When the late Richard Herrnstein and I published The Bell Curve eleven years ago, the furor over its discussion of ethnic differences in IQ was so intense that most people who have not read the book still think it was about race. Since then, I have deliberately not published anything about group differences in IQ, mostly to give the real topic of The Bell Curve—the role of intelligence in reshaping America’s class structure—a chance to surface.
The Lawrence Summers affair last January made me rethink my silence. The president of Harvard University offered a few mild, speculative, off-the-record remarks about innate differences between men and women in their aptitude for high-level science and mathematics, and was treated by Harvard’s faculty as if he were a crank. The typical news story portrayed the idea of innate sex differences as a renegade position that reputable scholars rejected.
It was depressingly familiar. In the autumn of 1994, I had watched with dismay as The Bell Curve’s scientifically unremarkable statements about black IQ were successfully labeled as racist pseudoscience. At the opening of 2005, I watched as some scientifically unremarkable statements about male-female differences were successfully labeled as sexist pseudoscience.
The Orwellian disinformation about innate group differences is not wholly the media’s fault. Many academics who are familiar with the state of knowledge are afraid to go on the record. Talking publicly can dry up research funding for senior professors and can cost assistant professors their jobs. But while the public’s misconception is understandable, it is also getting in the way of clear thinking about American social policy.
Good social policy can be based on premises that have nothing to do with scientific truth. The premise that is supposed to undergird all of our social policy, the founders’ assertion of an unalienable right to liberty, is not a falsifiable hypothesis. But specific policies based on premises that conflict with scientific truths about human beings tend not to work. Often they do harm.
One such premise is that the distribution of innate abilities and propensities is the same across different groups. The statistical tests for uncovering job discrimination assume that men are not innately different from women, blacks from whites, older people from younger people, homosexuals from heterosexuals, Latinos from Anglos, in ways that can legitimately affect employment decisions. Title IX of the Educational Amendments of 1972 assumes that women are no different from men in their attraction to sports. Affirmative action in all its forms assumes there are no innate differences between any of the groups it seeks to help and everyone else. The assumption of no innate differences among groups suffuses American social policy. That assumption is wrong.
Turning to race, we must begin with the fraught question of whether it even exists, or whether it is instead a social construct. The Harvard geneticist Richard Lewontin originated the idea of race as a social construct in 1972, arguing that the genetic differences across races were so trivial that no scientist working exclusively with genetic data would sort people into blacks, whites, or Asians. In his words, “racial classification is now seen to be of virtually no genetic or taxonomic significance.”25
Lewontin’s position, which quickly became a tenet of political correctness, carried with it a potential means of being falsified. If he was correct, then a statistical analysis of genetic markers would not produce clusters corresponding to common racial labels.
In the last few years, that test has become feasible, and now we know that Lewontin was wrong.26 Several analyses have confirmed the genetic reality of group identities going under the label of race or ethnicity.27 In the most recent, published this year, all but five of the 3,636 subjects fell into the cluster of genetic markers corresponding to their self-identified ethnic group.28 When a statistical procedure, blind to physical characteristics and working exclusively with genetic information, classifies 99.9 percent of the individuals in a large sample in the same way they classify themselves, it is hard to argue that race is imaginary.
Homo sapiens actually falls into many more interesting groups than the bulky ones known as “races.”29 As new findings appear almost weekly, it seems increasingly likely that we are just at the beginning of a process that will identify all sorts of genetic differences among groups, whether the groups being compared are Nigerian blacks and Kenyan blacks, lawyers and engineers, or Episcopalians and Baptists. At the moment, the differences that are obviously genetic involve diseases (Ashkenazi Jews and Tay-Sachs disease, black Africans and sickle-cell anemia, Swedes and hemochromatosis). As time goes on, we may yet come to understand better why, say, Italians are more vivacious than Scots.
Out of all the interesting and intractable differences that may eventually be identified, one in particular remains a hot button like no other: the IQ difference between blacks and whites. What is the present state of our knowledge about it?
There is no technical dispute on some of the core issues. In the aftermath of The Bell Curve, the American Psychological Association established a task force on intelligence whose report was published in early 1996.30 The task force reached the same conclusions as The Bell Curve on the size and meaningfulness of the black-white difference. Historically, it has been about one standard deviation31 in magnitude among subjects who have reached adolescence;32 cultural bias in IQ tests does not explain the difference; and the tests are about equally predictive of educational, social, and economic outcomes for blacks and whites. However controversial such assertions may still be in the eyes of the mainstream media, they are not controversial within the scientific community.
The case for an unchanged black-white IQ difference is straightforward. If you take all the black-white differences on IQ tests from the first ones in World War I up to the present, there is no statistically significant downward trend. Of course the results vary, because tests vary in the precision with which they measure the general mental factor (g) and samples vary in their size and representativeness. But results continue to center around a black-white difference of about 1.0 to 1.1 standard deviations through the most recent data.39
The case for a reduction has two important recent results to work with. The first is from the 1997 re-norming of the Armed Forces Qualification Test (AFQT), which showed a black-white difference of .97 standard deviations.40 Since the typical difference on paper-and-pencil IQ tests like the AFQT has been about 1.10 standard deviations, the 1997 results represent noticeable improvement.41 The second positive result comes from the 2003 standardization sample for the Wechsler Intelligence Scale for Children (WISC-IV), which showed a difference of .78 standard deviations, as against the 1.0 difference that has been typical for individually administered IQ tests.42
One cannot draw strong conclusions from two data points. Those who interpret them as part of an unchanging overall pattern can cite another recent result, from the 2001 standardization of the Woodcock-Johnson intelligence test. In line with the conventional gap, it showed an overall black-white difference of 1.05 standard deviations and, for youths aged six to eighteen, a difference of .99 standard deviations.43
There is more to be said on both sides of this issue, but nothing conclusive.44 Until new data become available, you may take your choice. If you are a pessimist, the gap has been unchanged at about one standard deviation. If you are an optimist, the IQ gap has decreased by a few points, but it is still close to one standard deviation. The clear and substantial convergence that occurred in academic tests has at best been but dimly reflected in IQ scores, and at worst not reflected at all.
