Read The Bell Curve: Intelligence and Class Structure in American Life Online
Authors: Richard J. Herrnstein,Charles A. Murray
Tags: #History, #Science, #General, #Psychology, #Sociology, #Genetics & Genomics, #Life Sciences, #Social Science, #Educational Psychology, #Intelligence Levels - United States, #Nature and Nurture, #United States, #Education, #Political Science, #Intelligence Levels - Social Aspects - United States, #Intellect, #Intelligence Levels
37
The actual figure, based on all births through 1990, was 95.7. It is produced by taking the mean (using sample weights as always) of the IQ associated with the mother of each child born to an NLSY mother.
38
Out of every 100 women ages 30 to 34 in 1990, only 2 had their first birth that year; after age 34, the proportion fell rapidly to near zero. See Bachu 1991, Table 4. We realize that many readers know personally of numerous women who had their first babies in their late thirties. It is one more useful example of the difference between the world in which most of our readers live and the rest of the country.
39
Women of the NLSY who had reached ages 32 to 33 may be expected to have borne about 83 percent of all the babies they will ever bear (interpolated from National Center for Health Statistics 1991, Table 2).
40
The biases will understate the age differential by cognitive class because (based on known patterns of childbearing by women of different educational
groups) the largest change in the final mean age of births will occur among the brightest women.
41
Bachu 1993, Table 2.
42
This finding echoes points made in other places. We showed earlier (see Chapter 8) that it is not IQ per se that depresses fertility but the things that a higher IQ results in, such as more education (see Retherford and Sewell 1989; Rindfuss, Morgan, and Spicegood 1980). At given IQ scores, blacks get more schooling than either whites or Latinos (Chapters 13,18). Hence we should not be surprised that, at given IQ scores, blacks have lower fertility than either of the other groups; they are more likely to be still in school.
43
Rindfuss, Morgan, and Spicegood 1980; Osborne 1973; Chen and Morgan 1991b.
44
Chen and Morgan 1991a; Rindfuss, Morgan, and Spicegood 1988.
45
The quotation is taken from Baker and Mott 1989, p. 24.
46
To mention just one of the most important reasons to hedge, the participation of Latino mothers in the NLSY testing program was comparatively low, making the white-Latino comparison quite tentative. And as we cautioned in Chapter 14, the PPVT is probably less valid for Latinos than for other groups. This may bear on the comparison between Latino-white differences among mothers and among children. In any case, the figure for the apparent dysgenic effect for the Latino-white comparison is small enough to deter strong conclusions.
In contrast, the black-white apparent dysgenic effect is large, and we examined it using several methods to see if it might be spurious. The table on page 356 reports the results using the children’s sample weights, and comparing tested children with the mothers of those children, counting a mother more than once if she had more than one child and counting the same child more than once if he or she had been tested in more than one year (after turning 6). If we repeat the same calculation but including all children who were tested (including those under the age of 6), the black-white difference among the mothers is 13.9 points, compared to a difference among the children of 20.0 points, an even larger dysgenic difference than the one produced by the children ages 6 and older. Another approach is to discard the sample weights (which are problematic in several respects, when comparing across test years) and instead restrict the sample to children born to mothers who were in the cross-sectional NLSY sample. Doing so for all children who took the PPVT after the age of 6 produces a B/W difference of 14.8 points for the mothers and 18.1 points for the children, or a dysgenic difference of 3.3 points. Doing so for all children who took the PPVT produces a B/W difference of 14.9 points for the mothers and 19.4 for the children, or a dysgenic difference of 4.5 points.
Our next step was to examine separately the results from the three test years (1986, 1988, and 1990). For the children who were 6 or older when they took the test (which again shows a smaller difference than when the test includes all children), the B/W differences for the three test years, using sample weights, were 5.9, 1.9, and 3.0 points, respectively. The differences across test year did not affect the conclusion that a significant dysgenic effect exists, but the reasons for the differences are worth investigating.
