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Charles Spearman, an early psychometrician, found that schoolchildren's grades across seemingly unrelated subjects were positively correlated, and proposed that these correlations reflected the influence of a dominant factor, which he termed g for "general" intelligence. He developed a model where all variation in intelligence test scores can be explained by two factors. The first is the factor specific to an individual mental task: the individual abilities that would make a person more skilled at one cognitive task than another. The second is g, a general factor that governs performance on all cognitive tasks.
The accumulation of cognitive testing data and improvements in analytical techniques have preserved g's central role and led to the modern conception of g. A hierarchy of factors with g at its apex and group factors at successively lower levels, is espoused to be the most widely accepted model of cognitive ability. Other models have also been proposed, and significant controversy attends g and its alternatives.
Mental testing and g
The abstraction of g stems from the observation that scores on all forms of cognitive tests correlate positively with one another.[How to reference and link to summary or text] g can be derived as the principal factor from cognitive test scores using the method of principal components analysis or factor analysis.
The relationship of g to intelligence tests may be more readily understood with an analogy. Irregular objects, such as the human body, are said to vary in "size". Yet no single measurement of a human body is obviously preferred to measure its "size". Instead, many and various measurements, such as those taken by a tailor, may be made. All of these measurements will be positively correlated with each other, and if one were to "add up" or combine all of the measurements, the aggregate would give a better description of an individual's size than any single measurement. The method of factor analysis allows this. The process is intuitively similar to taking the average of a sample of measurements of a single variable, but instead "size" is a summary measure of a sample of variables. g is like size, in that it is abstracted from various measures (of cognitive ability). Of course, variation in "size" does not fully account for all variation in the measurements of a human body. Factor analysis techniques are not limited to producing single factors, and an analysis of human bodies might produce (for example) two major factors, such as height and girth. However, the scores of tests of cognitive ability do in fact produce a primary dominant factor, g.
Tests of cognitive ability derive most of their validity from the extent to which they measure g. If quantifiable measures of the performance of a task correlate highly with g, it is said to be g-loaded. Creators of IQ tests, whose goals are generally to create highly reliable and valid tests, have thus made their tests as g-loaded as possible. Historically, this has meant dampening the influence of group factors by testing as wide a range of mental tasks as possible. However, tests such as Raven's Progressive Matrices are considered to be the most g-loaded in existence, even though Raven's is quite homogeneous in the types of tasks comprising it.
Elementary cognitive tasks (ECTs) also correlate strongly with g. ECTs are, as the name suggests, simple tasks that apparently require very little intelligence, but still correlate strongly with more exhaustive intelligence tests. Determining whether a light is red or blue and determining whether there are four or five squares drawn on a computer screen are two examples of ECTs. The answers to such questions are usually provided by quickly pressing buttons. Often, in addition to buttons for the two options provided, a third button is held down from the start of the test. When the stimulus is given to the subject, he removes his hand from the starting button to the button of the correct answer. This allows the examiner to determine how much time was spent thinking about the answer to the question (reaction time, usually measured in small fractions of second), and how much time was spent on physical hand movement to the correct button (movement time). Reaction time correlates strongly with g, while movement time correlates less strongly. ECT testing has allowed quantitative examination of hypotheses concerning test bias, subject motivation, and group differences. By virtue of their simplicity, ECTs provide a link between classical IQ testing and biological inquiries such as fMRI studies.
Biological and genetic correlates of g
- Main article: Heritability of IQ
g has a large number of biological correlates. Strong correlates include mass of the prefrontal lobe, overall brain mass, and glucose metabolization rate within the brain. g correlates less strongly, but significantly, with overall body size. There is conflicting evidence regarding the correlation between g and peripheral nerve conduction velocity, with some reports of significant positive correlations, and others of no or even negative correlations.
Brain size has long been known to be correlated with g . An MRI study on twins  showed that frontal gray matter volume was highly significantly correlated with g and highly heritable. A related study has reported that the correlation between brain size (reported to have a heritability of 0.85) and g is 0.4, and that correlation is mediated entirely by genetic factors . g has been observed in mice as well as humans .
Lehrl and Fischer (1990) have claimed that g is limited by the channel capacity of short-term memory. Mental power, or the capacity C of short-term memory (measured in bits of information), is the product of the individual mental speed Ck of information processing (in bit/s) (see the external link below to the paper by Lehrl and Fischer), and the duration time D (in s) of information in short-term working memory, meaning the duration of memory span. Hence:
- C (bit) = Ck(bit/s) × D (s).
