Book Read Free

The Bell Curve: Intelligence and Class Structure in American Life

Page 84

by Richard J. Herrnstein


  68 The NLSY reported scores on these indexes for infants under 1 year of age, not analyzed here.

  69 This statement applies to the full white sample. In the cross-sectional sample, used for the regression results in Appendix 4, the role of birth status (legitimate or illegitimate) was not significant when entered along with poverty and welfare receipt.

  70 A technical note that applies to the means reported in the table on page 230 and in Chapter 15. In applying the national norms, the NLSY declined to estimate scores for very low-scoring children not covered in the PPVT’s scoring tables, instead assigning them a score of zero. For purposes of computing the means above and in Chapter 15, we assigned a score of 40 (four SDs below the mean, and the lowest score assigned in the standard tables for scoring the PPVT) to all children with scores under 40.

  71 Careful readers may be wondering why white children, who have had less than their fair share of the bottom decile for most of the other indicators, account for fully 10 percent of all NLSY children in the bottom decile. The reason is that the women of the NLSY sample (all races) have had a high proportion of low-IQ children, based on the national norms for the PPVT—fully 23 percent of all NLSY children ages 6 and older when they took the test had IQs of 80 or lower. For whites, 10 percent of the children who have been tested fall into the bottom decile. This news is not quite as bad as it looks. Just because the NLSY mothers were a nationally representative sample of women in a certain age group does not mean that their children are a nationally representative sample of children. But the news is nonetheless worrisome, with implications that are discussed in Chapter 15.

  72 See Chapter 4 for the discussion of heritability of IQ.

  Chapter 11

  1 The proportional increases in property crime tracked more or less with the increases in violent crime until the late 1970s. Since then, property crime has moved within a narrow range and in 1992 was actually lower than it had been ten years earlier. This divergence between violent and property crimes is in itself a potentially significant phenomenon that has yet to be adequately explored.

  2 For citations of the extensive literature on this subject, see Chaiken and Chaiken 1983; Wilson and Herrnstein 1985. The official statistics may have understated the increase in these “crimes that people consider serious enough to warrant reporting to the police,” insofar as many burglaries, assaults, and street robberies that would have been reported in the 1950s (when there was a reasonable chance that the police would conduct a genuine investigation) are no longer reported in urban areas, where it is taken for granted that they are too minor to compete for limited police resources.

  3 A more traditional way to sort the theories is to contrast classical theories, which depict crime as the rational behavior of free agents, based on costs and benefits, with positive theories, which look for the causes of crime in society or in psychological makeup (for discussion of criminological theory, see, for example, Gottfredson and Hirschi 1990; Wilson and Herrnstein 1985). We are distinguishing only among positive theories, because the notion of criminals as rational agents seems to fit few actual criminals and the role of costs and benefits can readily be absorbed by a positive theory of criminal behavior (see Wilson and Herrnstein 1985, Chap. 2). A distinction similar to ours between psychological and sociological theories is one between “psychiatric” and “criminological” theories in Wessely and Taylor 1991.

  4 Freeman 1983; Mayer and Jencks 1989; Wilson and Herrnstein 1985, Chaps. 11, 12.

  5 Cleckley 1964; Colaizzi 1989.

  6 Wilson and Herrnstein 1985.

  7 Wilson and Herrnstein 1985.

  8 In fact, within criminological theory, the distinction between being disposed to break the law and being disposed to obey it has some resonance, as illustrated in, for example, Gottfredson and Hirschi 1990. This is a fine point of theory, which we cannot elaborate on here.

  9 For more extended discussion of the logic of the link between IQ and committing crime, see Gottfredson and Hirschi 1990; Hirschi 1969; Wilson and Herrnstein 1985.

  10 Goring 1913.

  11 Goddard l914.

  12 Murchison 1926. We know now that this was a peculiarity of a federal prison like Leavenworth, which had relatively few of the run-of-the-mill offenders typical in state prisons.

