Intelligence quotient

"IQ" redirects here. For other uses, see IQ (disambiguation).

IQ tests are designed to give approximately this Gaussian distribution. Colors delineate one standard deviation.

An intelligence quotient or IQ is a score derived from a one of several different standardized tests attempting to measure intelligence, more specifically the general intelligence. IQ tests are generally designed and used because they are found to be predictive of later intellectual achievement, such as educational achievement. IQ also correlates with job performance, socioeconomic advancement, and "social pathologies", but very weakly or not at all with accumulated wealth, especially inherited. Recent work has demonstrated links between IQ and health, longevity, and functional literacy.

For people living in the prevailing conditions of the developed world, IQ is highly heritable, and by adulthood the influence of family environment on IQ is undetectable. That is, significant variation in IQ between adults can be attributed to genetic variation, with the remaining variation attributable to environmental sources that are not shared within families. In the United States, marked variation in IQ occurs within families, with siblings differing on average by around 12 points.

The average IQ scores for many populations were rising rapidly during the 20th century: a phenomenon called the Flynn effect. It is not known whether these changes in scores reflect real changes in intellectual abilities (if not, then this raises questions about what IQ tests do measure). On average, IQ scores are stable over a person's lifetime, but some individuals undergo large changes. For example, scores can be affected by the presence of learning disabilities.

History

In 1905, the French psychologist Alfred Binet published the first modern intelligence test, the Binet-Simon intelligence scale. His principal goal was to identify students who needed special help in coping with the school curriculum. Along with his collaborator Theodore Simon, Binet published revisions of his intelligence scale in 1908 and 1911, the last appearing just before his untimely death.

In 1912, the abbreviation of "intelligence quotient" or I.Q., a translation of the German Intelligenz-Quotient, was coined by the German psychologist William Stern. A further refinement of the Binet-Simon scale was published in 1916 by Lewis M. Terman, from Stanford University, who incorporated Stern's proposal that an individual's intelligence level be measured as an intelligence quotient (I.Q.). Terman's test, which he named the Stanford-Binet Intelligence Scale formed the basis for one of the modern intelligence tests still commonly used today.

Originally, IQ was calculated with the formula $100\times {\frac {\text{mental age}}{\text{chronological age}}}.$ A 10-year-old who scored as high as the average 13-year-old, for example, would have an IQ of 130 (100*13/10).

In 1939 David Wechsler published the first intelligence test explicitly designed for an adult population, the Wechsler Adult Intelligence Scale, or WAIS. Since publication of the WAIS, Wechsler extended his scale downward to create the Wechsler Intelligence Scale for Children, or WISC, which is still in common usage. The Wechsler scales contained separate subscores for verbal and performance IQ, thus being less dependent on overall verbal ability than early versions of the Stanford-Binet scale, and was the first intelligence scale to base scores on a standardized normal distribution rather than an age-based quotient.

Because age-based quotients only worked for children, it was replaced by a projection of the measured rank on the Gaussian bell curve with a center value (average IQ) of 100, and a standard deviation of 15 or occasionally 16. Thus the modern version of the IQ is a mathematical transformation of a raw score (based on the rank of that score in a normalization sample; see quantile, percentile, percentile rank), which is the primary result of an IQ test. To differentiate the two scores, modern scores are sometimes referred to as "deviance IQ", while the age-specific scores are referred to as "ratio IQ".

Since the publication of the WAIS, almost all intelligence scales have adopted the normal distribution method of scoring. The use of the normal distribution scoring method makes the term "intelligence quotient" an inaccurate description of the intelligence measurement, but I.Q. still enjoys colloquial usage, and is used to describe all of the intelligence scales currently in use.

How an IQ test works

IQ tests come in many forms, and some tests use a single type of item or question, while other use several different subtests. Most tests yield both an overall score and individual subtest scores.

A typical IQ test requires the test subject to solve a fair number of problems in a set time under supervision. Most IQ tests include items from various domains, such as short-term memory, verbal knowledge, spatial visualization, and perceptual speed. Some tests have a total time limit, others have a time limit for each group of problems, and there are a few untimed, unsupervised tests, typically geared to measuring high intelligence.

To set the scale for an IQ test, a representative sample of the population for which the IQ is made is gathered. IQ tests are calibrated in such a way as to yield a normal distribution, or "bell curve."