This theory has been tested and found wanting by Roberts et al. (1992). There is much evidence that g is closely related to measures of the capacity of working memory (; ; ), but this capacity can not be measured in bits of information .
However recent studies attempting to find regions in the genome relating to intelligence have had little success. A recent study used several hundred people in two groups, one with a very high IQ, average 160, and a control group with an average IQ of 102. The study used 1,842 DNA markers and put them through a five step inspection process to eliminate false positives. By the fifth step the study could not find a single gene that was related to intelligence. Critics of these studies say the failure to find a specific gene associated with intelligence is indicative of the complex nature of intelligence. They contend that intelligence is probably under the influence of several genes. Some estimate that as much as 40% of the genome may contribute to intelligence.
Social correlates of g
Most measures of g positively correlate with conventional measures of success (income, academic achievement, job performance, career prestige) and negatively correlate with what are generally seen as undesirable life outcomes (school dropout, unplanned childbearing, poverty). IQ tests that measure a wide range of abilities do not predict much better than g. Scientific publishings of findings of differences in g between ethnic groups (see race and intelligence) have sparked public controversy.
The Flynn effect and g
The Flynn effect describes a rise in IQ scores over time. There is no strong consensus as to whether rising IQ scores also reflect increases in g. In addition, there is evidence that shows that the tendency for intelligence scores to rise has ended in some first world countries.    Statistical analyses of IQ subtest scores suggest a g-independent input to the Flynn effect .
Challenges to g
In 1981, the late Stephen Jay Gould, a paleontologist, voiced his objections to the concept of g, as well as intelligence testing in general, in his controversial book The Mismeasure of Man. In 1985, the British philosopher Philip Kitcher wrote that "Many scientists are now convinced that there is no single measure of intellectual ability" and that "it is useful to continue to expose the myth of "general intelligence". Some researchers in artificial intelligence have argued that the science of mental ability can be thought of as "computationalism" and is "either silly or pointless," noting, "Mental ability tests measure differences in tasks that will soon be performed for all of us by computational agents." And intelligence theorist Howard Gardner also has written that he does not believe "that there is a single general talent, whether it be called intelligence, creativity or 'g'." In 2005, Wendy Johnson and Thomas Bouchard investigated the structure of mental ability by administering 42 diverse tests of mental ability to 436 adults. The tests included "different uses" (generation of novel uses for specified objects), "object assembly" (reassembly of cut-up figures), "verbal—proverbs" (interpretation of proverbs) and "mechanical ability" (identification of mechanical principles and tools); factor analysis found a clear single higher order factor, g. In their report, published in the journal Intelligence, the study authors conclude:
In combination with our earlier findings regarding the consistency of general intelligence factors across test batteries, our results point unequivocally to the existence of a general intelligence factor contributing substantively to all aspects of intelligence.
- See also: Savant syndrome
Howard Gardner contends that the rare condition of savant syndrome argues against a single generalized intelligence. People with savant syndrome may have general IQs in the mentally retarded range but may possess certain mental abilities that are remarkable compared to the average person. These abilities include superior memory, lightning-fast arithmetic calculation, advanced musical ability, rapid language learning and exceptional artistic ability.On the other hand, Gardner's contention is rebutted by the fact that savants with low IQs tend to perform poorly in school and at work, despite their talents. This outcome is in line with the predictions made by modern IQ tests (see "Social Correlates of g", above).[How to reference and link to summary or text]
- Charles Spearman
- Fluid and crystallized intelligence
- General Cognitive Abilities
- Intelligence quotient
- Race and intelligence
- ↑ (Carroll 1993)
- ↑ Stalking the Wild Taboo -APA Statement on The Bell Curve - Intelligence: Knowns and Unknowns
- ↑ Jensen, 1998, p 38
- ↑ Jensen, 1998, p 213
- ↑ 5.0 5.1 (Jensen, 1998)
- ↑ (Thompson et al., 2001)
- ↑ (Posthuma et al., 2002)
- ↑ (Matzel et al., 2003)
- ↑ 9.0 9.1 Lehrl and Fischer (1990)
- ↑ Roberts et al. (1992)
- ↑ Ackerman et al., 2005
- ↑ Kane et al., 2005
- ↑ Oberauer et al., 2005
- ↑ (Miller, 1956)
- ↑ A Genome-Wide Scan of 1842 DNA Markers for Allelic Associations With General Cognitive Ability: A Five-Stage Design Using DNA Pooling and Extreme Selected Groups
- ↑ Geary, D.C. (2005). The Origin of Mind: Evolution of Brain Cognition and General Intelligence. Washington, D.C.: American Psychological Association. ISBN 1-59147-181-8
- ↑ The end of the Flynn Effect. A study of secular trends in mean intelligence scores of Norwegian conscripts during half a century..