  13 Sutherland 1931.

  14 Haskell and Yablonsky 1978, p. 268.

  15 Reid 1979, p. 156.

  16 Hirschi and Hindelang 1977.

  17 Reid 1982.

  18 A balanced, recent summary says, “At this juncture it seems reasonable to conclude that the difference [between offenders and nonoffenders in intelligence] is real and not due to any of the possible methodological or confounding factors that have been noted in the literature” (Quay 1987 p. 107ff.)·

  19 The gap between offenders and nonoffenders is typically larger on verbal than on performance (i.e., nonverbal) intelligence tests (Wilson and Herrnstein 1985). It has been suggested that this is because the essential difference between offenders and nonoffenders is the difference in g; it is well known that verbal scores are more dependent on g than performance scores (Gordon 1987; Jensen and Faulstich 1988). Another, not necessarily inconsistent, interpretation is that verbal intelligence scores do better at measuring the capacity for internalizing the prohibitions that help deter crime in nonoffenders (Wilson and Herrnstein 1985). Multiple offenders, as distinguished from offenders in general, also have significant deficits in logical reasoning ability per se (Reichel and Magnusson 1988). Whatever the reason for these patterns of differences, the methodological implications are clear: The rare study that fails to find much of an association between IQ and offending may have used nonverbal scores or scores that, for one reason or another, minimize individual differences in g.

  20 E.g., Blumstein et al. 1985; Denno 1990. National studies of convicts who get rearrested after release also show that those with low levels of education (which are presumably correlated with low test scores) are at higher risk for recidivism (Beck and Shipley 1989).

  21 Lipsitt et al. 1990.

  22 Reichel and Magnusson 1988.

  23 Hirschi 1969; Wilson and Herrnstein 1985.

  24 Nicholson and Kugler 1991.

  25 The evidence in fact suggests that smart offenders pick crimes with lesser likelihood of arrest and larger payoffs (Wilson and Herrnstein 1985).

  26 Moffitt and Silva 1988; Hindelang et al. 1981; Hirschi and Hindelang 1977; Wilson and Herrnstein 1985.

  27 Reichel and Magnusson 1988.

  28 Kandel et al. 1988.

  29 In this sample, there was no significant correlation between IQ and socioeconomic status, and IQ remained a significant predictor of offending even after the effects of parental SES and the sons’ own level of education were entered as covariates in an analysis of covariance.

  30 White et al. 1989.

  31 Werner and Smith 1982.

  32 Werner 1989; Werner and Smith 1982.

  33 For an entry into this literature, see Farrington and West 1990; Gottfredson and Hirschi 1990; Mednick and others 1987; Wilson and Herrnstein 1985.

  34 In this regard, it is perhaps worth mentioning that we originally intended for this book to be about individual differences generally and social policy, with intelligence as the centerpiece. We narrowed the focus to intelligence partly because it looms so much larger than any other individual trait in explaining what is going on, but also out of necessity: Only for criminal behavior is the scientific literature extensive enough to have permitted a thoroughgoing presentation of individual differences other than intellectual

  35 The most serious problem is the established and pronounced tendency of black juveniles to underreport offenses (Hindelang 1978, 1981).

  36 Not surprisingly, the most serious offenders are the ones who most often underreport their crimes. Serious offenders are also the ones most likely to go uninterviewed in survey research. At the other extreme, minor offenders brag about their criminal exploits. They inflate the real level o
f “crime” by putting minor incidents (for example, a school-yard fistfight, which can easily fit the technical definition of “aggravated assault”) in the same category with authentically felonious attacks.

  Since we are focusing on the role of intelligence, self-report data pose a special problem, for it has been observed that people of low intelligence are less candid than brighter respondents. This bias would tend to weaken the correlation between IQ and crime in self-report data.

  37 The authoritative source on self-report data for juveniles is still Hindelang et al. 1981. See also Hindelang 1978, 1981; Smith and Davidson 1986.

