the g factor? A meta-analysis”⁠, Jan te Nijenhuis, Birthe Jongeneel-Grimen, Elijah L. Armstrong (backlinks)

  • 2015-tucker-drob.pdf (backlinks)

  • 2015-wai.pdf: “The path and performance of a company leader: A historical examination of the education and cognitive ability of Fortune 500 CEOs”⁠, Jonathan Wai, Heiner Rindermann (backlinks)

  • 2015-woodley.pdf: “The association between g and K in a sample of 4246 Swedish twins: A behavior genetic analysis”⁠, Michael A. Woodley of Menie, Guy Madison

  • 2015-zhu.pdf (backlinks)

  • 2016-arden.pdf: “A general intelligence factor in dogs”⁠, Rosalind Arden, Mark James Adams

  • 2016-boccio.pdf: “The influence of nonshared environmental factors on number and word recall test performance”⁠, Cashen M. Boccio, Kevin M. Beaver

  • 2016-brandt.pdf: ⁠, Mark J. Brandt, Jarret T. Crawford (2016-01-01):

    Previous research finds that lower cognitive ability predicts greater prejudice. We test two unresolved questions about this association using a heterogeneous set of target groups and data from a representative sample of the United States (n = 5,914). First, we test “who are the targets of prejudice?” We replicate prior negative associations between cognitive ability and prejudice for groups who are perceived as liberal, unconventional, and having lower levels of choice over group membership. We find the opposite (i.e., positive associations), however, for groups perceived as conservative, conventional, and having higher levels of choice over group membership. Second, we test “who shows intergroup bias?” and find that people with both relatively higher and lower levels of cognitive ability show approximately equal levels of intergroup bias but toward different sets of groups.

  • 2016-carl.pdf: “IQ and socio-economic development across local authorities of the UK”⁠, Noah Carl (backlinks)

  • 2016-christensen.pdf (backlinks)

  • 2016-dutton.pdf (backlinks)

  • 2016-grigoriev.pdf: “Regional differences in intelligence, infant mortality, stature and fertility in European Russia in the late nineteenth century”⁠, Andrei Grigoriev, Ekaterina Lapteva, Richard Lynn (backlinks)

  • 2016-hughjones.pdf (backlinks)

  • 2016-knoll.pdf: ⁠, Abby R. Knoll, Hajime Otani, Reid L. Skeel, K. Roger Van Horn (2016-09-13):

    The concept of learning style is immensely popular despite the lack of evidence showing that learning style influences performance. This study tested the hypothesis that the popularity of learning style is maintained because it is associated with subjective aspects of learning, such as judgements of learning (JOLs). Preference for verbal and visual information was assessed using the revised Verbalizer-Visualizer Questionnaire (VVQ). Then, participants studied a list of word pairs and a list of picture pairs, making JOLs (immediate, delayed, and global) while studying each list. Learning was tested by cued recall. The results showed that higher VVQ verbalizer scores were associated with higher immediate JOLs for words, and higher VVQ visualizer scores were associated with higher immediate JOLs for pictures. There was no association between VVQ scores and recall or JOL accuracy. As predicted, learning style was associated with subjective aspects of learning but not objective aspects of learning.

  • 2016-muthukrishna-1-s2.0-S1090513815000586-mmc1.docx

  • 2016-muthukrishna-mmc2-mathematica.zip

  • 2016-obydenkova.pdf: ⁠, Anastassia Obydenkova, Zafar Nazarov, Raufhon Salahodjaev (2016-07-01):

    • We documented that intelligence has negative effect on deforestation.
    • We found that intelligence moderates the effect of democracy on deforestation.
    • We documented that democracy has inverted u-shaped link with deforestation.
    • Intelligence offsets negative effect of democracy on deforestation in weak democracies.

    This article examines the interconnection between national intelligence, political institutions, and the mismanagement of public resources (deforestation). The paper examines the reasons for deforestation and investigates the factors accountable for it.

    The analysis builds on authors-compiled cross-national dataset on 185 countries over the time period of twenty years, from 1990 to 2010. We find that, first, nation’s intelligence reduces statistically-significantly the level of deforestation in a state. Moreover, the nations’ IQ seems to play an offsetting role in the natural resource conservation (forest management) in the countries with weak democratic institutions. The analysis also discovered the presence of the U-shaped relationship between democracy and deforestation. Intelligence sheds more light on this interconnection and explains the results. Our results are robust to various sample selection strategies and model specifications.

    The main implication from our study is that intelligence not only shapes formal rules and informal regulations such as social trust, norms and traditions but also it has the ability to reverse the paradoxical process known as “resource curse.” The study contributes to better understanding of reasons of deforestation and shed light on the debated impact of political regime on forest management.

  • 2016-okbay-2.pdf: ⁠, Aysu Okbay, Jonathan P. Beauchamp, Mark Alan Fontana, James J. Lee, Tune H. Pers, Cornelius A. Rietveld, Patrick Turley, Guo-Bo Chen, Valur Emilsson, S. Fleur W. Meddens, Sven Oskarsson, Joseph K. Pickrell, Kevin Thom, Pascal Timshel, Ronald de Vlaming, Abdel Abdellaoui, Tarunveer S. Ahluwalia, Jonas Bacelis, Clemens Baumbach, Gyda Bjornsdottir, Johannes H. Brandsma, Maria Pina Concas, Jaime Derringer, Nicholas A. Furlotte, Tessel E. Galesloot, Giorgia Girotto, Richa Gupta, Leanne M. Hall, Sarah E. Harris, Edith Hofer, Momoko Horikoshi, Jennifer E. Huffman, Kadri Kaasik, Ioanna P. Kalafati, Robert Karlsson, Augustine Kong, Jari Lahti, Sven J. van der Lee, Christiaan de Leeuw, Penelope A. Lind, Karl-Oskar Lindgren, Tian Liu, Massimo Mangino, Jonathan Marten, Evelin Mihailov, Michael B. Miller, Peter J. van der Most, Christopher Oldmeadow, Antony Payton, Natalia Pervjakova, Wouter J. Peyrot, Yong Qian, Olli Raitakari, Rico Rueedi, Erika Salvi, Börge Schmidt, Katharina E. Schraut, Jianxin Shi, Albert V. Smith, Raymond A. Poot, Beate St Pourcain, Alexander Teumer, Gudmar Thorleifsson, Niek Verweij, Dragana Vuckovic, Juergen Wellmann, Harm-Jan Westra, Jingyun Yang, Wei Zhao, Zhihong Zhu, Behrooz Z. Alizadeh, Najaf Amin, Andrew Bakshi, Sebastian E. Baumeister, Ginevra Biino, Klaus Bønnelykke, Patricia A. Boyle, Harry Campbell, Francesco P. Cappuccio, Gail Davies, Jan-Emmanuel De Neve, Panos Deloukas, Ilja Demuth, Jun Ding, Peter Eibich, Lewin Eisele, Niina Eklund, David M. Evans, Jessica D. Faul, Mary F. Feitosa, Andreas J. Forstner, Ilaria Gandin, Bjarni Gunnarsson, Bjarni V. Halldórsson, Tamara B. Harris, Andrew C. Heath, Lynne J. Hocking, Elizabeth G. Holliday, Georg Homuth, Michael A. Horan, Jouke-Jan Hottenga, Philip L. de Jager, Peter K. Joshi, Astanand Jugessur, Marika A. Kaakinen, Mika Kähönen, Stavroula Kanoni, Liisa Keltigangas-Järvinen, Lambertus A. L. M. Kiemeney, Ivana Kolcic, Seppo Koskinen, Aldi T. Kraja, Martin Kroh, Zoltan Kutalik, Antti Latvala, Lenore J. Launer, Maël P. Lebreton, Douglas F. Levinson, Paul Lichtenstein, Peter Lichtner, David C. M. Liewald, LifeLines Cohort Study, Anu Loukola, Pamela A. Madden, Reedik Mägi, Tomi Mäki-Opas, Riccardo E. Marioni, Pedro Marques-Vidal, Gerardus A. Meddens, George McMahon, Christa Meisinger, Thomas Meitinger, Yusplitri Milaneschi, Lili Milani, Grant W. Montgomery, Ronny Myhre, Christopher P. Nelson, Dale R. Nyholt, William E. R. Ollier, Aarno Palotie, Lavinia Paternoster, Nancy L. Pedersen, Katja E. Petrovic, David J. Porteous, Katri Räikkönen, Susan M. Ring, Antonietta Robino, Olga Rostapshova, Igor Rudan, Aldo Rustichini, Veikko Salomaa, Alan R. Sanders, Antti-Pekka Sarin, Helena Schmidt, Rodney J. Scott, Blair H. Smith, Jennifer A. Smith, Jan A. Staessen, Elisabeth Steinhagen-Thiessen, Konstantin Strauch, Antonio Terracciano, Martin D. Tobin, Sheila Ulivi, Simona Vaccargiu, Lydia Quaye, Frank J. A. van Rooij, Cristina Venturini, Anna A. E. Vinkhuyzen, Uwe Völker, Henry Völzke, Judith M. Vonk, Diego Vozzi, Johannes Waage, Erin B. Ware, Gonneke Willemsen, John R. Attia, David A. Bennett, Klaus Berger, Lars Bertram, Hans Bisgaard, Dorret I. Boomsma, Ingrid B. Borecki, Ute Bültmann, Christopher F. Chabris, Francesco Cucca, Daniele Cusi, Ian J. Deary, George V. Dedoussis, Cornelia M. van Duijn, Johan G. Eriksson, Barbara Franke, Lude Franke, Paolo Gasparini, Pablo V. Gejman, Christian Gieger, Hans-Jörgen Grabe, Jacob Gratten, Patrick J. F. Groenen, Vilmundur Gudnason, Pim van der Harst, Caroline Hayward, David A. Hinds, Wolfgang Hoffmann, Elina Hyppönen, William G. Iacono, Bo Jacobsson, Marjo-Riitta Järvelin, Karl-Heinz Jöckel, Jaakko Kaprio, Sharon L. R. Kardia, Terho Lehtimäki, Steven F. Lehrer, Patrik K. E. Magnusson, Nicholas G. Martin, Matt McGue, Andres Metspalu, Neil Pendleton, Brenda W. J. H. Penninx, Markus Perola, Nicola Pirastu, Mario Pirastu, Ozren Polasek, Danielle Posthuma, Christine Power, Michael A. Province, Nilesh J. Samani, David Schlessinger, Reinhold Schmidt, Thorkild I. A. Sørensen, Tim D. Spector, Kari Stefansson, Unnur Thorsteinsdottir, A. Roy Thurik, Nicholas J. Timpson, Henning Tiemeier, Joyce Y. Tung, André G. Uitterlinden, Veronique Vitart, Peter Vollenweider, David R. Weir, James F. Wilson, Alan F. Wright, Dalton C. Conley, Robert F. Krueger, George Davey Smith, Albert Hofman, David I. Laibson, Sarah E. Medland, Michelle N. Meyer, Jian Yang, Magnus Johannesson, Tõnu Esko, Peter M. Visscher, Philipp D. Koellinger, David Cesarini, Daniel J. Benjamin (2016-05-11; backlinks):

    Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample1, of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide statistically-significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.

  • 2016-protzko.pdf: “Effects of cognitive training on the structure of intelligence”⁠, John Protzko

  • 2016-scheiber.pdf: “Do the Kaufman Tests of Cognitive Ability and Academic Achievement Display Construct Bias Across a Representative Sample of Black, Hispanic, and Caucasian School-Age Children in Grades 1 Through 12?”⁠, Caroline Scheiber

  • 2016-tsukahara.pdf: ⁠, Jason S. Tsukahara, Tyler L. Harrison, Randall W. Engle (2016-12-01; backlinks):

    • Higher order cognition is related to baseline pupil size.
    • Baseline pupil size is uniquely related to fluid intelligence.
    • Implications for resting-state brain organization and function.

    Pupil dilations of the eye are known to correspond to central cognitive processes. However, the relationship between pupil size and individual differences in cognitive ability is not as well studied. A peculiar finding that has cropped up in this research is that those high on cognitive ability have a larger pupil size, even during a passive baseline condition. Yet these findings were incidental and lacked a clear explanation. Therefore, in the present series of studies we systematically investigated whether pupil size during a passive baseline is associated with individual differences in working memory capacity and fluid intelligence.

    Across 3 studies we consistently found that baseline pupil size is, in fact, related to cognitive ability. We showed that this relationship could not be explained by differences in mental effort, and that the effect of working memory capacity and fluid intelligence on pupil size persisted even after 23 sessions and taking into account the effect of novelty or familiarity with the environment. We also accounted for potential confounding variables such as; age, ethnicity, and drug substances. Lastly, we found that it is fluid intelligence, more so than working memory capacity, which is related to baseline pupil size.

    In order to provide an explanation and suggestions for future research, we also consider our findings in the context of the underlying neural mechanisms involved. [Keywords: intelligence, pupil size, Locus coeruleus] [Followup: ⁠.]

  • 2016-woodley.pdf

  • 2017-billings.pdf

  • 2017-blum.pdf: “Spearman's law of diminishing returns. A meta-analysis”⁠, BlumDiego, HollingHeinz

  • 2017-bo.pdf: ⁠, Ernesto Dal Bó, Frederico Finan, Olle Folke, Torsten Persson, Johanna Rickne (2017-06-01):

    Can a democracy attract competent leaders, while attaining broad representation? Economic models suggest that free-riding incentives and lower opportunity costs give the less competent a comparative advantage at entering political life. Moreover, if elites have more human capital, selecting on competence may lead to uneven representation. This article examines patterns of political selection among the universe of municipal politicians and national legislators in Sweden, using extraordinarily rich data on competence traits and social background for the entire population.

    We document 4 new facts that together characterize an “inclusive meritocracy.” First, politicians are on average statistically-significantly smarter and better leaders than the population they represent. Second, this positive selection is present even when conditioning on family (and hence social) background, suggesting that individual competence is key for selection. Third, the representation of social background, whether measured by parental earnings or occupational social class, is remarkably even. Fourth, there is at best a weak trade-off in selection between competence and social representation, mainly due to strong positive selection of politicians of low (parental) socioeconomic status. A broad implication of these facts is that it is possible for democracy to generate competent and socially representative leadership.