Each IQ test, however, is designed and valid only for a certain IQ range. Because so few people score in the extreme ranges, IQ tests usually cannot accurately measure very low and very high IQs.

Various IQ tests measure a standard deviation with different number of points. Thus, when an IQ score is stated, the standard deviation used should also be stated. A result of 124 in a test with a 24-point standard deviation corresponds to a score of 115 in a test with a 15-point deviation.

Where an individual has scores that do not correlate with each other, there is a good reason to look for a learning disability or other cause for the lack of correlation. Tests have been chosen for inclusion because they display the ability to use this method to predict later difficulties in learning.

IQ and general intelligence factor

Main article: General intelligence factor

Modern IQ tests produce scores for different areas (e.g., language fluency, three-dimensional thinking), with the summary score calculated from subtest scores. The average score, according to the bell curve, is 100. Individual subtest scores tend to correlate with one another, even when seemingly disparate in content.

Mathematical analysis of individuals' scores on the subtests of a single IQ test or the scores from a variety of different IQ tests (e.g., Stanford-Binet, WISC-R, Raven's Progressive Matrices, Cattell Culture Fair III, Universal Nonverbal Intelligence Test, and others) find that they can be described mathematically as measuring a single common factor and various factors that are specific to each test. This kind of factor analysis has led to the theory that underlying these disparate cognitive tasks is a single factor, termed the general intelligence factor (or g), that corresponds with the common-sense concept of intelligence. In the normal population, g and IQ are roughly 90% correlated and are often used interchangeably.

Tests differ in their g-loading, which is the degree to which the test score reflects g rather than a specific skill or "group factor" such as verbal ability, spatial visualization, or mathematical reasoning). g-loading and validity have been observed to be related in the sense that most IQ tests derive their validity mostly or entirely from the degree to which they measure g(Jensen 1998).

Influences of genetics and environment

Main article: Inheritance of intelligence

"Heritability"

The role of genes and environment (nature and nurture) in determining IQ is reviewed in Plomin et al. (2001, 2003). The degree to which genetic variation contributes to observed variation in a trait is measured by a statistic called heritability. Heritability scores range from 0 to 1, and can be interpreted as the percentage of variation (e.g. in IQ) that is due to variation in genes. Twins studies and adoption studies are commonly used to determine the heritability of a trait. Until recently heritability was mostly studied in children. Some studies find the heritability of IQ around 0.5 but the studies show ranges from 0.4 to 0.8; that is, depending on the study, a little less than half to substantially more than half of the variation in IQ among the children studied was due to variation in their genes. The remainder was thus due to environmental variation and measurement error. A heritability in the range of 0.4 to 0.8 implies that IQ is "substantially" heritable. Studies with adults show that they have a higher heritability of IQ than children do and that heritability could be as high as 0.8. The American Psychological Association's 1995 task force on "Intelligence: Knowns and Unknowns" concluded that within the white population the heritability of IQ is "around .75" (p. 85). The Minnesota Study of Twins Reared Apart, a multiyear study of 100 sets of reared apart twins which was started in 1979, concluded that about 70% of the variance in IQ was found to be associated with genetic variation.

It is reasonable to expect that genetic influences on traits like IQ should become less important as one gains experiences with age. Surprisingly, the opposite occurs. Heritability measures in infancy are as low as 20%, around 40% in middle childhood, and as high as 80% in adulthood.

These estimates are based on studies from the US and assume that the strength of environmental and genetic factors remain constant. In developing nations the strength of the environmental factors may be stronger, for example due to widespread malnutrition, and then "heritability" will be a lower number. Also, even in developed nations, high heritability of a trait within a given group has no necessary implications for the source of a difference between groups.

Environment

See also: Health and intelligence

Environmental factors play a role in determining IQ. Proper childhood nutrition appears critical for cognitive development; malnutrition can lower IQ. Other research indicates environmental factors such as prenatal exposure to toxins, duration of breastfeeding, and micronutrient deficiency can affect IQ.