- ↑ A long-term rise and recent decline in intelligence test performance: The Flynn Effect in reverse..
- ↑ Children are less able than they used to be.
- ↑ (Wicherts et al. 2004)
- ↑ (Bringsjord, 2000)
- ↑ Johnson, Wendy and Bouchard, Thomas J. Jr. (2005). "The structure of human intelligence: It is verbal, perceptual, and image rotation (VPR), not fluid and crystallized." Intelligence, 33 393–416.
- ↑ Heaton, Pamela (2004). Annotation:The savant syndrome. Journal of Child Psychology and Psychiatry 45: 899.
- Ackerman, P. L., Beier, M. E., & Boyle, M. O. (2005). Working memory and intelligence: The same or different constructs? Psychological Bulletin, 131, 30–60.
- Brand, C. (1996). The g Factor: General Intelligence and Its Implications. (depublished) [originally Wiley]. ISBN 0-471-96070-5
- Bringsjord, S. (2000). In light of artificial intelligence, the science of mental ability is either silly or pointless: Review of Jensen's The g Factor. Psycoloquy, 11(44). 
- Carroll, J.B. (1993). Human Cognitive Abilities. Cambridge University Press.
- Gardner, H. (1993). The relationship between early giftedness and later achievement. In Ciba Foundation. The origins and development of high ability. Ciba Foundation Symposium (pp. 175–186). Chichester, England: John Wiley & Sons.
- Jensen, A.R. (1998). The g factor: The science of mental ability. Westport, CT: Praeger. ISBN 0-275-96103-6
- Kane, M. J., Hambrick, D. Z., & Conway, A. R. A. (2005). Working memory capacity and fluid intelligence are strongly related constructs: Comment on Ackerman, Beier, and Boyle (2004). Psychological Bulletin, 131, 66–71.
- Kitcher, P. (1985). Vaulting ambition: Sociobiology and the quest for human nature. Cambridge, MA: MIT Press.
- Matzel, L.D., Han, Y.R., Grossman, H., Karnik, M.S., Patel, D., Scott, N., Specht, S.M., & Gandhi, C.C. (2003). Individual differences in the expression of a "general" learning ability in mice. Journal of Neuroscience, 23(16), 6423–6433.
- Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81–97.
- Oberauer, K., Schulze, R., Wilhelm, O., & Süß, H.-M. (2005). Working memory and intelligence - their correlation and their relation: A comment on Ackerman, Beier, and Boyle (2005). Psychological Bulletin, 131, 61–65.
- Posthuma, D., De Geus, E.J., Baare, W.F., Hulshoff Pol, H.E., Kahn, R.S., Boomsma, D.I. (2002). The association between brain volume and intelligence is of genetic origin. Nature Neuroscience, 5(2), 83–84.
- Rindermann, Heiner (2007). The g-factor of international cognitive ability comparisons: the homogeneity of results in PISA, TIMSS, PIRLS and IQ-tests across nations. European Journal of Personality, 21, 667-706 
- Roberts, R. D., Pallier, G., & Stankov, L. (1996). The Basic Information Processing (BIP) unit, mental speed and human cognitive abilities: Should the BIP R.I.P.? Intelligence, 23, 133–155.
- Thompson, P.M., Cannon T.D., Narr, K.L., Erp, T. van, Poutanen, V.-P., Huttunen, M., et al. (2001). Genetic influences on brain structure. Nature Neuroscience, 4(12), 1253–1258.
- Wicherts, J.M., Dolan, C.V., Hessen, D.J., Oosterveld, P., Baal, G.C.M. van, Boomsma, D.I., & Span, M.M. (2004). Are intelligence tests measurement invariant over time? Investigating the nature of the Flynn effect. Intelligence, 32, 509–537. 
- Geary, D.C. (2005). The Origin of Mind: Evolution of Brain Cognition and General Intelligence. Washington, D.C.: American Psychological Association. ISBN 1-59147-181-8
- The g Factor - Jensen's book
- The General Intelligence Factor PDF - Good article for laymen
- The Basic Period of Individual Mental Speed, Underlying IQ
- A Genomewide Scan for Genes Underlying General Cognitive Ability
- Carroll model.
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