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The Proposal ***
1- Weber and Ludwig von Mises
2-Army Navy Club
3-News to Change You
4-Technical Corrections
5- "Wrong"
6-Clones, 2nd ed.
7-The Biology of Cognition
8-Bio War News
9-Bell Curve Papers
10-Abortion and Crime
11- Anthrax by Ross_Getman
12- Demon in the Freezer
13- Bioweaponeers
14- Water
15 - MILK
16 - Neglected Home Front
Judgment Day
9-Bell Curve Papers


Note to College Visitors:  


This web page was created after posting Clones, 2nd Edition.  Don Imus started making references about the Bell Curve.  ‘How can anyone who thinks like that . . .?  Well ok?’  Or ‘I didn’t know there were still people who thought like that . . . you know  . . . racists like that . . .’  Or,  ‘How do you live with your self . . . thinking that Blacks are inferior. . .?’


Now, anyone who has listened to the Don Imus show knows what a vile evil man Don Imus is.  And knows how boring he has gotten.   So I did not take him seriously.


For example, one day discussing illegal immigration he said “I do not care about the national origin of the person driving my cab . . .”  This line was stolen from a liberal pundit.  I say stolen because Imus did not give credit.  He presented it as his own.


More importantly there is the theft of the attitude as well, not just the words.  For example Imus does not ride in cabs he has a limousine.   But also there is the ‘liberal’ attitude.  ‘I don’t care about borders . . . etc.’ 


I guess it needs to be said that the Bell Curve is not about race.  The book could have been written solely about “White” test scores.  Race was examined only because American society is obsessed with “race.’  For one thing just think about this.  You are you.  You are not White, or Black, or whatever you are.  You are only you.  You will go to your grave only being you.  Race, (and the differences between races), is irrelevant.  I am not one wit smarter for being the same “race” as some genius who is also “White.”  Indeed IQ does not even exist at the level of the individual.  It is a statistic.  It exists as an abstraction.    If you had read the Bell Curve you would have known this Don (you damn fool) Imus!  


Imus says one nasty racist thing after another but when I mentioned the genetic differences in cognitive ability between people this gave him the opportunity to present himself as ‘liberal’ and opposed to racism etc.  Pure sham.


Then O’Reilly commented about the Clones post saying that “you can not tell a whole people they can not participate because of their race.”  I responded by adding to Clones and re-titled  it Clones 2nd Edition.


But then others started commenting on the Bell Curve and I realized that ten years after its publication the genetic basis of cognitive ability is still disputed.  So I set up this web page.


Imus is a damned liar and the facts will in no way change him.  Disgusting human being he is and will always be.  But he uses people’s ignorance, (as do so many others).


Hopefully as the truth becomes known Imus will have to find other things to lie about.


When I first read the Bell Curve it was a revelation.  I had been taught so many lies by the liberals who control education and the media.  For example in Public Administration we are taught that tests designed for jobs are more accurate predictors of performance than general IQ tests.  This is false.  IQ tests are superior predictors. 


But the power elite will continue to lie about IQ because their social power rest upon the belief that “all men are created equal” or as O’Reilly puts it everyone has an “equal chance” and he succeeded because of his superior “discipline.”   After the revelations of his court case his claim to discipline has been shown to be a lie also.     


My enemies have told so many lies about me I do not know which ones were used to destroy me.  I was accused of being an anti-Semite for example.  They told people, Doug Derry (?)  or the awful creep Scott Bobro (?)   ‘it is ok to harasse him he is an anti-Semite.’  Or racist.  Or just, ‘ . . . he is a conservative Republican.’


Who can say which lies were most useful against me when simply being a Republican in the San Francisco Bay Area is enough to make one a target?   So now, having a web page about the Bell Curve costs me very little, as I have already been ruined, driven into poverty, deprived of employment, ready to die . . .



October 10, 2004

“You Have To Tell The Truth”—The Bell Curve After Ten Years

By Steve Sailer

[See also: The Bell Curve, Ten Years After: It Tolls For Us, by Peter Brimelow]

The publication of The Bell Curve: Intelligence and Class Structure in American Life by the late Richard J. Herrnstein and Charles Murray in October 1994 was one of the pivotal events of the last decade. Along with the furious backlash, it permanently changed political movements such as neoliberalism and neoconservatism—not, alas, for the better.

Here are ten points about The Bell Curve that remain important today.

1.  How in the world did an 845-page book of social science statistics—including 94 quantitative graphs, 109 pages of notes, and a 58-page bibliography—sell more than 400,000 copies?

(Conversely, how in the world is this massive bestseller out of print today?)

The usual answer: "controversy." But controversial books are more likely to be squelched than flourish, as the sad fate of the other outstanding IQ books of the Nineties showed.

For example, Dan Seligman's 1992 A Question of Intelligence, which remains the best quick introduction to IQ, got a snippy two-paragraph review in the New York Times. (Here is Herrnstein's review in the old, pre-purge National Review.)

Similarly, the two books both entitled The g Factor that were written in the later 1990s barely saw the light of day. Arthur Jensen's monumental summary of 30 years of research ended up at a mail order publishing house. (Here's my review, which the post-purge National Review commissioned in 1998, but then turned down.)

Meanwhile, Chris Brand's suavely philosophical The g Factor was actually yanked from store shelves by its publisher, John Wiley & Co., only a couple of weeks after its release following an indiscreet but irrelevant interview Brand gave a newspaper. (You can download Brand’s book here.)

But rereading The Bell Curve, it's easy to see one reason it broke through: it's a model of how a serious nonfiction book ought to look and read.

The ubiquitous charts are elegantly uncluttered, yet get the story across lucidly, using only black, white and shades of gray. Even the text looks more inviting than usual because a tiny extra amount of leading was inserted between the lines. And the prose style is vivid yet calm, direct yet judicious. As Murray commented shrewdly:

"The descriptions of The Bell Curve as an angry, racist polemic have led people in bookstores to pick it up to see what the fuss is about. The pages to which they turn are nothing like what they expect, their curiosity is piqued, and some of them buy it."

2.  The admirable moral character displayed by The Bell Curve authors.

Humble, endlessly curious, honest, and large-hearted…the contrast between them and their critics—so many of them pompous, vicious, slanderous, and small—is overwhelming.

3.  The powerful content of The Bell Curve.  

This falls into two categories. The first is a far-ranging survey of what had previously been discovered about cognitive testing, citing over 1,000 sources in a massive bibliography. The second was new: an analysis of the lives of a nationally-representative sample of about 12,000 young people a decade after the military had paid them in 1980 to take the Armed Services Vocational Aptitude Battery [ASVAB]. Four of the ten subtests within the ASVAB comprise the IQ test that the military requires all applicants for enlistment to take—the Armed Forces Qualification Test.

The AFQT hadn't been renormed against the civilian population since 1944, so in 1980 the military hired the academics who had set up the National Longitudinal Survey of Youth (NLSY) the year before to give their enormous sample the AFQT.

When reinterviewed a decade later in 1990, the test-takers were now 25-33 years old. This allowed to Herrnstein and Murray to see how well their youthful IQs predicted their status as adults.

(Can’t accept the results Herrnstein and Murray got? Download their data from this page maintained by Prof. Eric Rasmusen of Indiana U. and crunch the numbers yourself.)

It’s constantly said in the Establishment Media that IQ and IQ tests have been "discredited." But the institution that has studied IQ testing in the greatest detail over the last 87 years—the U.S. military—remains utterly devoted to the value of cognitive tests. The Department of Defense says "AFQT scores are the primary measure of recruit potential."

Because the military spends billions to get high quality recruits, the average IQ of enlisted personnel is much higher than many civilians expect. About two thirds of enlisted men and women have IQs above the national average. Almost no recruits (1.1%) fall below the 30th percentile in IQ.

Did the violent denunciations of the book that was, after all, based on the military's test cause it to, well, rethink its use of IQ testing?

Absolutely not.

4. Contrary to the detractors' myth, relatively little of The Bell Curve concerns race.

The first 126 pages described "the emergence of a cognitive elite" via the higher education system. The heart of the book is the next 142 pages on "cognitive classes and social behavior," which examines the impact of IQ on poverty, schooling, unemployment, family, crime, and so forth. Here, Herrnstein and Murray looked only at data drawn from non-Hispanic whites—to avoid confusing the effect of IQ with that of race.

Then, from p. 269 to p. 315, comes the much-denounced Chapter 13 on "Ethnic Differences in Cognitive Ability." Murray and Herrnstein carefully step through the evidence, pro and con, and reach the following judicious conclusion:

"If the reader is now convinced that either the genetic or environmental explanation has won out to the exclusion of the other, we have not done a sufficiently good job of presenting one side or the other. It seems highly likely to us that both genes and the environment have something to do with racial differences. What might the mix be? We are resolutely agnostic on that issue; as far as we can determine, the evidence does not yet justify an estimate."

That's it—the conclusion to the chapter that launched a thousand screeds. Not surprisingly, it's almost never quoted. Try looking for parts of it in Google. Herrnstein and Murray's critics prefer to denounce straw persons.

5.  Herrnstein and Murray were right, dammit.

My friend Gregory Cochran, the physicist turned evolutionary biologist, likes to ask about controversial ideas, "Well, if it were true, how would the world look different from what we see around us?" The short answer for The Bell Curve: the world portrayed in the book is the world we live in to within a rounding error.

6. The Bell Curve marked the climax of first-generation neoconservatism.

Today, of course, neoconservatism means messianic Invade-the-World-Invite-the-World immigration and foreign policies. But for its first three decades, beginning with the founding of The Public Interest journal in 1965 by Irving Kristol and Daniel Bell, neoconservatism meant intensely quantitative social science research that cast doubt on liberal pieties about race and ethnicity.

Landmarks in the evolution of this long-lost form of neoconservatism: the 1965 report by Daniel Patrick Moynihan raising the alarm that the illegitimacy rate among blacks had reached 22 percent (it's now triple that); James Q. Wilson's 1975 book Thinking About Crime, which introduced the commonsensical solution that finally quelled the long crime wave of 1961-1995. (Lock up more criminals for longer, because they can't victimize the public when they’re in prison.)

Charles Murray was at the neoconservative Manhattan Institute when he became interested in researching IQ. The Manhattan Institute dropped him like a hot potato. But he was immediately picked by the neocon American Enterprise Institute.

The Bell Curve was the crowning achievement of 30 years of neoconservative analysis … and, as we'll see below, its death blow.

7. The backlash to The Bell Curve was the most unhinged in recent intellectual history.

As Cochran says: "Nobody ever gets that really mad at somebody unless they are telling the truth.”

The hysteria began among the "neoliberals" at The New Republic. Neoliberals are, more or less, neoconservatives who continue to vote Democratic. Neoliberalism doesn't much exist outside of journalism, but a neoliberal pundit can carve out an influential career starting at the Washington Monthly, moving up to The New Republic and Slate, and finally making some decent money at Newsweek and the Washington Post.

The New Republic's then editor, Andrew Sullivan, invited Herrnstein and Murray to introduce The Bell Curve in an 11-page cover story entitled "Race and IQ" in the October 31, 1994 issue. Sullivan's staff, however, rebelled at the very thought that such a vile essay would desecrate the pages of their magazine.

Why this berserk response? My theory: Honest talk about IQ exposes some deeply personal inconsistencies among our most influential thinkers. The typical white intellectual claims he wants to censor discussion of IQ to shield black self-esteem, but his reactions reveal that he finds it a peril to his own. Secretly, he considers himself superior to ordinary white people for two contradictory reasons: a] he constantly proclaims belief in human equality, but they don't; b] he has a high IQ, but they don't.

To maintain peace, Sullivan printed 17 almost uniformly ill-informed replies. Only owner Martin Peretz's was cautiously positive.

In National Review's December 5, 1994 symposium on The Bell Curve, Dan Seligman lamented:

"A howling mob of liberal commentators not knowing what in hell they are talking about is a dispiriting spectacle, and media reaction to the Herrnstein—Murray book has been infinitely depressing. I cannot remember any other work of scholarship, in any field at all, that has been assailed so cavalierly by writers ignorant of the material and manifestly unconcerned about accurately representing its ideas.

"I used to think that Mickey Kaus was a smart and serious guy. But there he was in The New Republic, attacking the authors for resisting 'a near-avalanche of evidence that the black-white difference in IQ is a function of environment rather than heredity.' The avalanche cited by Kaus consists of studies he apparently learned about from The Bell Curve itself. Its authors judiciously lead readers through a wide range of studies, some consistent with a purely environmental explanation of racial IQ differences, some powerfully suggesting that environment alone cannot explain them all. Kaus points to several studies in the former group, dismissively mentions one in the latter group, and ignores the survey data cited by Herrnstein and Murray, which tell us that expert opinion is strongly tilted toward some genetic contribution to the gap."

Not terribly long after, Peretz fired Sullivan—in part, reportedly, because TNR's staff never forgave Sullivan for publishing Herrnstein and Murray.

The New Republic, and neoliberalism in general, has not recovered its intellectual heft. Neoliberalism degenerated into high-IQ snarkiness—fast brain-food for smart people with short attention spans, exemplified by the Michael Kinsley-edited Slate, where Mickey is now the star blogger.

8. The neocons' slow distancing of themselves from The Bell Curve marked the death of neoconservatism as a serious intellectual movement.

Initially, neoconservatives rallied bravely to The Bell Curve's defense. Ten years later, their comments are surprising to read.

James Q. Wilson defended the book staunchly. (Unusually, Wilson has never backtracked about the importance of IQ—he wanted me to write an article on it for The Public Interest in 2000, but Nathan Glazer vetoed my proposal. That became instead the five part VDARE.COM series called "How to Help the Left Half of the Bell Curve.")

Murray's AEI colleague Michael Ledeen also added (rightly): "Never has such a moderate book attracted such an immoderate response." Another AEI colleague, Michael Novak, also praised it.

And Michael Barone even wrote in NR:

"Perhaps because I'm congenitally optimistic, I think The Bell Curve's message is already widely understood, by the American people if not by the elite. Ordinary citizens know that some people are in significant ways more intelligent than others, that only a relative few are extremely bright or extremely dull, and that intelligence bunches up at the center. They know that intelligence is not randomly distributed among members of different identifiable racial and ethnic groups. These are lessons that are taught in everyday life, and you have to undergo a pretty sophisticated indoctrination and enlist in a tightly disciplined ideological army to believe otherwise."

Commentary magazine, the neocon bible, printed Murray's long reply to his book's critics in the May 1995 issue, and his extensive response to letter writers in the August 1995 issue.

But then the neocons, perhaps worn down by the constant slinging about of the terrifying R-word, lost heart.

Barone has long since abandoned all mention of IQ. Seligman does continue to write for Commentary, but the magazine has grown so hostile to Murray that, when his intensely quantitative Human Accomplishment came out last year, it assigned the completely innumerate Terry Teachout to review it. He produced a predictably bad notice. (Here's my review and here's John Derbyshire's.) And Commentary managing editor Gary Rosen panned Human Accomplishment in the Wall Street Journal. 

After the Bell Curve wars, neoconservatism has become increasingly anti-quantitative and pro-ideological. On issues like university quotas, you no longer see quantitative research from neocons—just repeated affirmations of the principle of colorblindness.

Quantitative research quickly leads to the Bell Curve gap. And that's now a no-go zone.

Today, Abigail and Stefan Thernstrom are the neocons' designated authorities on racial differences in educational achievement. They frantically attempt to ignore the IQ elephant in the living room.

In neoconservatism's post-Bell Curve atmosphere of anti-realism, enthusiasm mounted for utopian schemes to remodel the Middle East using the U.S. military as a hammer. The disastrous results are today visible to all.

9. What has Murray found on IQ since The Bell Curve?

I'm aware of two further studies Murray did on the NLSY database:

an ingenious study of pairs of American siblings raised together in non-poor homes.

Murray described his findings in the Sunday Times of London in 1997:

"Each pair consists of one sibling with an IQ in the normal range of 90-110, a range that includes 50% of the population. I will call this group the normals. The second sibling in each pair had an IQ either higher than 110, putting him in the top quartile of intelligence (the brights) or lower than 90, putting him in the bottom quartile (the dulls). These constraints produced a sample of 710 pairs. How much difference did IQ make? Earned income is a good place to begin. In 1993, when we took our most recent look at them, members of the sample were aged 28-36. That year, the bright siblings earned almost double the average of the dull: £22,400 compared to £11,800. The normals were in the middle, averaging £16,800. “[IQ Will Put You In Your Place, Charles Murray, Sunday Times, UK, Day 25, 1997]

These earnings gaps are likely to widen with age, as the blue-collar workers' bodies wear out and therefore their incomes stagnate or fall.

Within families, parents do a better job of equalizing children's environments than any government less tyrannical than the Khmer Rouge could accomplish.

Yet, even with the same upbringing, IQ differences are both substantial and play a huge role in the kids' prosperity as adults.

Second, Murray's 1999 attempt to see if the Flynn Effect —the multi-decade upward drift in raw IQ scores—was leading to a convergence of black and white IQs.

Murray was able to do this because, by the 1996 wave of NLSY interviews, over 6,000 children of the females in the sample had given birth to children who had been tested on the Peabody Picture Vocabulary IQ test.

Murray reported:

"In the two generations of the NLSY, no convergence has occurred. The BW [black-white] difference on a highly g-loaded cognitive test for the 1st generation of the NLSY, born from 1957–64, was 16.6 points, amounting to 1.24 SDs relative to the black and white distributions. For the 2nd generation, born primarily in the 1980s, the difference on a widely used test of verbal cognitive ability was 17.8 points, or 1.26 SDs. The estimated magnitude of the BW difference in the 2nd generation is robust, surviving a variety of hypotheses about possible sources of attenuation."

So, despite the Flynn effect, the black-white IQ gap was almost exactly the same from the first generation to the next.

10. Dick Herrnstein was a great man and his death a great tragedy.

Herrnstein [click here for Peter Brimelow’s interview with him] died in September 1994, just before publication of The Bell Curve. Murray told this story in his obituary for National Review—which can also serve as the last word (for now) on The Bell Curve Wars:

"About four years ago, shortly after Dick and I had begun to collaborate on a new book about intelligence and social policy, we were talking over a late-evening Scotch at his home in Belmont, Mass. We had been musing about the warning shots the prospective book had already drawn and the heavy fire that was sure to come. The conversation began to depress me, and I said, 'Why the hell are we doing this, anyway?'

"Dick recalled the day when, as a young man, he had been awarded tenure. It was his dream fulfilled—a place in the university he so loved, the chance to follow his research wherever it took him, economic security. For Dick, being a tenured professor at Harvard was not just the perfect job, but the perfect way to live his life.

“It was too good to be true; there had to be a catch. What's my part of the bargain? he had asked himself.

“'And I figured it out,' he said, looking at me with that benign, gentle half-smile of his. ’You have to tell the truth.'

“There was no self-congratulation in his voice, just an answer to my question."

[Steve Sailer [email him], is founder of the Human Biodiversity Institute and movie critic for The American Conservative. His website features site-exclusive commentaries.]



Mainstream Science on Intelligence

This public statement, signed by 52 internationally known scholars, was active on the information highway early in 1995 following several rather heated and negative responses to Herrnstein & Murray's The Bell Curve. It was first published in The Wall Street Journal, Tuesday, December 13, 1994. An alphabetical listing of the scholars and their home institutions are given at the end of the statement.


Since the publication of "The BELL CURVE," many commentators have offered opinions about human intelligence that misstate current scientific evidence. Some conclusions dismissed in the media as discredited are actually firmly supported.

This statement outlines conclusions regarded as mainstream among researchers on intelligence, in particular, on the nature, origins, and practical consequences of individual and group differences in intelligence. Its aim is to promote more reasoned discussion of the vexing phenomenon that the research has revealed in recent decades. The following conclusions are fully described in the major textbooks, professional journals and encyclopedias in intelligence.

The Meaning and Measurement of Intelligence

  1. Intelligence is a very general mental capability that, among other things, involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly and learn from experience. It is not merely book learning, a narrow academic skill, or test-taking smarts. Rather, it reflects a broader and deeper capability for comprehending our surroundings -- "catching on," "making sense" of things, or "figuring out" what to do.
  2. Intelligence, so defined, can be measured, and intelligence tests measure it well. They are among the most accurate (in technical terms, reliable and valid) of all psychological tests and assessments. They do not measure creativity, character, personality, or other important differences among individuals, nor are they intended to.
  3. While there are different types of intelligence tests, they all measure the same intelligence. Some use words or numbers and require specific cultural knowledge (like vocabulary). Others do not, and instead use shapes or designs and require knowledge of only simple, universal concepts (many/few, open/closed, up/down).
  4. The spread of people along the IQ continuum, from low to high, can be represented well by the BELL CURVE (in statistical jargon, the "normal CURVE"). Most people cluster around the average (IQ 100). Few are either very bright or very dull: About 3% of Americans score above IQ 130 (often considered the threshold for "giftedness"), with about the same percentage below IQ 70 (IQ 70-75 often being considered the threshold for mental retardation).
  5. Intelligence tests are not culturally biased against American blacks or other native-born, English-speaking peoples in the U.S. Rather, IQ scores predict equally accurately for all such Americans, regardless of race and social class. Individuals who do not understand English well can be given either a nonverbal test or one in their native language.
  6. The brain processes underlying intelligence are still little understood. Current research looks, for example, at speed of neural transmission, glucose (energy) uptake, and electrical activity of the brain.