It is well known that it is possible to increase one's IQ score by training, for example by regularly playing puzzle games. Recent studies have shown that training in using one's working memory may increase IQ. (Klingberg et al., 2002)

Family environment

The American Psychological Association's report Intelligence: Knowns and Unknowns (1995) states that there is no doubt that normal child development requires a certain minimum level of responsible care. Severely deprived, neglectful, or abusive environments must have negative effects on a great many aspects of development, including intellectual aspects. Beyond that minimum, however, the role of family experience is in serious dispute. Do differences between children's family environments (within the normal range) produce differences in their intelligence test performance? The problem here is to disentangle causation from correlation. There is no doubt that such variables as resources of the home and parents' use of language are correlated with children's IQ scores, but such correlations may be mediated by genetic as well as (or instead of) environmental factors. But how much of that variance in IQ results from differences between families, as contrasted with the varying experiences of different children in the same family? Recent twin and adoption studies suggest that while the effect of the family environment is substantial in early childhood, it becomes quite small by late adolescence. These findings suggest that differences in the life styles of families whatever their importance may be for many aspects of children's lives make little long-term difference for the skills measured by intelligence tests. We should note, however, that low-income and non-white families are poorly represented in existing adoption studies as well as in most twin samples. Thus it is not yet clear whether these studies apply to the population as a whole. It re-mains possible that, across the full range of income and ethnicity, between-family differences have more lasting consequences for psychometric intelligence.

In the developed world, nearly all personality traits show that, contrary to expectations, environmental effects actually cause adoptive siblings raised in the same family to be as different as children raised in different families (Harris, 1998; Plomin & Daniels, 1987). There are some family effects on the IQ of children, accounting for up to a quarter of the variance. However, by adulthood, this correlation disappears, such that adopted adult siblings are not more similar in IQ than strangers. For IQ, adoption studies show that, after adolescence, adopted siblings are no more similar in IQ than strangers (IQ correlation near zero), while full siblings show an IQ correlation of 0.6. Twin studies reinforce this pattern: monozygotic (identical) twins raised separately are highly similar in IQ (0.86), more so than dizygotic (fraternal) twins raised together (0.6) and much more than adopted siblings (~0.0).

A study of French children adopted between the ages of 4 and 6 shows the continuing interplay of nature and nurture. The children came from poor backgrounds with I.Q.’s that initially averaged 77, putting them near retardation. Nine years later after adoption, they retook the I.Q. tests, and all of them did better. The amount they improved was directly related to the adopting family’s status. "Children adopted by farmers and laborers had average I.Q. scores of 85.5; those placed with middle-class families had average scores of 92. The average I.Q. scores of youngsters placed in well-to-do homes climbed more than 20 points, to 98." This study suggests that IQ is not stable over the course of one's lifetime and that, even in later childhood, a change in environment can have a significant effect on IQ.

Mental handicaps

About 75–80 percent of mental handicaps are familial (runs in the family), and 20–25 percent is due to not inherited biological problems, such as chromosomal abnormalities or brain damage. Mild to severe mental disability is a symptom of several hundred single-gene disorders and many chromosomal abnormalities, including small deletions. Based on twin studies, moderate to severe mental disability does not appear to be familial, but mild mental disability does. That is, the relatives of the moderate to severely mentally handicapped have normal ranges of IQs, whereas the families of the mildly mentally handicapped have lower IQs.

IQ score ranges (from DSM-IV):

• mild mental disability: IQ 50–55 to 70; children require mild support; formally called "Educable Mentally Retarded".
• moderate disability: IQ 35–40 to 50–55; children require moderate supervision and assistance; formally called "Trainable Mentally Retarded".
• severe mental disability: IQ 20–25 to 35–40; can be taught basic life skills and simple tasks with supervision.
• profound mental disability: IQ below 20–25; usually caused by a neurological condition; require constant care.

The rate of mental retardation is higher among males than females, according to a 1991 U.S. Centers for Disease Control and Prevention (CDC) study. This is aggravated by the fact that males, unlike females, do not have a spare X chromosome to offset chromosomal defects.

Regression towards the mean

The heritability of IQ measures the extent to which the IQ of children appears to be influenced by the IQ of parents. Because the heritability of IQ is less than 100%, the IQ of children tends to "regress" towards the mean IQ of the population. That is, high IQ parents tend to have children who are less bright than their parents, whereas low IQ parents tend to have children who are brighter than their parents. The effect can be quantified by the equation ${\hat {y}}={\bar {x}}+h^{2}\left({\frac {m+f}{2}}-{\bar {x}}\right)$ where

• ${\hat {y}}$ is the predicted average IQ of the children;
• ${\bar {x}}$ is the mean IQ of the population to which the parents belong;
• $h^{2}$ is the heritability of IQ;
• $m$ and $f$ are the IQs of the mother and father, respectively.

