The Bell Curve: Intelligence and Class Structure in American Life
Page 20
Which White Young Men Spent a Month or More Out of the Labor Force in 1989?
Cognitive Class Percentage
I Very 10
II Bright 14
III Normal 15
IV Dull 19
V Very dull 22
Overall average 15
SOCIOECONOMIC BACKGROUND VERSUS COGNITIVE ABILITY. The next step, in line with our standard procedure, is to examine how much of the difference may be accounted for by the man’s socioeconomic background. The thing to be explained (the dependent variable) is the probability of spending at least a month out of the labor force in 1989. Our basic analysis has the usual three explanatory variables: parental SES, age, and IQ. The results are shown in the figure below. In this analysis, we exclude all men who in either 1989 or 1990 reported that they were in school, the military, or were physically unable to work.
These results are the first example of a phenomenon you will see again in the chapters of Part II. If we had run this analysis with just socioeconomic background and age as the explanatory variables, we would have found a mildly interesting but unsurprising result: Holding age constant, white men from more privileged backgrounds have a modestly smaller chance of dropping out of the labor force than white men from deprived backgrounds. But when IQ is added to the equation, the role of socioeconomic background either disappears entirely or moves in the opposite direction. Given equal age and IQ, a young man from a family with high socioeconomic status was more likely to spend time out of the labor force than the young man from a family with low socioeconomic status.3 In contrast, IQ had a large positive impact on staying at work. A man of average age and socioeconomic background in the 2d centile of IQ had almost a 20 percent chance of spending at least a month out of the labor force, compared to only a 5 percent chance for a man at the 98th centile.
IQ and socioeconomic background have opposite effects on leaving the labor force among white men
Note: For computing the plot, age and either SES (for the black curve) or IQ (for the gray curve) were set at their mean values.
It is not hard to imagine why high intelligence helps keep a man at work. As Chapter 3 discussed, competence in the workplace is related to intelligence, and competent people more than incompetent people are likely to find the workplace a congenial and rewarding place. Hence, other things equal, they are more likely than incompetent people to be in the labor force. Intelligence is also related to time horizons. A male in his 20s has many diverting ways to spend his time, from traveling the world to seeing how many women he can romance, all of them a lot more fun than working forty hours a week at a job. A shortsighted man may be tempted to take a few months off here and there; he thinks he can always pick up again when he feels like it. A farsighted man tells himself that if he wants to lay the groundwork for a secure future, he had better establish a record as a reliable employee now, while he is young. Statistically, smart men tend to be more farsighted than dumb men.
In contrast to IQ, the role of parental SES is inherently ambiguous. One possibility is that growing up in a privileged home foretells low dropout rates, because the parents in such households socialize their sons to conventional work. But this relationship may break down among the wealthy, whose son has the option of living comfortably without a weekly paycheck. In any case, aren’t working-class homes also adamant about raising sons to go out and get a job? And don’t young men from lower-class homes have a strong economic incentive to stay in the labor force because they are likely to need the money? The statistical relationship with parental SES that shows up in the analysis suggests that higher status may facilitate labor force dropout, at least for short periods.
The analysis of labor force dropout is also the first example in Part II of a significant relationship that is nonetheless modest. When we know from the outset that 78 percent of white men in Class V—borderline retarded or below—did not drop out of the labor force for as much as a month, we can also infer that all sorts of things besides IQ are important in determining whether someone stays at work. The analysis we have presented adds to our understanding without enabling us to explain fully the phenomenon of labor force dropout.
EDUCATION. Conducting the analysis separately for our two educational samples (those with a bachelor’s degree, no more and no less, and those with a high school diploma, no more and no less) does not change the picture. High intelligence played a larger independent role in reducing labor force dropout among the college sample than among the high school sample. And for both samples, high socioeconomic background did not decrease labor force dropout independent of IQ and age. Once again, the probability of dropout actually increased with socioeconomic background.
JOB DISABILITIES
In the preceding analysis, we excluded all the cases in which men reported that they were unable to work. But it is not that simple. Low cognitive ability increases the risk of being out of the labor force for healthy young men, but it also increases the risk of not being healthy. The breakdown by cognitive classes is shown in the following table. The relationship of IQ with both variables is conspicuous but more dramatic for men reporting that their disability prevents them from working. The rate per 1,000 of men who said they were prevented from working by a physical disability jumped sevenfold from Class III to Class IV, and then more than doubled again from Class IV to Class V.