Group Differences

  1. Members of all racial-ethnic groups can be found at every IQ level. The BELL CURVES of different groups overlap considerably, but groups often differ in where their members tend to cluster along the IQ line. The BELL CURVES for some groups (Jews and East Asians) are centered somewhat higher than for whites in general. Other groups (blacks and Hispanics) are centered somewhat lower than non-Hispanic whites.
  2. The BELL CURVE for whites is centered roughly around IQ 100; the BELL CURVE for American blacks roughly around 85; and those for different subgroups of Hispanics roughly midway between those for whites and blacks. The evidence is less definitive for exactly where above IQ 100 the BELL CURVES for Jews and Asians are centered.

Practical Importance

  1. IQ is strongly related, probably more so than any other single measurable human trait, to many important educational, occupational, economic, and social outcomes. Its relation to the welfare and performance of individuals is very strong in some arenas in life (education, military training), moderate but robust in others (social competence), and modest but consistent in others (law-abidingness). Whatever IQ tests measure, it is of great practical and social importance.
  2. A high IQ is an advantage in life because virtually all activities require some reasoning and decision-making. Conversely, a low IQ is often a disadvantage, especially in disorganized environments. Of course, a high IQ no more guarantees success than a low IQ guarantees failure in life. There are many exceptions, but the odds for success in our society greatly favor individuals with higher IQs.
  3. The practical advantages of having a higher IQ increase as life settings become more complex (novel, ambiguous, changing, unpredictable, or multi-faceted). For example, a high IQ is generally necessary to perform well in highly complex or fluid jobs (the professions, management); it is a considerable advantage in moderately complex jobs (crafts, clerical and police work); but it provides less advantage in settings that require only routine decision making or simple problem solving (unskilled work).
  4. Differences in intelligence certainly are not the only factor affecting performance in education, training, and highly complex jobs (no one claims they are), but intelligence is often the most important. When individuals have already been selected for high (or low) intelligence and so do not differ as much in IQ, as in graduate school (or special education), other influences on performance loom larger in comparison.
  5. Certain personality traits, special talents, aptitudes, physical capabilities, experience, and the like are important (sometimes essential) for successful performance in many jobs, but they have narrower (or unknown) applicability or "transferability" across tasks and settings compared with general intelligence. Some scholars choose to refer to these other human traits as other "intelligences."

Source and Stability of Within-Group Differences

  1. Individuals differ in intelligence due to differences in both their environments and genetic heritage. Heritability estimates range from 0.4 to 0.8 (on a scale from 0 to 1), most thereby indicating that genetics plays a bigger role than does environment in creating IQ differences among individuals. (Heritability is the squared correlation of phenotype with genotype.) If all environments were to become equal for everyone, heritability would rise to 100% because all remaining differences in IQ would necessarily be genetic in origin.
  2. Members of the same family also tend to differ substantially in intelligence (by an average of about 12 IQ points) for both genetic and environmental reasons. They differ genetically because biological brothers and sisters share exactly half their genes with each parent and, on the average, only half with each other. They also differ in IQ because they experience different environments within the same family.
  3. That IQ may be highly heritable does not mean that it is not affected by the environment. Individuals are not born with fixed, unchangeable levels of intelligence (no one claims they are). IQs do gradually stabilize during childhood, however, and generally change little thereafter.
  4. Although the environment is important in creating IQ differences, we do not know yet how to manipulate it to raise low IQs permanently. Whether recent attempts show promise is still a matter of considerable scientific debate.
  5. Genetically caused differences are not necessarily irremediable (consider diabetes, poor vision, and phenal ketonuria), nor are environmentally caused ones necessarily remediable (consider injuries, poisons, severe neglect, and some diseases). Both may be preventable to some extent.

Source and Stability of Between-Group Differences

  1. There is no persuasive evidence that the IQ BELL CURVES for different racial-ethnic groups are converging. Surveys in some years show that gaps in academic achievement have narrowed a bit for some races, ages, school subjects and skill levels, but this picture seems too mixed to reflect a general shift in IQ levels themselves.
  2. Racial-ethnic differences in IQ BELL CURVES are essentially the same when youngsters leave high school as when they enter first grade. However, because bright youngsters learn faster than slow learners, these same IQ differences lead to growing disparities in amount learnedas youngsters progress from grades one to 12. As large national surveyscontinue to show, black 17-year-olds perform, on the average, more likewhite 13-year-olds in reading, math, and science, with Hispanics inbetween.
  3. The reasons that blacks differ among themselves in intelligenceappear to be basically the same as those for why whites (or Asians orHispanics) differ among themselves. Both environment and geneticheredity are involved.
  4. There is no definitive answer to why IQ bell curves differ acrossracial-ethnic groups. The reasons for these IQ differences betweengroups may be markedly different from the reasons for why individualsdiffer among themselves within any particular group (whites or blacks orAsians). In fact, it is wrong to assume, as many do, that the reason whysome individuals in a population have high IQs but others have low IQs must be the same reason why some populations contain more such high (or low) IQ individuals than others. Most experts believe that environment is important in pushing the bell curves apart, but that genetics could be involved too.
  5. Racial-ethnic differences are somewhat smaller but still substantial for individuals from the same socioeconomic backgrounds. To illustrate, black students from prosperous families tend to score higher in IQ than blacks from poor families, but they score no higher, on average, than whites from poor families.
  6. Almost all Americans who identify themselves as black have white ancestors -- the white admixture is about 20%, on average -- and many self-designated whites, Hispanics, and others likewise have mixed ancestry. Because research on intelligence relies on self-classification into distinct racial categories, as does most other social-science research, its findings likewise relate to some unclear mixture of social and biological distinctions among groups (no one claims otherwise).

Implications for Social Policy

  1. The research findings neither dictate nor preclude any particular social policy, because they can never determine our goals. They can, however, help us estimate the likely success and side-effects of pursuing those goals via different means.

The following professors -- all experts in intelligence and allied fields -- have signed this statement:

  • Richard D. Arvey, University of Minnesota
  • Thomas J. Bouchard, Jr., University of Minnesota
  • John B. Carroll, Un. of North Carolina at Chapel Hill
  • Raymond B. Cattell, University of Hawaii
  • David B. Cohen, University of Texas at Austin
  • Rene V. Dawis, University of Minnesota
  • Douglas K. Detterman, Case Western Reserve Un.
  • Marvin Dunnette, University of Minnesota
  • Hans Eysenck, University of London
  • Jack Feldman, Georgia Institute of Technology
  • Edwin A. Fleishman, George Mason University
  • Grover C. Gilmore, Case Western Reserve University
  • Robert A. Gordon, Johns Hopkins University
  • Linda S. Gottfredson, University of Delaware
  • Robert L. Greene, Case Western Reserve University
  • Richard J.Haier, University of Callifornia at Irvine
  • Garrett Hardin, University of California at Berkeley
  • Robert Hogan, University of Tulsa
  • Joseph M. Horn, University of Texas at Austin
  • Lloyd G. Humphreys, University of Illinois at Urbana-Champaign
  • John E. Hunter, Michigan State University
  • Seymour W. Itzkoff, Smith College
  • Douglas N. Jackson, Un. of Western Ontario
  • James J. Jenkins, University of South Florida
  • Arthur R. Jensen, University of California at Berkeley
  • Alan S. Kaufman, University of Alabama
  • Nadeen L. Kaufman, California School of Professional Psychology at San Diego
  • Timothy Z. Keith, Alfred University
  • Nadine Lambert, University of California at Berkeley
  • John C. Loehlin, University of Texas at Austin
  • David Lubinski, Iowa State University
  • David T. Lykken, University of Minnesota
  • Richard Lynn, University of Ulster at Coleraine
  • Paul E. Meehl, University of Minnesota
  • R. Travis Osborne, University of Georgia
  • Robert Perloff, University of Pittsburgh
  • Robert Plomin, Institute of Psychiatry, London
  • Cecil R. Reynolds, Texas A & M University
  • David C. Rowe, University of Arizona
  • J. Philippe Rushton, Un. of Western Ontario
  • Vincent Sarich, University of California at Berkeley
  • Sandra Scarr, University of Virginia
  • Frank L. Schmidt, University of Iowa
  • Lyle F. Schoenfeldt, Texas A & M University
  • James C. Sharf, George Washington University
  • Herman Spitz, former director E.R. Johnstone Training and Research Center, Bordentown, N.J.
  • Julian C. Stanley, Johns Hopkins University
  • Del Thiessen, University of Texas at Austin
  • Lee A. Thompson, Case Western Reserve University
  • Robert M. Thorndike, Western Washington Un.
  • Philip Anthony Vernon, Un. of Western Ontario
  • Lee Willerman, University of Texas at Austin





The evolution of intelligence

Natural genius?

Jun 2nd 2005
From The Economist print edition


The high intelligence of Ashkenazi Jews may be a result of their persecuted past

THE idea that some ethnic groups may, on average, be more intelligent than others is one of those hypotheses that dare not speak its name. But Gregory Cochran, a noted scientific iconoclast, is prepared to say it anyway. He is that rare bird, a scientist who works independently of any institution. He helped popularise the idea that some diseases not previously thought to have a bacterial cause were actually infections, which ruffled many scientific feathers when it was first suggested. And more controversially still, he has suggested that homosexuality is caused by an infection.


Even he, however, might tremble at the thought of what he is about to do. Together with Jason Hardy and Henry Harpending, of the University of Utah, he is publishing, in a forthcoming edition of the Journal of Biosocial Science, a paper which not only suggests that one group of humanity is more intelligent than the others, but explains the process that has brought this about. The group in question are Ashkenazi Jews. The process is natural selection.


History before science


Ashkenazim generally do well in IQ tests, scoring 12-15 points above the mean value of 100, and have contributed disproportionately to the intellectual and cultural life of the West, as the careers of Freud, Einstein and Mahler, pictured above, affirm. They also suffer more often than most people from a number of nasty genetic diseases, such as Tay-Sachs and breast cancer. These facts, however, have previously been thought unrelated.


 The former has been put down to social effects, such as a strong tradition of valuing education. The latter was seen as a consequence of genetic isolation. Even now, Ashkenazim tend to marry among themselves. In the past they did so almost exclusively.


Dr Cochran, however, suspects that the intelligence and the diseases are intimately linked. His argument is that the unusual history of the Ashkenazim has subjected them to unique evolutionary pressures that have resulted in this paradoxical state of affairs.

Ashkenazi history begins with the Jewish rebellion against Roman rule in the first century AD. When this was crushed, Jewish refugees fled in all directions. The descendants of those who fled to Europe became known as Ashkenazim.


In the Middle Ages, European Jews were subjected to legal discrimination, one effect of which was to drive them into money-related professions such as banking and tax farming which were often disdained by, or forbidden to, Christians. This, along with the low level of intermarriage with their gentile neighbours (which modern genetic analysis confirms was the case), is Dr Cochran's starting point.


He argues that the professions occupied by European Jews were all ones that put a premium on intelligence. Of course, it is hard to prove that this intelligence premium existed in the Middle Ages, but it is certainly true that it exists in the modern versions of those occupations. Several studies have shown that intelligence, as measured by IQ tests, is highly correlated with income in jobs such as banking.


What can, however, be shown from the historical records is that European Jews at the top of their professions in the Middle Ages raised more children to adulthood than those at the bottom. Of course, that was true of successful gentiles as well. But in the Middle Ages, success in Christian society tended to be violently aristocratic (warfare and land), rather than peacefully meritocratic (banking and trade).


Put these two things together—a correlation of intelligence and success, and a correlation of success and fecundity—and you have circumstances that favour the spread of genes that enhance intelligence. The questions are, do such genes exist, and what are they if they do? Dr Cochran thinks they do exist, and that they are exactly the genes that cause the inherited diseases which afflict Ashkenazi society.


That small, reproductively isolated groups of people are susceptible to genetic disease is well known. Constant mating with even distant relatives reduces genetic diversity, and some disease genes will thus, randomly, become more common. But the very randomness of this process means there should be no discernible pattern about which disease genes increase in frequency. In the case of Ashkenazim, Dr Cochran argues, this is not the case.


 Most of the dozen or so disease genes that are common in them belong to one of two types: they are involved either in the storage in nerve cells of special fats called sphingolipids, which form part of the insulating outer sheaths that allow nerve cells to transmit electrical signals, or in DNA repair. The former genes cause neurological diseases, such as Tay-Sachs, Gaucher's and Niemann-Pick. The latter cause cancer.


That does not look random. And what is even less random is that in several cases the genes for particular diseases come in different varieties, each the result of an independent original mutation. This really does suggest the mutated genes are being preserved by natural selection. But it does not answer the question of how evolution can favour genetic diseases. However, in certain circumstances, evolution can.


West Africans, and people of West African descent, are susceptible to a disease called sickle-cell anaemia that is virtually unknown elsewhere. The anaemia develops in those whose red blood cells contain a particular type of haemoglobin, the protein that carries oxygen. But the disease occurs only in those who have two copies of the gene for the disease-causing haemoglobin (one copy from each parent). Those who have only one copy have no symptoms. They are, however, protected against malaria, one of the biggest killers in that part of the world. Thus, the theory goes, the pressure to keep the sickle-cell gene in the population because of its malaria-protective effects balances the pressure to drive it out because of its anaemia-causing effects. It therefore persists without becoming ubiquitous.


Dr Cochran argues that something similar happened to the Ashkenazim. Genes that promote intelligence in an individual when present as a single copy create disease when present as a double copy. His thesis is not as strong as the sickle-cell/malaria theory, because he has not proved that any of his disease genes do actually affect intelligence. But the area of operation of some of them suggests that they might.


The sphingolipid-storage diseases, Tay-Sachs, Gaucher's and Niemann-Pick, all involve extra growth and branching of the protuberances that connect nerve cells together. Too much of this (as caused in those with double copies) is clearly pathological. But it may be that those with single copies experience a more limited, but still enhanced, protuberance growth. That would yield better linkage between brain cells, and might thus lead to increased intelligence. Indeed, in the case of Gaucher's disease, the only one of the three in which people routinely live to adulthood, there is evidence that those with full symptoms are more intelligent than the average. An Israeli clinic devoted to treating people with Gaucher's has vastly more engineers, scientists, accountants and lawyers on its books than would be expected by chance.


Why a failure of the DNA-repair system should boost intelligence is unclear—and is, perhaps, the weakest part of the thesis, although evidence is emerging that one of the genes in question is involved in regulating the early growth of the brain. But the thesis also has a strong point: it makes a clear and testable prediction. This is that people with a single copy of the gene for Tay-Sachs, or that for Gaucher's, or that for Niemann-Pick should be more intelligent than average. Dr Cochran and his colleagues predict they will be so by about five IQ points. If that turns out to be the case, it will strengthen the idea that, albeit unwillingly, Ashkenazi Jews have been part of an accidental experiment in eugenics. It has brought them some advantages. But, like the deliberate eugenics experiments of the 20th century, it has also exacted a terrible price.







TRENDS in Cognitive Sciences Vol.6 No.12 December 2002 1364-6613/02/$ – see front matter © 2002 Elsevier Science Ltd. All rights reserved.Forum


Back to nature

The Blank Slate: The Modern Denial of

Human Nature

by Steven Pinker,

Viking 2002. £25.00/$27.95 (509 pages) ISBN 0 670 03151 8


When Steven Pinker’s Language Instinct came out in 1994, a philosopher friend of mine described it as a wonderful book with an awful ending. Being greatly influenced by Noam Chomsky, she was sympathetic to Pinker’s arguments that language is an innate module – an instinct – and persuaded as well that language has evolved through natural selection. But she was troubled by his suggestion in the final chapter that the same approach should be extended to psychology more generally.


Pinker’s next book, How the Mind Works, did just that, applying a biological perspective to everything from depth perception to maternal love to aesthetic appreciation. She hated this book, seeing the whole enterprise of evolutionary psychology as repugnant: morally suspect and politically reactionary. The Blank Slate is written for her.


Pinker does a lot of things in thisextraordinary work, but his main goal is to show that the notion of an evolvedhuman nature does not have the negative connotations that many people think it does. There is no conflict between a  materialist and biological perspective on the mind and the religious, political and moral values that people hold most dear. Pinker starts by identifying three doctrines: the blank slate (mental structure comes from the environment, mostly from culture), the noble savage (humans are essentially good) and the ghost in the machine (mental life is the product of an immaterial soul).


Pinker argues that these views are pervasive, quoting adherents ranging from Mao Zedong to Walt Disney, and underlie contemporary discussion of just about any topic that matters. He also reviews the ugly history of how those who reject these doctrines (even in very mild ways, such as tentatively suggesting that aggression has biological roots) become the targets of ad hominem attacks, bizarre mischaracterizations, censorship, and even physical assault. The doctrines are sometimes presented in extreme forms that even their adherents do not believe, something that Pinker describes as a sure sign of a cult-like mentality, where ‘fantastical beliefs are flaunted as proof of one’s piety’.


Although the tone is calm and reasoned throughout, Pinker plainly takes delight in quoting, and dismantling, some of these sillier claims. Of course, if it were true that rejection of these doctrines entails an endorsement of sexism, racism, infanticide, war, rape, and everything else that is evil in the world, then a little bit of censorship and hypocrisy might well be justified.


In the core of this book, Pinker identifies several anxieties that people have about an evolved biological human nature – such that it would justify discrimination, or would strip life of any higher meaning –and argues that these are unfounded. He then goes further and reviews five ‘hot buttons’ – politics, violence, gender, children, and the arts. For each, he proposes that an enhanced appreciation of human nature can allow us to better understand, and improve, those areas that are most central to our lives.


This is a brilliant book. It is beautifully written, and addresses profound issues with courage and clarity. There is nothing else like it, and it is going to have an impact that extends well beyond the scientific academy. There is also plenty to disagree with. For one

thing, while Pinker makes an excellent case that a scientific conception of human nature does not clash with liberal Western values, he is too optimistic when it comes to reconciliation with religion.


Someone who is devout can easily give up on the blank slate and the noble savage – but the ghost in the machine is a very different story. Pinker notes that ‘some

biologists argue that a sophisticated deism, towards which many religions are

evolving, can be made compatible with an evolutionary understanding of the

mind and human nature’. But such a sophisticated deism would be so toothless

and secularized that it barely deserves to be called a religion.


The sorts of religions that people actually believe in include beliefs such as the soul surviving the death of the body and ascending to heaven. If you accept the scientific view

of human nature, you have to give this up. This is not small potatoes.


Pinker might be too optimistic as well about the relevance of scientific theories

to social and political life. He is plainly right that our feelings about issues such

as good parenting, violent crime and abortion are deeply related to tacit

assumptions about human nature, and he makes a persuasive case that this is

also true for broader-scale ideologies such as capitalism and communism.


But  although it is flattering to think that these tacit theories come from the discoveries of those who study mental life, this might just be hubris.


The assumptions about human nature held by dictators, reformers, racists, utopians and everyone else might have other origins, and it is unclear how much they are affected by insights from the laboratory or the seminar room.


Pinker approvingly quotes Chekhov, who wrote ‘Man will become better when you show him what he is like’. It would be nice if this were true, but so far there is little evidence to support it.


Paul Bloom

Dept of Psychology, Yale University,

PO Box 208205, New Haven,

CT 06520-8205, USA.







Is the Bell Curve Statistically Sound?

James Case

Society for Industrial and Applied Mathematics

SIAM News, Volume 28, Number 1, January 1995

The Bell Curve: Intelligence and Class Structure in American Life
By R.J. Herrnstein and Charles Murray
The Free Press, New York, 1994, 845 +xxvi pages, $30


R.J. Herrnstein (now deceased) and Charles Murray knew very well that the mere mention of race in The Bell Curve: Intelligence and Class Structure in American Life would expose their work (and themselves) to severe criticism. They were not prepared, however, for the verdict of "guilt by association" rendered by (among others) ABC News, which likened The Bell Curve to the work of the "Professors of Hate" profiled in the oft quoted Rolling Stone article of October 24. Nor were they prepared to hear no fewer than three respected commentators on the MacNeil Lehrer NewsHour of October 28 denounce the book as a "political tract," rather than a scientific treatise, despite its strict conformance with accepted guidelines for the conduct of scientific inquiry. Right or wrong, The Bell Curve is hardly the compendium of neo-nazi pseudoscience some make it out to be.


Despite the clarity of its exposition, the book's contents are only partially accessible to technically unsophisticated readers, since the claims made and the evidence adduced are both statistical in nature. The claim is made, in particular, that intelligence is an effectively scalar quantity, measurable by standard IQ tests administered (sometimes in as little as 12 minutes) by trained examiners, and that scores so obtained during the high school or even junior high school years are unexcelled predictors of adult employment status and earning power.