  • 2017-bonander.pdf: “Does gender moderate the association between intellectual ability and accidental injuries? Evidence from the 1953 Stockholm Birth Cohort study”⁠, Carl Bonander, Carolina Jernbro

  • 2017-flynn.pdf: “IQ decline and Piaget_ Does the rot start at the top?”⁠, James R. Flynn, Michael Shayer (backlinks)

  • 2017-gignac.pdf: “Brain volume and intelligence_ The moderating role of intelligence measurement quality”⁠, Gilles E. Gignac, Timothy C. Bates

  • 2017-jerrim.pdf: “Does teaching children how to play cognitively demanding games improve their educational attainment? Evidence from a Randomised Controlled Trial of chess instruction in England”⁠, john jerrim (backlinks)

  • 2017-keyes.pdf: “Association of Fluid Intelligence and Psychiatric Disorders in a Population-Representative Sample of US Adolescents”⁠, American Medical Association (backlinks)

  • 2017-lukowski.pdf: “Approximate number sense shares etiological overlap with mathematics and general cognitive ability”⁠, Sarah L. Lukowski, Miriam Rosenberg-Lee, Lee A. Thompson, Sara A. Hart, Erik G. Willcutt, Richard K. Olson, Stephen A. Petrill, Bruce F. Pennington

  • 2017-ritchie.pdf: “Book Review [Review of _The Rationality Quotient: Toward a Test of Rational Thinking_, Stanovich et al 2017]”⁠, Stuart J. Ritchie

  • 2017-ruffle.pdf: “Clever enough to tell the truth”⁠, Bradley J. Ruffle, Yossef Tobol (backlinks)

  • 2017-sniekers.pdf: ⁠, Suzanne Sniekers, Sven Stringer, Kyoko Watanabe, Philip R. Jansen, Jonathan R. I. Coleman, Eva Krapohl, Erdogan Taskesen, Anke R. Hammerschlag, Aysu Okbay, Delilah Zabaneh, Najaf Amin, Gerome Breen, David Cesarini, Christopher F. Chabris, William G. Iacono, M. Arfan Ikram, Magnus Johannesson, Philipp Koellinger, James J. Lee, Patrik K. E Magnusson, Matt McGue, Mike B. Miller, William E. R. Ollier, Antony Payton, Neil Pendleton, Robert Plomin, Cornelius A. Rietveld, Henning Tiemeier, Cornelia M. van Duijn, Danielle Posthuma (2017-05-22; backlinks):

    Intelligence is associated with important economic and health-related life outcomes1. Despite intelligence having substantial heritability2 (0.54) and a confirmed polygenic nature, initial genetic studies were mostly underpowered3,4,5. Here we report a meta-analysis for intelligence of 78,308 individuals. We identify 336 associated SNPs (METAL p < 5 × 10−8) in 18 genomic loci, of which 15 are new. Around half of the SNPs are located inside a gene, implicating 22 genes, of which 11 are new findings. Gene-based analyses identified an additional 30 genes (MAGMA p < 2.73 × 10−6), of which all but one had not been implicated previously. We show that the identified genes are predominantly expressed in brain tissue, and pathway analysis indicates the involvement of genes regulating cell development (MAGMA competitive p = 3.5 × 10−6). Despite the well-known difference in twin-based heritability2 for intelligence in childhood (0.45) and adulthood (0.80), we show substantial genetic correlation (rg = 0.89, LD score regression p = 5.4 × 10−29). These findings provide new insight into the genetic architecture of intelligence.

  • 2017-sorjonen.pdf: “Predicting group differences from the correlation of vectors”⁠, Kimmo Sorjonen, Jon Aurell, Bo Melin

  • 2017-treadway.pdf: “Comparing the Cognitive Abilities of Hackers and Non-Hackers Using a Self-Report Questionnaire”⁠, Kellin Nicol Treadway

  • 2017-trundt.pdf: ⁠, Katherine M. Trundt, Timothy Z. Keith, Jacqueline M. Caemmerer, Leann V. Smith (2017-01-01):

    Individually administered intelligence measures are commonly used in diagnostic work, but there is a continuing need for research investigating possible test bias among these measures. One current intelligence measure, the Differential Ability Scales, Second Edition (DAS-II), is a test with growing popularity. The issue of test bias, however, has not been thoroughly investigated with the DAS-II. The current study investigated whether the DAS-II demonstrates systematic construct bias when used with children from three racial and ethnic groups—African American, Asian, and Hispanic—when compared to non-Hispanic Caucasian children. Multi-group confirmatory factor analyses with data from the DAS-II standardization sample were used to assess whether the constructs and measurement of constructs were invariant across groups. Results indicate cross-group internal structure validity in the DAS-II, and thus a lack of construct bias. Minor differences were found, but these differences do not affect the calculation of composite scores on the DAS-II and thus would not result in unfair scoring for the groups involved. Results of this study support the appropriateness of the DAS-II for clinical use with these racial and ethnic groups.

  • 2017-wongupparaj.pdf: ⁠, Peera Wongupparaj, Rangsirat Wongupparaj, Veena Kumari, Robin G. Morris (2017-09):


    • Analysis of Digit span and Corsi-block span data from 1754 independent samples (n = 139,677), covering a period of 43 years
    • Verbal and visuospatial short-term memory (STM) were positively correlated with year of publication.
    • Verbal and visuospatial working memory (WM) were negatively correlated with year of publication.

    Abstract: The Flynn effect has been investigated extensively for IQ, but few attempts have been made to study it in relation to working memory (WM). Based on the findings from a cross-temporal meta-analysis using 1754 independent samples (n = 139,677), the Flynn effect was observed across a 43-year period, with changes here expressed in terms of correlations (coefficients) between year of publication and mean memory test scores. Specifically, the Flynn effect was found for forward digit span (r = 0.12, p < 0.01) and forward Corsi block span (r = 0.10, p < 0.01). Moreover, an anti-Flynn effect was found for backward digit span (r = −0.06, p < 0.01) and for backward Corsi block span (r = −0.17, p < 0.01). Overall, the results support co-occurrence theories that predict simultaneous secular gains in specialized abilities and declines in g. The causes of the differential trajectories are further discussed. [Keywords: Flynn effect, Short-term memory, Working memory, Forward and backward digit span, Forward and backward Corsi block span, Cross-temporal meta-analysis]

  • 2018-ashton.pdf: “Cognitive performance is linked to group size and affects fitness in Australian magpies”⁠, Benjamin J. Ashton, Amanda R. Ridley, Emily K. Edwards, Alex Thornton

  • 2018-bratsberg.pdf (backlinks)

  • 2018-coutrot.pdf: “Global Determinants of Navigation Ability”⁠, Antoine Coutrot, Ricardo Silva, Ed Manley, Will de Cothi, Saber Sami, Véronique D. Bohbot, Jan M. Wiener, Christoph Hölscher, Ruth C. Dalton, Michael Hornberger, Hugo J. Spiers (backlinks)

  • 2018-coyle.pdf: “General Intelligence (g), ACT Scores, and Theory of Mind_ (ACT)g Predicts Limited Variance Among Theory of Mind Tests”⁠, Thomas R. Coyle, Karrie E. Elpers, Miguel C. Gonzalez, Jacob Freeman, Jacopo A. Baggio

  • 2018-elliott.pdf: ⁠, Maxwell L. Elliott, Daniel W. Belsky, Kevin Anderson, David L. Corcoran, Tian Ge, Annchen Knodt, Joseph A. Prinz, Karen Sugden, Benjamin Williams, David Ireland, Richie Poulton, Avshalom Caspi, Avram Holmes, Terrie Moffitt, Ahmad R. Hariri (2018-01-01; backlinks):

    People who score higher on intelligence tests tend to have larger brains. Twin studies suggest the same genetic factors influence both brain size and intelligence. This has led to the hypothesis that genetics influence intelligence partly by contributing to the development of larger brains. We tested this hypothesis using four large imaging genetics studies (combined N = 7965) with polygenic scores derived from a genome-wide association study (GWAS) of educational attainment, a correlate of intelligence. We conducted meta-analysis to test associations among participants’ genetics, total brain volume (i.e., brain size), and cognitive test performance. Consistent with previous findings, participants with higher polygenic scores achieved higher scores on cognitive tests, as did participants with larger brains. Participants with higher polygenic scores also had larger brains. We found some evidence that brain size partly mediated associations between participants’ education polygenic scores and their cognitive test performance. Effect sizes were larger in the population-based samples than in the convenience-based samples. Recruitment and retention of population-representative samples should be a priority for neuroscience research. Findings suggest promise for studies integrating GWAS discoveries with brain imaging to understand neurobiology linking genetics with cognitive performance.

  • 2018-ganzach.pdf: “Wages, mental abilities and assessments in large scale international surveys_ Still not much more than g”⁠, Yoav Ganzach, Pankaj Patel (backlinks)

  • 2018-gensowski.pdf: ⁠, Miriam Gensowski (2018-04; backlinks):

    [Published version of ]

    • This paper estimates the effects of personality traits and IQ on lifetime earnings, both as a sum and individually by age.
    • The payoffs to personality traits display a concave life-cycle pattern, with the largest effects between the ages of 40 and 60.
    • The largest effects on earnings are found for Conscientiousness, Extraversion, and Agreeableness (negative).
    • An interaction of traits with education reveals that personality matters most for highly educated men.
    • The overall effect of Conscientiousness operates partly through education, which also has substantial returns.

    This paper estimates the effects of personality traits and IQ on lifetime earnings of the men and women of the Terman study, a high-IQ U.S. sample. Age-by-age earnings profiles allow a study of when personality traits affect earnings most, and for whom the effects are strongest. I document a concave life-cycle pattern in the payoffs to personality traits, with the largest effects between the ages of 40 and 60. An interaction of traits with education reveals that personality matters most for highly educated men. The largest effects are found for Conscientiousness, Extraversion, and Agreeableness (negative), where Conscientiousness operates partly through education, which also has substantial returns. [Keywords: Personality traits, Socio-emotional skills, Cognitive skills, Returns to education, Lifetime earnings, Big Five, Human capital, Factor analysis]

  • 2018-gignac.pdf

  • 2018-gottfredson.pdf: “g Theory: How Recurring Variation in Human Intelligence and the Complexity of Everyday Tasks Create Social Structure and the Democratic Dilemma”⁠, Linda S. Gottfredson

  • 2018-guez.pdf: “Are high-IQ students more at risk of school failure?”⁠, Ava Guez, Hugo Peyre, Marion Le Cam, Nicolas Gauvrit, Franck Ramus

  • 2018-hegelund.pdf: “Low IQ as a predictor of unsuccessful educational and occupational achievement_ A register-based study of 1,098,742 men in Denmark 1968–2016”⁠, Emilie Rune Hegelund, Trine Flensborg-Madsen, Jesper Dammeyer, Erik Lykke Mortensen (backlinks)

  • 2018-hopkins.pdf: “More intelligent chimpanzees (Pan troglodytes) have larger brains and increased cortical thickness”⁠, William D. Hopkins, Xiang Li, Neil Roberts

  • 2018-huguet.pdf: “Measuring and Estimating the Effect Sizes of Copy Number Variants on General Intelligence in Community-Based Samples”⁠, American Medical Association (backlinks)

  • 2018-kell.pdf: “SAGE Encyclopedia: Terman Study of the Gifted”⁠, Harrison J. Kell, Jonathan Wai

  • 2018-lee-supplement.pdf

  • 2018-lee.pdf: ⁠, James J. Lee, Robbee Wedow, Aysu Okbay, Edward Kong, Omeed Maghzian, Meghan Zacher, Tuan Anh Nguyen-Viet, Peter Bowers, Julia Sidorenko, Richard Karlsson Linnér, Mark Alan Fontana, Tushar Kundu, Chanwook Lee, Hui Li, Ruoxi Li, Rebecca Royer, Pascal N. Timshel, Raymond K. Walters, Emily A. Willoughby, Loïc Yengo, 23andMe Research Team, COGENT (Cognitive Genomics Consortium), Social Science Genetic Association Consortium, Maris Alver, Yanchun Bao, David W. Clark, Felix R. Day, Nicholas A. Furlotte, Peter K. Joshi, Kathryn E. Kemper, Aaron Kleinman, Claudia Langenberg, Reedik Mägi, Joey W. Trampush, Shefali Setia Verma, Yang Wu, Max Lam, Jing Hua Zhao, Zhili Zheng, Jason D. Boardman, Harry Campbell, Jeremy Freese, Kathleen Mullan Harris, Caroline Hayward, Pamela Herd, Meena Kumari, Todd Lencz, Jian’an Luan, Anil K. Malhotra, Andres Metspalu, Lili Milani, Ken K. Ong, John R. B. Perry, David J. Porteous, Marylyn D. Ritchie, Melissa C. Smart, Blair H. Smith, Joyce Y. Tung, Nicholas J. Wareham, James F. Wilson, Jonathan P. Beauchamp, Dalton C. Conley, Tõnu Esko, Steven F. Lehrer, Patrik K. E. Magnusson, Sven Oskarsson, Tune H. Pers, Matthew R. Robinson, Kevin Thom, Chelsea Watson, Christopher F. Chabris, Michelle N. Meyer, David I. Laibson, Jian Yang, Magnus Johannesson, Philipp D. Koellinger, Patrick Turley, Peter M. Visscher, Daniel J. Benjamin, David Cesarini (10.1038/s41588-018-0147-3; backlinks):

    Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11–13% of the variance in educational attainment and 7–10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.

  • 2018-mclarnon-supplement-1-s2.0-S0191886917306608-mmc1.docx

  • 2018-mclarnon.pdf: “Differentiation of cognitive abilities and the Medical College Admission Test”⁠, Matthew J. W. McLarnon, Richard D. Goffin, Mitchell G. Rothstein

  • 2018-mollon.pdf: “Genetic influence on cognitive development between childhood and adulthood”⁠, Josephine Mollon, Emma E. M. Knowles, Samuel R. Mathias, Ruben Gur, Juan Manuel Peralta, Daniel J. Weiner, Elise B. Robinson, Raquel E. Gur, John Blangero, Laura Almasy, David C. Glahn

  • 2018-mulder.pdf

  • 2018-plomin.pdf: ⁠, Robert Plomin, Sophie von Stumm (2018; backlinks):

    Intelligence—the ability to learn, reason and solve problems—is at the forefront of behavioural genetic research. Intelligence is highly heritable and predicts important educational, occupational and health outcomes better than any other trait. Recent genome-wide association studies have successfully identified inherited genome sequence differences that account for 20% of the 50% heritability of intelligence. These findings open new avenues for research into the causes and consequences of intelligence using genome-wide polygenic scores that aggregate the effects of thousands of genetic variants.