Thus, if the heritability of IQ is 50%, a couple averaging an IQ of 120 may have children that average around an IQ of 110, assuming that both parents come from a population with a median IQ of 100.

IQ and the brain

Main article: Neuroscience and intelligence

Modern studies using MRI imaging have found several relations between IQ and neuroanatomy. For example, brain size correlates with IQ (r = 0.4, a fairly low correlation) among adults of the same sex (McDaniel, 2005).

The Flynn effect

Main article: Flynn effect

The Flynn effect is named after James R. Flynn, a New Zealand based political scientist. He discovered that IQ scores worldwide appear to be slowly rising at a rate of around three IQ points per decade (Flynn, 1999). Attempted explanations have included improved nutrition, a trend towards smaller families, better education, greater environmental complexity, and heterosis (Mingroni, 2004). Tests are therefore renormalized occasionally to obtain mean scores of 100, for example WISC-R (1974), WISC-III (1991) and WISC-IV (2003). Hence it is difficult to compare IQ scores measured years apart, unless this is compensated for. There is recent evidence that the tendency for intelligence scores to rise has ended in some first world countries.

Group differences

Among the most controversial issues related to the study of intelligence is the observation that intelligence measures such as IQ scores vary between populations. While there is little scholarly debate about the existence of some of these differences, the reasons remain highly controversial both within academia and in the public sphere.

Health and intelligence

Main article: Health and intelligence

Several factors can lead to significant cognitive impairment, particularly if they occur during pregnancy and childhood when the brain is growing and the blood-brain barrier is less effective. Such impairment may sometimes be permanent, sometimes be partially or wholly compensated for by later growth. Several harmful factors may also combine, possibly causing greater impairment.

Developed nations have implemented several health policies regarding nutrients and toxins known to influence cognitive function. These include laws requiring micronutrient fortification of certain food products and laws establishing safe levels of pollutants (e.g. lead, mercury, and organochlorides). Comprehensive policy recommendations targeting reduction of cognitive impairment in children have been proposed.

Sex and intelligence

Main article: Sex and intelligence

Most studies show that despite sometimes significant differences in subtest scores, men and women have the same average IQ. Women perform better on tests of memory and verbal proficiency for example, while men perform better on tests of mathematical and spatial ability. Although gender-related differences in average IQ are insignificant, male scores display a higher variance: there are more men than women with both very high and very low IQs.

Religiosity and intelligence

Main article: Religiosity and intelligence

The topic of Religiosity and Intelligence pertains to possible relationships between intelligence and religious belief.

Topics dealing with the measurement of intelligence are often controversial. Critics in these areas examine the validity and fairness of cognitive testing, as well as the problems in the definition and operationalization of the other measurements under discussion, in this case religiosity. Many of the issues pertaining to the investigation of group differences in intelligence vis-à-vis religiosity are also raised in the investigation of race and intelligence—a better established, though even more controversial, area of intelligence research.

In scientific research, correlations can suggest, but not necessarily imply causation: even if a positive or negative correlation can be found between intelligence and religiosity, it may suggest, but doesn't involve as a necessary circumstance, that one is causing the other. (See also: spurious relationship; and correlation does not imply causation).

Race and IQ

Main article: Race and intelligence

Much research has been devoted to the extent and potential causes of racial group differences in IQ.

Practical validity

Linear correlations between 1000 pairs of numbers. The data are graphed on the lower left and their correlation coefficients listed on the upper right. Each set of points correlates maximally with itself, as shown on the diagonal (all correlations = +1).

Economic and social correlates of IQ in the USA

IQ	<75	75–90	90–110	110–125	>125
U.S. population distribution	5	20	50	20	5
Married by age 30	72	81	81	72	67
Out of labor force more than 1 month out of year (men)	22	19	15	14	10
Unemployed more than 1 month out of year (men)	12	10	7	7	2
Divorced in 5 years	21	22	23	15	9
% of children w/ IQ in bottom decile (mothers)	39	17	6	7	< 1
Had an illegitimate baby (mothers)	32	17	8	4	2
Lives in poverty	30	16	6	3	2
Ever incarcerated (men)	7	7	3	1	< 1
Chronic welfare recipient (mothers)	31	17	8	2	< 1
High school dropout	55	35	6	0.4	< 0.4
Values are the percentage of each IQ sub-population, among non-Hispanic whites only, fitting each descriptor. Compiled by Gottfredson (1997) from a U.S. study by Herrnstein & Murray (1994) pp. 171, 158, 163, 174, 230, 180, 132, 194, 247–248, 194, 146 respectively.