The authors express great confidence in the abstract measure of "general intelligence" proposed in 1904 by a former British Army officer named Charles Spearman, using the then still new concept of a correlation coefficient. As data from would-be intelligence tests began to accumulate, Spearman noticed that people who did well on one such test tended to do well on others, while those who did poorly on one tended to do poorly on all. Even when two tests were purposely designed to measure radically different cognitive skills, the correlation between scores remained positive. Although the correlations varied considerably in strength from one pair of tests to the next, they were (and continue to be) consistently positive. This convinced Spearman that differences between one intelligence and another are differences of degree, but not of kind, and motivated him to develop a scalar measure (and call it "g", for general intelligence) to quantify such differences.

An analogy from the world of boxing might shed some light on the nature of g. All the measurements included in the "tale of the tape" before a prize fight of any consequence -- such as height, weight, and reach, along with circumferences at the chest (expanded and normal), neck, waist, thigh, wrist, ankle, fist, and bicep -- correlate positively with one another, at least to the extent that heavyweights tend to be larger in each dimension than middleweights, who tend to be larger in every way than lightweights. In consequence, Spearman's algorithm can be employed to determine an abstract scalar measure b of "boxer size." Perhaps the fight game should replace its traditional weight classes with b-classes: Maybe young fighters could be better protected from injury that way. That still doesn't mean, however, that boxer size is a scalar quantity, or that the differences between two boxers of equal b are unimportant.


Spearman's method applies equally well to measurements of intelligence and boxer size and reveals no more about the one than about the other. Nevertheless, Herrnstein and Murray cite an extensive literature purportedly placing the essential correctness of Spearman's conclusions beyond reasonable doubt. They also point out that the current tests have largely been purged of the "cultural bias" once alleged to invalidate them: Twenty-five years have passed since the appearance of the report that made bias a sensitive issue (Arthur Jensen, 1969), and the problem never was as grave as advertised, say Herrnstein and Murray, nor, given time and good will, as hard to correct.


For these and other reasons, Herrnstein and Murray tend to ignore the distinctions between g, IQ, and intelligence. Because others refuse to concede that those distinctions are unimportant, however, the abbreviation "IQtelligence" is used in place of "intelligence as measured by g" in the remainder of this review. The extent to which intelligence and IQtelligence are one and the same thing may never be known. Although g is easily measured, attempts to define it and to observe it directly have never succeeded.

Because even the most efficient intelligence tests include many questions, a high degree of "data compression" is undoubtedly possible without significant information loss. The Educational Testing Service achieves it by reporting just two scores (for verbal and quantitative abilities) on its oft defamed SAT test and three (for verbal, quantitative, and analytical skills) on its Graduate Record Examination. Both sets of scores are expressed on the familiar SAT scale, with its standard deviation of 100 about a mean of 500. Spearmanites further simplify the reporting process by combining scores from the different segments of a given intelligence test into a weighted average representing g, typically expressed on the IQ scale, where the standard deviation is 15 about a mean score of 100.


Herrnstein and Murray justify (in part) their acceptance of g as a measure of intelligence by observing that little, if any, of the predictive power of intelligence testing seems to be lost by so doing. Although teenage IQ is not by itself a reliable predictor of success in engineering and other quantitative curricula, it does seem to predict adult employment status and earning power in today's increasingly complex world.


The first of the four parts of The Bell Curve summarizes extensive evidence indicating that IQtelligence is (at least statistically) predictive. Part II explores the extent to which low IQ appears to predispose an individual toward poverty, failure in school, unemployment, illness, injury in the workplace, family problems, welfare dependency, and ineffective parenting, or a life of crime, incivility, and poor citizenship. Although these and other social ills have been studied extensively, IQ and its equivalents have often been omitted from the list of potential explanators, seriously compromising (at least in the opinion of Herrnstein and Murray) the validity of the conclusions reached. They stress that "years in school" and "highest degree earned" are inadequate proxies for IQtelligence. Part III digresses on racial issues, and a short Part IV discusses conclusions and policy prescriptions.

Resting as it does on the still controversial statistical technique known as meta-analysis, the evidence with which the authors seek to establish the correlation between teenage IQtelligence and adult status and earning power demands scrutiny. In use since 1904, when Karl Pearson grouped data from the British military to conclude that the then current practice of vaccination against intestinal fever was ineffective, the technique did not become commonplace until the 1980s. Today, meta-analysis is prominent in medical research and is becoming more so in the social sciences, due in part to its 1992 endorsement by the National Research Council. It is designed to illuminate the not uncommon situation in which scores or even hundreds of costly studies of a given issue have already been made, by a host of different investigators, using a variety of different approaches, without achieving actionable consensus.


Meta-analysis represents an attempt to replace the blue ribbon committee approach to building such consensus with something more scientific. The idea is to treat the existing studies as data to which the tools of statistical inference may be applied. Yet meta-analysis remains a controversial method of inference which has sparked controversy in every field to which it has been applied: Few investigators, it has been suggested [1], possesses the statistical expertise to conduct and interpret meta-analysis.


That said, it does appear that postadolescent IQ has indeed become an excellent predictor of adult "employment status" and/or earning power. The authors of The Bell Curve point out, in summarizing the findings on which that conclusion presently rests, that whereas the year 1900 found the top 10% of American IQs scattered almost uniformly throughout the workforce (if not on the farms where half the population still lived, then in stores, churches, factories, bicycle shops, and the like), the second millennium will find them highly concentrated in science, medicine, the law, top management, and a handful of other more or less prestigious occupations. As the social and financial barriers that once restricted entry into the more desirable occupations have fallen, members of what Herrnstein and Murray term the "cognitive elite" have come to all but monopolize them.


Readers of The Bell Curve will, of necessity, learn much about this cognitive elite. In addition to spending more years in school than most, and receiving better grades, say the authors, members "watch far less television than the average American. Their movie-going tends to be highly selective. They seldom read the national tabloids that have the nation's highest circulation figures or listen to the talk radio that has become a major form of national communication for other parts of America." They are also, even at an early age, more politically inclined than average. None of this means that "the cognitive elite spend their lives at the ballet and reading Proust. Theirs is not a high culture, but it is distinctive enough to set them off from the rest of the country in many important ways."


Members tend, in particular, to live in virtual isolation from nonmembers. As columnist Mickey Kaus puts it, "I entered a good Ivy League college in 1969. I doubt I've had a friend or regular social acquaintance since who scored less than 1100 on his or her SAT boards." Isolated or not, members of the cognitive elite tend to earn substantially more than other Americans. The figure shown here, which appears on page 516 of The Bell Curve, provides historical perspective.


As shown in the figure, whereas median family income rose rather steadily to a 1973 peak, then leveled off at a somewhat lower level, the fraction of American families with income in excess of a hundred thousand 1990 dollars has continued to climb (with some irregularities). Their new-found riches, Herrnstein and Murray allege, tend to bring the political interests of the cognitive elite into alignment with those of the already affluent. The following established tendencies seem likely, say the authors, to persist and to aggravate existing social frictions:


An increasingly wealthy and isolated cognitive elite.

A merging of the cognitive and the affluent elites.

A deteriorating quality of life for people excluded from the upper reaches of the cognitive ability distribution.


The latter effect, which is partially documented by the figure, is a direct consequence of the other two. Unchecked, say Herrnstein and Murray, "these trends will lead the US toward something resembling a caste society, with the underclass mired ever more firmly at the bottom and the cognitive elite ever more firmly anchored at the top, restructuring the rules of society [italics added] so that it becomes harder and harder for them to lose. . . . Like other apocalyptic visions, this one is pessimistic, perhaps too much so. On the other hand, there is much to be pessimistic about."


The last remark would seem to explain why The Bell Curve was written in the first place. Herrnstein and Murray knew full well that they would be accused of racism, bigotry, and intellectual dishonesty, just as Arthur Jensen was some 25 years ago, for saying many of the same things. Yet as they (and apparently the electorate) interpret current events, the nation is in an alarming decline, due in large part to inadequate leadership and public policy. The forces of darkness are advancing on every front, and the authors genuinely believe that the measures they propose will help stem the tide.


Many of the policy reforms proposed by the authors have to do with education. They think it extraordinarily unwise, for instance, that "only one tenth of 1 percent of all the federal funds spent on elementary and secondary education go to programs for the gifted." After all, they say, "The people who run the United States -- create its jobs, expand its technologies, cure its sick, teach in its universities, administer its cultural and political institutions_are drawn mainly from a thin layer of cognitive ability at the top." Since the 1960s, however, "while a cognitive elite has become increasingly segregated from the rest of the country, the quality of the education they receive has been degraded." Would they not run things better if they were better educated? Would they not become the philosopher kings Plato sought to train?

The Bell Curve has more to say about the nature and causes of the nation's current decline, and contains more food for thought, than even a lengthy synopsis can hope to convey. At a guess, the book's most lasting contribution will be its documentation of the nation's increasing stratification according to IQtelligence and/or wealth, and its shrill warning against any alliance of the cognitive and affluent elites. The individual agendas of these groups transcend traditional party lines, and together they constitute an even greater menace than Herrnstein and Murray seem to realize: Each group reinforces the other's instinctive arrogance by lending its prestige to the never-ending quest of every elite to "restructure the rules of society" to its own advantage.



[1] Charles C. Mann, Can meta-analysis make policy?, Science, 266 (November 11, 1994), 960-962.

[2] William Overton, Creationism in schools: the decision in McLean versus the Arkansas Board of Education, Science, 215(February 19, 1982), 934-943.

James Case is an independent consultant who lives in Baltimore, Maryland.

Reprinted from SIAM News
Volume 28-01, January 1995
(C) 1995 by Society for Industrial and Applied Mathematics
All rights reserved.


Cronbach's α (alpha) is a quantity defined in  (Click link for more info and facts about multivariate statistics) multivariate statistics. It has an important use as measure of the reliability of a  (Click link for more info and facts about psychometric) psychometric instrument, since it assesses the extent to which a set of test items can be treated as measuring a single latent variable. It was first named as such in the article: Cronbach LJ. Coefficient alpha and the internal structure of tests. Psychometrika 1951;16:297-333, although an earlier version is the Kuder-Richardson Formula 20 (often shortened to KR-20), which is the equivalent for dichotomous items, and Louis Guttman (1945) developed the same quantity under the name lambda-2.

Given that a sample was measured on a set of k items, Cronbach's α is defined as the mean
correlation across the items, adjusted upward by the Spearman-Brown prophecy formula by k. It is related to the outcome of an analysis of variance of the item data into variance due to the individuals in the sample and variance due to the items. The higher the proportion of variance due to individuals, the higher Cronbach's α.

α can take values between minus infinity and 1 (although only positive values make sense). As a rule of thumb, a proposed psychometric instrument should only be used if an α value of 0.70 or higher is obtained on a substantial sample. However the standard of reliability required varies between fields of  (The science of mental life) 
psychology: cognitive tests (tests of intelligence or achievement) tend to be more reliable than tests of  (A complex mental state involving beliefs and feelings and values and dispositions to act in certain ways) attitudes or  (The complex of all the attributes--behavioral, temperamental, emotional and mental--that characterize a unique individual) personality. There is also variation within fields: it is easier to construct a reliable test of a specific attitude than of a general one, for example.

Alpha is most appropriately used when the items measure different substantive areas within a single construct (conversely, alpha can be artificially inflated by making superficial changes to the wording within a set of items). Although this description of the use of α is given in terms of psychology, the
statistic can be used in any discipline.

See also

 (Click link for more info and facts about statistical theory) statistical theory
 (A branch of applied mathematics concerned with the collection and interpretation of quantitative data and the use of probability theory to estimate population parameters) statistics

More Subjects form Category




August 1998


IQ Since “the Bell Curve”


Christopher F. Chabris


PAST January, Governor Zell Miller of Georgia asked his legislature for enough money to give a cassette or CD of classical music to every newborn child in the state. The governor cited scientific evidence to support this unusual budget request. "There's even a study," he declared in his State of the State address, "that showed that after college students listened to a Mozart piano sonata for ten minutes, their IQ scores increased by nine points." And he added: "Some argue that it didn't last, but no one doubts that listening to music, especially at a very early age, affects the spatial-temporal reasoning that underlies math, engineering, and chess."


The so-called "Mozart effect" is one of the most publicized recent examples of our ongoing preoccupation with intelligence, a subject that not only refuses to go away but continues to raise whirlwinds of controversy. The largest such controversy, of course, surrounds The Bell Curve (1994), by the late Richard J. Herrnstein and Charles Murray. A mountain of essays and books purporting to refute that work and its conclusions grows and grows to this day. But now we also have the magnum opus of Arthur Jensen,1 a leading figure in IQ research and, like Herrnstein and Murray, a favorite target of academic liberals, as well as a posthumous volume by another leading IQ researcher, Hans Eysenck.2 So it is a good moment to look again at what we know, what we do not know, and what we think we know about this vexed subject.


IN The Bell Curve, Herrnstein and Murray set out to prove that American society was becoming increasingly meritocratic, in the sense that wealth and other positive social outcomes were being distributed more and more according to people's intelligence and less and less according to their social backgrounds. Furthermore, to the extent that intelligence was not subject to easy environmental control, but was instead difficult to modify and even in part inherited, genetic differences among individuals, Herrnstein and Murray posited, would contribute significantly to their futures.


The evidence for this thesis came largely from an analysis of data compiled in the National Longitudinal Study of Youth (NLSY), an ongoing federal project that tested over 10,000 Americans in 1980, with follow-up interviews regularly thereafter. Each participant completed the Armed Forces Qualifying Test (AFQT)--which, like any diverse test of mental ability, can be used as a measure of intelligence--and was then evaluated for subsequent social outcomes (including high-school graduation, level of income, likelihood of being in jail, likelihood of getting divorced, and so forth). As a rule, a person's intelligence turned out to predict such outcomes more strongly than did the socio economic status of his parents. This relationship held for all ethnic groups; indeed, when intelligence was statistically controlled, many "outcome" differences among ethnic groups vanished.


Herrnstein, a professor of psychology at Harvard with an impeccable reputation for scientific integrity, died of cancer just a week before The Bell Curve arrived in bookstores. This in itself may have had something to do with the frenzy of the public response. Had Herrnstein lived to participate in the debate, critics might have found the book harder to malign than it became when Murray, whose training was not in psychology but in sociology, was left to promote and defend it by himself.


Not that Murray, the author of Losing Ground (1984) and a vocal critic of the liberal welfare state, failed to do so energetically. But his lack of credentials as a hard scientist, and his overabundant credentials as a scourge of liberalism, made him a tempting target for an attack that was itself motivated as much by political as by scientific differences, and that was almost entirely focused on a side-issue in the book. That side-issue was differences in intelligence not among individuals but among groups--and specifically between whites and blacks--the degree to which those differences might or might not be explained genetically. So heated, and so partisan, was the furor at its peak that even President Clinton was asked about the book at a press conference. (He had not read it, but disagreed with it nonetheless.)

But the overreaction to what was in essence a moderate and closely reasoned book would also not have surprised Herrnstein in the least. If anything, it was a replay--actually, a more civilized replay--of what had happened to him after he published his first article on intelligence in the Atlantic in 1971. That article, entitled "IQ," besides bringing to public attention several points raised by Arthur Jensen in a 1969 paper in the Harvard Educational Review, offered a more speculative version of the argument that would be fleshed out and documented with NLSY data in The Bell Curve 23 years later.

Just as with The Bell Curve, only a small portion of Herrnstein's 1971 article dealt with differences among groups, and only a portion of that portion dealt with possible genetic influences on those differences; and, just as with The Bell Curve, these were the passages that received the greatest attention. In his article, Herrnstein concluded that "although there are scraps of evidence for a genetic component in the black-white difference, the overwhelming case is for believing that American blacks have been at an environmental disadvantage" (emphasis added). This did not stop one Nathan Hare from writing in response that "one would think that the pseudo-scientific generalizations surrounding race and IQ had long been put to rest. But the ghoulish die hard." Nor did it keep students at Harvard and elsewhere from putting up posters accusing Herrnstein of racism and calling him "pigeon-man" (in reference to his animal-learning research). His lectures were filled with protesters, and his speeches at other universities were canceled, held under police guard, or aborted with last-second, back-door escapes into unmarked vehicles. Death threats were made.


PEOPLE OFTEN react most defensively when challenged not on their firmly held beliefs but on beliefs they wish were true but suspect at some level to be false. This is the psychology behind the controversy that ensued after "IQ" in 1971 and The Bell Curve in 1994.3 On each occasion intemperate articles were written (some by the same people, barely updated), and the most strident positions were taken by those least qualified to comment on the science.4


By now, five major books have been published in direct response to The Bell Curve. Two of them, though critical, are within the bounds of reasonable discourse. Thus, Intelligence, Genes, and Success (1997), edited by four professors from the University of Pittsburgh who seem opposed to the book's public-policy conclusions, offers a fairly balanced range of scholarly views. On the sensitive question of heritability, what is especially notable is that the argument takes place mainly at the margins; although some of the book's contributors contend that the heritability of intelligence falls within a range lower than the 40-80 percent given by Herrnstein and Murray, that range is in every case much greater than zero.


A tougher line is taken in Inequality by Design: Cracking the Bell Curve Myth (1996), written by six Berkeley sociologists. This book addresses Herrnstein and Murray's main argument--that intelligence is an important determiner of social outcomes in America. To their credit, the authors do some old-fashioned hard work, reanalyzing the NLSY data and even making one correction that strengthens The Bell Curve's conclusions. But their main effort is to show, by adding variables other than parental socioeconomic status to the mix of factors predicting outcomes, that intelligence is not as important as The Bell Curve claims. Murray has since responded to this argument in a pamphlet entitled Income Inequality and IQ (published by the American Enterprise Institute); there, by considering only the NLSY data from sibling groups, within which parental background is by definition equal, he is able to show that intelligence still has very strong effects.


The conclusion one may reasonably draw from these two books, and from Murray's response, is that while intelligence may matter more or less than family background, it certainly matters, and that if it is not entirely heritable, it is heritable in some degree. It is useful to bear this in mind when considering the other three books, for one would scarcely know from reading them that such a view has any reputable backing at all. Though a few chapters in Measured Lies (1996), the most vituperative and scientifically irrelevant of the five volumes under consideration, attempt data-based argumentation, most settle for sarcasm, self-righteousness, and name-calling. And then there are The Bell Curve Debate and The Bell Curve Wars (both published in 1995); the former is an anthology of historical documents and reviews, mostly negative, which the editors rightly claim represent the general trend among responses to Herrnstein and Murray's book; the latter is a set of essays, also mostly negative, that originally appeared in a single issue of the New Republic when The Bell Curve was first published, with a few similar pieces added for effect.

According to its back cover, The Bell Curve Wars "dismantles the alleged scientific foundations . . . of this incendiary book." Since, however, the vast majority of those commenting on The Bell Curve in the anthology's pages have little or no scientific authority, whoever wrote those last words probably had in mind the single entry by the Harvard zoology professor Stephen Jay Gould. That essay, entitled "Curveball," was originally published in the New Yorker and appears both in The Bell Curve Wars and The Bell Curve Debate, occupying the first position in each. In it, Gould repeats many of the same accusations of racism and attributions of political motive that he made in his 1981 book, The Mismeasure of Man, written in response to the earlier controversy sparked by Jensen and Herrnstein.


WITHIN THE social-science community and the academic world in general, Gould's critique has been widely accepted as the canonical demonstration that the concepts of intelligence and its heritability are at best nonscientific and at worst racist and evil. (For instance, all of the contributors to Measured Lies who cite Gould's essay do so approvingly, if we count the one who asserts that it does not go far enough.) Indeed, so well has The Mismeasure of Man endured that in 1996 its publisher reissued it with a new introduction and appendices, including the ubiquitous "Curveball," but left the main text essentially unrevised.


Gould charges that the craniometrists of the 19th century, and later intelligence researchers as well, operated from racist assumptions, and implies that on those grounds their work should be ignored or even suppressed. Insofar as the charge is meant to include figures like Herrnstein and Murray, it is absurd as well as malicious. But even in those cases in the past in which racist assumptions can indeed be demonstrated, the proof of the pudding remains in the eating, not in the beliefs of the chef. Useful science can proceed from all sorts of predispositions; nor--it seems necessary to add--do the predispositions of scientists always point in the same direction, especially where discussions of human nature are concerned.


Before World War II, for example, the anthropologist Margaret Mead, presumably basing herself on her observations of non-Western cultures, wrote: "We are forced to conclude that human nature is almost unbelievably malleable, responding accurately and contrastingly to contrasting cultural conditions." Later, Mead admitted that what forced this conclusion was not the data she had collected but the political goals she espoused: "We knew how politically loaded discussions of inborn differences could become. . . . [I]t seemed clear to us that [their] further study . . . would have to wait upon less troubled times." As the shoot-the-messenger responses of Gould and others show, the times may still be too troubled for the truth.


But what about Gould's main scientific contention--that, as he puts it in his 1996 introduction to The Mismeasure of Man, "the theory of unitary, innate, linearly rankable intelligence" is full of "fallacies"?


