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To estimate the effects of genes versus social environment upon something like intelligence, intelligence must first be measured accurately--that is, measured with little or no measurement error. Considerable debate exists about this issue--even apart from the question of the relative effect of genes versus social environment. Some researchers argue that intelligence and academic potential are quite accurately measured today, with little measurement error. At the same time, other researchers argue with equal verve that standardized ability tests today are not very accurate or fair measures of intelligence or academic potential of minorities as opposed to whites, of women as opposed to men, and of working-class persons as opposed to upper-middle- and upper-class persons. Both sides note, however, that achievement (specific subject) tests, as opposed to "ability" tests, are somewhat more valid across these groups.

Intelligence is an abstract concept; individuals are presumed to differ or vary from each other. "Intelligence" is itself not directly observable or measurable, but it is inferred to exist, to greater or lesser degrees, from actual results obtained on a test or indicator, such as an IQ test or the SAT (Scholastic Assessment Test). Thus "intelligence" (concept) is distinct from "intelligence test" (presumed indicator). The extent to which the indicator accurately measures how individuals differ on the concept is called the validity of the indicator or test. If the test lacks validity, then by definition some measurement error exists in the test. For example, what is called the "predictive validity" of a test, such as an IQ test (like the Stanford Binet or the Wechsler test) or the SAT, is the extent to which it predicts some later measured criterion, such as freshman-year college grades earned after taking the test. In other words, does the test do (predict) what it is supposed to? Hence, if for a sample of individuals, the higher one's SAT score and the higher one's freshman grade average (that is, if the test and grades had a high correlation), then the test would by definition have high predictive validity. If one's SAT score bore no such relationship (no correlation) to freshman grades, then the test would have low or no predictive validity.

The differential predictive validity of a test is the degree to which it predicts the same or differently, test-to-criterion, for different racial/ethnic groups, different social classes, or the two different genders. Thus if an ability test taken in high school predicts freshman grades in college to the same degree (with the same correlation and/or slope) for whites as for blacks, then the test would be considered to be of equal predictive validity for both racial groups. By definition, the test would then be considered racially unbiased--even if whites scored on the average higher on the test than blacks--as is the case with the SAT, on which blacks (and Hispanics) score about 100 points less on average than whites (on the 200-800 points scale per section). The lower average score for blacks would then be attributed to two possible causes. First, the genetic (nature) explanation, which states that, assuming the test is not biased, the average difference in test score is due to fewer "intelligence" genes on the part of blacks and Hispanics. (More on this follows, under "Heritability.") Second, the social environmental (nurture) explanation states that, again assuming that the test is not biased, the average black-white (and Hispanic-white) difference in test score occurs because of fewer educational opportunities and more environmental deprivation for blacks and Hispanics, rather than different genes.

But all this assumes zero measurement error; that is, the same predictive validity between racial groups. The fact of the matter is that, as shown in more than 100 studies of differential predictive validity, considerably more studies show different (lower) validities for blacks and Hispanics than for whites. A small number of studies do indeed show the same predictive validities for all three racial groups, but those showing different validities--thus measurement bias (measurement error) in the test--are far more numerous and also more recent. This means that the tests are significantly more biased--with significantly more measurement error--in the case of blacks and Hispanics than in the case of whites. (Asians tend to fall between whites on one hand and blacks and Hispanics on the other on predictive validity, even though Asians score on average higher than whites on the SAT math sections and somewhat lower on the verbal sections.)

