General intelligence factor

The general intelligence factor (abbreviated g) is a widely accepted but controversial construct used in the field of psychology (see also psychometrics) to quantify what is common to the scores of all intelligence tests. The phrase "g theory" refers to hypotheses and results regarding g ' s biological nature, stability/malleability, relevance to real-world tasks, and other inquiries.

History of g


Charles Spearman, an early psychometrician, found that schoolchildren's grades across seemingly unrelated subjects were positively correlated, and discovered 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. Spearman's theory proved too simple, however, as it ignored group factors in test scores (corresponding to broad abilities such as spatial visualization, memory and verbal ability) that may also be found through factor analysis.

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 (Carroll 1993). A hierarchy of factors with g at its apex and group factors at successively lower levels, is presently 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. 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 understood by an example. 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. Each of these measurements will be positively correlated, 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 would both be 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 correlates of g
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.

Current research suggests that broad-sense heritability of g is between 0.5 and 0.8, and narrow-sense heritability approximately 0.3, but the causal pathways are currently unknown. The heritability of most test performance is thus attributed to g.

Brain size has long been known to be correlated with g (Jensen, 1998). Recently, an MRI study on twins (Thompson et al., 2001) 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 (Posthuma et al., 2002). g has been observed in mice as well as humans (Matzel et al., 2003).

g is probably 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 (1990)), 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) &times; D (s).

Social correlates of g
g positively correlates with measures of success (academic achievement, job performance, career prestige) and negatively correlates with various social pathologies (school dropout, illegitimate 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.

Chris Brand, self-described "race realist" and author of The g Factor: General Intelligence and Its Implications discusses "the best established racial difference in g- that black people score markedly lower than whites." He adds, "The g factor is a reality discovered by science; yet egalitarian envy of excellence has meant that the discovery has yet to be harnessed to the advantage of all."

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. Statistical analyses of IQ subtest scores suggest a g-independent input to the Flynn effect (Wicherts et al. 2004).

Challenges to g
The late Stephen Jay Gould voiced his objections to the concept of g, as well as intelligence testing in general, in his book The Mismeasure of Man.

Some researchers into 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. Such abilities probably have nothing to do with genius."(Bringsjord, 2000).

Intelligence expert Howard Gardner notes:

"I do not believe that there is a single general talent, whether it be called intelligence, creativity or 'g'. I do not locate talents completely within the human skull, preferring to construe all accomplishments as an interaction between cognitive potentials on the one hand, and the resources and opportunities provided by the surrounding culture on the other....All intellectual and creative work takes place within some kind of social discipline, craft, or organized activity, termed a domain. Accordingly, there is no sense in which one can speak about a person as being intelligent, or creative, in general."

Philip Kitcher wrote in 1985:

"Many scientists are now convinced that there is no single measure of intellectual ability - no unitary intelligence. Their suspicion of the concept of general intelligence is based on the view that various intellectual capacities are not well correlated. ....it is useful to continue to expose the myth of 'general intelligence'."

This view point is heavily disputed however, and current evidence indicates that most psychometricians still accept g as a coherent and useful measure of intelligence.