In our attempt to see whether the dysgenic effect could be attenuated, we repeated all of these analyses with one difference: Instead of using the national norms for the PPVT (normed to a mean of 100 and SD of 15), we let the NLSY children be their own reference group, comparing the black and white scores using the observed mean and standard deviation for all NLSY children who took the test. This procedure reduces the estimate of the dysgenic effect. For example, the results, using sample weights, for the children who were 6 and older, showed an increasing B/W gap of 1.9 points instead of the 3.9 points produced by using the national norms. The difficulty in interpreting this finding is that the procedure itself has no good rationale. The PPVT national norms seem to have been properly determined. If anything, the Flynn effect should mean that the NLSY children, taking the test anywhere from seven to eleven years after the norms were established, should have a 2- to 3-point IQ edge when compared to the national norms. So we have no reason to think that the lower estimate is the correct one, but it does represent the best way we could concoct to minimize the B/W dysgenic effect.
Finally, we explored how the births to NLSY women might affect these findings by comparing black and white women who had not borne a child as of 1990. The mean IQ for the childless white women was 106.6, compared to 100.3 for childless black women. That black women without children have a mean of 100 is in itself striking evidence of the low fertility among the top part of the black IQ distribution, but even if subsequent fertility for the two groups is the same, the B/W gap in the next generation will presumably continue to diverge as the NLSY women complete their fertility.
47
New York Times.
“Slighting words, fighting words.” Feb. 13, 1990, p. A24.
48
The computation in the text counts each mother as many times as she had children who were tested. If instead each mother is counted only once, the white-black difference among mothers is 1.12 SDs. The white-Latino difference is 1.05 SDs.
49
Auster 1990; Bouvier 1991; Gould 1981; Simon 1989; Wattenberg 1987; Wattenberg and Zinsmeister 1990.
50
Holden 1988.
51
E.g., Higham 1973; Lukacs 1986.
52
Simon 1989. For a symposium, see Simon et al. 1993.
53
Auster 1990, and various contributors in Simon et al. 1993.
54
Bouvier and Davis 1982. This particular estimate is based on annual immigration of 1 million.
55
The figures for the 1950s, 1960s, and 1970s were 11 percent, 16 percent and 18 percent respectively.
SAUS
1992, Table 14 (
SAUS
1971, Table 4).
56
Lynn 1991.
57
SAUS
1992, Table 8. The figures also includes once-illegal immigrants who were granted permanent residence under the Immigration Reform and Control Act of 1986.
58
Sowell 1981.
59
A first, elementary consideration is that the NLSY data refer almost exclusively to the children of the adults who decided to immigrate. Whatever self-selection for IQ might have existed in the elders will be less visible in their offspring.
60
Carliner 1980; Chiswick 1978; Gabriel 1991.
61
Borjas 1987. Borjas’s formulation also draws on Roy 1951 and Sjaastad 1962. In forthcoming papers, Borjas has since extended his analysis through the 1990 census, showing a continuation of the trends from 1970 to 1980. Borjas 1993, 1994.
62
Borjas 1987, Table 3.
63
Sowell 1981, p. 220.
64
Borjas 1987, Table 3.
65
Borjas 1987, p. 552.
66
The procedure is limited to the NLSY’s cross-sectional sample (i.e., omitting the supplemental samples), so that sample weights are no longer an issue. Using random numbers, subjects with IQ scores above 97 had an equal chance of being discarded. Because different subsamples could yield different results, we created two separate samples with a mean of 97 and replicated all of the analyses. The data reported in the table on page 368 represent the average produced by the two replications, compared to the national mean as represented by unweighted calculations using the entire cross-sectional sample.
67
Cattell 1938, as reprinted in Cattell 1983.
68
Cattell 1983, pp. 167, 168.
69
Cattell 1983, pp. 167, 175.
70
Cattell 1983, pp. 167, 169.
71
The procedures parallel those used for the preceding analysis of a mean of 97.