While IQ is sometimes treated as an end unto itself, scholarly work on IQ focuses to a large extent on IQ's validity, that is, the degree to which IQ predicts or correlations with outcomes such as job performance, social pathologies, or academic achievement. Different IQ tests differ in their validity for various outcomes.

Validity is the correlation between score (in this case cognitive ability, as measured, typically, by a paper-and-pencil test) and outcome (in this case job performance, as measured by a range of factors including supervisor ratings, promotions, training success, and tenure), and ranges between −1.0 (the score is perfectly wrong in predicting outcome) and 1.0 (the score perfectly predicts the outcome). See validity (psychometric).

Research shows that general intelligence plays an important role in many valued life outcomes. In addition to academic success, IQ correlates to some degree with job performance (see below), socioeconomic advancement (e.g., level of education, occupation, and income), and "social pathology" (e.g., adult criminality, poverty, unemployment, dependence on welfare, children outside of marriage). Recent work has demonstrated links between general intelligence and health, longevity, and functional literacy. Correlations between g and life outcomes are pervasive, though IQ and happiness do not correlate. IQ and g correlate highly with school performance and job performance, less so with occupational prestige, moderately with income, and to a small degree with law-abidingness. IQ does not explain the inheritance of economic status and wealth.

It should be remembered that correlation is not causation.

School performance

The American Psychological Association's report Intelligence: Knowns and Unknowns (1995) Wherever it has been studied, children with high scores on tests of intelligence tend to learn more of what is taught in school than their lower-scoring peers. The correlation between IQ scores and grades is about .50. However, thid mean that they explain only 25% of the variance. Successful school learning depends on many personal characteristics other than intelligence, such as persistence, interest in school, and willingness to study.

Correlations between IQ scores and total years of education are about .55, implying that differences in psychometric intelligence account for about 30% of the outcome variance. Many occupations can only be entered through professional schools which base their admissions at least partly on test scores: the MCAT, the GMAT, the LSAT, etc. Individual scores on admission-related tests such as these are certainly correlated with scores on tests of intelligence. It is partly because intelligence test scores predict years of education that they also predict occupational status, and even income to a smaller extent.

Job performance

According to Schmidt and Hunter, "for hiring employees without previous experience in the job the most valid predictor of future performance is general mental ability." The validity of cognitive ability for job performance tends to increase with job complexity and varies across different studies, ranging from 0.2 for unskilled jobs to 0.6 for the most complex jobs.

A meta-analysis (Hunter and Hunter, 1984) which pooled validity results across many studies encompassing thousands of workers (32,124 for cognitive ability), reports that the validity of cognitive ability for entry-level jobs is 0.54, larger than any other measure including job tryout (0.44), experience (0.18), interview (0.14), age (−0.01), education (0.10), and biographical inventory (0.37). This implies that, across a wide range of occupations, intelligence test performance accounts for some 29% of the variance in job performance.

The American Psychological Association's report Intelligence: Knowns and Unknowns (1995) states that other individual characteristics such as interpersonal skills, aspects of personality, etc., are probably of equal or greater importance, but at this point we do not have equally reliable instruments to measure them.

Income and wealth

Relation between IQ and earnings in the U.S.

IQ	<75	75–90	90–110	110–125	>125
Age 18	2,000	5,000	8,000	8,000	3,000
Age 26	3,000	10,000	16,000	20,000	21,000
Age 32	5,000	12,400	20,000	27,000	36,000
Values are the average earnings (US Dollars) of each IQ sub-population.

Other studies question the real-world importance of whatever is measured with IQ tests. The economic importance of IQ varies as a function of age, though for the entire adult population combined, it explains about one sixth of the income variance. Even for school grades, other factors explain most the variance. One study found that, controlling for IQ across the entire population, 90 to 95 percent of economic inequality would continue to exist.

Some researchers have echoed the popular claim that "in economic terms it appears that the IQ score measures something with decreasing marginal value. It is important to have enough of it, but having lots and lots does not buy you that much."