Job Disability Among Young White Males
No. per 1,000 Who Reported Being Prevented from Working by Health Problems Cognitive Class No. per 1,000 Who Reported Limits in Amount or Kind of Work by Health Problems
0 I Very Bright 13
5 II Bright 21
5 III Normal 37
36 IV Dull 45
78 V Very dull 62
11 Overall average 33
A moment’s thought suggests a plausible explanation: Men with low intelligence work primarily in blue-collar, manual jobs and thus are more likely to get hurt than are men sitting around conference tables. Being injured is more likely to shrink the job market for a blue-collar worker than a for a white-collar worker. An executive with a limp can still be an executive; a manual laborer with a limp faces a more serious job impediment. This plausible hypothesis appears to be modestly confirmed in a simple cross-classification of disabilities with type of job. More blue-collar workers reported some health limitation than did white-collar workers (38 per 1,000 versus 28 per 1,000), and more blue-collar workers reported being prevented from working than did white-collar workers (5 per 1,000 versus 2 per 1,000).
But the explanation fails to account for the relationship of disability with intelligence. For example, given average cognitive ability and age, the odds of having reported a job limitation because of health were about 3.3 percent for white men working in white-collar jobs compared to 3.8 percent for white men working in blue-collar jobs, a very minor difference. But given that both men have blue-collar jobs, the man with an IQ of 85 had double the probability of a work disability of a man with an IQ of 115.
Might there be something within job categories to explain away this apparent relationship of IQ to job disability? We explored the question from many angles, as described in the extended note, and the finding seems to be robust. For whatever reasons, white men with low IQs are more likely to report being unable to work because of health than their smarter counterparts, even when the occupational hazards have been similar.4
Why might intelligence be related to disability, independent of the line of work itself? An answer leaps to mind: The smarter you are, the less likely that you will have accidents. In Lewis Terman’s sample of people with IQs above 140 (see Chapter 2), accidents were well below the level observed in the general population.5 In other studies, the risk of motor vehicle accidents rises as the driver’s IQ falls.6 Level of education—to some degree, a proxy measure of intelligence—has been linked to accidents and injury, including fatal injury, in other activities as well.7 Smarter workers are typically more productive workers (see Part I), and we can presume that some
portion of what makes a worker productive is that he avoids needless accidents.
Whatever validity this explanation may have, however, it is unlikely to be the whole story. We will simply observe that self-reported health problems are subject to a variety of biases, especially when the question is so sensitive as one that asks, in effect, “What is your excuse for not looking for a job, young man?” The evidence in the NLSY regarding the seriousness of the ailments, whether a doctor has been consulted, and their duration raises questions about whether the self-reported disability data have the same meaning when reported by (for example) a subject who reports that he was two months out of the labor market because of a broken leg and another who reports that he has been out of the labor market for five years because of a bad back.
We leave the analysis of labor force participation with a strong case to be made for two points: Cognitive ability is a significant determinant of dropout from the labor force by healthy young men, independent of other plausibly important variables. And the group of men who are out of the labor force because of self-described physical disability tend toward low cognitive ability, independent of the physical demands of their work.
UNEMPLOYMENT
Men who are out of the labor force are in one way or another unavailable for work; unemployed men, in contrast, want work but cannot find it. The distinction is important. The nation’s unemployment statistics are calculated on the basis of people who are looking for work, not on those who are out of the labor force. Being unemployed is transitory, a way station on the road to finding a job or dropping out of the work force. But it is hard to see much difference between unemployment and dropping out in the relationship with intelligence. We begin with the basic breakdown, set out in the following table. The extremes—Classes I and V—differed markedly in the frequency of unemployment lasting a month or more, with Class V experiencing six times the unemployment of Class I. Class IV also had higher unemployment than the upper three-quarters of the IQ distribution.
Which White Young Men Spent a Month or More Unemployed in 1989?
Cognitive Class Percentage
I Very bright 2
II Bright 7
III Normal 7
IV Dull 10
V Very dull 12
Overall average 7
Socioeconomic Background Versus Cognitive Ability
The independent roles of our three basic variables are shown in the figure below. For a man of average age and socioeconomic background, cognitive ability lowered the probability of being unemployed for a month from 15 percent for a man at the 2d centile of IQ to 4 percent for men at the 98th centile. Neither parental SES nor age had an appreciable (or statistically significant) independent effect.
The Role of Education
Before looking at the numbers, we would have guessed that cognitive ability would be more important for explaining unemployment among the high school sample than among the college sample. The logic is straightforward: A college degree supplies a credential and sometimes specific job skills that, combined with the college graduate’s greater average level of intelligence, should reduce the independent role of IQ in ways that would not apply as strongly to high school graduates.8 But this logic is not borne out by the NLSY. Cognitive ability was more important in determining unemployment among college graduates than among the high school sample, although the small sample sizes in this analysis make this conclusion only tentative. Socioeconomic background and age were not independently important in explaining unemployment in the high school or college samples.
High IQ lowers the probability of a month-long spell of unemployment among white men, while socioeconomic background has no effect
Note: For computing the plot, age and either SES (for the black curve) or IQ (for the gray curve) were set at their mean values.