The theory that Gould is attacking usually goes under the name of general intelligence. Its advocates, practitioners of the hybrid psychological-statistical discipline known as psychometrics, argue simply that while individuals differ in their abilities in a wide range of intellectual realms, a relationship exists among these variations that can be attributed to a common factor. This common factor is what the psychometricians label general intelligence, or g.


A brief example will illustrate the evidence they adduce for this proposition. Suppose a group of students takes a set of ten, timed mental-ability tests, five based on verbal materials (such as choosing antonyms) and five based on spatial materials (such as drawing paths through mazes). Each student will receive ten scores, and each student will have a unique profile of scores, higher on some tests than others.


Now suppose we correlate mathematically the students' scores on the five verbal tests. We will probably find them positively, though not perfectly, correlated--that is, the score on one will predict reasonably well the scores on the others. With the aid of a statistical procedure known as factor analysis, we can examine the pattern of these positive correlations and infer that they can be explained by the existence of a common factor, the most logical candidate being the "verbal ability" of the students who took the tests. Analogous results would likely occur if we factor-analyzed the set of five spatial tests.


What if we combined all ten tests in a single analysis, looking at all the possible correlations? Most likely we would find separate verbal and spatial factors at work. But those factors themselves will almost always be correlated. A superordinate, or "general," factor--g--can then be extracted to account for the commonalities across all the tests, though this factor will be revealed more by some tests than by others; such tests, known as "highly g-loaded," are taken as especially good measures of general intelligence.


TO THE extent that it is not simply political, the debate that followed The Bell Curve and "IQ," and that lies at the heart of Gould's critique in The Mismeasure of Man, is over the very existence and coherence of general intelligence. Each side has made the same points over and over, and each side believes it has refuted the other side's arguments. The reason this is so is that the two sides proceed according to different definitions of intelligence.


The psychometric camp, which includes Herrnstein and Murray, Jensen, Eysenck, John Carroll (whose 1993 treatise, Human Cognitive Abilities, offers the most extensive factor-analysis of mental tests), and most psychologists who have traditionally studied the topic, hold to a conception of intelligence that closely matches what common sense and the dictionary tell us the term means. The opposing side, which sports a more eclectic set of disciplinary backgrounds and prides itself on a more sophisticated and inclusive perspective, divides human abilities into broad classes--logical, spatial, interpersonal, verbal, etc.--and labels each class an "intelligence." The two sides then proceed to talk past each other.


Scientists make bad dictionary writers and worse philosophers. Their main skills are in constructing experiments and generating explanations for what they observe. Neither of these endeavors requires agreement on what the words involved "mean" in any deep or absolute sense, only on ways of converting the elements of the theory at issue into operations that can be carried out in an experiment and repeated later if necessary. Measurement is the most important such operation; as Kelvin pointed out long ago, without a way to measure something it cannot be studied scientifically.


This is why the oft-repeated phrase, "intelligence is nothing more than what intelligence tests measure," is, as an objection, merely a tautology. The truth is that as long as intelligence can be reliably measured--it can be, with a variety of tests--and validly applied--it can be, to predict a variety of outcomes--it is intelligence. If we suddenly started calling it "cognitive ability," "cognitive efficiency," or even "the tendency to perform well on mental tests," it would still have the same scientific properties. Nothing about the natural world would change.


One way to test the schemes of the proponents of "multiple intelligences" would be to apply research techniques that might (or might not) suggest a role in them for general intelligence. But this is an exercise the advocates of multiple intelligences tend to rule out of consideration a priori. Thus, as Howard Gardner correctly notes in Frames of Mind (1983), there is good evidence that different parts of the brain are responsible for different abilities. However, when at a recent seminar a member of Gardner's research group was asked how abilities in the various intelligences are measured, the swift response was, "We don't measure them."


The reason is obvious: any reasonable system of measurement would produce a set of scores whose correlations could be calculated, and the pattern of those correlations would likely reveal a common factor--in other words, g--accounting for some fraction of the total variation. Gardner's theory is very popular in educational circles these days, as is the idea, espoused by Daniel Goleman in Emotional Intelligence (1995), that skill at managing one's own emotions and interpreting those of others is very valuable to social interaction and success in life. Surely both of these ideas are correct, as far as they go. But neither one of them addresses intelligence in a complete way.


ANOTHER CRITICISM of the notion of general intelligence is that it is based on factor analysis, an indirect procedure that deals with the structure of tests rather than the nature of the mind and brain. This is a point raised with special vehemence by Gould. In The g Factor: The Science of Mental Ability, Arthur Jensen shows that the objection is without foundation.5


The g Factor is a deep, scholarly work laden with hundreds of tables, graphs, and endnotes, some of them with tables and graphs of their own. It is balanced and comprehensive, summarizing virtually all the relevant studies on the nature of intelligence and demolishing most of the challenges and alternative explanations of the major findings. (It is not, however, an easy book for nonspecialists to read, which is why we are also fortunate to have Hans Eysenck's much more accessible and even entertaining Intelligence: The New Look.)


In refuting Gould's point, Jensen demonstrates that mental-test scores correlate not just with one another but with many measures of information-processing efficiency, including reaction time (how quickly you can press a button after a light flashes), inspection time (how long two separate line-segments must be displayed for you to judge accurately which is longer), and working-memory capacity (how many random items of information you can remember while doing something else). Jensen also reviews the many direct biological correlates of IQ, such as myopia (a very heritable condition), brain electrical activity, estimates of nerve-conduction velocity (the speed at which brain cells communicate with one another), and the brain's metabolism of glucose. Even brain size, the study of which is richly derided by Gould, has been found with modern imaging technology to correlate with IQ.


These chapters, among the most impressive in Jensen's book, put general intelligence as a psychological trait on a more solid foundation than is enjoyed by any other aspect of personality or behavior. They also speak persuasively to the issue of its heritability, the argument for which becomes more plausible to the extent that intelligence can be associated with biological correlates.


One can go farther. To Stephen Jay Gould and other critics, belief in the heritability of intelligence is inextricably--and fatally--linked to belief in g; destroy the arguments for one and you have destroyed the arguments for the other. But as Kevin Korb pointed out in a reply to Gould in 1994, and as Jensen affirms here, the g factor and the heritability of intelligence are independent concepts: either hypothesis could be true with the other being false. In some alternate reality, intelligence could be determined by wholly uncorrelated factors, or for that matter by wholly environmental (i.e., nonheritable) factors. It is simply less of a stretch to imagine that a general factor both exists and is somewhat heritable, since, as Jensen shows, this combination describes our own reality.

STILL ANOTHER line of attack used by the detractors of g is to point to studies allegedly showing that intelligence is easy to change (and, therefore, a meaningless concept).


Arthur Jensen raised a firestorm three decades ago when he asked, "How much can we raise IQ and scholastic achievement?" and answered: not much. This brings us back to the Mozart effect, which purports to do in ten minutes what years of intensive educational interventions often fail to accomplish.


The Mozart effect was first shown in a study by Frances Rauscher, Gordon Shaw, and Katherine Ky that was reported in the British journal Nature in 1993. It is difficult to determine their experimental procedure with precision--their article was less than a page in length--but the essentials appear to be as follows. Thirty-six college students performed three spatial-ability subtests from the most recent version of the Stanford-Binet intelligence test. Before one of the tests, the students spent ten minutes in silence; before another, they listened to ten minutes of "progressive-relaxation" instructions; and before still another, they listened to ten minutes of Mozart's Sonata for Two Pianos in D Major (K. 448). The subjects performed the tests in different orders, and each test was paired with equal frequency against each listening option. The results, when converted to the scale of IQ scores: 110 for silence, 111 for relaxation, and 119 for Mozart.


"Mozart makes you smarter!" said the press releases as new classical CD's were rushed to market. A self-help entrepreneur named Don Campbell trademarked the phrase "The Mozart Effect," published a book by the same name, and began selling cassettes and CD's of his own, including versions designed specially for children. Frances Rauscher testified before a congressional committee and gave many press interviews.


What was wrong with this picture? The article in Nature did not give separate scores for each of the three Stanford-Binet tasks (necessary for comparative purposes), and it used dubious statistical procedures in suggesting that listening to Mozart enhanced overall "spatial IQ" or "abstract reasoning." Nor did the researchers analyze separately the first task done by each subject, to rule out the possibility that prior conditions may have influenced the Mozart score. Finally, they claimed that the effect lasted for only ten to fifteen minutes, but gave no direct evidence; since the subjects were apparently tested only immediately after each listening episode, there was no way to see how this interval was calculated.


IN AN attempt to reproduce the finding that classical music enhances "abstract reasoning," Joan Newman and her colleagues performed a simple experiment: each of three separate groups comprising at least 36 subjects completed two separate subsets of Raven's Matrices Test (a good measure of g) before and after listening to either silence, relaxation instructions, or the Mozart-effect sonata. All three groups improved from the first test to the second, but by the same amount; in other words, Mozart was of no particular help. In another experiment along the same lines, a group led by Kenneth Steele asked subjects to listen to ever-longer strings of digits and repeat them backward; it, too, found no benefit from prior exposure to Mozart. Other independent tests reported similar failures or equivocal results.


In response to these experiments, Rauscher and Shaw have considerably narrowed the scope of their original findings. They now concede that the post-Mozart increase in spatial performance occurred on just one of the three Stanford-Binet tasks, while on the others, varying the listening condition made no difference. According to their revised estimate, only "spatiotemporal" tasks, which require the transformation of visualized images over time, are affected by complex music, not spatial ability or reasoning in general.


Unfortunately, however, neither Nature nor any journal of similar stature has given space to the follow-up experiments, most of which have been reported in Perceptual and Motor Skills or other low-prestige journals that many psychologists never read. And the media have of course moved on, leaving the babies of Georgia with state-sponsored gifts and the public with the vague idea that if ten minutes of music can "make you smarter," then IQ cannot signify very much.


Similarly feeding this mistaken impression are other recent examples of brief treatments affecting performance either negatively or positively on IQ-type tests. Thus, the researchers Claude Steele and Joshua Aronson told one group of black undergraduates at Stanford that a difficult verbal test would diagnose their abilities and limitations, and another group that their answers would be used only for research on verbal processing. In four separate experiments, students did worse under the former conditions than under the latter.


Analogous results have been obtained with Asian female students in math tests: stressing to them that the test measures the abilities of their sex reduces their scores (women typically do worse than men in math), but stressing that it measures the abilities of their ethnic group increases their scores (Asians typically do better than other groups). But as Jensen points out, in such cases we are dealing with a stereotype about group differences that serves to increase or decrease test anxiety. That performance goes down when anxiety gets too high is a common enough finding in testing research, and says nothing about g.


What all these experiments do illustrate is that the human brain is a dynamic system whose functioning can change quite quickly. But this is not the same thing as changing intelligence itself. A few weeks of Prozac or another modern antidepressant can radically alter a person's behavior, but we still accept that his basic identity has not changed--he is still the man we knew before. Intelligence, too, is a stable characteristic of a person's behavior across a wide range of situations. He will be able to perform a task much better in one context than in another, with special training than without; but he is still the same person, and his intelligence is also still the same. Although the Mozart effect was promoted as though it were bad news for The Bell Curve and IQ, it is not.


AND NEITHER, finally, is the much-talked-about "Flynn effect." Over the past 50 years, the average score on intelligence tests has risen about three points per decade. This means that we are all getting smarter--indeed, the average adult of 1998 is, psychometrically at least, smarter than 84 percent of the population was in 1948.


The Flynn effect is named after James Flynn, who has been studying it for over fifteen years (although the phenomenon had been noted as early as the 1930's). In a chapter of a new book, The Rising Curve: Long-term Gains in IQ and Related Measures,6 Flynn notes that gains are occurring steadily in every country sampled, mainly in the West and the industrialized parts of Asia, though their size and specific nature varies in different cases. He believes the start of the increases coincided with industrialization in the 19th century, though the data are of course less reliable the farther back one goes. What he does not know is why the gains have been occurring, and the other contributors to The Rising Curve can offer only tentative theories at best.


Psychologists, like all scientists, prefer to test their theories with controlled experiments, but such experiments cannot be performed when the phenomenon to be explained is occurring throughout the world continuously over time. The difficulty in comparing times is that many things have changed with the times: the items on IQ tests are different; education is different; nutrition is better; airplanes, cars, radio, television, movies, computers, and the Internet have been invented; society has become more permissive and also more rewarding of risk-taking; testing is more widespread and people are more accustomed to being tested; birth rates are lower; and so on. Encompassing all of these time-correlated variables, the change in what might be called our cognitive environment has been simply tremendous over the past 150 years. The most relevant factors here are probably better nutrition--a topic Eysenck studied at the end of his career--plus greater, more diverse, and more complex stimulation of the brain by our everyday experiences.

Evidence of such a dramatic environmental effect on IQ scores should reinforce skepticism concerning a genetic basis for group differences. But, in any case, psychometric theory makes no claims about average or absolute levels of intelligence within or between populations, and behavioral genetics allows for complex environmental influences on traits that are still significantly heritable. And so, again contrary to popular belief, the concept of general intelligence remains as sound and as meaningful as ever, Flynn effect or no.

HAVING WITHSTOOD so many attacks, will the psychometric study of intelligence survive? Alas, not necessarily. In a pattern reminiscent of an earlier episode in the annals of modern psychology, the impact of Stephen Jay Gould's critique has been reinforced by the lack of a forceful response to it by psychometricians themselves, leaving the impression even within psychology at large that general intelligence has been routed.

Just as Gould, a paleontologist, has chided psychologists for misunderstanding genetics, so, in a review of B.F. Skinner's Verbal Behavior in 1959, the linguist Noam Chomsky chided behavioral psychologists for misunderstanding language. Like Gould, who has caricatured and ridiculed the notion of general intelligence and the factor analysis used to document it, Chomsky caricatured the tenets and methods of behaviorism, which argued that the task of psychology is to measure only behavior and to explain it only in terms of environmental and genetic causes, without referring to what goes on inside the head.

It took eleven years before a leading behaviorist, Kenneth MacCorquodale, answered Chomsky; the reason none of his colleagues had bothered to reply earlier, he explained, was that they found Chomsky's arguments simply uninformed and irrelevant to the work they did. In the meantime, however, Chomsky's review was widely read and subscribed to by the new wave of cognitive psychologists who were building a framework for psychology that remains dominant today.

Gould's book seems to have had a similar effect on young intelligence researchers. Although Jensen and several others did review The Mismeasure of Man very negatively at the time it appeared, like MacCorquodale they replied in obscure journals read mainly by their own supporters. Thanks in part to Gould's influence (and, of course, to the outrage directed against Jensen and Herrnstein in the 70's), the most popular new theories in the 1980's came to minimize the role of general intellectual ability in favor of other factors, to posit multiple "intelligences," and to give little attention to heritability. Now Eysenck, one of the heroes of psychometrics, and Herrnstein, one of its leading supporters, have died, Jensen and Carroll are approaching the end of their careers, and the psychometricians risk going into the same sort of extended bankruptcy proceedings as the behaviorists before them.

The great irony is that this is occurring just as the field of behavioral genetics has begun to thrive as never before. One of its most striking successes has been to document, through the convergence of numerous family and twin studies, the heritability of intelligence. Now researchers have been able to identify a specific gene whose variations are associated with differences in intelligence. This is a crucial step in building a complete theory of intelligence that can explain individual differences in biological as well as psychological terms. But the new generation of cognitive scientists, who focus on characteristics of the mind and brain that are common to everyone, are not too interested in differences among people, while the psychometricians, who stand to be vindicated, have been sidelined on their own playing field.

THE MOST basic claim put forth by Herrnstein and Murray was that smart people do better than dumb people. What is so troubling about that? We rarely encounter an argument over the fact that beautiful people do better than ugly people, or tall people better than short ones, though each of these propositions is also true. Is an intellectual meritocracy less just or moral than a physical one?

The answer, unfortunately, is that whenever intelligence is said, "race" is heard; whenever race is said, "genetics" is heard; and whenever genetics is said, "inferiority" is heard--even though these issues are not necessarily connected in any way. When I mentioned to friends that I was writing an article on intelligence, many were surprised, and some wanted to know why. I can only imagine how Herrnstein was treated by his colleagues during the last 25 years of his life. The public protests may have bothered him less than the fact that people in his own community never thought of him in the same way again: he had disturbed a pleasant conversation by bringing up unpleasant facts.

Since The Bell Curve, intelligence is stronger than ever as a scientific concept, but as unwelcome as ever as an issue in polite society. It would be reassuring to think that the next twenty years, which promise to be the heyday of behavioral genetics, will change this state of affairs. But if the past is any guide, many more phony controversies lie ahead.

CHRISTOPHER F. CHABRIS, here making his first appearance in COMMENTARY, is a Ph.D. candidate at Harvard specializing in cognitive neuroscience. He is at work on a book about the chess-playing machine Deep Blue and artificial intelligence.

1 The g Factor: The Science of Mental Ability. Praeger, 672 pp., $39.95.

2 Intelligence: The New Look. Transaction, 232 pp., $29.95.

3 For Richard J. Herrnstein's account of what happened after he published his Atlantic article, see his "On Challenging an Orthodoxy," COMMENTARY, April 1973. For Charles Murray's account of the later controversy, see his "The Bell Curve and Its Critics," COMMENTARY, May 1995 and subsequent letters, August 1995.--Ed.

4 In the case of The Bell Curve, a special committee set up by the American Psychological Association to report on the basic science eventually backed all of the book's main claims, as did an open letter signed by several dozen of the nation's most qualified intelligence researchers.

5 Jensen's work should not be confused with another of almost the same title, The g Factor: General Intelligence and its Implications, by Christopher Brand. This provocative but worthy book was published in the United Kingdom early in 1996 and was withdrawn within two months, after negative media coverage and a frenzy reminiscent of the early 1970's. The publisher, Wiley, also canceled the book's distribution in the United States before any copies went on sale. Brand has since been fired from his teaching position at Edinburgh University, and has yet to find a new publisher.

6 Edited by Ulric Neisser. American Psychological Association, 400 pp., $39.95.





Some Recent Overlooked Research on the Scientific Basis of "The Bell Curve"

Jensen, Arthur R. (2000) Some Recent Overlooked Research on the Scientific Basis of "The Bell Curve", Psycoloquy: 11,#106 Bell Curve (3)


Jensen, Arthur R.
Educational Psychology
School of Education
University of California
Berkeley, CA 94720-1670

nesnejanda AT


Reifman's (2000) method of literature search focuses so much on books and articles aimed specifically at criticizing "The Bell Curve" (TBC) by Herrnstein and Murray (1994) as to miss other recent publications that importantly advance the scientific underpinnings of the arguments involved in TBC. A few of these publications are noted here.

Commentary on: Reifman, Alan (2000) Revisiting the Bell Curve, Psycoloquy: 11,#99 Bell Curve (1)
Keywords: IQ, adoption studies, behavior genetics, bell curve, crime, education, intelligence, nature/nurture, poverty, twin studies, uterine environment

1. Reifman's (2000) review provides a rather lopsided impression of the scientific, as opposed to the ideological, reactions during the years since the publication of Herrnstein & Murray's (1994) "The Bell Curve" (TBC). Searching the literature by using little more than the keyword Bell Curve, as Reifman did, was bound to turn up a preponderance of negative criticisms of TBC and to overlook researches published in scholarly and scientific journals and books that are more relevant to understanding the scientific issues at the basis of TBC. Most empirical researchers in the relevant fields, as contrasted with a good many social philosophers, commentators, and ideological critics, have found little to disagree with scientifically in TBC and therefore have not had any incentive to write critical commentaries with an aim of putting down this important feature of TBC. However, specialized journals concerned with human variability in mental abilities, intelligence, and individual differences, such as INTELLIGENCE and PERSONALITY AND INDIVIDUAL DIFFERENCES, have published many studies since the appearance of TBC that extend and strengthen the body of evidence that supports the arguments of TBC. Those concerned with the issues raised by TBC will appreciate knowing of some of these recent additions to the literature. I will cite a few of them that seem to have the most far-reaching significance and are worthy of critical examination and further empirical research.

2. Reifman's most conspicuous omission is the research monograph by Charles Murray (1998), which I trust will be described in Murray's (2000) reply to Reifman's review. How could this important study have been overlooked? A follow-up analysis of the NLSY data, based on within-family measures of mental abilities and achievements, it deepens and amplifies the social concerns associated with the wide range of variation in these variables in the population. For one thing, it empirically opposes sociologists' long-favored theory that socio-economic status (SES) is a chief causal factor in individual and group differences in IQ and its important real-life correlates such as scholastic performance, job status, and income. It is surely an eye-opener and a 'must read' for all those who are concerned with the central issues of TBC.