However, some studies suggest IQ continues to confer significant benefits even at very high levels. Ability and performance for jobs are linearly related, such that at all IQ levels, an increase in IQ translates into a concomitant increase in performance (Coward and Sackett, 1990). In an analysis of hundreds of siblings, it was found that IQ has a substantial effect on income independently of family background (Murray, 1998).

Another recent study (2002) found that wealth, race, and schooling are important to the inheritance of economic status, but IQ is not a major contributor and the genetic transmission of IQ is even less important.

The American Psychological Association's report Intelligence: Knowns and Unknowns (1995) states that IQ scores account for about one-fourth of the social status variance and one-sixth of the income variance. Statistical controls for parental SES eliminate about a quarter of this predictive power. Psychometric intelligence appears as only one of a great many factors that influence social outcomes.

One reason why some studies claim that IQ only accounts for a sixth of the variation in income is because many studies are based on young adults (many of whom have not yet completed their education). On pg 568 of The g factor, Arthur Jensen claims that although the correlation between IQ and income averages a moderate 0.4 (16% of the variance), the relationship increases with age, and peaks at middle age when people have reached their maximum career potential. In the book, a Question of Intelligence, Danial Seligman cites an IQ income correlation of 0.5 (25% of the variance).

0ther effects

Economic and social correlates of IQ

Factors	Correlation
School grades and IQ	0.5
Total years of education and IQ	0.55
IQ and parental socioeconomic status	0.33
Job performance and IQ	0.54
Negative social outcomes and IQ	−0.2
IQs of identical twins	0.86
IQs of husband and wife	0.4
Heights of parent and child	0.47
GDP per capita and average national IQ	0.7

In addition, IQ and its correlation to health, violent crime, gross state product, and government effectiveness are the subject of a 2006 paper in the publication Intelligence. The paper breaks down IQ averages by U.S. states using the federal government's National Assessment of Educational Progress math and reading test scores as a source.

The book IQ and the Wealth of Nations claims to show that the GDP/person of a nation can in large part be explained by the average IQ score of its citizens. This claim has been both disputed and supported in peer-reviewed papers. The data used have also been questioned.

Tambs et al. (1989) found that occupational status, educational attainment, and IQ are individually heritable; and further found that "genetic variance influencing educational attainment … contributed approximately one-fourth of the genetic variance for occupational status and nearly half the genetic variance for IQ". In a sample of U.S. siblings, Rowe et al. (1997) report that the inequality in education and income was predominantly due to genes, with shared environmental factors playing a subordinate role.

Some argue that IQ scores are used as an excuse for not trying to reduce poverty or otherwise improve living standards for all. Claimed low intelligence has historically been used to justify the feudal system and unequal treatment of women (but note that many studies find identical average IQs among men and women; see sex and intelligence). In contrast, others claim that the refusal of "high-IQ elites" to take IQ seriously as a cause of inequality is itself immoral.

Public policy

Main article: Intelligence and public policy

In the United States, certain public policies and laws regarding employment, military service, education and crime incorporate IQ or similar measurements. Internationally, certain public policies, such as improving nutrition and prohibiting neurotoxic toxins, have as one of their goals raising or preventing a decline in intelligence.

Criticism

The Mismeasure of Man

Some scientists dispute psychometrics entirely. In The Mismeasure of Man professor Stephen Jay Gould argued that intelligence tests were based on faulty assumptions and showed their history of being used as the basis for scientific racism. He wrote:

…the abstraction of intelligence as a single entity, its location within the brain, its quantification as one number for each individual, and the use of these numbers to rank people in a single series of worthiness, invariably to find that oppressed and disadvantaged groups—races, classes, or sexes—are innately inferior and deserve their status. (pp. 24–25)

He spent much of the book criticizing the concept of IQ, including a historical discussion of how the IQ tests were created and a technical discussion of why g is simply a mathematical artifact. Later editions of the book included criticism of The Bell Curve.

Professor Arthur Jensen responded to Gould's criticisms in a paper titled The Debunking of Scientific Fossils and Straw Persons.

The view of the American Psychological Association

In response to the controversy surrounding The Bell Curve, the American Psychological Association's Board of Scientific Affairs established a task force to write a consensus statement on the state of intelligence research which could be used by all sides as a basis for discussion. The full text of the report is available at a third-party website.