72
In effect, our sample with a mean of 97 shows what happens when people with above-average IQs decrease their fertility, and our sample of 103 shows
what happens when people with below-average IQs decrease theirs. When we changed the NLSY sample so that the mean fell to 97, we used a random variable to delete people with IQs above 97 until the average reached 97. This did not do much to get rid of people who had the problems; most of its effect was to diminish the supply of people without problems. When we changed the NLSY sample so that the mean rose to 103, we were randomly deleting people with IQs below 103. In the course of that random deletion, a significant number of people toward the bottom of the distribution—our Classes IV and V—were deleted. Suppose instead we had lowered the IQ to 97 by randomly
duplicating
subjects with IQs below 97. In that case, we would have been simulating what happens when people with below-average IQs increase their fertility, and the results would have been more closely symmetrical with the effects shown for the 103 sample.
73
These figures continue to be based on the cross-sectional NLSY sample, used throughout this exercise. The 1989 poverty rate for the entire NLSY sample, calculated using sample weights, was 10.9 percent.
1
A woman was classified as a chronic welfare recipient if she had received welfare for at least five years by the 1990 interview. Women with incomplete data on AFDC in the years following the birth of the first child or whose first child was born after 1985 were not scored on this variable.
2
We do not weight the computations for the overrepresentation of below-average IQ mothers, but we continue to use sample weights.
3
This represents the mean of the mothers of the NLSY children, with each mother counted once for each illegitimate child. Because of the inverse relationship between IQ and the number of illegitimate children, the mean counting each mother of an illegitimate child only once was higher: 89.
4
As in the case of illegitimacy, IQ and the number of children of divorced and separated mothers were inversely related. When the mother is counted only once regardless of the number of children, the mean is 94.
5
See Chapter 10 for a description of this intelligence test: (the PPVT).
1
A brief refresher (see Chapter 4) : A heritability of 60 percent (a mid-range estimate) says that 40 percent of the observed variation in intelligence would disappear if a magic wand wiped out the differences in those aspects of the environment that bear on intelligence. Given that variance is the standard deviation squared and that the standard deviation of IQ is 15, this means that 40 percent of 152 is due to environmental variation, which is to say that the variance would drop from 225 to 135 and the standard deviation
would contract to 11.6 instead of 15 if all the environmental sources of variation disappeared.
2
“A healthy mind in a healthy body.” Some of the history is recounted in Lynn 1990b. Abstracts of a series of studies by Stephen Schoenthaler and his associates on the effects of diet on intelligence and on antisocial, criminal behavior are in Schoenthaler 1991.
3
Stein et al. 1972.
4
Lynn 1990b.
5
Benton and Roberts 1988.
6
At the age of 12 and 13, youngsters’ scores rise during an eight-month period in the natural course of events. The dietary supplement, then, is affecting the rate of increase of the nonverbal, but not the verbal, scores.
7
Schoenthaler et al. 1991.
8
WISC-R. Block Design, a highly g-loaded subtest of WISC-R, showed little or no benefit of the food supplement.
9
Earlier work suggesting that reductions in refined sugar increase intelligence are now being reinterpreted as the effect not of sugar per se but of shifting the diet away from foods with little in the way of vitamins and minerals to more nutritious foods; see Schoenthaler et al. 1991; Schoenthaler Doraz, and Wakefield 1986. The basic point is that we have almost no idea of the pathway between diet or food supplements and intellectual development; assuming there is a path, it could be long and winding.
10
A child taking a pill that gives, say, one RDA is getting more than the recommended daily allowances, since the rest of his diet cannot be utterly devoid of vitamins and minerals.
11
For a failure to confirm an effect of vitamin-mineral supplements, see Crombie et al. 1990, and for a failure to find an effect on intelligence of diet short of chronic malnutrition, see Church and Katigbak 1991. For more general discussion of the issue, see Eysenck 1991; Lynn 1990; Yudkin 1991.