3. Another unmentioned study, comparing the causal contributions of SES and genetic and/or biological factors to individual differences in IQ, is especially cogent because it is based on a full adoption design. This design yields an assessment of the separate effects of the SES of adopted children's biological parents (from whom they were separated in infancy. i.e., a genetic/ biological effect) and the SES of their adoptive parents (who reared them from infancy, i.e., a cultural/ environmental effect). The full adoption study consists of a 2 X 2 factorial design comparing the IQs of four evenly divided groups of subjects: school-age children who were born either to biological parents of high SES or to parents of low SES, and were adopted as infants either by parents of high SES or by parents of low SES. The original study (Capron & Duyme, 1989) is often cited to show that, indeed, both the biological and the environmental conditions influenced IQ scores based on the Wechsler Intelligence Scale for Children-Revised (WISC-R). But these data also allow a further analysis, which reveals a most crucial finding regarding the interpretation of these adoption data (Jensen, 1998a). The g factor scores derived from the intercorrelations of the various WISC-R subtests and accounting for some 50 to 60 percent of their total variance show virtually no effect of the SES-related environmental difference (i.e., the SES of the children's adoptive parents) but strongly and significantly reflect the SES-related genetic/biological effect (i.e., the SES of the children's biological parents).

4. As amply reviewed in TBC and elsewhere (Gottfredson, 1997; Jensen, 1998b), the psychometric evidence shows that the g factor is by far the largest component of the practical validity of the Wechsler scales and most other general ability test batteries for predicting scholastic achievement, success in job training programs, job performance, and occupational status. It also shows larger correlations with more physical, brain-related variables, such as brain size, brain glucose metabolic rate, and evoked electrical brain potentials, than any other psychometric factors independent of g. Accounting for only about half of the total variance in all of a battery's diverse subtests, their common factor, g, is the component of variance that most accounts for mental test scores' correlations with so many educationally, socially, and economically significant variables. The remaining reliable variance in test scores consists of group factors (e.g., verbal, numerical, and spatial abilities independent of g) that constitute less general and more specialized abilities or skills, and test specificity -- items of informational content or skill that are unique to the particular test.

5. It is a serious mistake in the context of Reifman's review to confuse the specific item-information content of the tests with the construct or latent trait that IQ tests are intended to measure, which is g. Whether or not a person knows who wrote Hamlet? or can define the meaning of vindicate, or can recall a string of seven digits is itself trivial. What the test is intended to measure and in fact what constitutes the largest proportion of the test's population variance is the general factor that is common to all of the highly diverse items composing the test and accounts for the substantial correlations between verbal and nonverbal, numerical and spatial, and many other kinds of mental tests. In the Wechsler battery, for example, g factor emerges from the substantial correlations between such diverse subtests as Vocabulary and Block Designs, General Information and Object Assembly, Similarities and Picture Arrangement. These tests have no elements of information content or skills in common; but they do have g in common.

6. It is clear that g does not reflect a property of the test itself, because many extremely different tests can measure one and the same g, which is a result of individual differences in the speed and efficiency of information processing, whatever the content of the information to which the individuals are exposed may be. An IQ test is a vehicle for assessing individuals' level of g. And as I have explained in detail elsewhere (Jensen, 1998, Chapter 10), a vehicle carries some excess baggage besides the latent trait it is intended to measure. This excess baggage in the case of IQ tests consists of certain so-called group factors (verbal, spatial, numerical, memory) and specificity, or variance that is unique to particular subtests or items and therefore contributes nothing to the item intercorrelations or subtest intercorrelations. But in virtually all present-day IQ tests the group factors and specificity, when residualized from g, constitute only a minor portion of the total variance in IQ as measured in a representative sample of native born, English speaking Americans. In the previously cited adoption study it is this excess baggage rather than g that accounts for the effect of SES of the adoptive parents on the adoptees' IQ. The SES difference in adoption experience affected only the non-g aspect of the test scores; the g factor scores that best reflect the g factor showed no effect of the SES factor at all but was clearly correlated with the biological parents' SES.

7. It should also be noted that the Armed Forces Qualification Test (AFQT) used in TBC as a measure of general intelligence is highly g-loaded and correlates as much with a variety of other IQ tests as they correlate with each other. Reifman's (par. 7) endorsement of the claim that the AFQT is really a test of schooling is therefore misleading and invalidates his conclusion that this claim strengthens the case against TBC.

8. The secular increase of approximately 3 IQ points per decade over the last few decades, a phenomenon now known as the Flynn effect, has been a favorite citation by those who wish to minimize the importance of IQ, their theory being that if the average IQ of the population can rise across time, it must not represent anything very important, or at least not anything genetic (see Neisser, 1998). Since the Flynn effect is discussed in TBC, it is surprising that Reifman does not bring it up. Probably the most interesting thing that has been discovered about the Flynn effect since the publication of TBC is similar to the finding of the adoption study previously mentioned. The Flynn effect for Wechsler tests shows it to be unrelated to the g factor; that is, the magnitudes of the secular gains on the various subtests are not at all related to the subtests' g loadings (Rushton, 1999). Apparently the secular gains in Wechsler IQ are attributable to gains in the non-g variance components in the subtests rather than to their common factor, g. What these non-g components consist of in terms of group factors or specificity is as yet undetermined. But Rushton's finding is made worrisome to TBC critics by the fact that the average difference between the mean White IQ and the mean Black IQ on the Wechsler tests is strongly related to g; that is, the g loadings of the subtests significantly predict the magnitudes of the White-Black mean differences on each of the various subtests, an effect known as Spearman's hypothesis (Jensen, 1998b, Chapter 11). When the identical statistical analysis of White-Black differences on the Wechsler scales that displays the effect predicted by Spearman's hypothesis is applied to the subtest differences due to secular gains on the Wechsler scales the result is completely different. Hence, as far as we can tell at present, the Flynn effect and the Spearman effect are entirely different phenomena. So it is unwarranted to use the Flynn effect to belittle the import of the Spearman effect or the Black-White IQ difference.

9. Heritability is most easily understood as the squared coefficient of correlation between phenotype and genotype for a given continuous polygenic trait in the general population. Most critics of TBC do their best to minimize the heritability of IQ. They would prefer to have it zero, but as that has proved wholly impossible they settle for values around 0.4, which is about the heritability of test scores obtained on very young children. The evidence indicates that the heritability of IQ increases with age from early childhood (with heritability around 0.4) to later maturity (over 0.7). Hence it is improper to speak of estimates of heritability without taking age into consideration, rather than viewing all the existing studies of IQ heritability as attempts to estimate one and the same true value of IQ heritability in the population.

10. A more serious problem and less understood phenomenon, however, is the nature of the non-genetic variance in IQ, which may constitute anywhere from 25 to 50 percent of the total IQ variance, depending on the age of the subjects. The preponderance of evidence indicates that by late adolescence virtually none of the non-genetic variance in the population consists of between-families or shared environmental influences, but consists of within-family or unshared environmental influences. To social reformers who discount the message of TBC, this finding, which came as a surprise even to behavioral geneticists, is almost as unacceptable as the evidence for IQ heritability. The non-genetic within-family causes of IQ variation are NOT shared by children who are reared together in the same family, whether they are twins, full siblings, or genetically unrelated adopted children. But TBC critics who minimize heritability appear to believe that the environmental variance in IQ consists mostly of influences that affect all of the children reared togther in the same family (i.e., shared environmental influences). These include the cultural and socio-economic factors on which well-intentioned social reformers have largely based their their hopes of explaining, or even overcoming, the wide range of IQ variation in the population. But it is that between-families component of IQ variance that diminishes to near-zero by mid-adolescence. The only remaining non-genetic variance by that time exists almost entirely within families. The environmentally caused differences in IQ between children reared together are as large as those between children picked at random from different environments.

11. What are the causes of this unsystematic environmental variation in IQ that constitutes all of its non-genetic variation? My analysis of within-family environmental variation affecting IQ, based on identical (i.e., monozygotic) twins reared together, suggests that the unshared or within-family variance is largely the result of a great number of purely random microenvironmental influences (Jensen, 1997). Any one of these influences has too small an effect to be reliably detected on the IQ scale, but their effects are normally distributed and, in concert, cause a considerable range of IQ variation. Similarly the game of roulette is purely random, and all the players who spend, say, an hour playing roulette leave the casino with widely differing amounts of winnings and losses. In the case of IQ, however, my analysis indicates that the IQ 'losses' due to the random microenvironment somewhat exceed the 'winnings.' That is, the microenvironmental factors unfavorable to mental development appear to be either more potent or more prevalent than those that are favorable.

12. Much of the random microenvironment effect on IQ is probably biological and originates from the moment of conception. It is related, for example, to maternal age, parity, immunological incompatibilities between mother and child, variation in birth weight, obstetrical practices, and other perinatal and postnatal effects, including traumas and childhood diseases add to the microenvironment. Then there are other purely random non-genetic effects that might be called 'para-genetic,' as they are carried by genes that are 'tagged' or 'imprinted' by certain molecules; but the essential genes, though 'imprinted,' are not themselves a part of the individual's genotype for a given trait. Yet these 'tagged' genes cause differences in fetal size and birth weight independent of mother's age, size, or parity; low birth weight especially affects IQ unfavorably.

13. It is believed likely that there are a great many more randomly imprinted genes (perhaps hundreds) whose effects are not yet identified (Melton, 2000). The biological and random nature of the microenvironment probably accounts for the difficulty and meager results of attempts to raise children's IQ (especially its g component), substantially and durably, by manipulating only the psychological-educational and cultural-socioeconomic aspects of the child's environment. These are alas not the main locus of control of mental development (Jensen, 1989).


Capron, C. & Duyme,M. (1989). Assessment of effects of socioeconomic status on IQ in a full cross-fostering design. Nature, 340, 552-553.

Gottfredson, L.S. (Ed.) (1997). Intelligence and social policy [special issue]. Intelligence, 24, (1)

Herrnstein, R. J., & Murray, C. (1994). The Bell Curve: Intelligence and Class Structure in American Life. New York: Free Press.

Jensen, A.R. (1989). Raising IQ without increasing g? A review of 'The Milwaukee Project: Preventing mental retardation in children at risk' by H.L. Garber. Developmental Review, 9, 234-258.

Jensen, A.R. (1997). The puzzle of nongenetic variance. In R.J. Sternberg & E.L. Grigorenko (Eds.) Heredity, intelligence, and environment (pp. 42-88). Cambridge:Cambridge University Press.

Jensen, A.R. (1998a). Adoption data and two g-related hypotheses. Intelligence, 25, 1-6.

Jensen, A.R. (1998b). The g factor: The science of mental ability. Westport, CT: Praeger.

Jensen, A.R. (1999). Precis of: "The g Factor: The Science of Mental Ability" PSYCOLOQUY 10(023) psyc.99.10.023.intelligence-g-factor.1.jensen

Melton, L. (2000). Womb wars. Scientific American, 283, 24-26.

Murray, C. (1998). Income inequality and IQ. Washington, D.C.: American Enterprise Institute.

Murray, C. (2000). Heritability and the Independent Causal Role of IQ in "The Bell Curve" (Herrnstein & Murray 1994). PSYCOLOQUY 11(105) psyc.00.11.105.bell-curve.2.murray

Neisser, U. (Ed.) (1998). The rising curve: Long term gains in IQ and related measures. Washington, DC: American Psychological Association.

Reifman, A. (2000). Revisiting The Bell Curve. PSYCOLOQUY 11(099) psyc.00.11.099.bell-curve.1.reifman

Rushton, J. P. (1999) Secular gains in IQ not related to the g factor and inbreeding depression unlike Black-White differences: A reply to Flynn. Personality and Individual Differences, 26: 381-389.

Authors: Jensen, Arthur R.
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Heritability and the Independent Causal Role of IQ in "The Bell Curve" (herrnstein & Murray 1994)

Murray, Charles (2000) Heritability and the Independent Causal Role of IQ in "The Bell Curve" (herrnstein & Murray 1994), Psycoloquy: 11,#105 Bell Curve (2)


Murray, C
American Enterprise Institute
1150 Seventeenth St. NW
Washington, DC 20036

Cmurray AT


I cite text clarifying the position of Herrnstein & Murray's (1994) "The Bell Curve" on heritability, present evidence that the independent effect of IQ on social and economic outcomes is stable across independent methods of controlling for family background, and propose that Reifman's (2000) target article assigns a curiously short time frame for assessing the outcome of the controversy over the book.

Commentary on: Reifman, Alan (2000) Revisiting the Bell Curve, Psycoloquy: 11,#99 Bell Curve (1)
Keywords: IQ, adoption studies, behavior genetics, bell curve, crime, education, intelligence, nature/nurture, poverty, twin studies, uterine environment

1. I will confine myself to two topics raised by the target article and a comment on its framework. The two topics respond to several of Reifman's (2000) more specific points.


2. An overarching confusion about Herrnstein & Murray's (1994) "The Bell Curve" (TBC), one that has led to many subsidiary confusions, concerns with importance of the heritability of IQ. The received wisdom about TBC in the mass media and in many technical discussions has been that its conclusions depend on a particular level of heritability of IQ, and that particular level is unusually high. That widespread view of the book is incorrect. The conclusions assume only "substantial" heritability and depend primarily on observed relationships between IQ and a variety of social phenomena. Many of those relationships do not involve passage of IQ from generation to generation. Others do, but whether that relationship is the result of heritability in the technical sense (genetic) or in a loose sense (being passed from parents to children through any mechanism) is usually irrelevant.

3. The reputation of TBC is such that many readers will find this characterization hard to accept. I therefore ask the indulgence of presenting verbatim the significant passages that present our view of the magnitude of heritability and the relative importance of genes and environment.

4. TBC has two extended discussions of heritability. One is in Chapter 13 and (with the exception of a passage reprinted below) is concerned with the state of knowledge about a genetic role, if any, for observed ethnic differences in test scores. The other extended discussion of heritability occurs earlier in the book, in Chapter 4, pp. 105-108, and deals with magnitude of heritability. The concluding paragraphs of that initial discussion are reprinted below, deleting the footnotes:

The technical literature is filled with varying estimates of the heritability of IQ, owing to the varying models being used for estimation and to the varying sets of data. Some people seem eager to throw up their hands and declare that, "No one knows (or can know) how heritable IQ is." But that reaction is as unwarranted as it is hasty, if one is content, as we are, to accept a range of uncertainty about the heritability that specialists may find nerve-wracking. We are content, in other words, to say that the heritability of IQ falls somewhere within a broad range, and that, for purposes of our discussion, a value of .6 to .2 does no violence to any of the competent and responsible recent estimates. The range of .4 to .8 includes virtually all recent (since 1980) estimates competent, responsible, or otherwise.

Recent studies have uncovered other salient facts about the way IQ scores depend on genes. They have found, for example, that the more general the measure of intelligence-the closer it is to g-the higher the heritability. Also, the evidence seems to say that the heritability of IQ rises as one ages, all the way from early childhood to late adulthood. This means that the variation in IQ among, say, youths ages 18 to 22 is less dependent on genes than that among people ages 40 to 44. Most of the traditional estimates of heritability have been based on youngsters, which means that they are likely to underestimate the role of genes later in life. Finally, and most surprisingly, the evidence is growing that whatever variation is left over for the environment to explain (i.e., 40 percent of the total variation, if the heritability of IQ is taken to be .6), relatively little can be traced to the shared environments created by families. It is, rather, a set of environmental influences, mostly unknown at present, that are experienced by individuals as individuals. The fact that family members resemble each other in intelligence in adulthood as much as they do is very largely explained by the genes they share, rather than the family environment they shared as children. These findings suggest deep roots indeed for the cognitive stratification of society.

5. We reiterate our position on heritability elsewhere in the book. Here are the relevant additional passages.

From Chapter 5, p. 130:

In discussions of intelligence, people obsess about nature versus nurture, thinking that it matters fundamentally whether a person with a low IQ at, say, age 15 came by that IQ through a deficient environment or by bad luck in the genetic draw. But it does not matter for the kinds of issues we consider in Part II. The AFQT test scores for the NLSY sample were obtained when the subjects were 15 to 23 years of age, and their IQ scores were already as deeply rooted a fact about them as their height.

From Chapter 13, p. 314:

Aren't genetic differences passed down through the generations, while environmental differences are not? Yes and no. Environmentally-caused characteristics are by definition not heritable in the narrow technical sense that they do not involve genetic transmission. But nongenetic characteristics can nonetheless run in families. For practical purposes, environments are heritable too. The child who grows up in a punishing environment and thereby is intellectually stunted takes that deficit to the parenting of his children. The learning environment he encountered and the learning environment he provides for his children tend to be similar. The correlation between parents and children is just that: a statistical tendency for these things to be passed down, despite societys attempts to change things, without any necessary genetic component. In trying to break these intergenerational links, even adoption at birth has its limits. Poor prenatal nutrition can stunt cognitive potential in ways that cannot be remedied after birth. Prenatal drug and alcohol abuse can stunt cognitive potential. These traits also run in families and communities and persist for generations, for reasons that have proved difficult to affect.

From Chapter 15, p. 342:

We will refer to this downward pressure as dysgenesis, borrowing a term from population biology. However, it is important once again not to be sidetracked by the role of genes versus the role of environment. Children resemble their parents in IQ, for whatever reason, and that immigrants and their descendants may not duplicate the distribution of America's resident cognitive ability distribution. If women with low scores are reproducing more rapidly than women with high scores, the distribution of scores will, other things equal, decline, no matter whether the women with the low scores came by them through nature or nurture.

6. When one finds that others are widely misinterpreting one's text, it is natural to ask how the point could have been made more clearly. Were Herrnstein and I writing anew, I would favor expanding our discussion of the nonshared environment and linking it with findings about the increasing heritability of IQ with age. Even though everyone, including Herrnstein and I, believe that environment plays a substantial role in IQ, the net result of age and nonshared environment leads to findings of near-zero correlations between the IQs of adoptive siblings by their mid and late teens (Scarr & Weinberg 1978; Loehlin, Horn, and Willerman, 1989). Since all of TBC's discussion of the relationship of IQ to social and economic outcomes bears on behaviors that occur in the teenage years and beyond, perhaps elaborating on this combination of age and the role of the shared environment would have been helpful in underscoring why the narrow genetic understanding of heritability is less important than the de facto transmission of IQ from generation to generation. Perhaps not, however. The passages quoted above are not really ambiguous even as they stand.

7. To sum up: The scientific assertion of TBC regarding nature vs. nurture is that IQ is substantially heritable, between 40-80 percent, that the environmental component is dominated by the nonshared environment, and that environmental influences can become as hard-wired by adolescence as genetic heritage. None of these views was exceptional in the technical literature at the time we wrote them, nor are they now.


8. A large cluster of issues regarding TBC centers on the book's estimates of the independent effect of IQ on various social and economic outcomes after taking socioeconomic status into account, using an SES index comprised of parental education, occupation, and income entered as an independent variable in a regression analysis. Once again, an extended direct quotation from TBC may be helpful in understanding what TBC set out-and did not set out-to demonstrate. From the introduction to Part II, pp. 122-123:

In most of the chapters of Part II, we will be looking at a variety of social behaviors, ranging from crime to childbearing to unemployment to citizenship. In each instance, we will look first at the direct relationship of cognitive ability to that behavior. After observing a statistical connection, the next question to come to mind is, What else might be another source of the relationship?

In the case of IQ, the obvious answer is socioeconomic status. To what extent is this relationship really founded on the social background and economic resources that shaped the environment in which the person grew up-the parents' socioeconomic status (SES)-rather than intelligence? Our measure of SES is an index combining indicators of parental education, income, and occupational prestige (details may be found in Appendix 2). Our basic procedure has been to run regression analyses in which the independent variables include IQ and parental SES. The result is a statement of the form: "Here is the relationship of IQ to social behavior X after the effects of socioeconomic background have been extracted," or vice versa. Usually, this takes the analysis most of the distance it can sensibly be pushed. If the independent relationship of IQ to social behavior X is small, there is no point in looking further. If the role of IQ remains large independently of SES, then it is worth thinking about, for it may cast social behavior and public policy in a new light.

We do not have the choice of leaving the issue of causation at that, however. Because intelligence has been such a taboo explanation for social behavior, we assume that our conclusions will often be resisted, if not condemned. We can already hear critics saying, "If only they had added this other variable to the analysis, they would have seen that intelligence has nothing to do with X." A major part of our analysis has accordingly been to anticipate what other variables might be invoked, and seeing if they do in fact attenuate the relationship of IQ to any given social behavior. This was not a scattershot effort. For any given relationship, we asked ourselves if evidence, theory, or common sense suggests another major causal story. Sometimes it did. When looking at whether a new mother went on welfare, for example, it clearly was not enough to know the general socioeconomic background of the woman's parents. It was also essential to examine her own economic situation at the time she had the baby: whatever her IQ is, would she go on welfare if she had economic resources to draw on?

At this point, however, statistical analysis can become a bottomless pit. It is not uncommon in technical journals to read articles built around the estimated effects of a dozen or more independent variables. Sometimes the entire set of variables is loaded into a single regression equation. Sometimes, sets of equations are used, modeling even more complex relationships, in which all the variables can exert mutual effects on one another.

Why should we not press forward? Why not also ask if religious background has an effect on the decision to go on welfare, for example? It is an interesting question, as are fifty others that might come to mind. Our principle was to explore additional dynamics when there was another factor that was not only conceivably important but for clear logical reasons might be important BECAUSE OF DYNAMICS HAVING LITTLE OR NOTHING TO DO WITH IQ. This last proviso is crucial, for one of the most common misuses of regression analysis is to introduce an additional variable that in reality is mostly another expression of variables that are already in the equation.