A CONCLUSION AND A REMINDER ABOUT INTERPRETING RARE EVENTS
The most basic implication of the analysis is that intelligence and its correlates—maturity, farsightedness, and personal competence—are important in keeping a person employed and in the labor force. Because such qualities are not entirely governed by economic conditions, the question of who is working and who is not cannot be answered just in terms of what jobs are available.
This does not mean we reject the relevance of structural or economic conditions. In bad economic times, we assume, finding a job is harder for the mature and farsighted as well as for the immature and the shortsighted, and it is easier to get discouraged and drop the search. Our goal is to add some leavening to the usual formulation. The state of the economy matters, but so do personal qualities, a point that most economists would probably accept if it were brought to their attention so baldly, but somehow it gets left out of virtually all discussions of unemployment and labor force participation.
As we close this discussion of cognitive ability and labor force behavior, let us be clear about what has and has not been demonstrated. In focusing on those who did drop out of the labor force and those who were unemployed, we do not want to forget that most white males at every level of cognitive ability were in the labor force and working, even at the lowest cognitive levels. Among physically able white males in Class V, the bottom 5 percent of the IQ distribution, comprising men who are intellectually borderline or clinically retarded, seven out of ten were in the labor force for all fifty-two weeks of 1989. Of those who were in the labor force throughout the year, more than eight out of ten experienced not a single week of unemployment. Condescension toward these men is not in order, nor are glib assumptions that those who are cognitively disadvantaged cannot be productive citizens. The world is statistically tougher for them than for others who are more fortunate, but most of them are overcoming the odds.
Chapter 8
Family Matters
Rumors of the death of the traditional family have much truth in them for some parts of white American society—those with low cognitive ability and little education—and much less truth for the college educated and very bright Americans of all educational levels. In this instance, cognitive ability and education appear to play mutually reinforcing but also independent roles.
For marriage, the general rule is that the more intelligent get married at higher rates than the less intelligent. This relationship, which applies across the range of intelligence, is obscured among people with high levels of education because college and graduate school are powerful delayers of marriage.
Divorce has long been more prevalent in the lower socioeconomic and educational brackets, but this turns out to be explained better by cognitive level than by social status. Once the marriage-breaking impact of low intelligence is taken into account, people of higher socioeconomic status are more likely to get divorced than people of lower status.
Illegitimacy, one of the central social problems of the times, is strongly related to intelligence. White women in the bottom 5 percent of the cognitive ability distribution are six times as likely to have an illegitimate first child as those in the top 5 percent. One out of five of the legitimate first babies of women in the bottom 5 percent was conceived prior to marriage, compared to fewer than one out of twenty of the legitimate babies to women in the top 5 percent. Even among young women who have grown up in broken homes and among young women who are poor—both of which foster illegitimacy—low cognitive ability further raises the odds of giving birth illegitimately. Low cognitive ability is a much stronger predisposing factor for illegitimacy than low socioeconomic background.
At lower educational levels, a woman’s intelligence best predicts whether she will bear an illegitimate child. Toward the higher reaches of education, almost no white women are having illegitimate children, whatever their family background or intelligence.
The conventional understanding of troubles in the American family has several story lines. The happily married couple where the husband works and the wife stays home with the children is said to be as outmoded as the bustle. Large proportions of young people are staying single. Half the
marriages end in divorce. Out-of-wedlock births are soaring.
These features of modern families are usually discussed in the media (and often in academic presentations) as if they were spread more or less evenly across society1 In this chapter, we introduce greater discrimination into that description. Unquestionably, the late twentieth century has seen profound changes in the structure of the family. But it is easy to misperceive what is going on. The differences across socioeconomic classes are large, and they reflect important differences by cognitive class as well.
MARRIAGE
Marriage is a fundamental building block of social life and society itself and thus is a good place to start, because this is one area where much has changed and little has changed, depending on the vantage point one takes.
From a demographic perspective, the changes are huge, as shown in the next figure. The marriage rate since the 1920s has been volatile, but the valleys and peaks in the figure have explanations that do not necessarily involve the underlying propensity to marry. The Great Depression probably had a lot to do with the valley in the early 1930s, and World War II not only had a lot to do with the spike in the late 1940s but may well have had reverberations on the marriage rate that lasted into the 1950s. It could even be argued that once these disruptive events are taken into account, the underlying propensity to marry did not change from 1930 to the early 1970s. The one prolonged decline for which there is no obvious explanation excepta change in the propensity to marry began in 1973, when marriage rates per 1,000 women began dropping and have been dropping ever since, in good years and bad. In 1987, the nation passed a landmark: Marriage rates hit an all-time low, dropping below the previous mark set in the depths of the depression. A new record was promptly set again in 1988.