Source: NYTimes, Sep 2016
irrationality — or what Professor Stanovich called “dysrationalia” — correlates relatively weakly with I.Q.
A person with a high I.Q. is about as likely to suffer from dysrationalia as a person with a low I.Q. In a 2008 study, Professor Stanovich and colleagues gave subjects the Linda problem and found that those with a high I.Q. were, if anything, more prone to the conjunction fallacy.
Source: Psychological Comments, Sep 2016
Source: Sage, Aug 2007
Sex differences in science and math achievement and ability are smaller for the mid-range of the abilities distribution than they are for those with the highest levels of achievement and ability. Males are more variable on most measures of quantitative and visuospatial ability, which necessarily results in more males at both high- and low-ability extremes …
Males outperform females on most measures of visuospatial abilities, which have been implicated as contributing to sex differences on standardized exams in mathematics and science.
We conclude that early experience, biological factors, educational policy, and cultural context affect the number of women and men who pursue advanced study in science and math and that these effects add and interact in complex ways.
Source: Stanford alumni mag, Jul/Aug 2000
Though the Terman kids were handpicked for high IQ, the longitudinal results tell us little about the meaning of IQ, except for one study conducted by Terman’s associate, Melita Oden.
In 1968, she compared the 100 most successful and 100 least successful men in the group, defining success as holding jobs that required their intellectual gifts. The successes, predictably, included professors, scientists, doctors and lawyers. The non-successes included electronics technicians, police, carpenters and pool cleaners, plus a smattering of failed lawyers, doctors and academics.
But here’s the catch: the successes and non-successes barely differed in average IQ. The big differences turned out to be in confidence, persistence and early parental encouragement.
Source: Nature.com, Sep 2014
five genetic findings that are special to intelligence differences and that have important implications for its genetic architecture and for gene-hunting expeditions.
- The heritability of intelligence increases from about 20% in infancy to perhaps 80% in later adulthood.
- Intelligence captures genetic effects on diverse cognitive and learning abilities, which correlate phenotypically about 0.30 on average but correlate genetically about 0.60 or higher.
- Assortative mating is greater for intelligence (spouse correlations ~0.40) than for other behavioural traits such as personality and psychopathology (~0.10) or physical traits such as height and weight (~0.20). Assortative mating pumps additive genetic variance into the population every generation, contributing to the high narrow heritability (additive genetic variance) of intelligence.
- Unlike psychiatric disorders, intelligence is normally distributed with a positive end of exceptional performance that is a model for ‘positive genetics’.
- Intelligence is associated with education and social class and broadens the causal perspectives on how these three inter-correlated variables contribute to social mobility, and health, illness and mortality differences.
These five findings arose primarily from twin studies. They are being confirmed by the first new quantitative genetic technique in a century—Genome-wide Complex Trait Analysis (GCTA)—which estimates genetic influence using genome-wide genotypes in large samples of unrelated individuals. Comparing GCTA results to the results of twin studies reveals important insights into the genetic architecture of intelligence that are relevant to attempts to narrow the ‘missing heritability’ gap.
Intelligence … is also one of the most stable behavioural traits, yielding a correlation of 0.63 in a study of people tested at age 11 and then again at age 79.
for intelligence, heritability increases linearly, from (approximately) 20% in infancy to 40% in adolescence, and to 60% in adulthood. Some evidence suggests that heritability might increase to as much as 80% in later adulthood47 but then decline to about 60% after age 80.48
A meta-analysis of 11000 pairs of twins shows that the heritability of intelligence increases significantly from childhood (age 9) to adolescence (age 12) and to young adulthood (age 17).
Source: The Atlantic, Jul/Aug 2016
… according to the 1979 National Longitudinal Survey of Youth, a long-running federal study, IQ correlates with chances of landing a financially rewarding job. Other analyses suggest that each IQ point is worth hundreds of dollars in annual income—surely a painful formula for the 80 million Americans with an IQ of 90 or below.
Rather than looking for ways to give the less intelligent a break, the successful and influential seem more determined than ever to freeze them out.
The College Board has suggested a “college readiness benchmark” that works out to roughly 500 on each portion of the SAT as a score below which students are not likely to achieve at least a B-minus average at “a four-year college”—presumably an average one. (By comparison, at Ohio State University, a considerably better-than-average school ranked 52nd among U.S. universities by U.S. News & World Report, freshmen entering in 2014 averaged 605 on the reading section of the SAT and 668 on the math section.)
it seems safe to say that no more than one in three American high-school students is capable of hitting the College Board’s benchmark. Quibble with the details all you want, but there’s no escaping the conclusion that most Americans aren’t smart enough to do something we are told is an essential step toward succeeding in our new, brain-centric economy—namely, get through four years of college with moderately good grades.