The findings of the task force state that IQ scores do have high predictive validity for individual differences in school achievement. They confirm the predictive validity of IQ for adult occupational status, even when variables such as education and family background have been statistically controlled. They agree that individual (but specifically not population) differences in intelligence are substantially influenced by genetics.

They state there is little evidence to show that childhood diet influences intelligence except in cases of severe malnutrition. They agree that there are no significant differences between the average IQ scores of males and females. The task force agrees that large differences do exist between the average IQ scores of blacks and whites, and that these differences cannot be attributed to biases in test construction. While they admit there is no empirical evidence supporting it, the APA task force suggests that explanations based on social status and cultural differences may be possible. Regarding genetic causes, they noted that there is not much direct evidence on this point, but what little there is fails to support the genetic hypothesis.

The APA journal that published the statement, American Psychologist, subsequently published eleven critical responses in January 1997, most arguing that the report failed to examine adequately the evidence for partly-genetic explanations.

The report was published in 1995 and thus does not include a decade of recent research.

Relation between IQ and intelligence

Several other ways of measuring intelligence have been proposed. See the Intelligence article.

Test bias

See also: Stereotype threat

The American Psychological Association's report Intelligence: Knowns and Unknowns (1995) states that that IQ tests are not biased against African Americans since they predict future performance, such as school achievement, similarly to the way they predict future performance for whites.

However, IQ tests may well be biased when used in other situations. A 2005 study finds some evidence that the WAIS-R is not culture-fair for Mexican American. Other recent studies have questioned the culture-fairness of IQ tests when used in South Africa.

Outdated methodology?

A 2006 paper finds that mainstream contemporary test analysis does not reflect substantial recent developments in the field and "bears an uncanny resemblance to the psychometric state of the art as it existed in the 1950s." This applies to many areas of mainstream experimental and quasi-experimental research, such as research on personality, attitudes, cognitive development, and intelligence. For example, it notes that some of the most influential recent studies on group differences in intelligence, in order to show that the tests are unbiased, use outdated methodology, if anything indicative of that test bias exist. It also states that "psychological testing also has a significant and direct impact on people’s lives—for instance, through the use of tests in psychiatric diagnoses or for the selection of employees—and at present such applications do not always stand on firm grounds, to say the least. Thus, we face a pressing obligation to improve the practice of psychological research, and this obligation is not merely of a scientific nature."

See also

• High IQ Societies
• Nature versus nurture
• Emotional intelligence
• Theory of multiple intelligences
• Gifted
• SAT
• Graduate Record Examination
• Child prodigy
• Compulsory sterilization
• Eugenics
• Mental chronometry
• Scientific Method