9. The italics were in the original, and they point to my broad objection to many of the reanalyses of TBC. The addition of independent variables to try to explain away the independent role of IQ has commonly included variables that are worse than irrelevant; they soak up variance that logic tells us is likely to be attributable to parental IQ or the subjects own IQ.

10. Working out the technical debates on the appropriate treatment of causally related independent variables is complex and seldom decisive. There is, however, a way of bypassing some aspects of the debate by using an independent means of analysis. The sample for the National Longitudinal Survey of Youth (NLSY) used for many of the analyses in TBC included 5,863 subjects who shared the same household with at least one other NLSY subject as brother or sister. A sample this large permits analysis of sibling pairs, thereby controlling not only for socioeconomic status but for the entire constellation of variables that go into the shared environment. Korenman and Winship (2000) have conducted such an analysis, using a siblings fixed-effects model. I also used sibling comparisons in a monograph on income inequality and IQ (Murray 1998).

11. The Korenman and Winship paper offers a nice illustration of where the debate can and cannot be resolved. Part of their paper involves the kind of elaboration of independent variables that I find unrealistic, adding to regression equations variables that certainly have a correlation with, and are probably a function of, IQ. On the interpretation of these analyses, we disagree. But part of their analysis of sibling pairs simply replicates TBC's method, asking how the independent effect of IQ using sibling pairs compares to the independent effect of IQ when an SES index is used as a control. They present a direct comparison of the results for virtually all of the dependent variables used in the Part II of TBC. (Korenman and Winship 2000 Table 7.2). Thus, for example, the OLS estimate of the independent effect of IQ on annual wages for year-round workers is $5,548 using TBC's control for parental SES compared to $5,317 in the siblings fixed-effects model. For years of schooling, the respective coefficients are .59 and .45. The logit coefficients for the TBC control for parental SES and the siblings fixed-effects model are, respectively, 1.76 and 1.87 for attainment of a BA degree, 1.39 and 1.72 for being in a high-IQ occupation, .34 and .30 for probability of being out of the labor force for a month or longer in the most recent year, and .52 and .47 for probability of being unemployed for a month or longer in the most recent year. These are examples from a long list, but not atypical ones. As Korenman and Winship observe as they introduce Table 7.2, "[w]ith few exceptions, the fixed-effects estimates for AFQT are remarkably similar to the standard OLS and logit estimates." (Korenman and Winship 2000: 146).

12. I emphasize that the sibling results do not demonstrate that socioeconomic status, or family background more generally, are unimportant in determining social and economic outcomes. Herrnstein and I accepted that they often are. The sibling analysis simply gives us a way of pushing these factors out of the picture and asking whether differences in IQ still make a difference among children from the same family. They do make such a difference, of the same magnitude as the independent effect claimed in TBC. This puts a burden on those who would dismiss the importance of IQ in social and economic outcomes that few critics of TBC have taken up. Many of them seem to be trying to refute a claim ("IQ is important and other factors arent") that TBC never made.


13. Professor Reifman frames the target article by referring to my expectation, expressed in the Afterword to the soft cover edition of TBC, that the attacks on TBC would eventually prove embarrassing to many of the critics. He sets out to ask whether I have been proved right five years later and concludes that I was wrong.

14. I did not specify a timetable for the process, but even so I am puzzled that Reifman could think the three-stage sequence I specified in the Afterword has gotten past the first stage. Certainly the sources cited by Reifman are overwhelmingly part of the first stage of the process. Many of them were already in draft form within six months of the publication of TBC. Apart from that, it didn't occur to me that anyone could imagine that the dust would settle within five years. Can anyone think of another social science controversy generating as much emotion as this one that has been resolved so quickly? As for the special case of the heritability of IQ, we can all sit back and relax. The answer is on the way, not from psychometrics but from genetics, and the wait should not be more than another decade or so. If I were to have to set a timetable, I suppose another ten years would also be a good time to revisit TBC.


Herrnstein, R. J., & Murray, C. (1994). The Bell Curve: Intelligence and Class Structure in American Life. New York: Free Press.

Korenman, S., & Winship, C. (2000). A reanalysis of The Bell Curve: Intelligence, family background, and schooling. In K. Arrow & S. Bowles & S. Durlauf (Eds.), Meritocracy and Economic Inequality. Princeton: Princeton University Press.

Loehlin, J. C., Horn, J. M., & Willerman, L. (1989). Modeling IQ change: Evidence from the Texas Adoption Project. Child Development, 60 (4), 993-1004.

Murray, C. (1998). Income Inequality and IQ. Washington: AEI Press. Scarr, S., & Weinberg, R. A. (1978). The influence of "family background" on intellectual attainment. American Sociological Review, 43 (October), 674-692.

Reifman, A. (2000). Revisiting The Bell Curve. PSYCOLOQUY 11(099) psyc.00.11.099.bell-curve.1.reifman

Authors: Murray, Charles
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Commentary on some of the empirical and theoretical support for The Bell Curve.

Kranzler, John
Vol. 24, School Psychology Review, 01-01-1995, pp 36.

John H. Kranzler, PhD, received doctorate from the University of California ay Berkeley in 1990. He is currently an Assistant Professor of School Psychology at the University of Florida. His research focuses on the structure, development, and assessment of human cognitive abilities Address all correspondence concerning this article to John H. Kranzler, College of Education, University of Florida, 1403 Norman Hall, Gainesville, FL 32611-2053.

Abstract: This commentary discusses two important components of The Bell Curve: Intelligence and Class Structure in American Life. The first is the original empirical evidence presented by Herrnstein and Murray to demonstrate the central role of intelligence in American life. The second is Spearman's g, the general factor underlying individual differences in all tests and performances involving cognitive ability. This article concludes that: (a) although the results of Herrnstein and Murray's multiple regression analyses of the National Longitudinal Survey of Youth (NLSY) cannot be easily dismissed, these data do not provide unequivocal support for theft policy recommendations; and (b) despite the fact that a considerable amount of contemporary research substantiates the importance of g as a psychological construct, educational and public policy should be based on more than psychometrics and statistics.

The Bell Curve: Intelligence and Class Structure in American Life, by the late Richard J. Herrnstein and Charles Murray (1994), is about the implications of individual and group differences in intelligence for educational and public policy. According to Herrnstein and Murray:

To try to come to grips with the nation's problems without understanding the role of intelligence is to see through a glass darkly indeed, to grope with symptoms instead of causes, to stumble into supposed remedies that have no chance of working. (pp. xxii-xxiii)

Briefly, they argued that, because intelligence is largely inherited and substantially immutable, social programs based on environmentalist ideals (e.g., Affirmative Action) are unlikely to succeed and should be drastically altered or eliminated. Herrnstein and Murray's recommendations for educational policy include: increasing the funding of programs for the intellectually gifted (at the expense of programs for those with learning difficulties); allowing all parents to choose the schools their children attend; and emphasizing the classical notion of the "educated person" as the overarching goal of public schools.

The Bell Curve received an incredible amount of almost entirely negative attention in the media, mainly because it addressed, in part, the controversial issues of the heritability of intelligence and racial- ethnic group differences in cognitive ability. According to Herrnstein and Murray, the possibility that group differences in intelligence are partly responsible for many of the social and economic inequalities that exist across racial-ethnic groups has long been considered too sensitive to discuss in public, yet badly needs airing. Many have disagreed, asserting that the book will only fan the flames of racism and exacerbate ethnic balkanization. Criticism of The Bell Curve has been harsh. In The New Republic (October 31, 1994), for example, respondents referred to it as "pseudo-scientific racism" and "errant nonsense. " One commentary was even entitled, "Neo-Nazis!" Stephen Jay Gould (1994), the Harvard paleontologist who wrote The Mismeasure of Man, characterized Herrnstein and Murray's policy recommendations as " anachronistic social Darwinism" (p. 138) and called the book a "manifesto of conservative ideology" (p. 141).

For better or worse, the arguments presented in The Bell Curve are being widely contemplated, if book sales and media coverage are any indication. My intention in this commentary is not to review The Bell Curve in its entirety. Space limitations preclude a thorough discussion of all the complex issues addressed by Herrnstein and Murray. Instead, two important components of The Bell Curve will be examined. The first is the original empirical evidence presented by Herrnstein and Murray to demonstrate the central role of intelligence in American life. The second is Spearman's g. Although not discussed in depth in The Bell Curve, the g factor is, as Gould (1994) noted, "the sine qua non of their entire argument" (p. 143).


Herrnstein and Murray provided considerable empirical support for their detailed arguments in The Bell Curve. A significant portion of their 845-page book presents the results of original analyses of data from the National Longitudinal Survey of Youth (NLSY). The NLSY began in 1979 as a nationally representative sample of 12,686 individuals between 14 and 22 years of age, each of whom has been resurveyed annually for the past 15 years. The demographic information gathered for the NLSY includes the youths' childhood environment and parental socioeconomic status (SES), as well as their subsequent educational and occupational attainment, work history, and family formation. Participants in the NLSY also have been administered a number of intelligence and cognitive ability measures. As stated in The Bell Curve, the NLSY is "the mother lode for scholars who wish to understand the relationship of cognitive ability to social and economic outcomes" (p. 119).

Herrnstein and Murray analyzed the NLSY data with multiple regression. In most of their analyses, they used intelligence and SES to predict important social and economic outcomes. Herrnstein and Murray's main objective was to determine the relationship between intelligence and these outcomes after controlling for socioeconomic background, and vice versa. They asserted that, "if the role of IQ remains largely independent of SES, then it is worth thinking about, for it may cast social behavior and public policy in a new light" (p. 123). To measure cognitive ability, they used the Armed Forces Qualification Test (AFQT), a highly g-loaded instrument with excellent psychometric properties. To assess socio-economic background, Herrnstein and Murray created a new index based on family income, education, and occupation. They re-potted a Cronbach's alpha reliability coefficient of .76 for this measure, but no evidence of validity.

According to Herrnstein and Murray, results of these analyses underscore the predominant influence of intelligence in determining wealth, poverty, and social status. They asserted that their findings also demonstrate the integral relationship between intelligence and a host of important social behaviors, such as parenting, welfare dependency, crime, child neglect, and illegitimacy, among others. Herrnstein and Murray concluded that intelligence is a much better predictor of these behaviors than socioeconomic background. In fact, after controlling for intelligence, they found that the relationship between socio -economic background and many social, educational, occupational, and economic outcomes was negligible. Despite the fact that the substantive conclusions reached by Herrnstein and Murray in The Bell Curve rest largely on the analysis of one set of data with one statistical technique, their findings cannot be easily dismissed. Not only did they analyze an excellent set of data with appropriate statistical techniques, but their findings are generally consistent with the results of past studies (see Brody, 1992; Jensen, 1980, 1993a, for reviews).

Nevertheless, Herrnstein and Murray's interpretation of these statistically significant results has been subject to criticism. Judis (1994), for example, argued that "Murray and Herrnstein acknowledge the difference between demonstrating correlation and causation, but consistently use the language of causation when they merely have demonstrated correlation" (p. 18). As a result, he maintained, "a distorted picture of social change emerges" (p. 18) in their recommendations for public policy. Gould (1994) raised the issue of practical versus statistical significance of empirical results. He asserted that:

In violation of all statistical norms that rye ever learned, they plot only [emphasis in the original] the regression curve and do not show the scatter of variation around the curve, so their graphs do not show anything about the size of the relationship -that is, the amount of variation in social factors explained by IQ and socio-economic status. (pp. 145-146)

After examining the analysis of variance tables in Appendix 4 of The Bell Curve, Gould concluded that "their own data indicate that IQ is not a major factor in determining variation in nearly all the social behaviors they study" (p. 146). He stated that "although low figures are not atypical for large social-science surveys involving many variables, most of Herrnstein and Murray's correlations are very weak -- often in the 0.2 to 0.4 range" (p. 147). Gould also accused Herrnstein and Murray of "pervasive disingenuousness" (p. 140), partly because information on the variance explained in their regression analyses is "tucked away" in an appendix, instead of discussed in the text along with graphic presentation of their results.

Although Herrnstein and Murray did consider the fact that substantial dispersion is bound to exist around regression lines for moderately correlated variables, they argued that "the exceptions [to the general relationship] do not invalidate the importance of a statistically significant correlation" (p. 68). They also provided a rationale for deemphasizing the variance accounted for by the independent variables in their analyses. As Herrnstein and Murray stated:

A crucial point to keep in mind abut correlation coefficients... is that correlations in the social sciences are seldom much higher than .5 (or lower than-.5) and often much weaker -- because social events are imprecisely measured and are usually affected by variables besides the ones that happened to be included in any particular body of data. A correlation of .2 can nevertheless be "big" for many social science topics. In terms of social phenomena, modest correlations can produce large aggregate effects. (p. 67)

Given Herrnstein and Murray's focus on the implications of their results for educational and public policy, emphasizing the interpretation of statistically significant regression slopes rather than the variance explained seems reasonable. In addition, many researchers in the social and behavioral sciences would not agree with Gould's (1994) description of correlations in the 0.2 to 0.4 range, which explain between .4 and 16% of the variance, as "very weak." According to Cohen (1977), a "large" effect explains more than 15% of the variance, a "medium" effect about 6%, and a "small" effect about 1%. On this "scale," Herrnstein and Murray's results are best described as medium to large. Regardless of the label one attaches to the amount of variance explained in Herrnstein's and Murray's analyses, it is important to note that these are still correlational results. Causality is not established by the existence of a correlation between variables.

One potential problem with the multiple regression analyses reported in The Bell Curve that has not been mentioned in prior reviews concerns measurement error. Reliability of measurement affects correlations. The maximum correlation that can be obtained between any two variables is the square root of the product of their reliabilities. When the reliability of either or both is less than perfect, the correlation will be attenuated. Because some degree of measurement error is the rule rather than the exception, correlations usually underestimate the true degree of association between variables. Fortunately, they can be corrected for measurement error to estimate the true population value. Correlations corrected for attenuation are larger than uncorrected correlations, sometimes substantially so.

In contrast to the predictable effect of measurement error on zero- order correlations, in multiple regression the effect of measurement error is unpredictable. True regression parameters will be either overestimated or underestimated as a function of measurement error, depending upon the pattern of correlations among the variables and their reliabilities (Pedhazur, 1982). The reliability of a variable partialed out in multiple regression is especially important. Regarding the independent variables used by Herrnstein and Murray, the reliability of the AFQT is quite high, but the reliability of their index of socioeconomic background is only moderate (i.e., less than 0.80). Nevertheless, Herrnstein and Murray apparently did not correct for attenuation while conducting their multiple regression analyses. Results of their analyses of the NLSY data, therefore, must be viewed with caution until the unpredictable effect of measurement error has been examined, particularly when controlling for socioeconomic background.


The Bell Curve is based on six conclusions about tests of cognitive ability that, according to Herrnstein and Murray (1994), are beyond significant dispute in the scientific literature:

1. There is such a thing as a general factor of cognitive ability on which human beings differ.

2. All standardized tests of academic aptitude or achievement measure this general factor to some degree, but IQ tests expressly designed for that purpose measure it most accurately.

3. IQ scores match, to a first degree, whatever it is that people mean when they use the word intelligent or smart [emphases in the original] in ordinary language.

4. IQ scores are stable, although not perfectly so, over much of a person's life.

5. Properly administered IQ tests are not demonstrably biased against social, economic, ethnic, or racial groups.

6. Cognitive ability is substantially heritable, apparently no less than 40 percent and no more than 80 percent. (pp. 22-23)

Herrnstein and Murray derived these six conclusions from what they referred to as the classical paradigm of intelligence research and theory. Classicist researchers maintain that the structure of mental ability is best described as hierarchical, with Spearman's g at the apex (e.g., see Carroll, 1993). Although g is recognized as but one of many factors of cognitive ability, they contend that it is the most important one. As Jensen (1992a) stated:

In recent years, the study of general mental ability [emphasis in the original], or g, has begun to look as a science should. Along with the increasing realization of the tremendous importance of this subject, there has been an unusually rapid growth of theoretical and empirical research, both psychometric and experimental. (p. 271)

Herrnstein and Murray agreed with researchers in the classical paradigm on the importance of g, yet did not discuss this central concept in sufficient detail. My aim here is to sketch some of the most fundamental things known about g, so that readers of The Bell Curve may better evaluate its theoretical foundation.

What is g?

Spearman's g is a scientific construct, not a real thing that resides in the brain. It is used to explain an observable phenomenon known as the "positive manifold," which is the empirical fact that correlations between tests of cognitive ability are almost always positive. The positive manifold indicates that a common source of variance underlies individual differences in all tests and performances involving cognitive ability. Spearman (1994) invented factor analysis to measure g empirically. For any particular battery of mental tests, the g factor is estimated equally well by the first (unrotated) principal factor, the first principal component, the single highest-order factor in a Schmid-Leiman hierarchical factor analysis, and LISREL methods of factor analysis (Jensen & Weng, 1994; Ree & Earles, 1991). Estimates of g also are quite stable. According to Thorndike (1987), the g factor extracted from any large and varied battery of mental tests will be essentially the same g.

No test or performance involving cognitive ability measures only g, however. The nonerror variance of most tests also reflects specificity and group factors. Nevertheless, g accounts for more variance than any other independent component of individual differences in tests of cognitive ability (see Jensen, 1980). In fact, the g factor often accounts for more variance than all other group factors combined, even when tests are designed without the expressed intent of measuring g. For example, Kranzler and Weng (in press) recently found that a battery of tests developed by Naglieri, Das, Stevens, and Ledbetter (1991) to measure the constructs of the planning, attention, and simultaneous- successive (PASS) processes theory of human cognition primarily measured g. The second-order g accounted for 59.3% of the common factor variance among the PASS tests, which is considerably more than that accounted for by the g of conventional IQ tests, such as the Weschler Intelligence Scales for Children-3rd Edition (see Sattler, 1992).

Another well-established fact about g is that it is related to processing complexity. Cognitive tasks' g-loadings are an increasing monotonic function of the complexity of information processing required for successful task completion. Loadings on g are not related to the task' s surface characteristics. As Jensen (1992a) asserted, "The knowledge and skill content of performance on mental ability tests is merely a vehicle for g, which reflects the overall capacity and efficiency of information processes by which the knowledge and skill are acquired and used" p. 275, emphases in the original).

Why is g Important?

The importance of g lies in the fact that it correlates substantially with phenomena outside the domain of psychometric tests and factor analysis. Psychometric g is therefore not simply a mathematical artifact. For example, g is more predictive of outcomes in educational achievement, job training, and job success than any other factor derived from tests of cognitive ability (Jensen, 1992b, 1993a; Ree & Earles, 1992). In addition, Jensen (1993b) argued that the size of the black-white group difference on cognitive tasks is a direct function of the tasks' loading on g. Psychometric g also is related to the heritability (i.e., the proportion of genetic variance) of cognitive tests, which indicates that individual differences in g are determined in part by genetics and therefore influenced by biological functioning (e. g., Bouchard, Lykken, McGue, Segal, & Tellegen, 1990).

A great deal of contemporary research is now aimed at determining the neurophysiological and psychological mechanisms that underlie g (for review, see Jensen, 1992a; Vernon, 1993). The significant correlates of g identified by researchers thus far include: averaged evoked potentials (e.g., Barrett & Eysenck, 1992), nerve conduction velocity (e.g., Vernon & Mori, 1992), speed of neural and synaptic transmission in the visual brain as measured by the positron emission tomography scanning technique (e.g., Haler, Siegel, Crinella, & Buchsbaum, 1993), and the speed and efficiency of elementary cognitive processes (see Vernon, 1990a, for a review). The consistency and coherence of these data reflect real scientific progress that must be explained by any viable theory of intelligence. Many now believe that the results of this research substantiate a neural efficiency model of g (see Vernon, 1993). According to Vernon (1900b), this model postulates that "persons who perform well on intelligence tests (who have high "IQs") have brains that can operate faster and more efficiently than those of persons who perform less well" (p. 295).

In The Bell Curve, Herrnstein and Murray have gone further than most in discussing the implications of individual and group differences in g for educational and public policy. Some would say they have gone too far. Because human abilities obviously comprise more than g, it is misleading, or possibly even hazardous, to hold g as the sine qua non of American life. Policy decisions must be based on more than psychometrics or statistics. Science should inform policy as best it can, but policy also should be based on political, social, and moral considerations.


The Bell Curve should be discussed seriously and rationally by school psychologists, not suppressed. Whether we like it or not, Herrnstein and Murray's data, and the conclusions they draw from them, will not fade away. Although they may not be correct in all their assertions, there are lessons to be learned from The Bell Curve and from how the media reacted to it. The worst possible outcome would be for this discussion not to take place.


Barrett, P T., & Eysenck, H. J. (1992). Brain evoked potentials and intelligence: The Hendrickson paradigm. Intelligence, 16, 361-382.

Bouchard, T. J., Jr., Lykken, D. T. McGue, M., Segal, N., L., & Tellegen, A. (1990). Sources of human psychological differences: The Minnesota study of twins reared apart. Science, 250, 223-258.

