The Bell Curve: Intelligence and Class Structure in American Life (93 page)

But there is a more direct way of asking whether
g
is a valid construct:
g
is a construct in the same way that energy is a construct. Both have theoretical underpinnings, but neither is a reified “thing.” Evidence that they are useful constructs is found in the ways they relate to real-world phenomena. In the case of
g,
we have three possibilities. One is that
g
is an arbitrary creation of number crunching. If so, it should be nothing but noise in statistical analysis, showing no more relationship to phenomena in the real world than numbers generated by a random number table. A second possibility is that
g
is a surrogate for something else—a proxy measure of educational attainment, perhaps, or socio-economic background. If this is the case, the correlations of
g
to real-world phenomena are spurious, and it should be easy to demonstrate by showing that the “real” causes (such as educational attainment) can explain everything that
g
explains, more parsimoniously. The third possibility is that
g
is a (partly) biological phenomenon in its own right—a basic characteristic of the organism that exerts some influence on its ability to reason, think, and learn.

On the first two possibilities, the empirical record is rich and large. Chapter 3 tells this story for job productivity, showing how
g
explains productivity in ways that education and socioeconomic background cannot. The eight chapters of Part II tell the story for a wide variety of social indicators, again after taking the contributions of education or socioeconomic status into account. As for the third possibility, that
g
is a biological phenomenon, let us count the ways in which
g
seems to capture a “real property in the head.”

First, a growing body of evidence links
g,
and IQ scores more generally, with neurophysiological functioning and a genetic ground: The higher the
g
loading of a subtest is, the higher is its heritability. The higher the
g
loading of a subtest is, the higher is the degree of inbreeding depression (an established genetic phenomenon). Reaction times on elementary cognitive tasks that require no conscious thought, such as responding to a lighted button, show a significant correlation with IQ test scores. This correlation depends mostly, perhaps entirely, on
g.
A significant relationship exists between
g
and evoked electrical potentials of the cerebral cortex. A significant inverse relationship exists between nonverbal (and highly
g
loaded) IQ test scores and the brain’s consumption of glucose in the areas of the brain tapped by the cognitive test. The higher the scores are on IQ tests, the faster is the speed of neural and synaptic transmission in the visual tract.
¹¹

For each of these statements, there is a corollary: No alternative casting of the test items can compete with
g
in producing such results. For example, suppose you give a psychometrician the chance to extract
g
and leave you with all the remaining factors in a given mental test. You cannot manipulate any one or any combination of those factors so as to produce the relationships I just listed. Only
g,
that supposedly arbitrary creation of the psychometricians, can do so. To sum up: The reality and importance of
g
has long since, in many ways, been established independent of its statistical properties.

Gould’s popularity is such that his review in the
New Yorker
was circulated by some nonpsychologists as the canonical refutation of
The Bell Curve.
But I think he made a mistake in reraising the factor-analytic argument. By doing so, he accomplished something that
The Bell Curve
alone could not do: He made scholars who know what the evidence shows angry enough to go public. By and large, scholars of intelligence are reclusive. The experiences in the 1970s of people like Arthur Jensen, Hans Eysenck, and Richard Herrnstein himself taught them that the consequences of being visible can be extremely punishing. But Gould was saying things that, to professionals in the field, were palpably wrong about a topic of deep importance. The early results were a few outraged letters sent to the
New Yorker
(none was printed). Then came a statement of mainstream intelligence signed by fifty-two scholars and published in the
Wall Street Journal
in which all of the main scientific findings of
The Bell Curve
were endorsed (without any explicit mention of the book or its critics).
¹²
I also hear second-hand that reporters have
called scholars about “this pseudoscience
g
business” and received an answer that they did not expect.

These may be harbingers of a shift in the media’s treatment of intelligence. There is now a real chance that the press will begin to discover that it has been missing the story. The big news about the study of intelligence is not that science has moved beyond the concept of a general mental ability but the remarkable resilience and utility of this construct called
g.

I come now to the second example of how the attacks on
The Bell Curve
are likely to have unintended consequences: the determination of the critics to focus on race and genes, even though
The Bell Curve
does not.

In Chapter 13,
The Bell Curve
draws three important conclusions about intelligence and race: (1) All races are represented across the range of intelligence, from lowest to highest. (2) American blacks and whites continue to have different mean scores on mental tests, varying from test to test but usually about one standard deviation in magnitude—about fifteen IQ points. “One standard deviation” means roughly that the average black scores at the sixteenth percentile of the white distribution. (3) Mental-test scores are generally as predictive of academic and job performance for blacks as for other ethnic groups. Insofar as the tests are biased at all, they tend to overpredict, not underpredict, black performance.

These facts are useful in the quest to understand why (for example) occupational and wage differences separate blacks and whites, or why aggressive affirmative action has produced academic apartheid in our universities. More generally, Herrnstein and I believe that a broad range of American social issues cannot be interpreted without understanding the ways in which intelligence plays a role that is often, and wrongly, conflated with the role of race. When it comes to government policy, and as we say emphatically at various points in Part IV, there is just one authentic policy implication: Return as quickly as possible to the cornerstone of the American ideal—that people are to be treated as individuals, not as members of groups.

The furor over
The Bell Curve
and race has barely touched on these core points. Instead, the critics have been obsessed—no hyperbole
here—with genes, trying to stamp out any consideration of the possibility that race differences have a genetic component.