  • 2018-reeve.pdf: “A systematic review of the state of literature relating parental general cognitive ability and number of offspring”⁠, Charlie L. Reeve, Michael D. Heeney, Michael A. Woodley of Menie

  • 2018-rindermann-2.pdf: ⁠, Heiner Rindermann, Stephen J. Ceci (2018-09-26):

    In 19 (sub)samples from seven countries (United States, Austria, Germany, Costa Rica, Ecuador, Vietnam, Brazil), we analyzed the impact of parental education compared with wealth on the cognitive ability of children (aged 4–22 years, total n = 15,297). The background of their families ranged from poor indigenous remote villagers to academic families in developed countries, including parents of the gifted. Children’s cognitive ability was measured with mental speed tests, Culture Fair Intelligence Test (CFT), the Raven’s, Wiener Entwicklungstest (WET), Cognitive Abilities Test (CogAT), Piagetian tasks, Armed Forces Qualification Test (AFQT), Progress in International Reading Literacy Study (PIRLS), Trends in International Mathematics and Science Study (TIMSS), and Programme for International Student Assessment (PISA). Parental wealth was estimated by asking for income, indirectly by self-assessment of relative wealth, and by evaluating assets. The mean direct effect of parental education was greater than wealth. In path analyses, parental education (βEd) also showed a stronger impact on children’s intelligence than familial economic status (βIn, total effect averages: βEd = .30–.45, βIn = .09–.12; N = 15,125, k = 18). The effects on mental speed were smaller than for crystallized intelligence, but still larger for parental education than familial economic status (βEd → MS = .25, βIn → MS = .00, βEd → CI = .36, βIn → CI = .09; N = 394, k = 3). Additional factors affecting children’s cognitive ability are number of books, marital status, educational behavior of parents, and behavior of children. If added, a general background (ethnicity, migration) factor shows strong effects (βBg = .30–.36). These findings are discussed in terms of environmental versus hidden genetic effects. [Keywords: cognitive competence, intelligence development, fluid and crystallized intelligence, SES, number of books, marital status, smoking]

  • 2018-rindermann.pdf: “FLynn-effect and economic growth_ Do national increases in intelligence lead to increases in GDP?”⁠, Heiner Rindermann, David Becker (backlinks)

  • 2018-scharfen.pdf: “Retest effects in cognitive ability tests_ A meta-analysis”⁠, Jana Scharfen, Judith Marie Peters, Heinz Holling

  • 2018-tervonen.pdf: ⁠, Lassi Tervonen, Mika Kortelainen, Ohto Kanninen (2018; backlinks):

    Finnish elite high school students enrol in university and so-called elite fields of study more often than Finnish high school students on average. However, those who attend elite high schools are also higher-achieving in terms of baseline grade point average (GPA) from comprehensive school. This selection bias must be taken into account in studying the causal effects of elite high schools.

    This study focuses on 5 elite high schools in the Helsinki region and aims to solve the problem of selection bias by using a regression discontinuity design (RDD). In our case RDD exploits the entrance thresholds of elite high schools as a rule which assigns applicants near the threshold into treatment and control groups. By comparing the outcomes (e.g. the probability of enrolment in a university) of these groups we can estimate the causal effects of an elite high school offer on various educational outcomes, such as university enrolment.

    We find that crossing the threshold of an elite high school leads to a higher-achieving peer group in terms of baseline GPA. However, the elite high school offer does not have a statistically-significant effect on the probability of enrolment in a university or on the probability of enrolment in an elite field of study. The only exception is Etelä-Tapiola high school, which has a positive effect on the probability of enrolment in a university. [Keywords: education, regression discontinuity design, peer effects, school choice]

  • 2018-trenkmann.pdf: “Lessons from 1 million genomes”⁠, Michelle Trenkmann

  • 2018-wai-2.pdf (backlinks)

  • 2018-wai.pdf: “Sex differences in ability tilt in the right tail of cognitive abilities_ A 35-year examination”⁠, Jonathan Wai, Jaret Hodges, Matthew C. Makel (backlinks)

  • 2018-wang.pdf: “Intelligence in the People's Republic of China”⁠, Mingrui Wang, Richard Lynn

  • 2018-warne-2.pdf: ⁠, Russell T. Warne (2018; backlinks):

    is widely seen as the “father of gifted education,” yet his work is controversial. Terman’s “mixed legacy” includes the pioneering work in the creation of intelligence tests, the first large-scale ⁠, and the earliest discussions of gifted identification, curriculum, ability grouping, acceleration, and more. However, since the 1950s, Terman has been viewed as a sloppy thinker at best and a racist, sexist, and/or classist at worst.

    This article explores the most common criticisms of Terman’s legacy: an overemphasis on IQ, support for the meritocracy, and emphasizing genetic explanations for the origin of intelligence differences over environmental ones. Each of these criticisms is justified to some extent by the historical record, and each is relevant today. Frequently overlooked, however, is Terman’s willingness to form a strong opinion based on weak data.

    The article concludes with a discussion of the important lessons that Terman’s work has for modern educators and psychologists, including his contributions to psychometrics and gifted education, his willingness to modify his opinions in the face of new evidence, and his inventiveness and inclination to experiment. Terman’s legacy is complex, but one that provides insights that can enrich modern researchers and practitioners in these areas.

  • 2018-warne.pdf

  • 2018-willoughby.pdf: “'Importance of Intelligence and Emotional Intelligence for Physicians': Letter to The Editor by Emily Willoughby & Brian B. Boutwell”⁠, Emily Willoughby, Brian B. Boutwell

  • 2018-zaboski.pdf: “Meta-analysis of the relationship between academic achievement and broad abilities of the Cattell-horn-Carroll theory”⁠, Brian A. Zaboski, John H. Kranzler, Nicholas A. Gage

  • 2019-alemany.pdf: ⁠, Silvia Alemany, Philip R. Jansen, Ryan L. Muetzel, Natália Marques, Hanan El Marroun, Vincent W. V. Jaddoe, Tinca J. C. Polderman, Henning Tiemeier, Danielle Posthuma, Tonya White (2019-01):

    Objective: This study examined the relation between polygenic scores (PGSs) for 5 major psychiatric disorders and 2 cognitive traits with brain magnetic resonance imaging morphologic measurements in a large population-based sample of children. In addition, this study tested for differences in brain morphology-mediated associations between PGSs for psychiatric disorders and PGSs for related behavioral phenotypes.

    Method: Participants included 1,139 children from the Generation R Study assessed at 10 years of age with genotype and neuroimaging data available. PGSs were calculated for schizophrenia, bipolar disorder, major depression disorder, attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, intelligence, and educational attainment using results from the most recent genome-wide association studies. Image processing was performed using FreeSurfer to extract cortical and subcortical brain volumes.

    Results: Greater genetic susceptibility for ADHD was associated with smaller caudate volume (strongest prior = 0.01: β = −0.07, p = 0.006). In boys, mediation analysis estimates showed that 11% of the association between the PGS for ADHD and the PGS attention problems was mediated by differences in caudate volume (n = 535), whereas mediation was not statistically-significant in girls or the entire sample. PGSs for educational attainment and intelligence showed positive associations with total brain volume (strongest prior = 0.5: β = 0.14, p = 7.12 × 10−8; and β = 0.12, p = 6.87 × 10−7, respectively).

    Conclusion: The present findings indicate that the neurobiological manifestation of polygenic susceptibility for ADHD, educational attainment, and intelligence involve early morphologic differences in caudate and total brain volumes in childhood. Furthermore, the genetic risk for ADHD might influence attention problems through the caudate nucleus in boys. [Keywords: polygenic risk score, neuroimaging, ADHD, educational attainment, intelligence]

  • 2019-allegrini.pdf: “Genomic prediction of cognitive traits in childhood and adolescence”⁠, A. G. Allegrini, S. Selzam, K. Rimfeld, S. Stumm, J. B. Pingault, R. Plomin

  • 2019-andreoni.pdf: ⁠, James Andreoni, Michael A. Kuhn, John A. List, Anya Samek, Kevin Sokal, Charles Sprenger (2019-09-01):


    • We conduct field experiments on time preferences with children ages 3–12.
    • Time preferences evolve statistically-significantly during this period, with older children displaying more patience.
    • Neither assignment to early schooling or parent preferences can explain child time preferences.
    • Interestingly, we observe that black children are more impatient than white or Hispanic children.

    Abstract: Time preferences have been correlated with a range of life outcomes, yet little is known about their early development. We conduct a field experiment to elicit time preferences of over 1200 children ages 3–12, who make several intertemporal decisions. To shed light on how such primitives form, we explore various channels that might affect time preferences, from background characteristics to the causal impact of an early schooling program that we developed and operated. Our results suggest that time preferences evolve substantially during this period, with younger children displaying more impatience than older children. We also find a strong association with race: black children, relative to white or Hispanic children, are more impatient. Finally, assignment to different schooling opportunities is not statistically-significantly associated with child time preferences. [Keywords: Time preferences, Child behavior, Experiment, Inter-generational transmission]

  • 2019-barth.pdf: “Genetic Endowments and Wealth Inequality”⁠, Daniel Barth, Nicholas W. Papageorge, Kevin Thom

  • 2019-carl-supplement.zip

  • 2019-carl.pdf: “A scientometric analysis of controversies in the field of intelligence research”⁠, Noah Carl, Michael A. Woodley of Menie

  • 2019-coyle.pdf: “Tech tilt predicts jobs, college majors, and specific abilities_ Support for investment theories”⁠, Thomas R. Coyle

  • 2019-dacunto.pdf: “IQ, [Inflation] Expectations, and Choice”⁠, Francesco D'Acunto, Daniel Hoang, Maritta Paloviita, Michael Webe

  • 2019-finet.pdf

  • 2019-furnham.pdf: “Factors influencing adult savings and investment_ Findings from a nationally representative sample”⁠, Adrian Furnham, Helen Cheng (backlinks)

  • 2019-genc.pdf: ⁠, Erhan Genç, Christoph Fraenz, Caroline Schlüter, Patrick Friedrich, Manuel C. Voelkle, Rüdiger Hossiep, Onur Güntürkün, René Mõttus (2019-01-01):

    Cognitive performance varies widely between individuals and is highly influenced by structural and functional properties of the brain. In the past, neuroscientific research was principally concerned with fluid intelligence, while neglecting its equally important counterpart crystallized intelligence. Crystallized intelligence is defined as the depth and breadth of knowledge and skills that are valued by one’s culture. The accumulation of crystallized intelligence is guided by information storage capacities and is likely to be reflected in an individual’s level of general knowledge. In spite of the significant role general knowledge plays for everyday life, its neural foundation largely remains unknown. In a large sample of 324 healthy individuals, we used standard magnetic resonance imaging along with functional magnetic resonance imaging and diffusion tensor imaging to examine different estimates of brain volume and brain network connectivity and assessed their predictive power with regard to both general knowledge and fluid intelligence. Our results demonstrate that an individual’s level of general knowledge is associated with structural brain network connectivity beyond any confounding effects exerted by age or sex. Moreover, we found fluid intelligence to be best predicted by cortex volume in male subjects and functional network connectivity in female subjects. Combined, these findings potentially indicate different neural architectures for information storage and information processing. © 2019 European Association of Personality Psychology

  • 2019-giangrande-supplementary.zip

  • 2019-graves.pdf

  • 2019-hegelund-supplement.docx (backlinks)

  • 2019-hegelund.pdf: ⁠, Emilie Rune Hegelund, Trine Flensborg-Madsen, Jesper Dammeyer, Laust Hvas Mortensen, Erik Lykke Mortensen (2019-06-04; backlinks):

    The present register-based study investigated the influence of familial factors on the association of IQ with educational and occupational achievement among young men in Denmark. The study population comprised all men with at least one full brother where both the individual and his brothers were born from 1950 and appeared before a draft board in 1968–1984 and 1987–2015 (n = 364,193 individuals). Intelligence was measured by Børge Priens Prøve at age 18. Educational and occupational achievement were measured by grade point average (GPA) in lower secondary school, time to receiving social benefits at ages 18–30, and gross income at age 30. The statistical analyses comprised two distinct statistical analyses of the investigated associations: A conventional cohort analysis and a within-sibship analysis in which the association under investigation was analysed within siblings while keeping familial factors shared by siblings fixed. The results showed that an appreciable part of the associations of IQ with educational and occupational achievement could be attributed to familial factors shared by siblings. However, only the within sibling association between IQ and GPA in lower secondary school clearly differed from the association observed in the cohort analysis after covariates had been taken into account.

  • 2019-hoffmann.pdf

  • 2019-horschler.pdf: ⁠, Daniel J. Horschler, Brian Hare, Josep Call, Juliane Kaminski, Ádám Miklósi, Evan L. MacLean (2019-01-03; backlinks):

    Large-scale phylogenetic studies of animal cognition have revealed robust links between absolute brain volume and species differences in executive function. However, past comparative samples have been composed largely of primates, which are characterized by evolutionarily derived neural scaling rules. Therefore, it is currently unknown whether positive associations between brain volume and executive function reflect a broad-scale evolutionary phenomenon, or alternatively, a unique consequence of primate brain evolution. Domestic dogs provide a powerful opportunity for investigating this question due to their close genetic relatedness, but vast intraspecific variation. Using citizen science data on more than 7000 purebred dogs from 74 breeds, and controlling for genetic relatedness between breeds, we identify strong relationships between estimated absolute brain weight and breed differences in cognition. Specifically, larger-brained breeds performed statistically-significantly better on measures of short-term memory and self-control. However, the relationships between estimated brain weight and other cognitive measures varied widely, supporting domain-specific accounts of cognitive evolution. Our results suggest that evolutionary increases in brain size are positively associated with taxonomic differences in executive function, even in the absence of primate-like neuroanatomy. These findings also suggest that variation between dog breeds may present a powerful model for investigating correlated changes in neuroanatomy and cognition among closely related taxa.

  • 2019-jiang.pdf: “Multimodal data revealed different neurobiological correlates of intelligence between males and females”⁠, Rongtao Jiang, Vince D. Calhoun, Yue Cui, Shile Qi, Chuanjun Zhuo, Jin Li, Rex Jung, Jian Yang, Yuhui Du, Tianzi Jiang, Jing Sui

  • 2019-joy.pdf: “CCR5 Is a Therapeutic Target for Recovery after Stroke and Traumatic Brain Injury”⁠, Mary T. Joy, Einor Ben Assayag, Dalia Shabashov-Stone, Sigal Liraz-Zaltsman, Jose Mazzitelli, Marcela Arenas, Nora Abduljawad, Efrat Kliper, Amos D. Korczyn, Nikita S. Thareja, Efrat L. Kesner, Miou Zhou, Shan Huang, Tawnie K. Silva, Noomi Katz, Natan M. Bornstein, Alcino J. Silva, Esther Shohami, S. Thomas Carmichael

  • 2019-jung.pdf: ⁠, Rex E. Jung, Muhammad O. Chohan (2019-06-01):

    The study of human individual differences has matured substantially, in the last decade or so owing, in part, to the notable advances in neuroimaging techniques. There are three major domains of inquiry within individual differences research: personality, creativity, and intelligence. Each has a discrete, testable definition (a new definition for intelligence is offered: rapid and accurate problem solving), and each has been associated with distinct brain regions and interactive networks.

    Here, we outline commonalities between these constructs, which appear to conform to two major axes: exploratory behavior and restraint. These axes, in turn, conform largely to two major brain networks dedicated to novelty generation (i.e. DMN), and refinement of ideas (i.e. CCN).