We must stop glorifying intelligence and treating our society as a playground for the smart minority. We should instead begin shaping our economy, our schools, even our culture with an eye to the abilities and needs of the majority, and to the full range of human capacity.
Source: Psychological Comments, May 2016
If we use Emil’s visualizer and put in mean=104 (sd 15) for the men in blue, and mean=100 (sd 14) for the women in red, and set the high mark cut-off as IQ 130 (corresponding to the top 2.28% of the overall population) then 4.15% of men make the cut and only 1.60% of women: the sex ratio will be 2.58 to 1. That means that 72% of bright people will be men.
Moving up to IQ 140 (the top 0.38% of the overall population) then 0.82% of men make the cut and only 0.21% women: the sex ratio is 3.8 to 1. That means that 80% of these even brighter people will be men.
Moving up to IQ 145 (the top 0.13% of the population) then 0.31% of men make the cut and only 0.06% of women: the sex ratio is 4.8 to 1. That means that 83% of these very bright people (the three sigmas) will be men.
In the refined company of my loyal readers, you may well say that IQ 145 is no great shakes: there will be 13 three sigmas in a thousand at this level of intellect. Too common. What if we take the 1 in a thousand criterion, equivalent to an IQ of about 155 (3.7 sigma). At that refined level the sex ratio will be 7.9 to 1. Call it an 8 to 1 chance that this very bright person will be a man.
Source: University of Utah, 2005
Ashkenazi Jews have the highest average IQ of any ethnic group for which there are reliable data. They score 0·75 to 1·0 standard deviations above the general European average, corresponding to an IQ of 112–115. This has been seen in many studies (Levinson, 1959; Backman, 1972; Romanoff, 1976), although a recent review concludes that the advantage is slightly less – only half a standard deviation (Lynn, 2004). This fact has social significance because IQ (as measured by IQ tests) is the best predictor we have of success in academic subjects and most jobs. Ashkenazi Jews are just as successful as their tested IQ would predict, and they are hugely overrepresented in occupations and fields with the highest cognitive demands.
During the 20th century, they made up about 3% of the US population but won 27% of the US Nobel science prizes and 25% of the ACM Turing awards. They account for more than half of world chess champions.
Source: James Thompson blog, Sep 2015
Paul Sackett identifies an issue which can prevent the brightest people solving the hardest problems. He says: One recurring theme in my work is the tension between designing selection systems to maximize job performance vs. to maximize ethnic, racial, and gender diversity. The current controversies over the future of affirmative action attest to the prominence of this concern.
You know what I think. I think it is wrong to confuse competence with demographic representativeness. Competence is needed so as to obtain the best outcomes of skilled behaviour. Representativeness is needed to establish that a sample represents a population. Confusing the two will lead to bad decisions and sub-standard performance.
Sackett and Kuncel found that SAT and high school grades contributed to predicting academic performance in college. Taking parents’ education and family income into account had little effect on the relationship between SAT scores and college performance.
Source: Research UK, Sep 2015
1. The problem, research question, or background?
Numerous theories seek to account for differences in reasoning without recourse to trait-IQ. Among these are Dweck’s (Mueller & Dweck, 1998) Incremental Mindset, Baumeister’s Resource Depletion Theory (Vohs, Baumeister, & Schmeichel, 2012) and, for woking in groups, Woolley’s Collective IQ (C: Woolley, et al., 2010).
In this presentation, we test the extent to which these models predict performance independent of g (if at all).
2. Methods including N, sample characteristics and study design
The Baumeister and Dweck models of will power are tested in a repeated measures design involving 80 students.
The Woolley Collective IQ model is tested in three experiments with 28 to 80 groups of individuals. In addition manipulations of empathy-equality are contrasted with manipulations of authority-obedience to test non-cognitive origins of group performance.
The Dweck incremental vs fixed mindset model of IQ test performance was tested in three experiments of between 80 and 400 subjects, testing the predicted link of beliefs about performance to actualized performance both observationally and via belief priming.
3. Results and conclusions
We found no significant support for willpower depletion as a cause of cognitive decrements during testing. Moreover we find no support for incremental beliefs about will-power on measured cognitive test scores.
Group-IQ performance showed a strong g-factor, but this was almost completely explained by individual differences in IQ. We found no support for empathizing, or for the role of women as factors raising group IQ scores.
Study three showed, instead, support for authority/group morality manipulations in raising collective performance.
We found no support for incremental vs fixed mindset on grades.
We further found no significant effect of mindset priming on IQ scores post a performance setback challenge in either of two replications.