You may read everything we say about the relationship of genes to race differences in intelligence on pp. 295-315. Our position does not take long to summarize, however: A legitimate scientific debate on the topic is underway; it is scientifically prudent at this point to assume that both environment and genes are involved, in unknown proportions; and, most important, people are getting far too excited about the whole issue. Genetically caused differences are not as fearful, or environmentally caused differences as benign, as many think. What matters is not the source but the existence of group differences and their intractability (for whatever reasons).

As I have watched the frenzied attacks on this scientifically unexceptional part of the book, I have decided that Richard Herrnstein and I were what is known as “prematurely right.” Certainly we were right empirically when we observed that the public at large is fascinated by the possibility of genetic differences (pp. 296-297) and that the intellectual elites have been “almost hysterically in denial about that possibility” (p. 315). I think we were right in trying to dampen that fascination. But as I listen to some of my most loyal friends insisting that I
must
be disingenuous when I continue to say that the genetic question is not a big deal, it also appears that Herrnstein and I failed to make the case persuasively. This does not mean I can now improve our presentation. I have reread the concluding pages of Chapter 13 many times since the publication of the book, pondering how we could have stated our case more clearly. To this day, I have no good ideas. As far as I can tell, we said it right the first time.

My main point here is that the attacks on our discussion of genes and race are not doing any good for the cause of those who want to discredit the idea that genes could be involved. They have based their attacks on the premise that a full, fair look at the data will make the issue go away. No one appears to have recognized that Herrnstein and I did not make nearly as aggressive a case for genetic differences as the data permit.

The most abundant source of data that we downplayed is in the work of J. Philippe Rushton, a psychologist who since 1985 has been publishing increasingly detailed data to support his theory that the three races he labels Negroid, Caucasoid, and Mongoloid vary not just in intelligence but in a wide variety of other characteristics. We put our discussion of Rushton in Appendix 5. The critics of
The Bell Curve
are
putting him on the front page, often outrageously caricaturing his work. The trouble with this strategy is that Rushton is a serious scholar who has assembled serious data.
¹³
Consider just one example: brain size. One of the most memorable features of Gould’s
The Mismeasure of Man
was his ridicule of the attempts by nineteenth-century scientists to establish a relationship between cranial capacity and intelligence. But the empirical reality, verified by numerous modern studies, including several based on magnetic resonance imaging, is that a significant and substantial relationship
does
exist between brain size and measured intelligence after body size is taken into account and that the races do have different distributions of brain size.
¹⁴
Rushton brings this large empirical documentation together. The attacks on
The Bell Curve
ensure that such data will get more attention.

Among those who have tried to quell any consideration that genes might play a role in racial differences, Charles Lane and Leon Kamin probably miscalculated most egregiously. I refer to their highly publicized attack on the “tainted sources” used in
The Bell Curve.
Lane introduced this theme with an initial article in the
New Republic
and then a much longer one in the
New York Review of Books.
¹⁵
In the latter piece, he proclaimed that “no fewer than seventeen researchers cited in the bibliography of
The Bell Curve
have contributed to
Mankind Quarterly
… a notorious journal of’racial history’ founded, and funded, by men who believe in the genetic superiority of the white race.” Lane also discovered that we cite thirteen scholars who have received funding from the Pioneer Fund, founded and run (he alleged) by men who were Nazi sympathizers, eugenicists, and advocates of white racial superiority. Leon Kamin, a vociferous critic of IQ in all its manifestations, took up the same argument at length in his review of
The Bell Curve
in
Scientific American.
¹⁶

Never mind that
The Bell Curve
draws its evidence from more than a thousand scholars. Never mind that among the scholars in Lane’s short list are some of the most respected psychologists of our time and that almost all of the sources referred to as tainted are articles published in leading refereed journals. Never mind that the relationship between the founder of the Pioneer Fund and today’s Pioneer Fund is roughly analogous to that between Henry Ford and today’s Ford Foundation. The charges have been made, they have wide currency, and some people will always believe that
The Bell Curve
rests on data concocted by neo-Nazi eugenicists.

But in the process of making their case, Lane and Kamin tried to go
beyond guilt by association: They tried to demonstrate the specific ways in which these
Mankind Quarterly
and Pioneer Fund scholars we cited were racist. To do that, they focused on our citations of studies of African IQ.

The topic of African IQ is a tiny piece of
The Bell Curve—
three paragraphs on pp. 288-289 intended to address a hypothesis Herrnstein and I heard frequently: The test scores of American blacks have been depressed by the experience of slavery and African blacks will be found to do better. We briefly summarize the literature indicating that African blacks in fact have lower test scores than American blacks.

Lane and Kamin assault this conclusion ferociously. We are an easy target. We say so little about African IQ that it is easy for Lane and Kamin to point to the many technical difficulties of knowing exactly what is going on. But we also omit many more details that make a strong case that African blacks have very low scores on standardized mental tests. Lane and Kamin want our sources to be weak and racist. That they are not bears importantly, if inconclusively, on possible genetic racial differences.

Blinded to that possibility by their seeming prejudgment of the issue, Lane and Kamin apparently are not worried about what will happen when their critiques lead other scholars to explore the studies that we cited. They should be. Even when samples of Africans are selected in ways that will tend to bias the results upward—for example, by limiting the sample to people who have completed primary school (many of the least able have dropped out by that time), people who are employed, or people who live in urban areas—and even when the tests involved are ones such as the Ravens Standard Progressive Matrices (SPM), designed for cross-cultural comparisons, devoid of any requirements of literacy or numeracy, the scores of African samples everywhere have been in the region of two standard deviations below European or East Asian means. The studies vary in quality, but some are excellent, and it is not the case that the better the study is, the higher the African score is found to be. On the contrary, some of the lowest scores have been found in the largest, most careful, and most recent studies.