Whether we are talking about academic achievement or about IQ, are the causes of the black-white difference environmental or genetic? Everyone agrees that environment plays a part. The controversy is about whether biology is also involved.
It has been known for many years that the obvious environmental factors such as income, parental occupation, and schools explain only part of the absolute black-white difference and none of the relative difference. Black and white students from affluent neighborhoods are separated by as large a proportional gap as are blacks and whites from poor neighborhoods.45 Thus the most interesting recent studies of environmental causes have worked with cultural explanations instead of socioeconomic status.46
This brings us to the state of knowledge about genetic explanations. “There is not much direct evidence on this point,” said the American Psychological Association’s task force dismissively, “but what little there is fails to support the genetic hypothesis.”49 Actually, there is no direct evidence at all, just a wide variety of indirect evidence, almost all of which the task force chose to ignore.50
When you compare black and white mean scores on a battery of subtests, you do not find a uniform set of differences; nor do you find a random assortment. The size of the difference varies systematically by type of subtest. Asked to predict which subtests show the largest difference, most people will think first of ones that have the most cultural content and are the most sensitive to good schooling. But this natural expectation is wrong. Some of the largest differences are found on subtests that have little or no cultural content, such as ones based on abstract designs.
As long ago as 1927, Charles Spearman, the pioneer psychometrician who discovered g, proposed a hypothesis to explain the pattern: the size of the black-white difference would be “most marked in just those [subtests] which are known to be saturated with g.”58 In other words, Spearman conjectured that the black-white difference would be greatest on tests that were the purest measures of intelligence, as opposed to tests of knowledge or memory.
A concrete example illustrates how Spearman’s hypothesis works. Two items in the Wechsler and Stanford-Binet IQ tests are known as “forward digit span” and “backward digit span.” In the forward version, the subject repeats a random sequence of one-digit numbers given by the examiner, starting with two digits and adding another with each iteration. The subject’s score is the number of digits that he can repeat without error on two consecutive trials. Digits-backward works exactly the same way except that the digits must be repeated in the opposite order.
Digits-backward is much more g-loaded than digits-forward. Try it yourself and you will see why. Digits-forward is a straightforward matter of short-term memory. Digits-backward makes your brain work much harder.59
The black-white difference in digits-backward is about twice as large as the difference in digits-forward.60 It is a clean example of an effect that resists cultural explanation. It cannot be explained by differential educational attainment, income, or any other socioeconomic factor. Parenting style is irrelevant. Reluctance to “act white” is irrelevant. Motivation is irrelevant. There is no way that any of these variables could systematically encourage black performance in digits-forward while depressing it in digits-backward in the same test at the same time with the same examiner in the same setting.61
Even to begin listing the topics that could be enriched by an inquiry into the nature of group differences is to reveal how stifled today’s conversation is. Besides liberating that conversation, an open and undefensive discussion would puncture the irrational fear of the male-female and black-white differences I have surveyed here. We would be free to talk about other sexual and racial differences as well, many of which favor women and blacks, and none of which is large enough to frighten anyone who looks at them dispassionately.
Talking about group differences does not require any of us to change our politics. For every implication that the Right might seize upon (affirmative-action quotas are ill-conceived), another gives fodder to the Left (innate group differences help rationalize compensatory redistribution by the state).81 But if we do not need to change our politics, talking about group differences obligates all of us to renew our commitment to the ideal of equality that Thomas Jefferson had in mind when he wrote as a self-evident truth that all men are created equal. Steven Pinker put that ideal in today’s language in The Blank Slate, writing that “Equality is not the empirical claim that all groups of humans are interchangeable; it is the moral principle that individuals should not be judged or constrained by the average properties of their group.”82
Nothing in this essay implies that this moral principle has already been realized or that we are powerless to make progress. In elementary and secondary education, many outcomes are tractable even if group differences in ability remain unchanged. Dropout rates, literacy, and numeracy are all tractable. School discipline, teacher performance, and the quality of the curriculum are tractable. Academic performance within a given IQ range is tractable. The existence of group differences need not and should not discourage attempts to improve schooling for millions of American children who are now getting bad educations.
In university education and in the world of work, overall openness of opportunity has been transformed for the better over the last half-century. But the policies we now have in place are impeding, not facilitating, further progress. Creating double standards for physically demanding jobs so that women can qualify ensures that men in those jobs will never see women as their equals. In universities, affirmative action ensures that the black-white difference in IQ in the population at large is brought onto the campus and made visible to every student. The intentions of their designers notwithstanding, today’s policies are perfectly fashioned to create separation, condescension, and resentment—and so they have done.
The world need not be that way. Any university or employer that genuinely applied a single set of standards for hiring, firing, admitting, and promoting would find that performance across different groups really is distributed indistinguishably. But getting to that point nationwide will require us to jettison an apparatus of laws, regulations, and bureaucracies that has been 40 years in the making. That will not happen until the conversation has opened up. So let us take one step at a time. Let us stop being afraid of data that tell us a story we do not want to hear, stop the name-calling, stop the denial, and start facing reality.
CHARLES MURRAY is the W.H. Brady Scholar in Freedom and Culture at the American Enterprise Institute. His previous contributions to COMMENTARY, available online, include “The Bell Curve and Its Critics” (May 1995, with a subsequent exchange in the August 1995 issue).