    Thus, human individual differences represent the expression of adaptive behaviors leading to exploratory and/or restrained action arising from brain structure and function.

  • 2019-kaufman.pdf: “The structure of ape (hominoidea) intelligence”⁠, Allison B. Kaufman, Matthew R. Reynolds, Alan S. Kaufman

  • 2019-king.pdf: “Genetic and environmental influences on spatial reasoning_ A meta-analysis of twin studies”⁠, Michael J. King, David P. Katz, Lee A. Thompson, Brooke N. Macnamara

  • 2019-kirkegaard.pdf: “Solid numbers, missed opportunities: Review of _The Intelligence Of Nations_ [Lynn & Becker 2019]”⁠, Emil O. W. Kirkegaard

  • 2019-kremen.pdf: ⁠, William S. Kremen, Asad Beck, Jeremy A. Elman, Daniel E. Gustavson, Chandra A. Reynolds, Xin M. Tu, Mark E. Sanderson-Cimino, Matthew S. Panizzon, Eero Vuoksimaa, Rosemary Toomey, Christine Fennema-Notestine, Donald J. Hagler Jr., Bin Fang, Anders M. Dale, Michael J. Lyons, Carol E. Franz (2019-01-01):

    How and when education improves cognitive capacity is an issue of profound societal importance. Education and later-life education-related factors, such as occupational complexity and engagement in cognitive-intellectual activities, are frequently considered indices of cognitive reserve, but whether their effects are truly causal remains unclear. In this study, after accounting for general cognitive ability (GCA) at an average age of 20 y, additional education, occupational complexity, or engagement in cognitive-intellectual activities accounted for little variance in late midlife cognitive functioning in men age 56–66 (n= 1009). Age 20 GCA accounted for 40% of variance in the same measure in late midlife and approximately 10% of variance in each of seven cognitive domains. The other factors each accounted for <1% of the variance in cognitive outcomes. The impact of these other factors likely reflects reverse causation—namely, downstream effects of early adult GCA. Supporting that idea, age 20 GCA, but not education, was associated with late midlife cortical surface area (n= 367). In our view, the most parsimonious explanation of our results, a meta-analysis of the impact of education, and epidemiologic studies of the Flynn effect is that intellectual capacity gains due to education plateau in late adolescence/early adulthood. Longitudinal studies with multiple cognitive assessments before completion of education would be needed to confirm this speculation. If cognitive gains reach an asymptote by early adulthood, then strengthening cognitive reserve and reducing later-life cognitive decline and dementia risk may really begin with improving educational quality and access in childhood and adolescence.

  • 2019-lang.pdf: ⁠, Jonas W. Lang, Harrison J. Kell (2019; backlinks):

    Recent research on the role of general mental ability (GMA) and specific abilities in work-related outcomes has shown that the results differ depending on the theoretical and conceptual approach that researchers use. While earlier research has typically assumed that GMA causes the specific abilities and has thus used incremental validity analysis, more recent research has explored the implications of treating GMA and specific abilities as equals (differing only in breadth and not subordination) and has used relative importance analysis. In this article, we extend this work to the prediction of extrinsic career success operationalized as pay, income, and the attainment of jobs with high prestige. Results, based on a large national sample, revealed that GMA and specific abilities measured in school were good predictors of job prestige measured after 11 years, pay measured after 11 years, and income 51 years later toward the end of the participants’ work lives. With 1 exception, GMA was a dominant predictor in incremental validity analyses. However, in relative importance analyses, the majority of the explained variance was explained by specific abilities, and GMA was not more important than single specific abilities in relative importance analyses. Visuospatial, verbal, and mathematical abilities all had substantial variance shares and were also more important than GMA in some of the analyses. Implications for the interpretation of cognitive ability data and facilitating people’s success in their careers are discussed.

  • 2019-lee.pdf: ⁠, James J. Lee, Matt McGue, William G. Iacono, Andrew M. Michael, Christopher F. Chabris (2019-07; backlinks):

    There exists a moderate correlation between MRI-measured brain size and the general factor of IQ performance (g), but the question of whether the association reflects a theoretically important causal relationship or spurious confounding remains somewhat open. Previous small studies (n < 100) looking for the persistence of this correlation within families failed to find a tendency for the sibling with the larger brain to obtain a higher test score. We studied the within-family relationship between brain volume and intelligence in the much larger sample provided by the Human Connectome Project (n = 1022) and found a highly statistically-significant correlation (disattenuated ρ = 0.18, p_ < 0.001). We replicated this result in the Minnesota Center for Twin and Family Research (n = 2698), finding a highly statistically-significant within-family correlation between head circumference and intelligence (disattenuated ρ = 0.19, p < 0.001). We also employed novel methods of causal inference relying on summary statistics from genome-wide association studies (GWAS) of head size (n ≈ 10,000) and measures of cognition (257,000 < n < 767,000). Using bivariate LD Score regression, we found a genetic correlation between intracranial volume (ICV) and years of education (EduYears) of 0.41 (p < 0.001). Using the Latent Causal Variable method, we found a genetic causality proportion of 0.72 (p < 0.001); thus the genetic correlation arises from an asymmetric pattern, extending to sub-significant loci, of genetic variants associated with ICV also being associated with EduYears but many genetic variants associated with EduYears not being associated with ICV. This is the pattern of genetic results expected from a causal effect of brain size on intelligence. These findings give reason to take up the hypothesis that the dramatic increase in brain volume over the course of human evolution has been the result of natural selection favoring general intelligence.

  • 2019-mansson.pdf: ⁠, Johanna Månsson, Karin Stjernqvist, Fredrik Serenius, Ulrika Ådén, Karin Källén (2018-06-28; backlinks):

    The study aim was to explore the relationship between a developmental assessment at preschool age and an intelligence quotient (IQ) assessment at school age. One hundred sixty-two children were assessed at 2.5 years with the Bayley Scales of Infant and Toddler Development—Third Edition (Bayley-III) and then at 6.5 years with the Wechsler Intelligence Scale for Children—Fourth Edition (WISC-IV). The Bayley-III Cognitive Index score was the Bayley entity that showed the highest correlation with WISC-IV Full-Scale IQ (FSIQ; r = .41). There was a statistically-significant difference between the individual WISC-IV FSIQ and the Bayley-III Cognitive Index scores. Analyses showed an average difference of −4 units and 95% limits of agreement of −18.5 to 26.4 units. A multivariate model identified the Bayley-III Cognitive Index score as the most important predictor for FSIQ and General Ability Index (GAI), respectively, in comparison with demographic factors. The model explained 24% of the total FSIQ variation and 26% of the GAI variation. It was concluded that the Bayley-III measurement was an insufficient predictor of later IQ.

  • 2019-oconnell.pdf: “Is the impact of SES on educational performance overestimated? Evidence from the PISA survey”⁠, Michael O'Connell

  • 2019-platt.pdf: “The Flynn effect for fluid IQ may not generalize to all ages or ability levels: A population-based study of 10,000 US adolescents”⁠, Jonathan M. Platt, Katherine M. Keyes, Katie A. McLaughlin, Alan S. Kaufman

  • 2019-rabinowitz.pdf

  • 2019-schlegel.pdf: “A meta-analysis of the relationship between emotion recognition ability and intelligence”⁠, Katja Schlegel, Tristan Palese, Marianne Schmid Mast, Thomas H. Rammsayer, Judith A. Hall, Nora A. Murphy

  • 2019-schmitt-2.pdf

  • 2019-schmitt.pdf: ⁠, J Eric Schmitt, Armin Raznahan, Liv S. Clasen, Greg L. Wallace, Joshua N. Pritikin, Nancy Raitano Lee, Jay N. Giedd, Michael C. Neale (2019-01-01):

    The neural substrates of intelligence represent a fundamental but largely uncharted topic in human developmental neuroscience. Prior neuroimaging studies have identified modest but highly dynamic associations between intelligence and cortical thickness (CT) in childhood and adolescence. In a separate thread of research, quantitative genetic studies have repeatedly demonstrated that most measures of intelligence are highly heritable, as are many brain regions associated with intelligence. In the current study, we integrate these 2 streams of prior work by examining the genetic contributions to CT–intelligence relationships using a genetically informative longitudinal sample of 813 typically developing youth, imaged with high-resolution MRI and assessed with Wechsler Intelligence Scales (IQ). In addition to replicating the phenotypic association between multimodal association cortex and language centers with IQ, we find that CT–IQ covariance is nearly entirely genetically mediated. Moreover, shared genetic factors drive the rapidly evolving landscape of CT–IQ relationships in the developing brain.

  • 2019-tadayon.pdf: ⁠, Ehsan Tadayon, Alvaro Pascual-Leone, Emiliano Santarnecchi (2019):

    Human intelligence can be broadly subdivided into fluid (gf) and crystallized (gc) intelligence, each tapping into distinct cognitive abilities. Although neuroanatomical correlates of intelligence have been previously studied, differential contribution of cortical morphologies to gf and gc has not been fully delineated. Here, we tried to disentangle the contribution of cortical thickness, cortical surface area, and cortical gyrification to gf and gc in a large sample of healthy young subjects (n = 740, Human Connectome Project) with high-resolution MRIs, followed by replication in a separate data set with distinct cognitive measures indexing gf and gc. We found that while gyrification in distributed cortical regions had positive association with both gf and gc, surface area and thickness showed more regional associations. Specifically, higher performance in gf was associated with cortical expansion in regions related to working memory, attention, and visuo-spatial processing, while gc was associated with thinner cortex as well as higher cortical surface area in language-related networks. We discuss the results in a framework where “horizontal” cortical expansion enables higher resource allocation, computational capacity, and functional specificity relevant to gf and gc, while lower cortical thickness possibly reflects cortical pruning facilitating “vertical” intracolumnar efficiency in knowledge-based tasks relevant mostly to gc.

  • 2019-twenge.pdf: “Declines in vocabulary among American adults within levels of educational attainment, 1974–2016”⁠, Jean M. Twenge, W. Keith Campbell, Ryne A. Sherman

  • 2019-vaci.pdf: ⁠, Nemanja Vaci, Peter Edelsbrunner, Elsbeth Stern, Aljoscha Neubauer, Merim Bilalić, Rol,H. Grabner (2019-08-26):

    The relative importance of different factors in the development of human skills has been extensively discussed. Research on expertise indicates that focused practice may be the sole determinant of skill, while intelligence researchers underline the relative importance of abilities at even the highest level of skill. There is indeed a large body of research that acknowledges the role of both factors in skill development and retention. It is, however, unknown how intelligence and practice come together to enable the acquisition and retention of complex skills across the life span. Instead of focusing on the 2 factors, intelligence and practice, in isolation, here we look at their interplay throughout development. In a longitudinal study that tracked chess players throughout their careers, we show that both intelligence and practice positively affect the acquisition and retention of chess skill. Importantly, the nonlinear interaction between the 2 factors revealed that more intelligent individuals benefited more from practice. With the same amount of practice, they acquired chess skill more quickly than less intelligent players, reached a higher peak performance, and arrested decline in older age. Our research demonstrates the futility of scrutinizing the relative importance of highly intertwined factors in human development.

  • 2019-willoughby.pdf: “The role of parental genotype in predicting offspring years of education: evidence for genetic nurture”⁠, Emily A. Willoughby, Matt McGue, William G. Iacono, Aldo Rustichini, James J. Lee (backlinks)

  • 2019-woodley-2.pdf: ⁠, Michael A. Woodley of Menie, Heiner Rindermann, Jonatan Pallesen, Matthew A. Sarraf (2019; backlinks):

    Using newly available polygenic scores for educational attainment and cognitive ability, this paper investigates the possible presence and causes of a negative association between IQ and fertility in the Wisconsin Longitudinal Study sample, an issue that Retherford and Sewell first addressed 30 years ago. The effect of the polygenic score on the sample’s reproductive characteristics was indirect: a latent cognitive ability measure, comprised of both educational attainment and IQ, wholly mediated the relationship. Age at first birth mediated the negative effect of cognitive ability on sample fertility, which had a direct (positive) effect on the number of grandchildren. statistically-significantly greater impacts of cognitive ability on the sample’s fertility characteristics were found among the female subsample. This indicates that, in this sample, having a genetic disposition toward higher cognitive ability does not directly reduce number of offspring; instead, higher cognitive ability is a risk factor for prolonging reproductive debut, which, especially for women, reduces the fertility window and, thus, the number of children and grandchildren that can be produced. By estimating the effect of the sample’s reproductive characteristics on the strength of polygenic selection, it was found that the genetic variance component of IQ should be declining at a rate between −0.208 (95% CI [−0.020, −0.383]) and −0.424 (95% CI [−0.041, −0.766]) points per decade, depending on whether GCTA-GREML or classical behavior genetic estimates of IQ heritability are used to correct for ‘missing’ heritability.

  • 2019-woodley.pdf: “Are the effects of lead exposure linked to the g factor? A meta-analysis”⁠, Michael A. Woodley of Menie, Jan te Nijenhuis, Vladimir Shibaev, Miao Li, Jan Smit

  • 2020-ackerman.pdf: “A primer on assessing intelligence in laboratory studies”⁠, Phillip L. Ackerman, David Z. Hambrick

  • 2020-barrow.pdf: ⁠, Lisa Barrow, Lauren Sartain, Marisa de la Torre (2020-10-01; backlinks):

    We investigate whether elite Chicago public high schools differentially benefit high-achieving students from more and less affluent neighborhoods. Chicago’s place-based affirmative action policy allocates seats based on achievement and neighborhood socioeconomic status (SES). Using regression discontinuity design (RDD), we find that these schools do not raise test scores overall, but students are generally more positive about their high school experiences. For students from low-SES neighborhoods, we estimate negative effects on grades and the probability of attending a selective college. We present suggestive evidence that these findings for students from low-SES neighborhoods are driven by the negative effect of relative achievement ranking.

    Figure 3B: Relationship between the Centered Application Score and Select Outcomes, Tiers 1 and 4.
  • 2020-berggren.pdf: ⁠, Rasmus Berggren, Jonna Nilsson, Yvonne Brehmer, Florian Schmiedek, Martin Lövdén (2020-03-01; backlinks):

    Foreign language learning in older age has been proposed as a promising avenue for combatting age-related cognitive decline. We tested this hypothesis in a randomized controlled study in a sample of 160 healthy older participants (aged 65–75 years) who were randomized to 11 weeks of either language learning or relaxation training. Participants in the language learning condition obtained some basic knowledge in the new language (Italian), but between-groups differences in improvements on latent factors of verbal intelligence, spatial intelligence, working memory, item memory, or associative memory were negligible. We argue that this is not due to either poor measurement, low course intensity, or low statistical power, but that basic studies in foreign languages in older age are likely to have no or trivially small effects on cognitive abilities. We place this in the context of the cognitive training and engagement literature and conclude that while foreign language learning may expand the behavioral repertoire, it does little to improve cognitive processing abilities.