  38 Wolfang, Figlio, and Sellin 1972; Wilson and Herrnstein 1985.

  39 These results for the entire age range are substantially the same when age subgroups are examined, but some differences may be found. Those who become involved with the criminal justice system at an early age tended to have lower intelligence than those who first become involved later in their teens.

  40 This represents the top decile of white males. To use the same index across racial groups is inadvisable because of the different reporting characteristics of whites and blacks.

  41 For a review of the literature, see Wilson and Herrnstein 1985.

  42 Elliott and Voss 1974.

  43 Thornberry et al. 1985 uses the Philadelphia Cohort Study to demonstrate rising crime after dropout for that well-known sample.

  44 The sample includes those who got a GED—most of whom had gotten it at the correctional institution in which they were incarcerated at the time of their interview. The results are shown in Appendix 4.

  Chapter 12

  1 Gove 1964. The definition is listed, sadly, as “obsolete.” We can think of no modern word doing that semantic job now.

  2 More recently, Walter Lippmann used civility in his worrying book (Lippmann 1955) about what he feared was disappearing with the rising “Jacobinism” of American political life, the shift he saw early in the century away from representative government toward populist democracy. Early in his career as a journalist and social commentator (Lippmann 1922b), Lippmann noted that the ordinary, private person sets the concerns of governance very low on his or her list of priorities. To govern us, he said, we needed a special breed of person, leaders with the capacity to fathom, and the desire to promote, the public good. That capacity is what he called civility. For a reflection on Lippmann’s conception of civility by a social scientist, see Burdick 1959.

  3 There are other rationales for not voting, as, for example, the one promoted on a T-shirt favored by libertarians: “Don’t vote. It only encourages them.”

  4 For an attempt to construe voting as a rational act from the economic standpoint, see Downs 1957.

  5 Aristotle 1905 ed., p. 1129.

  6 Although the sample was not strictly representative of the American population, it was a broad cross-section, unlikely to be atypical except as a result of its underrepresentation of rural and minority children. Hess and Torney 1967.

  7 The second graders were excluded from some of the analyses because some questionnaire items evoked too high a rate of meaningless or nonresponses.

  8 A measure of political efficacy was based on the children’s “agree” or “disagree” responses to five statements, including: “I don’t think public officials care much what people like me think.” Or, “People like me don’t have any say about what the government does.”

  9 Harvey and Harvey 1970.

  10 The exceptions included the measures for political efficacy and political participation, both of which were barely correlated with intelligence, although slightly correlated with socioeconomic status (primarily via parental education, rather than family wealth). The authors speculated that the rising cynicism of the young during the later 1960s may in part account for these deviant results.

  11 Like other studies (e.g., Neuman 1986, see below), this one also found that the more intelligent someone is, the more likely he or she is to be liberal on social issues and conservative on economic ones. Chauvinistic, militaristic, and anticommunistic attitude were inversely related to intelligence.

  12 For a brief summary of this literature as of the late 1960s, see White 1969, who similarly concludes that political socialization, as he calls it, is highly dependent on intelligence itself rather than on socioeconomic status.

  13 Sidney Verba and Norman Nie ( 1972), leading scholars of American voting, distinguish cogently between the study of politics as a political scientist approaches it and political psychology. A political scientist mostly wants to understand how political participation shapes the choices a community makes; a political psychologist tries to understand the participation itself. This chapter comes closer to political psychology than to political science.

  14 Campbell et al. 1960; Milbrath and Goel 1977; Verba and Nie 1972; Wolfinger and Rosenstone 1980.

  15 Wolfinger and Rosenstone 1980, p. 13.

  16 Verba and Nie 1972.

  17 The one exception, the frequency with which an individual contacted political officials for matters of personal concern, showed no such correlation, but it is also the most ambiguously political. See Verba and Nie 1972.

  18 There are hints, however, that, if socioeconomic status had been broken into components of educational level and income, educational level would have predicted political participation better than income. See Figures 6-1 to 6-3 in Verba and Nie 1972.