References

• Carroll, J.B. (1993). Human cognitive abilities: A survey of factor-analytical studies. New York: Cambridge University Press.
• Coward, W.M. and Sackett, P.R. (1990). Linearity of ability-performance relationships: A reconfirmation. Journal of Applied Psychology, 75:297–300.
• Duncan, J., P. Burgess, and H. Emslie (1995) Fluid intelligence after frontal lobe lesions. Neuropsychologia, 33(3): p. 261-8.
• Duncan, J., et al., A neural basis for general intelligence. Science, 2000. 289(5478): p. 457-60.
• Flynn, J.R. (1999). Searching for Justice: The discovery of IQ gains over time. American Psychologist, v. 54, p. 5-20
• Frey, M.C. and Detterman, D.K. (2003) Scholastic Assessment or g? The Relationship Between the Scholastic Assessment Test and General Cognitive Ability. Psychological Science, 15(6):373–378. PDF
• Gottfredson, L. S. (1997). "Why g matters: The complexity of everyday life." Intelligence, 24(1), 79–132. PDF
• Gottfredson, L.S. (1998). The general intelligence factor. Scientific American Presents, 9(4):24–29. PDF
• Gottfredson, L. S. (2005). Suppressing intelligence research: Hurting those we intend to help. In R. H. Wright & N. A. Cummings (Eds.), Destructive trends in mental health: The well-intentioned path to harm (pp. 155–186). New York: Taylor and Francis. Pre-print PDF PDF
• Gottfredson, L. S. (in press). "Social consequences of group differences in cognitive ability (Consequencias sociais das diferencas de grupo em habilidade cognitiva)". In C. E. Flores-Mendoza & R. Colom (Eds.), Introdução à psicologia das diferenças individuais. Porto Alegre, Brazil: ArtMed Publishers. PDF
• Gray, J.R., C.F. Chabris, and T.S. Braver, Neural mechanisms of general fluid intelligence. Nat Neurosci, 2003. 6(3): p. 316-22.
• Gray, J.R. and P.M. Thompson, Neurobiology of intelligence: science and ethics. Nat Rev Neurosci, 2004. 5(6): p. 471-82.
• Haier RJ, Jung RE, Yeo RA; et al. (2005). "The neuroanatomy of general intelligence: sex matters". NeuroImage. 25: 320–327. {{cite journal}}: Explicit use of et al. in: |author= (help)CS1 maint: multiple names: authors list (link)
• Harris, J. R. (1998). The nurture assumption : why children turn out the way they do. New York, Free Press.
• Hunt, E. (2001). Multiple views of multiple intelligence. [Review of Intelligence Reframed: Multiple Intelligences for the 21st Century.]
• Jensen, A.R. (1979). Bias in mental testing. New York: Free Press.
• Jensen, A.R. (1998). The g Factor. Praeger, Connecticut, USA.
• Jensen, A.R. (2006). "Clocking the Mind: Mental Chronometry and Individual Differences." Elsevier Science. --->New release scheduled for early June, 2006.
• Klingberg, T., Forssberg, H., & Westerberg, H. (2002). Training of working memory in children with ADHD. Journal of Clinical & Experimental Neuropsychology, 24, 781-791.
• McClearn, G. E., Johansson, B., Berg, S., Pedersen, N. L., Ahern, F., Petrill, S. A., & Plomin, R. (1997). Substantial genetic influence on cognitive abilities in twins 80 or more years old. Science, 276, 1560–1563.
• McDaniel, M.A. (2005) Big-brained people are smarter: A meta-analysis of the relationship between in vivo brain volume and intelligence. Intelligence, 33, 337-346.
• Mingroni, M.A. (2004). "The secular rise in IQ: Giving heterosis a closer look". Intelligence 32: 65–83.
• Murray, Charles (1998). Income Inequality and IQ, AEI Press PDF
• Noguera, P.A. (2001). Racial politics and the elusive quest for excellence and equity in education. In Motion Magazine article
• Plomin, R., DeFries, J. C., Craig, I. W., & McGuffin, P. (2003). Behavioral genetics in the postgenomic era. Washington, DC: American Psychological Association.
• Plomin, R., DeFries, J. C., McClearn, G. E., & McGuffin, P. (2001). Behavioral genetics (4th ed.). New York: Worth Publishers.
• Rowe, D. C., W. J. Vesterdal, and J. L. Rodgers, "The Bell Curve Revisited: How Genes and Shared Environment Mediate IQ-SES Associations," University of Arizona, 1997
• Schoenemann, P.T., M.J. Sheehan, and L.D. Glotzer, Prefrontal white matter volume is disproportionately larger in humans than in other primates. Nat Neurosci, 2005.
• Shaw P, Greenstein D, Lerch J, Clasen L, Lenroot R, Gogtay N, Evans A, Rapoport J, and Giedd J (2006), "Intellectual ability and cortical development in children and adolescents". Nature 440, 676-679.
• Tambs K, Sundet JM, Magnus P, Berg K. "Genetic and environmental contributions to the covariance between occupational status, educational attainment, and IQ: a study of twins." Behav Genet. 1989 Mar;19(2):209–22. PMID 2719624.
• Thompson, P.M., Cannon, T.D., Narr, K.L., Van Erp, T., Poutanen, V.-P., Huttunen, M., Lönnqvist, J., Standertskjöld-Nordenstam, C.-G., Kaprio, J., Khaledy, M., Dail, R., Zoumalan, C.I., Toga, A.W. (2001). "Genetic influences on brain structure." Nature Neuroscience 4, 1253-1258.

External links

Collective statements

• The Wall Street Journal: Mainstream Science on Intelligence
• PDF Reprint - Mainstream science on intelligence: An editorial with 52 signatories, history, and bibliography.
• APA: Intelligence: Knowns and Unknowns
• APA Committee on Online Psychological Tests and Assessment report

Review papers

• Scientific American: Intelligence Considered