  • 2020-bergold.pdf: ⁠, Sebastian Bergold, Linda Wirthwein, and Ricarda Steinmayr (2020-07-29):

    Terman’s study was the first to systematically document the lives of the intellectually gifted. This cross-sectional study replicates and extends some of Terman’s findings on characteristics of the gifted in childhood, comparing largely unselected samples of gifted (n = 50) and average-ability (n = 50) adolescents matched by means of propensity score matching. Students were compared on their school performance (standardized math and reading tests and grades), motivation (math ability self-concept, intrinsic motivation, vocational interests, and educational aspirations), parental educational expectations, students’ evaluation of school instruction (perceived quality and pressure), and subjective well-being. The gifted scored higher on math performance (rank-biserial r = 0.66/0.81), math ability self-concept (0.71), intrinsic motivation (0.62), and investigative vocational interests (0.65). Some smaller differences were found for realistic (0.42) and social interests (−0.37) and for pressure in math lessons (−0.52). Results support Terman’s findings on gifted individuals’ psychological functioning and contradict negative stereotypes about the gifted.

  • 2020-borgonovi-supplement.pdf

  • 2020-borgonovi.pdf

  • 2020-bryan.pdf: ⁠, Victoria M. Bryan, John D. Mayer (2020-07-01):


    • In a meta-analysis, we determine the average correlation among broad intelligences.
    • Based on model type, the average correlation was between r = 0.58 and r = 0.65.
    • We conduct factor analyses on a composite correlation matrix of broad intelligences.
    • Our results indicate the degree and nature of relations among broad intelligences.

    Abstract: The broad intelligences include a group of mental abilities such as comprehension knowledge, quantitative reasoning, and visuospatial processing that are relatively specific in their focus and fall at the second stratum of the Cattell-Horn-Carroll (CHC) model of intelligence. In recent years, the field has seen a proliferation of mental abilities being considered for inclusion among the broad intelligences, which poses challenges in terms of their effective and efficient assessment. We conducted a meta-analysis of 61 articles that reported correlations among the broad intelligences. Results indicated that the average correlation among broad intelligences fell between r = 0.58, 95% CI [0.53, 0.64], and r = 0.65, 95% CI [0.62, 0.68], depending upon the model employed to estimate the relations. Applying factor analysis to a composite correlation matrix drawn from the studies, we obtained dimensions of broad intelligence that may be useful to organizing the group. Finally, we discuss the implications of the correlations among broad intelligences as an evaluative tool for candidate intelligences. [Keywords: Broad intelligences, Cattell-Horn-Carroll (CHC) model, Intelligence]

  • 2020-burgoyne-2.pdf: ⁠, Alexander P. Burgoyne (2020-11-01):

    Why do some individuals learn more quickly than others, or perform better in complex cognitive tasks? In this article, we describe how differential and experimental research methods can be used to study intelligence in humans and non-human animals. More than one hundred years ago, discovered a general factor underpinning performance across cognitive domains in humans. Shortly thereafter, discovered positive correlations between cognitive performance measures in the albino rat. Today, research continues to shed light on the underpinnings of the positive manifold observed among ability measures.

    In this review, we focus on the relationship between cognitive performance and attention control: the domain-general ability to maintain focus on task-relevant information while preventing attentional capture by task-irrelevant thoughts and events. Recent work from our laboratory has revealed that individual differences in attention control can largely explain the positive associations between broad cognitive abilities such as working memory capacity and fluid intelligence. In research on mice, attention control has been closely linked to a general ability factor reflecting route learning and problem solving.

    Taken together, both lines of research suggest that individual differences in attention control underpin performance in a variety of complex cognitive tasks, helping to explain why measures of cognitive ability correlate positively. Efforts to find confirmatory and disconfirmatory evidence across species stands to improve not only our understanding of attention control, but cognition in general. [Keywords: individual differences, differential psychology, intelligence, attention control, executive attention]

  • 2020-delafuente.pdf: ⁠, Javier de la Fuente, Gail Davies, Andrew D. Grotzinger, Elliot M. Tucker-Drob, Ian J. Deary (2020-09-07; backlinks):

    It has been known since 1904 that, in humans, diverse cognitive traits are positively intercorrelated. This forms the basis for the general factor of intelligence (g). Here, we directly test whether there is a partial genetic basis for individual differences in g using data from seven different cognitive tests (n = 11,263–331,679) and genome-wide autosomal single-nucleotide polymorphisms. A genetic g factor accounts for an average of 58.4% (s.e. = 4.8%) of the genetic variance in the cognitive traits considered, with the proportion varying widely across traits (range, 9–95%). We distill genetic loci that are broadly relevant for many cognitive traits (g) from loci associated specifically with individual cognitive traits. These results contribute to elucidating the aetiology of a long-known yet poorly understood phenomenon, revealing a fundamental dimension of genetic sharing across diverse cognitive traits.

  • 2020-detterman.pdf: “Will foolish ideas die in an avalanche of data? [Book review of Human Diversity, Charles C. Murray, 'Human Diversity: The Biology of Gender, Race and Class', Twelve, New York (2020)]”⁠, Douglas K. Detterman

  • 2020-douard.pdf: ⁠, Elise Douard, Abderrahim Zeribi, Catherine Schramm, Petra Tamer, Mor Absa Loum, Sabrina Nowak, Zohra Saci, Marie-Pier Lord, Borja Rodríguez-Herreros, Martineau Jean-Louis, Clara Moreau, Eva Loth, Gunter Schumann, Zdenka Pausova, Mayada Elsabbagh, Laura Almasy, David C. Glahn, Thomas Bourgeron, Aurélie Labbe, Tomas Paus, Laurent Mottron, Celia M. T. Greenwood, Guillaume Huguet, Sébastien Jacquemont (2020-09-11):

    Objective: Deleterious copy number variants (CNVs) are identified in up to 20% of individuals with autism. However, levels of autism risk conferred by most rare CNVs remain unknown. The authors recently developed statistical models to estimate the effect size on IQ of all CNVs, including undocumented ones. In this study, the authors extended this model to autism susceptibility.

    Methods: The authors identified CNVs in two autism populations (Simons Simplex Collection and MSSNG) and two unselected populations (IMAGEN and Saguenay Youth Study). Statistical models were used to test nine quantitative variables associated with genes encompassed in CNVs to explain their effects on IQ, autism susceptibility, and behavioral domains.

    Results: The “probability of being loss-of-function intolerant” (pLI) best explains the effect of CNVs on IQ and autism risk. Deleting 1 point of pLI decreases IQ by 2.6 points in autism and unselected populations. The effect of duplications on IQ is threefold smaller. Autism susceptibility increases when deleting or duplicating any point of pLI. This is true for individuals with high or low IQ and after removing de novo and known recurrent neuropsychiatric CNVs. When CNV effects on IQ are accounted for, autism susceptibility remains mostly unchanged for duplications but decreases for deletions. Model estimates for autism risk overlap with previously published observations. Deletions and duplications differentially affect social communication, behavior, and phonological memory, whereas both equally affect motor skills.

    Conclusions: Autism risk conferred by duplications is less influenced by IQ compared with deletions. The model applied in this study, trained on CNVs encompassing >4,500 genes, suggests highly polygenic properties of gene dosage with respect to autism risk and IQ loss. These models will help to interpret CNVs identified in the clinic.

  • 2020-east.pdf: ⁠, Patricia East, Jenalee Doom, Estela Blanco, Raquel Burrows, Betsy Lozoff, Sheila Gahagan (2020-08-11; backlinks):

    Objective: This study examined how the lower cognitive skills in children who consumed iron-fortified formula in infancy relate to outcomes in young adulthood.

    Methods: Participants were 443 Chilean young adults (M age = 21.2y, 55% female) who took part in a randomized controlled iron-deficiency anemia preventive trial during infancy (6–12 m). Slightly over half of participants (n = 237) received iron-fortified formula (12.7 mg/L) and 206 received a low-iron formula (2.3 mg/L). Spatial memory, IQ, and visual-motor integration were measured at age 10, and neurocognition, emotion regulation, educational level, and attainment of adult developmental milestones were assessed at age 21.

    Results: Consumption of iron-fortified formula in infancy was associated with poorer performance on neurocognitive tests in childhood, and these effects related to poorer neurocognitive, emotional, and educational outcomes in young adulthood. Dosage effects associated with consumption of iron-fortified formula were found for lower educational attainment and, marginally, slower mental processing. Those who received iron-fortified formula and had low age 10 cognitive abilities performed most poorly on neurocognitive tests at age 21.

    Conclusion: Findings suggest that the long-term development of infants who consume iron-fortified formula may be adversely affected.

    Clinical Trials number: NCT01166451. [Keywords: Iron supplementation, neurocognition, emotion regulation, memory, executive function, Chile]

  • 2020-fernandes.pdf: ⁠, Heitor B. F. Fernandes, Mateo Peñaherrera-Aguirre, Michael A. Woodley of Menie, Aurelio José Figueredo (2020-05-01):


    • Evolutionary rates of G vs. neuroanatomical proxies are compared.
    • G exhibits greater evolutionary lability.
    • This suggests different selection regimes.
    • cerebellar volume residualised against body size is the best proxy.

    Abstract: Various neuroanatomical volume measures (NVMs) are frequently used as proxies for intelligence in comparative studies, such as the size of the brain, neocortex, and hippocampus, either absolute or controlled for other size measures (e.g., body size, or rest of the brain). Mean species NVMs are moderately correlated with aggregate general intelligence (G), however G and NVMs are yet to be compared in their evolutionary patterns (e.g., conservatism and evolutionary rates) and processes (i.e., their fit to diverse models of evolution reflecting selection regimes).

    Such evolutionary information is valuable for examining convergence in the evolutionary history among traits and is not available from simple correlation coefficients. Considering accumulating evidence that non-volumetric neurological measures may be as important as (or more so than) volumetric measures as substrates of intelligence, and that certain NVMs negatively predict neuronal density, we hypothesized that discrepancies would be found in evolutionary patterns and processes of G compared to NVMs.

    We collated data from the literature on primate species means for G, the volumes of the brain, neocortex, cerebellum, and hippocampus, and body mass, and employed phylogenetic comparative methods that examine phylogenetic signal (λ, K), evolutionary rates (σ2), and several parameters of evolutionary models (Brownian motion, Early-burst, acceleration, and Ornstein-Uhlenbeck).

    Evolutionary rates and acceleration trends were up to an order of magnitude higher for G than for most NVMs, and a strong selection optimum toward which clades evolved was found for G, whereas NVMs conformed mostly to Brownian motion. Brain size was the most contrasting NVM compared to intelligence across most phylogenetic indices examined, showing signs of deceleration and extreme conservativeness. Only certain operationalizations of neocortical and hippocampal volume showed convergence with G, albeit still notably weakly. The NVM with results that most strongly approached the patterns identified for G is residual cerebellar size (relative to body size).

    In comparison to the most commonly used volumetric measures (operationalization of brain and neocortex size), G must be seen as an evolutionarily labile trait under considerable selection pressure, necessitating that the role of the cerebellum be more aptly recognized and that other neurological factors be invoked as potential substrates for its evolutionary trajectory. [Keywords: general intelligence, phylogenetic comparative methods, cerebellum, brain size, neocortex]

  • 2020-flaim.pdf: ⁠, Mary Flaim, Aaron P. Blaisdell (2020-10-15):

    The study of intelligence in humans has been ongoing for over 100 years, including the underlying structure, predictive validity, related cognitive measures, and source of differences. One of the key findings in intelligence research is the uniform positive correlations among cognitive tasks. This has been replicated with every cognitive test battery in humans. Nevertheless, many other aspects of intelligence research have revealed contradictory lines of evidence. Recently, cognitive test batteries have been developed for animals to examine similarities to humans in cognitive structure. The results are inconsistent, but there is evidence for some similarities. This article reviews the way intelligence and related cognitive abilities are assessed in humans and animals and suggests a different way of devising test batteries for maximizing between-species comparisons.

  • 2020-freeman.pdf: ⁠, Jacob Freeman, Jacopo A. Baggio, Thomas R. Coyle (2020-03-24):

    On a planet experiencing global environmental change, the governance of natural resources depends on sustained collective action by diverse populations. Engaging in such collective action can only build upon the foundation of human cognition in social–ecological settings. To help understand this foundation, we assess the effect of cognitive abilities on the management of a common pool resource. We present evidence that two functionally distinct cognitive abilities, general and social intelligence, improve the ability of groups to manage a common pool resource. Groups high in both forms of intelligence engage in more effective collective action that is also more consistent, despite social or ecological change. This result provides a foundation for integrating the effects of cognitive abilities with other dimensions of cognitive diversity to explain when groups will and will not sustainably govern natural resources.

  • 2020-gignac.pdf: ⁠, Gilles E. Gignac, Marcin Zajenkowski (2020-04-01):


    • Conventional tests of the Dunning-Kruger hypothesis are shown to be confounded.
    • The Glejser test is argued to be a valid test of the Dunning-Kruger hypothesis.
    • Nonlinear regression is argued to be a valid test of the Dunning-Kruger hypothesis.
    • Failed to identify the Dunning-Kruger effect with IQ data and both valid tests.


    The Dunning-Kruger hypothesis states that the degree to which people can estimate their ability accurately depends, in part, upon possessing the ability in question. Consequently, people with lower levels of the ability tend to self-assess their ability less well than people who have relatively higher levels of the ability. The most common method used to test the Dunning-Kruger hypothesis involves plotting the self-assessed and objectively assessed means across four categories (quartiles) of objective ability. However, this method has been argued to be confounded by the better-than-average effect and regression toward the mean. In this investigation, it is argued that the Dunning-Kruger hypothesis can be tested validly with two inferential statistical techniques: the Glejser test of heteroscedasticity and nonlinear (quadratic) regression. On the basis of a sample of 929 general community participants who completed a self-assessment of intelligence and the Advanced Raven’s Progressive Matrices, we failed to identify statistically-significant heteroscedasticity, contrary to the Dunning-Kruger hypothesis. Additionally, the association between objectively measured intelligence and self-assessed intelligence was found to be essentially entirely linear, again, contrary to the Dunning-Kruger hypothesis. It is concluded that, although the phenomenon described by the Dunning-Kruger hypothesis may be to some degree plausible for some skills, the magnitude of the effect may be much smaller than reported previously. [Keywords: Dunning-Kruger effect, Intelligence, Self-assessed intelligence]

  • 2020-giofre.pdf: ⁠, D. Giofrè, C. Cornoldi, A. Martini, E. Toffalini (2020-07-01):


    • Gender differences in mathematics are largely explained by a regional gradient in Italy.
    • Gender differences in reading are not influenced by a regional gradient and are stable across Italy.
    • A number of factors, could influence the gender gap in mathematics.