  19 Wolfinger and Rosenstone 1980. In even-numbered years, the CPS, a survey conducted monthly of a nationally representative sample of tens of thousands of Americans, asks about voting in the November election. These surveys also include data on income, occupation, education, and other personal and regional variables. The Wolfinger and Rosenstone analysis was based on the entire sample of almost 100,000 respondents in the November surveys in 1972 and 1974 and a random subsample used for more detailed modeling. The main technIQue they used is the probit analysis, a form of multivariate analysis for estimating the changes in probability of some dependent variable—voting, in this case—associated with a change in an independent variable—educational attainment, for example—after the effects of the other variables—say, income or occupational level—are taken account of.

  20 E.g., Peterson 1990.

  21 Neuman 1986. This book aggregates data from nine studies of voting between 1948 and 1980 and comes up with a measure of “political sophistication,” which seems to have considerable power in explaining much about voting, including simple turnout. The “key causal factor” for political sophistication, Neuman found, is education, which explained four times as much of the variance in sophistication as the next most influential factor in a list that included age, race, sex, the other components of socioeconomic status, parental behavior, and region of the country.

  22 Wolfinger and Rosenstone 1980, p. 19.

  23 Besides the works already cited, for other overviews coming to the same basic conclusion, see Campbell et al. 1960; Milbrath and Goel 1977; Neuman 1986.

  24 “It is difficult to find support in our data for notions that a generic status variable plays any part in the motivational foundations of the decision to vote” (Wolfinger and Rosenstone 1980, p. 35). Perhaps there is some effect of income on voting at the lowest levels but throughout the range of income, it seems to have no independent predictive value of its own.

  25 Verba and Nie 1972, p. 335.

  26 How someone votes, rather than whether, can be more plausibly connected to the outward benefits gained from the outcome of an election. And many political scientists focus more on political preference than on level of engagement. Political preferences, too, have their individual correlates, but we will not try to summarize these results as well (but see, for example, Fletcher and Forbes, 1990; Granberg and Holmberg 1990; Milbrath 1977; Neuman 1986; Nie et al. 1976).

  27 There is an indirect argument to be made by combining four observations: (1) We know for sure that one of the traits roughly measured by educational attainment is intelligence. (2) As
we showed in Chapter 1, American educational opportunities are more efficiently distributed by cognitive ability than they have ever been, here or elsewhere. (3) It is here and now that we see the strongest correlations between voting and educational attainment. (4) In countries where education and cognitive ability are not so thoroughly enmeshed, education has less impact on voting. To fill in the story: During the 1950s and 1960s, the level of political participation rose more rapidly than the educational level of the population (Verba and Nie 1972, p. 252). Looking backward, we see the other side of the same coin. In 1870, only 2 percent of the American population had finished high school; even fewer were going to college. Yet voting rates may have been higher than they are now. Kleppner (1982) concludes that voting rates were more than 11 percentage points above where they should have been, had education had the same effects in the 1880s that they had in 1968. Shortridge (1981) has a lower estimate of voter turnout in the late nineteenth century, but still one that exceeds expectations, given the educational levels of the period. Proper historical comparisons must, of course, take into account changes in voting laws, in poll taxes, in registration requirements, as well as the effects of the extension of suffrage to women and to 18- to 20-year olds. However, after all those corrections are made, scholars agree that past voting rates (post-Civil War, nineteenth century, for example) are incommensurately high or present rates are incommensurately low, given the changes in levels of formal education of the general public. Except in the South of the Reconstruction, the correlation between education and voting rate was negative from 1876 to 1892, just the reverse of what it is now (see Kleppner 1982). The international data indicating that education is less important in voting where education is not so enmeshed with cognitive ability come from Milbrath and Goel (1977).

  28 Exposure to political print media was another influential factor, but this, too, turned out to be most strongly associated with rated intelligence (see Luskin 1990).

 

‹ Prev