Brody, N. (1992). Intelligence (2nd ed.). New York: Academic Press.

Carroll, J. B. (1993). Human cognitive abilities: A survey of factor- analytic studies. New York: Cambridge University Press.

Cohen, J. (1977). Statistical power for the social sciences. New York: Academic Press.

Gould, S. J. (1994, November 28). Curveball. The New Yorker, pp. 139- 149.

Haier, R. J., Siegel, B. V., Crinella, E M., & Buchsbaum, M. S. (1993). Biological and psychometric intelligence: Testing an animal model in humans with positron emission tomography. In D. K. Detterman (Ed. ), Current topics in human intelligence: Individual differences and cognition (vol. 3; pp. 157-170). Norwood, NJ: Ablex Publishing Corporation.

Herrnstein, R. J., & Murray, C. (1994). The bell curve: Intelligence and class structure in American life. New York: Free Press.

Jensen, A. R. (1980). Bias in mental testing. New York: The Free Press.

Jensen, A. R. (1992a). Understanding g in terms of information processing. Educational Psychology Review, 4, 271-308.

Jensen, A. R. (1992b). Commentary: Vehicles of g. Psychological Science, 3, 275-278.

Jensen, A. R. (1993a). Psychometric g and achievement. In B. R. Gifford (Ed.), Policy perspectives on educational testing. Norwell, MA: Kluwer Academic Publishers.

Jensen, A. R. (1993b). Spearman's hypothesis tested with chronometric information-processing tasks. Intelligence, 17, 47-78.

Jensen, A. R., & Weng, L. (1994). What is a good g? Intelligence, 18, 231-258.

Judis, J. J. (1994, October 31). Taboo you. The New Republic, p. 18.

Kranzler, J. H., & Weng, L. (in press). The factor structure of the PASS cognitive tasks: A reexamination of Naglieri et al. (1991). Journal of School Psychology.

Naglieri, J. A., Das, J. P., Stevens, J. J., & Ledbetter, M. F. (1991). Confirmatory factor analysis of planning, attention, simultaneous, and successive cognitive processing tasks. Journal of School Psychology, 29, 1-17.

Naglieri, J. A., Das, J. P, Stevens, J. J., & Ledbetter, M. F. (1991). Continuatory factor analysis of planning, attention, simultaneous, and successive cognitive processing tasks. Journal of School Psychology, 29, 1-17.

Pedhazur, E. J. (1982). Multiple regression in behavioral research 2nd ed.). New York: Holt, Rhinehart, and Winston.

Ree, M., & Earles, J. A. (1991). The stability of convergent estimates of g. Intelligence, 15, 86-89.

Ree, M., & Earles, J. A. (1992). Intelligence is the best predictor of job performance. Psychological Science, 3, 86-89.

Reed, T. E., & Jensen, A. R. (1992). Conduction velocity in a brain neural pathway of normal adults correlates with intelligence level. Intelligence, 16, 259-272.

Sattler, J. M. (1992). Assessment of Children (rev. 3rd ed.). San Diego: J. M. Sattler, Publisher.

Spearman, C. E. (1904). "General intelligence" objectively determined and measured. American Journal of Psychology, 15, 201-293.

Thorndike, R. L. (1987). The stability of factor loadings. Personality and Individual Differences, 8, 585-586.

Vernon, P A. (1990a). An overview of chronometric measures of intelligence. School Psychology Review, 19, 399-410.

Vernon, P. A. (1990b). The use of biological measures to estimate behavioral intelligence. Educational Psychologist, 25, 293-304.

Vernon, P. A. (1993). Intelligence and neural efficiency. In D. K. Detterman (Ed.), Current topics in human intelligence: Individual differences and cognition (Vol. 3; pp. 171-187). Norwood, NJ: Ablex Publishing Corporation.

Vernon, P A., & Mori, M. (1992). Intelligence, reaction times, and peripheral nerve conduction velocity. Intelligence, 16, 273-288.



The g Factor: The Science of Mental Ability

Arthur R. Jensen
Westport, CT: Praeger, 1998
700pp, $39.95 HB.

Reviewed by J. Philippe Rushton, Professor of Psychology at the University of Western Ontario
London, Ontario N6A 5C2, Canada.
Appeared in Politics and the Life Sciences, 1998, 17, 230-232.

Few scientists have effects or laws named after them. Arthur Jensen’s name is listed in a number of dictionaries as an "ism!" The Random House and Webster’s Unabridged Dictionaries contain the following entry:

Jen-sen-ism (jen´se niz´em), n. the theory that an individual’s IQ is largely due to heredity, including racial heritage. [1965-1970]; after Arthur R. Jensen (born 1923), U.S. educational psychologist, who proposed such a theory; see -ism] --Jen´sen-ist, Jen´sen-ite´, n., adj.

The "theory" attributed to Jensen has, in fact, been around since the time of Francis Galton (1822-1911), whose Hereditary Genius (1869) predated by exactly one century Jensen’s famous Harvard Educational Review article that led him to be labeled a "hereditarian." The dictionary definition can’t be overly derided, however, as Jensen’s (1969) review of the evidence that IQ is heritable and that genetic factors are involved in the Black-White IQ gap had enormous impact.

Jensenism, one of the great heresies of 20th century science, is partly responsible for getting the Darwinian-Galtonian paradigm back on track in differential psychology after it had been derailed in the behavioral sciences for at least a generation following World War II. In a brilliant 40-year career that has earned him a place among the most frequently cited figures in contemporary psychology, Arthur Jensen has systematically researched and extended Charles Spearman’s (1927) seminal concept of g, the general factor of intelligence. The g Factor is an awesome and monumental exposition of the case for the reality of g. It does not draw back from its most controversial conclusions—that the average differences in IQ found between Blacks and Whites has a substantial hereditary component, and that this difference has important societal consequences.

However, The g Factor is not about race, as such. The first five chapters deal with the intellectual history of the discovery of g and various models of how to conceptualize intelligence. Other chapters deal with the biological correlates of g (excluding race), its heritability, and its practical predictive power. The fact that psychometric g has many physical correlates proves that it is not just a methodological artifact. Among biological variables, gloads on heritability coefficients determined from twin studies and inbreeding depression scores calculated in children born from cousin-marriages. g is also related to brain size measured by Magnetic Resonance Imaging (MRI), brain evoked potentials, and intracellular brain pH levels. It (g) is a product of human evolution and is also found in non-human animals.

Despite these caveats, The Bell Curve affair allows one to safely predict that The g Factor’s coverage of race will strike many as of central importance. All the issues Jensen raised in 1969 are still with us today. Indeed, much of the opposition to IQ testing and heritability would probably disappear if it were not for the stubborn and unwelcome fact that, despite extensive well funded programs of intervention, the Black-White difference refuses to go quietly into the night. Chapter 11 of The g Factor fully documents that, on average, the American Black population scores below the White population by about 1.2 standard deviations, equivalent to 18 IQ points. (This magnitude of difference gives a median overlap of less than 15 percent, meaning that less than 15 percent of the Black population exceeds the White average of 50 percent).

The difference between Blacks and Whites in average IQ scores has scarcely changed over the past 80 years (despite some claims that the gap is narrowing) and can be observed as early as three years of age. Controlling for overall socioeconomic level only reduces the mean difference by 4 IQ points. Culture-fair tests tend to give Blacks slightly lower scores, on the average, than more conventional tests, as do non-verbal tests compared with verbal tests, and abstract reasoning tests compared with tests of acquired knowledge. On average, Blacks also score 1 standard deviation below Whites in academic achievement throughout the period from grades 1 through 12 (and also considerably below all other disadvantaged minorities tested — Puerto Rican, Mexican-American, and American Indian).

International IQ Distribution

Inspired by "Jensenism," researchers like Richard Lynn and Philip E. Vernon not only pushed the envelope, but extended the ‘outside of the envelope’ and made the race-IQ debate international in scope with their findings that East Asians average higher on tests of mental ability than do Whites, whereas Caribbeans (and especially Africans) average lower. East Asians, measured in North America and in Pacific Rim countries, typically average IQs in the range of 101 to 111. Caucasoid populations in North America, Europe, and Australasia typically have average IQs from 85 to 115 with an overall mean of 100. African populations living south of the Sahara, in North America, in the Caribbean, and in Britain typically have mean IQs from 70 to 90. (Blacks in sub-Saharan Africa score about 2 standard deviations [approximately 30 IQ points] below the mean of Whites on nonverbal tests.)

Spearman’s Hypothesis

But the 18 point IQ difference between American Blacks and Whites is only an average. On some sub-tests the Black-White difference is smaller and on other sub-tests the Black-White difference is larger. Black-White differences are markedly smaller on tests of rote learning and short term memory than on tests of reasoning and those requiring transformation of the input. For example, on the Forward Digit Span Test, in which people are asked to recall a series of digits in the same order as that in which they were presented, Black-White differences are quite small, but on the Backward Digit Span Test in which people recall a series of digits in the reverse order to that in which they were presented, they are quite large. One day, while re-reading Spearman’s (1927) The Abilities of Man, Jensen tells us that he noted the suggestion (which appears on page 379), that Black-White differences on various tests are a function of each tests’ g loading. Here, Jensen thought, was the essential phenomenon that would explain, in much broader, more fundamental terms, the specific psychometric phenomenon that gave rise to the variation in the Black-White average differences.

The g Factor summarizes the results of numerous investigations of Spearman’s hypothesis on a wide variety of psychometric tests administered to large representative samples of Whites and Blacks. Chapter 11, for example, describes the results from 17 independent data sets on a total of nearly 45,000 Blacks and 245,000 Whites derived from 171 psychometric tests. G loadings consistently predict the magnitude of the Black-White difference (r = +.63). Spearman’s hypothesis is borne out even among three-year-olds administered eight subtests of the Stanford-Binet. The rank correlation between the g loadings and the Black-White differences is +.71 (p <.05).

These g related race differences are not due to factors such as the reliability of the test, social class differences, or tautologies based on some inevitability of factor analysis. Indeed, it is not even universally true that all groups that differ, on average, in their overall score on a test battery will conform to Spearman’s hypothesis. In South Africa, although the nearly 1 standard deviation difference between Whites and East Indians showed no correlation between g loadings and standardized mean differences, the 2 standard deviation difference between Whites and Blacks showed a correlation of +.62.

Spearman’s hypothesis even applies to the g factor extracted from performance on elementary cognitive tasks. In some of these studies, 9-to-12-year-olds are asked to decide which of several lights is illuminated and move their hand to press a button that turns that light off. All children can perform the tasks in less than one second, but children with higher IQ scores perform faster than do those with lower scores, and White children, on average, perform faster than Black children. The correlations between the g loadings of these types of reaction time tasks and the Black-White differences range from +.70 to +.81.

Jensen also applied Spearman’s hypothesis to East Asian-White comparisons using these same reaction time measures. The direction of the correlation is opposite to that in the Black-White studies, indicating that, on average, East Asians score higher in g than do Whites. No one so far seems to have looked at East Asian-White differences on conventional psychometric tests as a function of their g loadings. From the study just mentioned, however, Jensen’s prediction is clear: One should find the reverse of Spearman’s hypothesis for Black-White differences.

Are Race Differences Heritable?

Chapter 12 presents Jensen’s technical arguments for why he believes that race differences are about 50 percent heritable. He emphasizes the fact that it is precisely those components of intelligence tests that are most heritable and that most relate to brain size which most profoundly differentiate Blacks from Whites. Thus, Black-White differences on 11 sub-tests of the Wechsler Intelligence Scale for Children are predicted by the amount of inbreeding depression on the same 11 sub-test scores from Japan (r = +.48). The inbreeding prediction was a sufficiently robust predictor to overcome generalization from the Japanese in Japan to Blacks and Whites in the U.S. There really is no non-genetic explanation for the inbreeding effect and its ability to predict Black-White differences in scores on IQ tests.

The g Factor also cites the evidence of transracial adoption studies. Three studies have been carried out on Korean and Vietnamese children adopted into White American and White Belgian homes. Though many had been hospitalized for malnutrition, prior to adoption, they went on to develop IQs ten or more points higher than their adoptive national norms. By contrast, Black and Mixed-Race (Black-White) children adopted into White middle-class families typically perform at a lower level than similarly adopted White children. In the well known Minnesota Transracial Adoption Study, by age 17, adopted children with two White biological parents had an average IQ of 106, adopted children with one Black and one White biological parent averaged an IQ of 99, and adopted children with two Black biological parents had an average IQ of 89.

The g Factor also devotes a fair amount of space to racial differences in brain size. Chapter 6 reviewed the literature that found that the brain-size/IQ relation was most clearly shown using Magnetic Resonance Imaging (r = .44 across eight separate studies). Chapter 12 documents the three-way racial gradient in brain size established by aggregating data from studies using four kinds of measurements: (a) wet brain weight at autopsy, (b) volume of empty skulls using filler, (c) volume estimated from external head sizes, and (d) volume estimated from external head measurements and corrected for body size. East Asians and their descendants average about 17 cm3 (1 in3) larger brain volumes than do Europeans and their descendants, whose brains average about 80 cm3 (5 in3) larger than do those of Africans and their descendants. Jensen calculated an "ecological" correlation (widely used in epidemiological studies) of +0.99 between median IQ and mean cranial capacity across the three populations of "Mongoloids," "Caucasoids," and "Negroids."

The g Factor also considers the race differences from an evolutionary perspective. Jensen endorses the "Out-of-Africa" theory, that Homo sapiens arose in Africa about 100,000 years ago, expanded beyond Africa after that, and then migrated east after a European/East Asian split about 40,000 years ago. Since evolutionary selection pressures were different in the hot savanna where Africans evolved than in the cold Arctic where Mongoloids evolved, these ecological differences had not only morphological, but also behavioral effects. The farther north the populations migrated ‘Out of Africa,’ the more they encountered the cognitively demanding problems of gathering and storing food, gaining shelter, making clothes, and raising children during prolonged winters. As these populations evolved into present-day Europeans and East Asians, they underwent selective pressure for larger brains.

In recent years, the equalitarian dogma has run headlong into some bad karma. In the wake of the success of The Bell Curve (Herrnstein & Murray, 1994), and other recent books about race (including my own) to provide race-realist answers to the question of differential group achievement, there has been an intense effort to get the ‘race genie’ back in the bottle, to get the previously tabooed toothpaste back in the tube. By firmly establishing the psychometric, neurophysiological, behavior genetic, and comparative evidence for the existence and importance of Spearman’s g, Jensen’s The g Factor makes it near certain that such efforts will end up shredded by Occam’s razor.


Galton, F. (1869). Hereditary Genius. London: Macmillan.

Herrnstein, R.J., & Murray, C. (1994). The Bell Curve: Intelligence and class structure in American life. New York: Free Press.

Jensen, A. R. (1969). How much can we boost IQ and scholastic achievement? Harvard Educational Review, 39, 1-123.

Spearman, C. (1927). The Abilities of Man: Their nature and measurement. New York: Macmillan.


The Genetic Basis of Intelligence

Farnoosh Tayyari
Graphics: Jen

Can Intelligence be Quantified?

Intelligence is a very difficult concept to define. Intellect is described as “the power of the mind to think in a logical manner and acquire knowledge”1. Even psychology experts have not agreed upon what this actually means. 2. Intelligence can be divided into various subcategories such as reasoning, problem solving, and memory, and so creating a consistent scale by which one can measure intelligence is quite difficult.
Figure 1. IQ testing is a widely used measure of g.
Many researchers working on intelligence use a psychometric definition for intelligence, termed “general mental ability” or “the g factor”. This concept originated from the work of Sir Francis Galton and Charles Spearman3 of the London School of psychology. Today many psychometricians worldwide accept the theory of general mental ability. According to this theory, on average, those who do well on one mental test also are likely to do well on other mental tests.

In most genetic studies, researchers lump the different subcategories of intelligence into Intelligence Quotient (IQ), a single scale used to quantify intelligence. The concept of IQ was first developed by Alfred Binet, a French psychologist and lawyer in 1905. In 1914 Stern, a German psychologist, created the measurement scale of IQ by dividing the subject’s mental age by his or her chronological age. Later Terman, a professor at Stanford University, removed the decimal from Stern’s formula by multiplying it by 100. Wechsler developed a similar test for adults called the Wechsler Adult Intelligence Scale4.

To determine whether scores such as IQs are of genetic or environmental origin, scientific validation is required. Arthur Jensen points to the statistical and biological realities of the g factor. The correlation of g with the overall size of brain, its glucose metabolic rate during problem solving, the complexity and speed of brain waves, as well as estimates of heritability point towards genetic influence2.

Genetics of Intelligence

The study of intelligence genetics examines how much and by what manner mental abilities are affected by genes. Since many genetic and environmental factors influence intelligence, it is considered a complex trait. However, we do not know much about the quantity and character of genes responsible for mental abilities. We know even less about the factors responsible for expression of these genes.

Intelligence is of primary interest to human genetic research. The first methodical set of experimental observations can be traced back to Galton’s work in 1865, a year before Mendel’s influential article on the laws of heredity5. Galton evaluated the transmission of several traits in families using statistical tools. He concluded that many traits including mental ability are genetically transmitted and
normally distributed in the general population. He did not analyze the role of the common environment within the families, biasing his conclusions towards the genetic. He did, however, recognize significant general principles such as regression to the mean in children of parents with extreme phenotypic traits.

The first
adoptee and twin studies on intelligence were carried out in 1920s. Later animal studies on maze-bright and maze-dull rats investigated individual differences in intelligence. Studies on inbred mice also demonstrated the critical role of genetics in individual differences for aspects of learning. By the 1960s genetic studies on intelligence resulted in declining interest in the environmental origins of intelligence in psychology, enhancing acceptance of a genetic influence on intellect [reviewed in 6]. Then in 1969, in the Harvard Educational Review Jensen suggested that while cultural factors contributed to the 15-point difference in average IQ between black and white Americans, genes could not be ruled out. This declaration made Jensen a target of student protests, acts of vandalism, death threats, and introduced the word “Jensenism” 2. However, Jensen pointed to an issue that brought strong criticism to genetic research on intelligence, leading to a generation of bigger behavioral genetic studies.

Large sample size studies in monozygotic (MZ) and dizygotic (DZ) twins raised together show an average correlation of .86 for MZ twins, while the correlation for DZ twins is only .60. Twenty-five years later, in The Bell Curve, Herrnstein and Murray7 claimed that intelligence is strongly inherited with a heritability estimation of .60 + .2 within whites. Based on data from the National Longitudinal Survey of Youth (NLSY), a federal project testing over 10,000 youths in the 1980’s, they declared that social intervention had very little effect on IQ. A large group of scientists and researchers see this claim as racist.

The g factor has a normal distribution in the general population, suggesting g is probably a product of several genes that interact with the environment. Moreover, although g correlates with the parental value, it has a tendency to be closer to the population mean, suggesting a regression to the mean. These observations suggest that some genetic variants that influence g will vary between populations rather than within populations. For instance, certain Asian populations have a frequency of 0.60 in COMT Met158 allele, which predicts lower COMT-enzyme activity and thereby better cognitive performance, while Caucasians have a frequency of 0.42 for the same allele8.

Studies show a moderate increase in g over time in developed countries, correlating with improvements in nutrition, health and education. Environmental conditions such as socio-economic status have been shown to play a significant role in intelligence. A study by Wahlsten9 showed that children transferred from a home with low socio-economic status to a home with high socio-economic status improved their test scores as much as 16 points. Moreover, in a study by Plomin et al. there was a .19 correlation for adoptive parents and their adopted children and a .32 correlation for the adopted siblings who had no genetic relatedness, suggesting the shared environment could be responsible for a third of the total variance of g between individuals 6. It has been reported that heritability for intelligence increases during development, resulting in heritability as high as 80% in adulthood while there is also some evidence that heritability might be lower in adulthood than in childhood 10,11.

Molecular Biology of Intelligence

The correlation between DNA sequence and behavioral differences such as intelligence is considered causal because DNA variations can lead to behavioral differences but behavioral differences do not change DNA sequences 6 . Several methods have been used for DNA research including linkage and association studies.

In contrast to Mendel’s second law of independent assortment, if two genes or a gene and a DNA marker located on the same chromosome are close they can be inherited together within families. This is called linkage. Linkage studies have discovered the location of many single-gene disorders. However, linkage studies are only useful in situations that a single gene has a very large effect: Huntington’s disease, for example.

Cognitive problems including learning disabilities or dementia appear to be complex disorders affected by both multiple genes and environment. Multiple-gene systems result in dimensions (quantitative traits) as opposed to disorders (qualitative dichotomies). Hence, genes in multiple-gene systems are called quantitative trait loci (QTLs). The objective of QTL study is to discover multiple genes with different
effect sizes, contributing to the variation of the trait. Improved QTL linkage studies, which use many small families instead of few large ones, can be used to study the extremes of a dimension and are capable of finding genes with more than 10% effect size 6 . Cardon et al.12identified the first QTL linkage, a linkage for reading disability.

QTLs can also be identified with a simpler method that can detect QTLs with even much smaller effect sizes on the variance of the trait. This method is called allelic association and detects the correlation between a specific allele and trait in the population.