    Abstract: Whether males outperform females in mathematics is still debated. Such a gender gap varies across countries, but the determinants of the differences are unclear and could be produced by heterogeneity in the instructional systems or cultures and may vary across school grades. To clarify this issue, we took advantage of the INVALSI dataset, that offered over 13 million observations covering one single instructional system (i.e., the Italian system) in grades 2, 5, and 8, in the period 2010–2018. Results showed that males outperformed females in mathematics (and vice versa in reading), with gaps widening from the 2nd through to the 8th grade. The gender gap in mathematics was larger in the richer northern Italian regions (also characterized by greater gender equality) than in southern regions. This was not explained by average performance or fully accounted for by economic factors. No such north-south difference of the gap emerged in reading. Results are discussed with reference to the literature showing that the gender gap varies across world regions. [Keywords: Gender differences, Mathematics, Reading, Achievement, Sociocultural factors]

  • 2020-grasby.pdf: ⁠, Katrina L. Grasby, Neda Jahanshad, Jodie N. Painter, Lucía Colodro-Conde, Janita Bralten, Derrek P. Hibar, Penelope A. Lind, Fabrizio Pizzagalli, Christopher R. K. Ching, Mary Agnes B. McMahon, Natalia Shatokhina, Leo C. P. Zsembik, Sophia I. Thomopoulos, Alyssa H. Zhu, Lachlan T. Strike, Ingrid Agartz, Saud Alhusaini, Marcio A. A. Almeida, Dag Alnæs, Inge K. Amlien, Micael Andersson, Tyler Ard, Nicola J. Armstrong, Allison Ashley-Koch, Joshua R. Atkins, Manon Bernard, Rachel M. Brouwer, Elizabeth E. L. Buimer, Robin Bülow, Christian Bürger, Dara M. Cannon, Mallar Chakravarty, Qiang Chen, Joshua W. Cheung, Baptiste Couvy-Duchesne, Anders M. Dale, Shareefa Dalvie, Tânia K. de Araujo, Greig I. de Zubicaray, Sonja M. C. de Zwarte, Anouk den Braber, Nhat Trung Doan, Katharina Dohm, Stefan Ehrlich, Hannah-Ruth Engelbrecht, Susanne Erk, Chun Chieh Fan, Iryna O. Fedko, Sonya F. Foley, Judith M. Ford, Masaki Fukunaga, Melanie E. Garrett, Tian Ge, Sudheer Giddaluru, Aaron L. Goldman, Melissa J. Green, Nynke A. Groenewold, Dominik Grotegerd, Tiril P. Gurholt, Boris A. Gutman, Narelle K. Hansell, Mathew A. Harris, Marc B. Harrison, Courtney C. Haswell, Michael Hauser, Stefan Herms, Dirk J. Heslenfeld, New Fei Ho, David Hoehn, Per Hoffmann, Laurena Holleran, Martine Hoogman, Jouke-Jan Hottenga, Masashi Ikeda, Deborah Janowitz, Iris E. Jansen, Tianye Jia, Christiane Jockwitz, Ryota Kanai, Sherif Karama, Dalia Kasperaviciute, Tobias Kaufmann, Sinead Kelly, Masataka Kikuchi, Marieke Klein, Michael Knapp, Annchen R. Knodt, Bernd Krämer, Max Lam, Thomas M. Lancaster, Phil H. Lee, Tristram A. Lett, Lindsay B. Lewis, Iscia Lopes-Cendes, Michelle Luciano, Fabio Macciardi, Andre F. Marquand, Samuel R. Mathias, Tracy R. Melzer, Yuri Milaneschi, Nazanin Mirza-Schreiber, Jose C. V. Moreira, Thomas W. Mühleisen, Bertram Müller-Myhsok, Pablo Najt, Soichiro Nakahara, Kwangsik Nho, Loes M. Olde Loohuis, Dimitri Papadopoulos Orfanos, John F. Pearson, Toni L. Pitcher, Benno Pütz, Yann Quidé, Anjanibhargavi Ragothaman, Faisal M. Rashid, William R. Reay, Ronny Redlich, Céline S. Reinbold, Jonathan Repple, Geneviève Richard, Brandalyn C. Riedel, Shannon L. Risacher, Cristiane S. Rocha, Nina Roth Mota, Lauren Salminen, Arvin Saremi, Andrew J. Saykin, Fenja Schlag, Lianne Schmaal, Peter R. Schofield, Rodrigo Secolin, Chin Yang Shapland, Li Shen, Jean Shin, Elena Shumskaya, Ida E. Sønderby, Emma Sprooten, Katherine E. Tansey, Alexander Teumer, Anbupalam Thalamuthu, Diana Tordesillas-Gutiérrez, Jessica A. Turner, Anne Uhlmann, Costanza Ludovica Vallerga, Dennis van der Meer, Marjolein M. J. van Donkelaar, Liza van Eijk, Theo G. M. van Erp, Neeltje E. M. van Haren, Daan van Rooij, Marie-José van Tol, Jan H. Veldink, Ellen Verhoef, Esther Walton, Mingyuan Wang, Yunpeng Wang, Joanna M. Wardlaw, Wei Wen, Lars T. Westlye, Christopher D. Whelan, Stephanie H. Witt, Katharina Wittfeld, Christiane Wolf, Thomas Wolfers, Jing Qin Wu, Clarissa L. Yasuda, Dario Zaremba, Zuo Zhang, Marcel P. Zwiers, Eric Artiges, Amelia A. Assareh, Rosa Ayesa-Arriola, Aysenil Belger, Christine L. Brandt, Gregory G. Brown, Sven Cichon, Joanne E. Curran, Gareth E. Davies, Franziska Degenhardt, Michelle F. Dennis, Bruno Dietsche, Srdjan Djurovic, Colin P. Doherty, Ryan Espiritu, Daniel Garijo, Yolanda Gil, Penny A. Gowland, Robert C. Green, Alexander N. Häusler, Walter Heindel, Beng-Choon Ho, Wolfgang U. Hoffmann, Florian Holsboer, Georg Homuth, Norbert Hosten, Clifford R. Jack Jr., MiHyun Jang, Andreas Jansen, Nathan A. Kimbrel, Knut Kolskår, Sanne Koops, Axel Krug, Kelvin O. Lim, Jurjen J. Luykx, Daniel H. Mathalon, Karen A. Mather, Venkata S. Mattay, Sarah Matthews, Jaqueline Mayoral Van Son, Sarah C. McEwen, Ingrid Melle, Derek W. Morris, Bryon A. Mueller, Matthias Nauck, Jan E. Nordvik, Markus M. Nöthen, Daniel S. O’Leary, Nils Opel, Marie-Laure Paillère Martinot, G. Bruce Pike, Adrian Preda, Erin B. Quinlan, Paul E. Rasser, Varun Ratnakar, Simone Reppermund, Vidar M. Steen, Paul A. Tooney, Fábio R. Torres, Dick J. Veltman, James T. Voyvodic, Robert Whelan, Tonya White, Hidenaga Yamamori, Hieab H. H. Adams, Joshua C. Bis, Stephanie Debette, Charles Decarli, Myriam Fornage, Vilmundur Gudnason, Edith Hofer, M. Arfan Ikram, Lenore Launer, W. T. Longstreth, Oscar L. Lopez, Bernard Mazoyer, Thomas H. Mosley, Gennady V. Roshchupkin, Claudia L. Satizabal, Reinhold Schmidt, Sudha Seshadri, Qiong Yang, Alzheimer’s Disease Neuroimaging Initiative, CHARGE Consortium, EPIGEN Consortium, IMAGEN Consortium, SYS Consortium, Parkinson’s Progression Markers Initiative, Marina K. M. Alvim, David Ames, Tim J. Anderson, Ole A. Andreassen, Alejandro Arias-Vasquez, Mark E. Bastin, Bernhard T. Baune, Jean C. Beckham, John Blangero, Dorret I. Boomsma, Henry Brodaty, Han G. Brunner, Randy L. Buckner, Jan K. Buitelaar, Juan R. Bustillo, Wiepke Cahn, Murray J. Cairns, Vince Calhoun, Vaughan J. Carr, Xavier Caseras, Svenja Caspers, Gianpiero L. Cavalleri, Fernando Cendes, Aiden Corvin, Benedicto Crespo-Facorro, John C. Dalrymple-Alford, Udo Dannlowski, Eco J. C. de Geus, Ian J. Deary, Norman Delanty, Chantal Depondt, Sylvane Desrivières, Gary Donohoe, Thomas Espeseth, Guillén Fernández, Simon E. Fisher, Herta Flor, Andreas J. Forstner, Clyde Francks, Barbara Franke, David C. Glahn, Randy L. Gollub, Hans J. Grabe, Oliver Gruber, Asta K. Håberg, Ahmad R. Hariri, Catharina A. Hartman, Ryota Hashimoto, Andreas Heinz, Frans A. Henskens, Manon H. J. Hillegers, Pieter J. Hoekstra, Avram J. Holmes, L. Elliot Hong, William D. Hopkins, Hilleke E. Hulshoff Pol, Terry L. Jernigan, Erik G. Jönsson, René S. Kahn, Martin A. Kennedy, Tilo T. J. Kircher, Peter Kochunov, John B. J. Kwok, Stephanie Le Hellard, Carmel M. Loughland, Nicholas G. Martin, Jean-Luc Martinot, Colm McDonald, Katie L. McMahon, Andreas Meyer-Lindenberg, Patricia T. Michie, Rajendra A. Morey, Bryan Mowry, Lars Nyberg, Jaap Oosterlaan, Roel A. Ophoff, Christos Pantelis, Tomas Paus, Zdenka Pausova, Brenda W. J. H. Penninx, Tinca J. C. Polderman, Danielle Posthuma, Marcella Rietschel, Joshua L. Roffman, Laura M. Rowland, Perminder S. Sachdev, Philipp G. Sämann, Ulrich Schall, Gunter Schumann, Rodney J. Scott, Kang Sim, Sanjay M. Sisodiya, Jordan W. Smoller, Iris E. Sommer, Beate St Pourcain, Dan J. Stein, Arthur W. Toga, Julian N. Trollor, Nic J. A. Van der Wee, Dennis van ’t Ent, Henry Völzke, Henrik Walter, Bernd Weber, Daniel R. Weinberger, Margaret J. Wright, Juan Zhou, Jason L. Stein, Paul M. Thompson, Sarah E. Medland, Enhancing NeuroImaging Genetics through Meta-Analysis Consortium (ENIGMA)—Genetics working group (2020-03-20; backlinks):

    The human cerebral cortex is important for cognition, and it is of interest to see how genetic variants affect its structure. Grasby et al. combined genetic data with brain magnetic resonance imaging from more than 50,000 people to generate a genome-wide analysis of how human genetic variation influences human cortical surface area and thickness. From this analysis, they identified variants associated with cortical structure, some of which affect signaling and gene expression. They observed overlap between genetic loci affecting cortical structure, brain development, and neuropsychiatric disease, and the correlation between these phenotypes is of interest for further study.

    Introduction: The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure.

    Rationale: To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations.

    Results: We identified 306 nominally genome-wide statistically-significant loci (p < 5 × 10−8) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained statistically-significant after replication, with 199 loci passing multiple testing correction (p < 8.3 × 10−10; 187 influencing surface area and 12 influencing thickness).

    Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation (rg = −0.32, SE = 0.05, p = 6.5 × 10−12), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness.

    To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 10 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity.

    We observed statistically-significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism.

    Conclusion: This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function.

  • 2020-gronqvist.pdf: ⁠, Hans Grönqvist, J. Peter Nilsson, and Per-Olof Robling (2020-07-01):

    We study the impact of lead exposure from birth to adulthood and provide evidence on the mechanisms producing these effects. Following 800,000 children differentially exposed to the phaseout of leaded gasoline in Sweden, we find that even a low exposure affects long-run outcomes, that boys are more affected, and that changes in noncognitive skills explain a sizeable share of the impact on crime and human capital. The effects are greater above exposure thresholds still relevant for the general population, and reductions in exposure equivalent to the magnitude of the recent redefinition of elevated blood lead levels can increase earnings by 4%.

  • 2020-horne.pdf: ⁠, Kristina S. Horne, Hannah L. Filmer, Zoie E. Nott, Ziarih Hawi, Kealan Pugsley, Jason B. Mattingley, Paul E. Dux (2020-10-26):

    Cognitive training and brain stimulation show promise for ameliorating age-related neurocognitive decline. However, evidence for this is controversial. In a Registered Report, we investigated the effects of these interventions, where 133 older adults were allocated to four groups (left prefrontal cortex anodal transcranial direct current stimulation (tDCS) with decision-making training, and three control groups) and trained over 5 days. They completed a task/questionnaire battery pre-training and post-training, and at 1- and 3-month follow-ups. COMT and BDNF Val/Met polymorphisms were also assessed. Contrary to work in younger adults, there was evidence against tDCS-induced training enhancement on the decision-making task. Moreover, there was evidence against transfer of training gains to untrained tasks or everyday function measures at any post-intervention time points. As indicated by exploratory work, individual differences may have influenced outcomes. But, overall, the current decision-making training and tDCS protocol appears unlikely to lead to benefits for older adults.

  • 2020-lerche.pdf: ⁠, Veronika Lerche, Mischa von Krause, Andreas Voss, Gidon T. Frischkorn, Anna-Lena Schubert, Dirk Hagemann (2020-05-07):

    Several previous studies reported relationships between speed of information processing as measured with the drift parameter of the diffusion model (Ratcliff, 1978) and general intelligence. Most of these studies utilized only few tasks and none of them used more complex tasks. In contrast, our study (n = 125) was based on a large battery of 18 different response time tasks that varied both in content (numeric, figural, and verbal) and complexity (fast tasks with mean RTs of ca. 600 ms vs. more complex tasks with mean RTs of ca. 3,000 ms). Structural equation models indicated a strong relationship between a domain-general drift factor and general intelligence. Beyond that, domain-specific speed of information processing factors were closely related to the respective domain scores of the intelligence test. Furthermore, speed of information processing in the more complex tasks explained additional variance in general intelligence. In addition to these theoretically relevant findings, our study also makes methodological contributions showing that there are meaningful interindividual differences in content specific drift rates and that not only fast tasks, but also more complex tasks can be modeled with the diffusion model.