The same issue applies to comparisons of females to males and to comparisons across social classes, as upper (or middle) class versus working class. While females and males score on average about the same on the SAT verbal (and writing) sections, men have consistently outperformed women on the mathematics (quantitative) sections. Some argue that this is because of "inherent" (genetic?) intellectual differences between men and women--a position once taken by the president of Harvard University, Lawrence Summers. But the results of quite a few studies on test bias strongly suggest otherwise: differential predictive validity, predicting college grades from SAT math scores, is higher (in correlation) for men than for women. This means that by definition, the test is biased (in the prediction sense) against women. And women tend to get higher grades in the sciences in college than their SATs would predict. In this sense women's grades are underpredicted. This finding is buttressed by two kinds of evidence. First, the SAT, as well as intelligence tests, contains a number of sex-typed (thus biased) questions on the word-math problems (questions more relevant to traditional male socialization practices, like calculating the volume of an automobile crankcase, than to traditional female socialization practices, such as calculating the volume of a pot on the stove). Second, evidence, especially recent evidence, shows that overall socialization practices in general differ between boys and girls as children and as teens, thus leading to different cultures for men and women. Thus cultural differences between female and male show up as test bias on tests such as the SAT, as is the case also with racial/ethnic comparisons.

Finally, there is the case of social class differences. In general, the higher one's family (parents') income (and education), then the higher one's test score. This is a consistent, well-documented, clear relationship found in literally all studies. This relationship remains the same even when one compares people of different social classes who are of the same race. The richer your parents are, the more likely you are to score on average higher on the SAT (and the ACT as well). The poorer your parents, the lower your test score. In addition, the lower the social class of the test-taker, the less the predictive validity of the SAT test. So the SAT has some class bias in it, just as it has bias on the basis of race and of gender. Two arguments for all this are, first, families of higher social class (higher parental income, education, and occupational status) are more able to give their children better educations, wider experiences, and more cultural advantages, which all translate into higher test scores and also higher predictive validity of the test. Second, families of higher social class are more likely able to foot the bill for a test-taking seminar (such as the well-known Kaplan Seminars or Princeton Review series), which are expensive and currently cost $1,000 or more for one sequence of test prep sessions. Thus, the often heard argument that the lower a person's social class, the less intellectual genetic endowment the person has (the argument advanced a few years back by the bestselling book entitled The Bell Curve [1994]) is untenable given the evidence of both less test validity for lower-class persons and fewer economic and cultural advantages for them.

References:

1) Bouchard, Thomas J., Jr. 1998. "Genetic and Environmental Influences on Adult Intelligence and Special Mental Abilities." Human Biology 70(April):257-79.

2) Bouchard, Thomas J., Jr. and Matt McGue. 2003. "Genetic and Environmental Influences on Human Psychological Differences." Journal of Neurobiology 54(1):4-45.

3) Chipuer, Heather M., Michael J. Rovine, and Robert Plomin. 1990. "LISREL Modeling: Genetic and Environmental Influences on IQ Revisited." Intelligence 14(1):11-29.

4) Gardner, Howard. 1998. "A Multiplicity of Intelligences." Scientific American Presents 9(Winter):19-23.

5) Goldberger, Arthur S. 1977. "Twins Methods: A Skeptical View." Pp. 299-324 in Kinometrics: Determinants of Socioeconomic Success Within and Between Families, edited by P. Taubman. New York: North-Holland.

6) Goldberger, Arthur S. 1979. "Heritability." Econometrica 46(November): 327-47.

7) Herrnstein, Richard J. and Charles Murray. 1994. The Bell Curve: Intelligence and Class Structure in American Life. New York: Free Press.

8) Jensen, Arthur R. "How Much Can We Boost IQ and Scholastic Achievement?" Harvard Educational Review 39:1-123.

9) Kamin, Leon J. 1974. The Science and Politics of I.Q. Potomac, MD: Erlbaum.

10) Manning, Winton H. 1968. "The Measurement of Intellectual Capacity and Performance." Journal of Negro Education 37:258-67.

11) Scarr, Sandra. 1981. Race, Social Class and Individual Differences in IQ. Hillsdale, NJ: Erlbaum.

12) Steele, Claude M. 1999. "Stereotyping and Its Threat Are Real." American Psychologist 53(June):690-91.

13) Taylor, Howard F. 1980. The IQ Game: A Methodological Inquiry Into the Heredity-Environment Controversy. New Brunswick, NJ: Rutgers University Press.

14) Taylor, Howard F. 1995. "Review Essay: The Bell Curve." Contemporary Sociology 24(March):153-58.

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