  • 2020-lin.pdf: “The social and genetic inheritance of educational attainment: Genes, parental education, and educational expansion”⁠, Meng-Jung Lin (backlinks)

  • 2020-marks.pdf: ⁠, Gary N. Marks (2020-10-13):

    The literature on the relationship between socioeconomic background (SES) and university education is inconsistent. Some studies conclude SES is important to university entry and course completion, others find trivial SES effects, net of students’ prior performance, and a third group concludes that SES effects are important and policy relevant even when considering prior performance. Parallel arguments apply to demographic, school sector, and institutional differences in the university career, that is, are they unimportant when considering student performance? Using comprehensive and accurate measures of SES and student performance, and a statistical method that utilizes all non-missing data, this study quantifies the effects of socioeconomic, demographic, and institutional factors and prior student performance. SES has only weak effects on university entry and attrition, and no effects on course completion. Student performance has strong effects on entry and has moderate effects on attrition and completion. Demographic other differences mostly disappear when controlling for student performance. [Keywords: PISA test scores, tertiary entrance performance (ATAR), university participation, university course attrition, university course completion]

  • 2020-marr.pdf: ⁠, M. Jackson Marr (2020-06-11):

    There are no undebated definitions of “creativity,” and any definition will reflect how this rich topic is treated. Nearly 20 years ago I discussed how behavior analysis might contribute—or not—to an understanding of creativity. I revisit this topic, expanding on some issues and reconsidering others. As before, my focus is on scientific and mathematical accomplishments, which, though tied closely to Weisberg’s placement of creative achievements in the domains of problem posing and problem solving, places emphasis on the extraordinary and productive giftedness of certain individuals. From the massive empirical, theoretical, and historical literature at least three essential and dynamically interlocking dimensions of their creative achievements emerge: talent, expertise, and motivation. I emphasize “interlocking” because the productive expression of each of these elements depends on the others. The role of behavior analysis in these elements is modest at best. It has nothing to say about talent—and even in some cases might deny its role altogether. As for expertise, with some notable exceptions, behavior analysis has had little to say about the acquisition of truly complex performances; this has been left to other fields. As for motivation, one must go well beyond naïve “pleasure and pain” accounts to more elusive, yet more powerful behavior-consequence relations. Many challenges to understanding remain for all behavioral scientists.

  • 2020-mcgue.pdf: ⁠, Matt McGue, Emily A. Willoughby, Aldo Rustichini, Wendy Johnson, William G. Iacono, James J. Lee (2020-06-30; backlinks):

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

  • 2020-nikolasevic.pdf: ⁠, Željka Nikolašević, Snežana Smederevac, Vojislava Bugarski Ignjatović, Jasmina Kodžopeljić, Ilija Milovanović, Mechthild Prinz, Zoran Budimlija (2020-09-01):

    • Executive functions cannot be reduced to intellectual abilities.
    • Certain part of the genetic variance is common to these 2 phenomena.
    • Some aspects of executive control have higher heritability than others.
    • Executive functions include a series of specific abilities, with specific genetic foundations.

    The first aim of this study was to explore the aetiology of phenotypic relationships between different measures of executive functions. The second objective was to examine sources of the covariation between different measures of executive functions and the measure of general cognitive ability.

    The study sample consisted of 468 twins (154 pairs of monozygotic twins and 80 pairs of dizygotic twins) of the same and different gender who grew up together. Executive functions were evaluated by the Wisconsin Card Sorting Test, the Trail Making Test—form B, and verbal fluency tests. Raven’s Advanced Progressive Matrices were used as a measure of general cognitive ability.

    The study results suggest a primarily genetic origin of the mutual covariation of different executive measures and their covariation with the general cognitive ability construct. While the shared genetic variance primarily lies in the bases of similarity/unity of the used cognitive measures, their particularity/difference is determined by a specific unshared environment.

    The obtained result on the presence of a single general genetic factor, which can be singled out in the case of different executive measures, at least partially speaks in favor of the thesis about the unity of various executive measures and the existence of a common basic ability. Together with the specific unshared environment, the specific genetic influence speaks in favor of a difference between each of the individual measures. [Keywords: behavioral genetics, cognitive abilities, executive functions, general cognitive ability]

  • 2020-sanchez-ucstandardizedtestingtaskforcefinalreport.pdf: “Report of the UC Academic Council Standardized Testing Task Force (STTF)”⁠, Standardized Testing Task Force (Henry Sánchez, Eva Baker, Julian Betts, Li Cai, Eddie Comeaux, Darlene Francis, Patricia Gandara, Jonathan Glater, James Griesemer, Andrea Hasenstaub, George Johnson, Mona Lynch, Andrew Maul, Yolanda Moses, Wendy Rummerfield, Kit Tellez, Haim Weizman, Anne Zanzucchi)

  • 2020-schubert.pdf: ⁠, Anna-Lena Schubert, Dirk Hagemann, Christoph Löffler, Jan Rummel, Stefan Arnau (2020-06-25):

    Individual differences in cognitive control have been suggested to act as a domain-general bottleneck constraining performance in a variety of cognitive ability measures, including but not limited to fluid intelligence, working memory capacity, and processing speed. However, owing to psychometric problems associated with the measurement of individual differences in cognitive control, it has been challenging to empirically test the assumption that individual differences in cognitive control underlie individual differences in cognitive abilities. In the present study, we addressed these issues by analyzing the chronometry of intelligence-related differences in midfrontal global theta connectivity, which has been shown to reflect cognitive control functions. We demonstrate in a sample of 98 adults, who completed a cognitive control task while their electroencephalogram was recorded, that individual differences in midfrontal global theta connectivity during stages of higher-order information-processing explained 65% of the variance in fluid intelligence. In comparison, task-evoked theta connectivity during earlier stages of information processing was not related to fluid intelligence. These results suggest that more intelligent individuals benefit from an adaptive modulation of theta-band synchronization during the time-course of information processing. Moreover, they emphasize the role of interregional goal-directed information-processing for cognitive control processes in human intelligence and support theoretical accounts of intelligence, which propose that individual differences in cognitive control processes give rise to individual differences in cognitive abilities.

  • 2020-shaffer.pdf: ⁠, Jonathan A. Shaffer (2020-06; backlinks):

    This study examined a model in which conscientiousness is related to net worth through its relationship with future planning, and in which general mental ability (GMA) moderates the effects of future planning on net worth. Data for this study were drawn from 1,135 participants in the National Survey of Midlife Development in the United States. Results from an analysis of conditional indirect effects suggest that conscientiousness shared a positive, indirect association with net worth through its relationship with future planning that was realized only for individuals higher in GMA. In contrast, conscientiousness had no indirect association with net worth for those low in GMA. This study helps add to the understanding of how noncognitive (personality) and cognitive (ability) traits affect individual-level economic outcomes and offers an explanation for both how and when conscientiousness influences net worth. These findings may be particularly important given efforts to design interventions that help improve individual financial outcomes.

  • 2020-simonton.pdf: ⁠, Dean Keith Simonton (2020-05-22):

    With just one exception, all of the volumes in Terman’s Genetic Studies of Genius report the results of a longitudinal study of more than a thousand intellectually gifted children. That single exception is Volume II, Cox’s single-authored The Early Mental Traits of Three Hundred Geniuses, which instead was a retrospective study of 301 eminent creators and leaders, using historiometric methods to estimate their IQs (as well as to assess a subset of 100 on 67 character traits). This article discusses how this volume actually fits with the other four volumes in the set. After giving the historical background, discussion turns to the emergence of Cox’s doctoral dissertation. Then comes a narrative of the aftermath, including subsequent contributions by Cox, Terman, and numerous other researchers extending into the 21st century. The article closes by treating the ways that the intellectually gifted and the historic geniuses are not comparable, thus indicating the need for more recent replications and extensions of her work. [Keywords: archival, biographical, historical analysis, early childhood, gifted, intelligence]

  • 2020-stoet.pdf: ⁠, Gijsbert Stoet, David C. Geary (2020-07-01):


    • Student sex can often be predicted based on a set of achievement and attitude data.
    • Student sex can often be predicted based on classification models from other countries.
    • Universal patterns in academic sex differences are larger than hitherto thought.
    • Academic sex differences are stronger in societies with more socioeconomic equality.

    Abstract: The extent of sex differences in psychological traits is vigorously debated. We show that the overall sex difference in the pattern of adolescents’ achievement and academic attitudes is relatively large and similar across countries. We used a binomial regression modeling approach to predict the sex of 15 and 16 year olds based on sets of academic ability and attitude variables in three cycles of the Programme for International Student Assessment (PISA) data (n = 969,673 across 55 to 71 countries and regions). We found that the sex of students in any country can be reliably predicted based on regression models created from the data of all other countries, indicating a common (universal) sex-specific component. Averaged over three different PISA cycles (2009, 2012, 2015), the sex of 69% of students can be correctly classified using this approach, corresponding to a large effect. Moreover, the universal component of these sex differences is stronger in countries with relative income equality and women’s participation in the labor force and politics. We conclude that patterns in academic sex differences are larger than hitherto thought and appear to become stronger when societies have more socioeconomic equality. We explore reasons why this may be the case and possible implications.

  • 2020-unsworth.pdf: ⁠, Nash Unsworth, Ashley L. Miller, Matthew K. Robison (2020-10-01):

    The relation between working memory capacity (WMC) and baseline pupil diameter was examined. Participants (n = 341) performed several WMC tasks and baseline pupil diameter was measured in a dark room with a black background screen. The results indicated a weak and non-significant correlation between WMC and baseline pupil diameter consistent with some prior research. A meta-analysis of available studies (k = 26; n = 4356) similarly indicated a weak and non-significant correlation between WMC and baseline pupil diameter. Moderator analyses indicated that the primary moderator responsible for heterogeneity across studies was where the study was conducted. Studies from one laboratory tend to demonstrate a statistically-significant positive correlation, whereas other laboratories have yet to demonstrate the correlation. Broadly, the results suggest that the correlation between WMC and baseline pupil diameter is weak and not particularly robust.

  • 2020-warne.pdf: ⁠, Russell T. Warne, Jared Z. Burton (2020-03-24; backlinks):

    Research in educational psychology consistently finds a relationship between intelligence and academic performance. However, in recent decades, educational fields, including gifted education, have resisted intelligence research, and there are some experts who argue that intelligence tests should not be used in identifying giftedness. Hoping to better understand this resistance to intelligence research, we created a survey of beliefs about intelligence and administered it online to a sample of the general public and a sample of teachers. We found that there are conflicts between currently accepted intelligence theory and beliefs from the American public and teachers, which has important consequences on gifted education, educational policy, and the effectiveness of interventions.

  • 2020-zigerell.pdf: ⁠, LJ Zigerell (2020-05-27):

    Intelligence quotient (IQ) is a common measure of intelligence that associates with many important life outcomes. Research over several decades has indicated that the average IQ test score among Black Americans is lower than the average IQ test score among White Americans, but in weighted results from a national nonprobability survey, only about 41% of US adults indicated awareness of this IQ gap. Results from a follow-up convenience survey indicated that, in the aggregate, White participants’ rating of White Americans’ average IQ and average intelligence is higher than Blacks Americans’ average IQ test score and average intelligence and was not driven by White participants’ belief in a universal White intellectual superiority. These and other results could have implications regarding the US public’s perceptions about the reasons for Black/White inequality and implications for the use of intelligence stereotype scales as measures of racial prejudice. [Keywords: intelligence quotient, IQ, intelligence, stereotypes, race, perceptions, inequality]

  • 2020-zissman.pdf: ⁠, Chen Zissman, Yoav Ganzach (2020-07-14):

    We compare the relative contribution of grit and intelligence to educational and job-market success in a representative sample of the American population. We find that, in terms of Δ R 2, intelligence contributes 48–90 times more than grit to educational success and 13 times more to job-market success. Conscientiousness also contributes to success more than grit but only twice as much. We show that the reason our results differ from those of previous studies which showed that grit has a stronger effect on success is that these previous studies used nonrepresentative samples that were range restricted on intelligence. Our findings suggest that although grit has some effect on success, it is negligible compared to intelligence and perhaps also to other traditional predictors of success.

  • 2021-aggeborn.pdf: ⁠, Linuz Aggeborn, Mattias Öhman (2021-01-13; backlinks):

    Water fluoridation is a common but debated public policy. In this paper, we use Swedish registry data to study the causal effects of fluoride in drinking water. We exploit exogenous variation in natural fluoride stemming from variation in geological characteristics at water sources to identify its effects. First, we reconfirm the long-established positive effect of fluoride on dental health. Second, we estimate a zero effect on cognitive ability in contrast to several recent debated epidemiological studies. Third, fluoride is furthermore found to increase labor income. This effect is foremost driven by individuals from a lower socioeconomic background.

    …Let us continue to our main results. We begin with cognitive ability for men born between 1985 and 1987. Our conclusion from Table 4 is that fluoride does not affect cognitive ability. Column 1 displays the unconditional treatment effect. In columns 2 and 3, we add fixed effects for cohort and municipality of birth. We then include parental covariates, which results in a reduced sample since we have data on fathers’ cognitive ability only from 1969 and onward. To make the samples comparable with and without these covariates, we run column 4 for the same sample as in column 5. We also run two subsample analyses: in column 6, we run the analysis for those who have lived in the same SAMS in a municipality for the entire period from age 0 to 18, and in column 7 we restrict the sample to those who have moved only within a municipality.

    Table 4: cognitive ability

    Looking at the estimates, they are very small and often not statistically-significantly different from zero. Sometimes the estimates are negative and sometimes positive, but they are always close to zero. If we take the largest negative point estimates (−0.0047, col. 1) and the largest standard error for that specification (0.0045), the 95% confidence interval would be −0.014 to 0.004. We may thus rule out negative effects larger than 0.14 standard deviations in cognitive ability if fluoride is increased by 1 milligram/liter (the level often considered when artificially fluoridating the water).

    …We now continue with the long-term outcome of annual labor income in 2014 for individuals born between 1985 and 1992. Given our results for cognitive ability, we do not expect negative effects of fluoride. However, positive effects are possible given the results found for dental health.

    The results are presented in Table 5. The point estimates are often statistically-significant, and the coefficients are always positive. Taking column 6 as an example, where all covariates and fixed effects are included, we find that the point estimate equals 0.0044, meaning that income increases by 4.4% if fluoride is increased by 1 milligram/liter. These reduced form estimates may be compared with ⁠, who, by using American data, found that women who drink fluoridated water have on average 4% higher earnings. Our estimated effect on income may also be compared with estimated education premiums. The return of one additional year of education yields an increase in income by 6%–10%, according to the instrumental variable estimates in the review in Card (1999). An increase in fluoride by 1 milligram/liter would thus yield a similar increase as roughly half a year of additional education. Nonlinear specifications are presented in figure A1 and tables A8–A10, which overall supports the findings presented here. In section B5 in the appendix, we present the result for employment status (another margin for labor market status), and we find that fluoride has a positive effect.

    Table 5: Log Annual Labor Income
  • 2021-brown.pdf: ⁠, Matt I. Brown, Jonathan Wai, Christopher F. Chabris (2021-03-08; backlinks):

    Despite a long-standing expert consensus about the importance of cognitive ability for life outcomes, contrary views continue to proliferate in scholarly and popular literature. This divergence of beliefs presents an obstacle for evidence-based policymaking and decision-making in a variety of settings. One commonly held idea is that greater cognitive ability does not matter or is actually harmful beyond a certain point (sometimes stated as > 100 or 120 IQ points). We empirically tested these notions using data from four longitudinal, representative cohort studies comprising 48,558 participants in the United States and United Kingdom from 1957 to the present. We found that ability measured in youth has a positive association with most occupational, educational, health, and social outcomes later in life. Most effects were characterized by a moderate to strong linear trend or a practically null effect (mean R2 range = 0.002–.256). Nearly all nonlinear effects were practically insignificant in magnitude (mean incremental R2 = 0.001) or were not replicated across cohorts or survey waves. We found no support for any downside to higher ability and no evidence for a threshold beyond which greater scores cease to be beneficial. Thus, greater cognitive ability is generally advantageous—and virtually never detrimental.

  • 2021-elder.pdf: ⁠, Todd Elder, Yuqing Zhou (2021-01):

    Using two nationally representative datasets, we find large differences between Black and White children in teacher-reported measures of noncognitive skills. We show that teacher reports understate true Black-White skill gaps because of reference bias: teachers appear to rate children relative to others in the same school, and Black students have lower-skilled classmates on average than do White students. We pursue three approaches to addressing these reference biases. Each approach nearly doubles the estimated Black-White gaps in noncognitive skills, to roughly 0.9 standard deviations in third grade.

  • 2021-peters.pdf: ⁠, Heinrich Peters, Andrew Kyngdon, David Stillwell (2021-06-01):

    • We introduce the first game-based intelligence assessment in ⁠.
    • Three intelligence tasks were implemented in the interactive game environment.
    • Two of the three tasks exhibit satisfactory psychometric properties.
    • Process data from game-logs encodes information about ability levels.
    • Minecraft is a promising platform for game-based assessment research.

    Video games are a promising tool for the psychometric assessment of cognitive abilities. They can present novel task types and answer formats, they can record process data, and they can be highly motivating for test takers. This paper introduces the first game-based intelligence assessment implemented in Minecraft, an exceptionally popular video game with more than 200m copies sold.

    A matrix-based pattern completion task (PC), a mental rotation task (MR) and a spatial construction task (SC) were implemented in the three-dimensional, immersive environment of the game. PC was intended as a measure of inductive reasoning, whereas MR and SC were measures of spatial ability. We tested 129 children aged 10–12 years old on the Minecraft-based tests as well as equivalent pen-and-paper tests. All three scales fit the Rasch model and were moderately reliable. Factorial validity was good with regard to the distinction between PC and SC, but no distinct factor was found for MR. Convergent validity was good as abilities measured with Minecraft and conventional tests were highly correlated at the latent level (r = 0.72). Subtest-level correlations were in the moderate range. Furthermore, we found that behavioral log-data collected from the game environment was highly predictive of performance in the Minecraft test and, to a lesser extent, also predicted scores in conventional tests. We identify a number of behavioral features associated with spatial reasoning ability, demonstrating the utility of analyzing granular behavioral data in addition to traditional response formats.

    Overall, our findings indicate that Minecraft is a suitable platform for game-based intelligence assessment and encourage future work aiming to explore game-based problem solving tasks that would not be feasible on paper or in conventional computer-based tests.

    [Keywords: Game-based assessment Intelligence assessment, Minecraft, ⁠, process data, game log-data]

  • 2021-santarnecchi.pdf: ⁠, Emiliano Santarnecchi, Davide Momi, Lucia Mencarelli, Franziska Plessow, Sadhvi Saxena, Simone Rossi, Alessandro Rossi, Santosh Mathan, Alvaro Pascual-Leone (2021-04-26):

    Cognitive enhancement interventions aimed at boosting human fluid intelligence (gf) have targeted executive functions (EFs), such as updating, inhibition, and switching, in the context of transfer-inducing cognitive training. However, even though the link between EFs and gf has been demonstrated at the psychometric level, their neurofunctional overlap has not been quantitatively investigated. Identifying whether and how EFs and gf might share neural activation patterns could provide important insights into the overall hierarchical organization of human higher-order cognition, as well as suggest specific targets for interventions aimed at maximizing cognitive transfer.

    We present the results of a quantitative meta-analysis of the available fMRI and PET literature on EFs and gf in humans, showing the similarity between gf and (1) the overall global EF network, as well as (2) specific maps for updating, switching, and inhibition. Results highlight a higher degree of similarity between gf and updating (80% overlap) compared with gf and inhibition (34%), and gf and switching (17%). Moreover, 3 brain regions activated for both gf and each of the 3 EFs also were identified, located in the left middle frontal gyrus, left inferior parietal lobule, and anterior cingulate cortex. Finally, resting-state functional connectivity analysis on 2 independent fMRI datasets showed the preferential behavioural correlation and anatomical overlap between updating and gf.

    These findings confirm a close link between gf and EFs, with implications for brain stimulation and cognitive training interventions. [Keywords: executive functions, fluid intelligence, fMRI, functional connectivity, cognitive enhancement]

  • 2021-tsukahara.pdf: ⁠, Jason S. Tsukahara (2021-06-01; backlinks):

    There has been some controversy as to whether baseline pupil size is related to individual differences in cognitive ability. Previously, we had shown that a larger baseline pupil size was associated with higher cognitive ability and that the correlation to fluid intelligence was larger than that to working memory capacity (). However, other researchers have not been able to replicate our findings—though they only measured working memory capacity and not fluid intelligence. Many of the studies showing no relationship had major methodological issues, namely small baseline pupil size values—down to the physiological minimum—that resulted in reduced variability on baseline pupil size.

    We conducted 2 large-scale studies to investigate how different lighting conditions affect baseline pupil size values and the correlation with cognitive abilities. We found that fluid intelligence, working memory capacity, and attention control did correlate with baseline pupil size except in the brightest lighting conditions. We showed that a reduced variability in baseline pupil size values is due to the monitor settings being too bright. Overall, our findings demonstrated that the baseline pupil size-working memory capacity relationship was not as strong or robust as that with fluid intelligence or attention control.

    Our findings have strong methodological implications for researchers investigating individual differences in task-free or task-evoked pupil size. We conclude that fluid intelligence does correlate with baseline pupil size and that this is related to the functional organization of the resting-state brain through the locus coeruleus-norepinephrine system. [Keywords: fluid intelligence, working memory capacity, pupil size, luminance]

    …Our pupils respond to more than just the light. They indicate arousal, interest or mental exhaustion. Pupil dilation is even used by the FBI to detect deception. Now work conducted in our laboratory at the Georgia Institute of Technology suggests that baseline pupil size is closely related to individual differences in intelligence. The larger the pupils, the higher the intelligence, as measured by tests of reasoning, attention and memory. In fact, across 3 studies, we found that the difference in baseline pupil size between people who scored the highest on the cognitive tests and those who scored the lowest was large enough to be detected by the unaided eye.

    …We found that a larger baseline pupil size was correlated with greater fluid intelligence, attention control and, to a lesser degree, working memory capacity—indicating a fascinating relationship between the brain and eye. Interestingly, pupil size was negatively correlated with age: older participants tended to have smaller, more constricted, pupils. Once standardized for age, however, the relationship between pupil size and cognitive ability remained.

    But why does pupil size correlate with intelligence? To answer this question, we need to understand what is going on in the brain. Pupil size is related to activity in the , a nucleus situated in the upper brain stem with far-reaching neural connections to the rest of the brain. The locus coeruleus releases norepinephrine, which functions as both a neurotransmitter and hormone in the brain and body, and it regulates processes such as perception, attention, learning and memory. It also helps maintain a healthy organization of brain activity so that distant brain regions can work together to accomplish challenging tasks and goals. Dysfunction of the locus coeruleus, and the resulting breakdown of organized brain activity, has been related to several conditions, including Alzheimer’s disease and attention deficit hyperactivity disorder. In fact, this organization of activity is so important that the brain devotes most of its energy to maintain it, even when we are not doing anything at all—such as when we stare at a blank computer screen for minutes on end.

    One hypothesis is that people who have larger pupils at rest have greater regulation of activity by the locus coeruleus, which benefits cognitive performance and resting-state brain function. Additional research is needed to explore this possibility and determine why larger pupils are associated with higher fluid intelligence and attention control. But it’s clear that there is more happening than meets the eye.

  • 2021-velthorst.pdf: ⁠, Eva Velthorst, Josephine Mollon, Robin M. Murray, Lieuwe Haan, Inez Myin Germeys, David C. Glahn, Celso Arango, Els Ven, Marta Forti, Miguel Bernardo, Sinan Guloksuz, Philippe Delespaul, Gisela Mezquida, Silvia Amoretti, Julio Bobes, Pilar A. Saiz, María Paz García-Portilla, José Luis Santos, Estela Jiménez-López, Julio Sanjuan, Eduardo J. Aguilar, Manuel Arrojo, Angel Carracedo, Gonzalo López, Javier González-Peñas, Mara Parellada, Cem Atbaşoğlu, Meram Can Saka, Alp Üçok, Köksal Alptekin, Berna Akdede, Tolga Binbay, Vesile Altınyazar, Halis Ulaş, Berna Yalınçetin, Güvem Gümüş-Akay, Burçin Cihan Beyaz, Haldun Soygür, Eylem Şahin Cankurtaran, Semra Ulusoy Kaymak, Nadja P. Maric, Marina M. Mihaljevic, Sanja Andric Petrovic, Tijana Mirjanic, Cristina Marta Del-Ben, Laura Ferraro, Charlotte Gayer-Anderson, Peter B. Jones, Hannah E. Jongsma, James B. Kirkbride, Caterina Cascia, Antonio Lasalvia, Sarah Tosato, Pierre-Michel Llorca, Paulo Rossi Menezes, Craig Morgan, Diego Quattrone, Marco Menchetti, Jean-Paul Selten, Andrei Szöke, Ilaria Tarricone, Andrea Tortelli, Philip McGuire, Lucia Valmaggia, Matthew J. Kempton, Mark Gaag, Anita Riecher-Rössler, Rodrigo A. Bressan, Neus Barrantes-Vidal, Barnaby Nelson, Patrick McGorry, Chris Pantelis, Marie-Odile Krebs, Stephan Ruhrmann, Gabriele Sachs, Bart P. F. Rutten, Jim Os, Behrooz Z. Alizadeh, Therese Amelsvoort, Agna A. Bartels-Velthuis, Richard Bruggeman, Nico J. Beveren, Jurjen J. Luykx, Wiepke Cahn, Claudia J. P. Simons, Rene S. Kahn, Frederike Schirmbeck, Ruud Winkel, Maria Calem, Stefania Tognin, Gemma Modinos, Sara Pisani, Tamar C. Kraan, Daniella S. van Dam, Nadine Burger, G. Paul Amminger, Athena Politis, Joanne Goodall, Stefan Borgwardt, Erich Studerus, Ary Gadelha, Elisa Brietzke, Graccielle Asevedo, Elson Asevedo, Andre Zugman, Tecelli Domínguez-Martínez, Manel Monsonet, Paula Cristóbal-Narváez, Anna Racioppi, Thomas R. Kwapil, Mathilde Kazes, Claire Daban, Julie Bourgin, Olivier Gay, Célia Mam-Lam-Fook, Dorte Nordholm, Lasse Rander, Kristine Krakauer, Louise Birkedal Glenthøj, Birte Glenthøj, Dominika Gebhard, Julia Arnhold, Joachim Klosterkötter, Iris Lasser, Bernadette Winklbaur, Abraham Reichenberg (2021-01-07):

    Important questions remain about the profile of cognitive impairment in psychotic disorders across adulthood and illness stages. The age-associated profile of familial impairments also remains unclear, as well as the effect of factors, such as symptoms, functioning, and medication. Using cross-sectional data from the EU-GEI and GROUP studies, comprising 8455 participants aged 18 to 65, we examined cognitive functioning across adulthood in patients with psychotic disorders (n = 2883), and their unaffected siblings (n = 2271), compared to controls (n = 3301). An abbreviated WAIS-III measured verbal knowledge, working memory, visuospatial processing, processing speed, and IQ. Patients showed medium to large deficits across all functions (ES range = −0.45 to −0.73, p < 0.001), while siblings showed small deficits on IQ, verbal knowledge, and working memory (ES = −0.14 to −0.33, p < 0.001). Magnitude of impairment was not associated with participant age, such that the size of impairment in older and younger patients did not statistically-significantly differ. However, first-episode patients performed worse than prodromal patients (ES range = −0.88 to −0.60, p < 0.001). Adjusting for cannabis use, symptom severity, and global functioning attenuated impairments in siblings, while deficits in patients remained statistically-significant, albeit reduced by half (ES range = −0.13 to −0.38, p < 0.01). Antipsychotic medication also accounted for around half of the impairment in patients (ES range = −0.21 to −0.43, p < 0.01). Deficits in verbal knowledge, and working memory may specifically index familial, i.e., shared genetic and/or shared environmental, liability for psychotic disorders. Nevertheless, potentially modifiable illness-related factors account for a substantial portion of the cognitive impairment in psychotic disorders.

  • 2021-vonstumm.pdf: ⁠, Sophie von Stumm, Robert Plomin (2021-03-19; backlinks):

    • In 10 years, the ability to predict intelligence from DNA has gone from 0% to 10%.
    • Genome-wide polygenic scores (GPS) are transforming research on intelligence.
    • GPS will transport intelligence to many new areas of science.
    • The availability of GPS at birth, prenatally, and before conception will impact society.
    • We need to maximize benefits and minimize risks of DNA prediction of intelligence.

    The DNA revolution made it possible to use DNA to predict intelligence. We argue that this advance will transform intelligence research and society.

    Our paper has 3 objectives:

    1. First, we review how the DNA revolution has transformed the ability to predict individual differences in intelligence. Thousands of DNA variants have been identified that—aggregated into genome-wide polygenic scores (GPS)—account for more than of the variance in phenotypic intelligence. The intelligence GPS is now one of the most powerful predictors in the behavioral sciences.
    2. Second, we consider the impact of GPS on intelligence research. The intelligence GPS can be added as a genetic predictor of intelligence to any study without the need to assess phenotypic intelligence. This feature will help export intelligence to many new areas of science. Also, the intelligence GPS will help to address complex questions in intelligence research, in particular how the gene-environment interplay affects the development of individual differences in intelligence.
    3. Third, we consider the societal impact of the intelligence GPS, focusing on DNA testing at birth, DNA testing before birth (e.g., embryo selection), and DNA testing before conception (e.g., DNA dating).

    The intelligence GPS represents a major scientific advance, and, like all scientific advances, it can be used for bad as well as good. We stress the need to maximize the considerable benefits and minimize the risks of our new ability to use DNA to predict intelligence. [Keywords: DNA, intelligence, prediction, genome-wide polygenic scores (PGS), review]