Benjamin et al.13 reported one of the first associations for personality: the association between dopamine D4 receptor (DRD4), and novelty seeking. DRD4 gene has two types of alleles, short and long. Novelty seeking scores were higher in subjects with long DRD4 alleles. However, long alleles are also associated with hyperactivity 14. Association methods have also been used to study diseases such as Alzheimer’s disease 15. The allele associated with this disease is apolipoprotein E (APOE)-4.

QTLs associated with intelligence are being investigated under the IQ QTL Project. The project focuses on ability rather than disability. The hypothesis of this project is that being very high functioning calls for most of the positive alleles and hardly any of the negative ones. The aim is to use very high functioning individuals to identify QTLs that work all through the total distribution6. Studies of complex traits such as intelligence have 80% power to detect QTLs when they are responsible for 1% heritability. This means that when a single marker is studied, the size of an unselected sample should be about 800. Some of the studies that have used such a large-scale sample size of unselected individuals have reported positive association between normal variation in g and candidate genes including Cathepsin D (CTSD) and cholinergic muscarinic 2 receptor (CHRM2)16,17 , and the association of catechol-o-methyltransferase gene (COMT) with working memory18,19. The studies need to be replicated: Wickelgren et al.20 reported a positive association between insulin-like growth factor receptor gene with learning and memory but using a larger sample Hill et al.21 did not find such an association. Moreover, there are many QTLs that are responsible for less than 1% heritability, which means detecting them is difficult.

Functional Genomics

While genomics provides information about what proteins could potentially be in a cell, only functional genomics determines which of those proteins actually exist. Proteins also undergo modifications and interactions that cannot be predicted from genomics alone. Functional genomics operates under three major categories: gene manipulation, gene expression profiling, and proteomics.

In gene manipulation studies the sequence of a gene of interest in an animal model can be deleted, “knocking out” the gene. This method has been used in intelligence related studies. Silva et al.22, for example, found that knocking out a particular kinase gene interferes with mouse spatial tasks. Another approach involves “knocking down” the genes using antisense DNA, which binds a complimentary RNA and prevents its translation. Using this approach, Guzowski and McGaugh23 reported the importance of CRE-binding protein (CREB) gene in memory formation. While knocking out or knocking down a gene can affect a behavior this does not mean that the gene causes that behavior: it is possible the gene along with hundreds of others is involved. Conversely, redundancy in living systems can result in little effect when genes are knocked down and out. Moreover, since different knock out strains can show different results, the importance of other genes is evident. Lastly, knocking out or knocking down genes of interest does not exactly parallel natural control behavior.

Gene expression can be determined by the presence of mRNA which could be transcribed into proteins. Microarrays can detect the expression of many genes at the same time. Gene expression depends on the tissue that is sampled, making the approach difficult for human studies because brain tissue is required. Nevertheless, gene expression profiling has been broadly used in mice.

Proteomics is the study the entire protein complement (proteome) of a cell, tissue or organism. The level of mRNA expression is not always a good reflection of protein level, thus proteomics yields a much more accurate snapshot of a cell’s proteome.


There remains a lack of scientific precision for the definition of intelligence, although many scientists use the psychometric definition, g (general cognitive ability). Whether nature or nurture influences intelligence remains a matter of debate between geneticists and environmentalists, and sits at about 50/50. Intelligence appears to be controlled in part by quantitative trait loci (QTLs). Multiple-gene systems like intelligence result in dimensions (quantitative traits) as opposed to disorders (qualitative dichotomies). The objective of QTL study is to discover multiple genes with different sized effects contributing to the variation of the trait. Several methods including linkage and association have been used for discovering the QTLs. Postgenomics holds promise for understanding the genetics of intelligence.


psychometricians-mental testing experts

normal distribution- a distribution that can be represented as a symmetrical bell-shaped curve, with the greatest frequency in the center.

adoptee and twin studies- adopted individuals can acquire traits from their adopted family only environmentally, and from their biological parents only genetically, making them ideal for study of environmental/genetic effects. Twins raised apart share genetic material, but have different environments.

effect size-strength of the relationship of two variables, calculated by dividing the difference between two population means by their standard deviation


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Two Views of The Bell Curve

The following book reviews will appear in the May 1995 (Volume 40, Number 5) issue of Contemporary Psychology, APA's journal of book reviews.

Richard J. Herrnstein and Charles Murray
Bell Curve: Intelligence and Class Structure in American Life

New York: Free Press, 1994. 845 pp. ISBN 0-02-914673-9. $30.00

Reviews by Thomas J. Bouchard, Jr., and Donald D. Dorfman

Breaking the Last Taboo

Review by Thomas J. Bouchard, Jr.

"We hold these truths to be self-evident, that all men are created equal, that they are endowed by their Creator with certain inalienable Rights, that among these are Life, Liberty, and the pursuit of Happiness." With these words Jefferson introduced one of America's most treasured documents, the Declaration of Independence. Successive generations of Americans have not only embraced Jefferson's noble sentiments, they have embellished them. Equality of political rights and legal standing has been expanded into a belief in literal equality; today, differences in outcome are taken as prima facie evidence of unequal opportunity. In an egalitarian society such as ours, the existence of significant and enduring individual or group differences in intelligence is seen as a challenge to our highest ideals. This challenge is taken up by Richard J. Herrnstein and Charles Murray in The Bell Curve.

The Bell Curve has a simple but powerful thesis: There are substantial individual and group differences in intelligence; these differences profoundly influence the social structure and organization of work in modern industrial societies, and they defy easy remediation. In the current political milieu, this book's message is not merely controversial, it is incendiary. As scholars such as Daniel Moynihan, Arthur Jensen, and E. O. Wilson have learned, the mainstream media and much of the scientific community have little tolerance for those who would question our most cherished beliefs. Herrnstein and Murray have received similar treatment. They have been cast as racists and elitists, and The Bell Curve has been dismissed as pseudoscience, ironically by some commentators who broadly proclaim that their critique has not benefited from a reading of the book. The book's message cannot be dismissed so easily. Herrnstein and Murray have written one of the most provocative social science books published in many years. The issues raised are likely to be debated by academics and policymakers for years to come.

The emergence of a cognitive elite

Commentators from across the political spectrum have documented the profound social changes that all industrialized societies are undergoing at the end of the 20th century--erosion of the middle class, loss of well-paying manufacturing jobs, and an emerging information age in which individual success will depend on brains not brawn. The Bell Curve tells a similar story regarding the United States. It differs from other works by focusing on intelligence, rather than education or social class as a causal variable. The authors tell us that true educational opportunity as a function of ability (measured by IQ tests) did not arrive in the United States until about 1950. Until that date only about 55 percent of high school graduates in the top IQ quartile went directly to college. From 1950 to 1960, this number jumped to 72 percent, and in 1980 over 80 percent of graduates in the highest ability quartile went to college. In addition, sorting by cognitive ability continues as students move through college. It also occurs across colleges, with the elite schools selecting the more intellectually talented students. Finally, it continues across careers in the world of work. The authors argue that intellectual stratification through occupations is driven by powerful economic pressures. This argument is based on a number of different and compelling lines of evidence. If Herrnstein and Murray are correct, current social inequalities reflect, in large part, the achievement of a meritocracy based on cognitive ability.

The notion of a meritocracy is not, in itself, an affront to American sensibilities. Social scientists have carefully documented that social mobility does occur from one generation to the next and that cognitive ability is a major factor in determining whether an individual will achieve greater or lesser social status than did his or her parents (Waller, 1971). When each generation resorts in this way, the elements of fairness and opportunity are preserved. If, however, as The Bell Curve asserts, the heritability of IQ is quite high and there is a strong tendency for those similar in ability to marry, there will be less regression toward the mean in the cognitive ability of children of the intellectually talented and, therefore, less intergenerational reassortment. Under these circumstances a meritocracy begins to look like an aristocracy, a perception that is strongly reinforced when the intellectual elite segregate themselves from the rest of society by living in separate neighborhoods, sending their children to private schools, and supporting social institutions that cater to their own unique interests.

The authors do argue that general cognitive ability (i.e., "g") is a major determiner of social status and that variance in general mental ability is largely attributable to genetic factors--propositions that are certainly endorsed by many experts in the field. The book explicitly disclaims, however, that general mental ability is the only determinant of social status, or that g is the sum total of an individual's social worth.

The role of social class of origin

The Bell Curve carefully documents in table after table, graph after graph that cognitive ability has become a more important determinant of social status than social class of origin. Although this may come as a surprise to many, it is consistent with a large body of evidence. Research methodology in the domain of individual differences has changed dramatically in the past 20 years. Many investigators in this domain now accept two major methodological principles: that single studies based on small samples are inherently uninformative and that correlations calculated from data gathered within biological families are seriously confounded. Understanding both of these principles is important when evaluating evidence often brought to bear against The Bell Curve.

Results from a single modest study carry little more weight than does a single anecdote, no matter how compelling the finding. Most social scientists, but certainly not all, have adopted the methodology of meta-analysis, a statistical tool that systematically combines the results from many studies to provide a single reliable conclusion. In a similar fashion, behavioral geneticists combine the results from numerous kinships weighted by their sample sizes to provide the best estimate of the degree of environmental and genetic influence on any particular trait. Any single study is viewed as providing only weak evidence on its own.

The confound generated by data drawn from within biological families provides numerous pitfalls when assessing this book's claims and reviewers' counterclaims. Within a biological family, correlations (e.g., parental socioeconomic status x child's IQ) are ambiguous because the cause of the correlation could be the family environment or the parent's genes. Within biological families, the correlation between parental socioeconomic status (SES) and child's IQ, based on a meta-analysis of the literature, is .333 (White, 1982). However, in studies where genetic effects are held constant, through twin or adoption designs, the correlation drops dramatically (Bouchard, Lykken, McGue, Segal, & Tellegen, 1990; Scarr & Weinberg, 1978). Another striking exemplar of this phenomenon is the IQ correlation between unrelated individuals reared together who share a common family environment but lack a common genetic background. When the cognitive ability of these "unrelated siblings" is measured in adulthood the correlation is zero (McGue, Bouchard, Iacono, & Lykken, 1993). Thus the correlation between parental SES and offspring IQ in biological families is due, in some measure, to genetic endowment. Consequently, when examining the relationship between IQ and a dependent variable, to "hold constant" the SES of biological parents (on the grounds that SES is a competing "environmental explanation") results in an underestimate of the true influence of IQ. As early as 1970, Paul Meehl warned that "the commonest error in handling nuisance variables of the `status' sort (e.g., income, education, locale, marriage) is the error of suppressing statistically components of variance that, being genetic, ought not be thus arbitrarily relegated to the `spurious influence' category" (pp. 393-394). In this book, intended for lay readers as well as academicians, the authors have purposefully provided simple and straightforward analyses of SES and cognitive ability. They have, in many instances, understated the role of cognitive ability by holding SES constant. We can expect to see numerous reanalyses and the presentation of many more complex models derived to support both sides of the debate. The careful reader will remember Meehl's caution when examining the data and drawing conclusions.

Cognitive classes and social behavior

Part II of The Bell Curve reviews the role of cognitive ability in areas of social dysfunction. In this section, the data are more complicated, conclusions more equivocal. In spite of claims to the contrary by some reviewers, the book makes it clear that with regard to the issues discussed in this section of the book (e.g., poverty, schooling, unemployment, idleness and injury, family matters, welfare dependency, parenting, crime, civility, and citizenship), IQ "almost always explains less than 20 percent of the variance, . . . usually less than 10 percent and often less than 5 percent" (p. 117). These analyses deal only with non-Latino Whites and make use of the National Longitudinal Survey of Labor Market Experience of Youth (NLSY). This large nationally representative survey, begun in 1979, incorporated the Armed Forces Qualification Test (AFQT). The AFQT provides an excellent measure of g, and the survey contains sufficiently detailed information that questions regarding the influence of g on the outcomes listed above can now be addressed systematically.

I discuss the results regarding poverty as an exemplar. First, it must be noted that the decline in poverty from 1940 to 1970 is dramatic and linear, dropping from over 50 percent to less than 15 percent. It has remained nearly constant since 1970. This means that the rise in crime, drug abuse, and many other discontents over the past 25 years cannot be ascribed to poverty per se. It also means the analyses in The Bell Curve are being carried out on a very different population than would have been used had the analysis been carried out before 1970. Consequently, comparisons with earlier research are problematical. The evidence strongly supports the conclusion that high IQ is an important protective factor, and low IQ is an important risk factor. Parental SES is not nearly as protective or nearly as debilitating. IQ has an effect even when education is held constant. When one looks at poverty among women with children, the situation is quite different. For separated, divorced, or never married White mothers with very low IQs, the probability of being in poverty is almost 70 percent. For the same group of mothers with very high IQs, the risk of poverty is about 10 percent. For married mothers, however, the range is from under 20 percent to near zero. IQ is influential, but marriage is clearly more important. Thus poverty among children is strongly associated with the marital status of their mothers. Holding IQ constant washes out any influence of parental SES for both types of mothers but leaves a large marital effect. Similar empirical demonstrations, with numerous twists and turns, are made regarding the other dependent variables enumerated above.

The national context

Part III of The Bell Curve contains the most controversial chapter in the book, "Ethnic Differences in Cognitive Ability." The data reviewed here are neither new nor surprising and find strong support in the current psychological literature (Humphreys, 1988). East Asians, living in Asia or America, score above White Americans in tests of cognitive ability; the best estimate of that difference is about three points with findings ranging from no difference to a 10-point spread in test scores. The difference in measured IQ between African Americans and Whites has remained at about 15 IQ points for decades, although there is some indication of very modest convergence due to fewer low scores in the African American population. Controlling for SES reduces but does not eliminate this difference, and of course, controlling for SES in ethnic group contrasts may eliminate a valid source of IQ variance. Moreover, ethnic differences on cognitive tests cannot be attributed to test bias.

As described earlier, The Bell Curve asserts that differences in cognitive ability between individuals are due in part to differences in their genetic endowment. A great deal of research supports this conclusion (Bouchard, 1993; Pedersen, Plomin, Nesselroade, & McClearn, 1992). The question is, What can we infer from these findings about the origins of ethnic group differences? As any graduate student knows, the source of individual differences in a trait cannot be taken as evidence for the source of group differences in the same trait. A great deal of indirect evidence points to both genetic and environmental contributions to ethnic group differences in IQ. None of this evidence, however, is as firm as the evidence for genetic influence on individual differences in IQ. Many experts in the field (Snyderman & Rothman, 1988) agree with Herrnstein and Murray when they state that "it seems highly likely to us that both genes and the environment have something to do with racial differences. What might the mix be? We are resolutely agnostic on the issue; as far as we can determine, the evidence does not yet justify an estimate" (p. 311).

Science, ethics, and social policy

The Bell Curve closes with a review of the policy implications of their findings. What is the role of the social scientist in the formulation of social policy? I agree with Kendler (1993) that it is clearly within the scientific realm to comment on the likely consequences of competing social policies. Judging the value, as opposed to the costs, of such policies is, however, a matter of political rather than scientific discourse. As Kendler documents, many social scientists confuse these two functions. Herrnstein and Murray have been vigorously chastised for discussing policy implications on the basis of the work reviewed and the data analyzed in their book. Similar assertions are, however, regularly made by many investigators in the social sciences. For example, the implications of specific research projects are regularly found in grant applications where they are used to justify the request for funds. Seldom are the value judgments underlying these implications explicitly stated, but they are easily inferred. Herrnstein and Murray have, in my opinion, been much more "up front" about these matters than many social scientists, and their discussions fall clearly within the boundaries discussed by Kendler. They argue, for example, with regard to affirmative action, "Our contribution (we hope) is to calibrate the policy choices associated with affirmative action, to make costs and benefits clearer than they usually are" (pp. 387-388).

In writing the Declaration of Independence, Jefferson was attempting to give birth to a shared political goal--freedom, as expressed in the right to life, liberty, and the pursuit of happiness. Herrnstein and Murray also address this important theme. They make it clear that a meritocracy need not be a Darwinian jungle and that a responsible society should make a place for everyone. Their description of the ideal meritocracy will not be to everyone's taste, but it is neither more foolish nor more naive than many proposals that have been suggested in the past. Nevertheless, predicting the future is an extremely hazardous enterprise. We have recently seen the virtual collapse of a number of societies that were based on a totally different conception of human nature than that underlying The Bell Curve. Virtually no one predicted this dramatic outcome for one of history's largest social experiments. Undoubtedly, Herrnstein and Murray's arguments are wrong in some of the details, and they may be wrong about the larger picture. Nevertheless, one of the goals of the intellectual enterprise is to question received wisdom, to ask difficult questions, and to seek novel and "better" solutions to both new and old problems. They have succeeded admirably at this task.

This is a superbly written and exceedingly well-documented book. It raises many troubling questions regarding the organization of our society. It deserves the attention of every well-informed and thoughtful citizen.


Bouchard, T. J., Jr. (1993). The genetic architecture of human intelligence. In P. A. Vernon (Ed.), Biological approaches to the study of human intelligence (pp. 33-93). Norwood, NJ: Ablex.

Bouchard, T. J., Jr., Lykken, D. T., McGue, M., Segal, N. L., & Tellegen, A. (1990). Sources of human psychological differences: The Minnesota study of twins reared apart. Science, 250, 223-228.

Humphreys, L. G. (1988). Trends and levels of academic achievement of Blacks and other minorities. Intelligence, 12, 231-260.

Kendler, H. H. (1993). Psychology and the ethics of social policy. American Psychologist, 48, 1046-1053.

McGue, M., Bouchard, T. J., Jr., Iacono, W. G., & Lykken, D. T. (1993). Behavior genetics of cognitive ability: A life-span perspective. In R. Plomin & G. E. McClearn (Eds.), Nature, nurture and psychology (pp. 59-76). Washington, DC: American Psychological Association.

Meehl, P. E. (1970). Nuisance variables and the ex post facto design. In M. Radner & S. Winokur (Eds.), Minnesota studies in the philosophy of science IV (pp. 373-402). Minneapolis: University of Minnesota Press. Pedersen, N. L., Plomin, R., Nesselroade, J. R., & McClearn, G. E. (1992). A quantitative genetic analysis of cognitive abilities during the second half of the life span. Psychological Science, 3, 346-353.

Scarr, S., & Weinberg, R. A. (1978). The influence of family background on intellectual attainment. American Sociological Review, 43, 674-692.

Snyderman, M., & Rothman, S. (1988). The IQ controversy: The media and public policy. New Brunswick, NJ: Transaction Books.

Waller, J. H. (1971). Achievement and social mobility: Relationship among IQ score, education and occupation in two generations. Social Biology, 18, 252-259.

White, R. K. (1982). The relation between socioeconomic status and academic achievement. Psychological Bulletin, 91, 461-481.

Soft Science With a Neoconservative Agenda

Review by Donald D. Dorfman

"Is there a danger that current welfare policies, unaided by eugenic foresight, could lead to the genetic enslavement of a substantial segment of our population? The possible consequences of our failure seriously to study these questions may well be viewed by future generations as our society's greatest injustice to Negro Americans" (Jensen, 1969, p. 95).

So said Arthur Jensen in 1969 in a Harvard Educational Review article on race and general intelligence. General intelligence is often called IQ for short. In the most controversial parts of The Bell Curve, a book written for the general reader, Richard J. Herrnstein and Charles Murray present much the same theories and general concerns as did Jensen with regard to Black cognitive intelligence, while extending the analysis to include Latinos. They greatly expand on the evidence, present possible causal links between IQ and socially undesirable behaviors, and at the end of the book suggest implications for public policy. They are especially worried about a supposed downward pressure on the distribution of IQ in the United States, which they call dysgenic pressure. Dysgenic is a term borrowed from population biology. As does Jensen, the authors believe that Blacks "are experiencing even more severe dysgenic pressures than Whites" (p. 341). Part of the problem may be differences in reproductive strategies among the races, according to J. Philippe Rushton's theory discussed in the book (pp. 642-643). Herrnstein and Murray mention Rushton's theory that Blacks have the largest genitals and the highest frequency of sexual intercourse among the three major races (p. 642). Consistent with customary academic standards of scholarly objectivity and neutrality, Herrnstein and Murray reserve judgment on whether Rushton is right or wrong: "We expect that time will tell whether it [Rushton's theory] is right or wrong in fact" (p. 643).

In addition to supposed downward pressures on the distribution of intelligence in this country produced by high fertility rates in Blacks, Herrnstein and Murray believe that Latinos are also experiencing more severe dysgenic pressures than Whites (p. 341) and that Latino immigration is putting downward pressure on the distribution of American national intelligence. So should we be worrying about dysgenic pressure on our national cognitive intelligence? They conclude, "Putting the pieces together--higher fertility and a faster generational cycle among the less intelligent and an immigrant population that is probably somewhat below the native-born average--the case is strong that something worth worrying about is happening to the cognitive capital of the country" (p. 364).

The authors present a large number of research analyses that they performed themselves, in which they pit parental socioeconomic status (SES) against IQ on a variety of economic and social behaviors. They conclude that the major cause of economic and social behaviors is IQ, not SES. The authors' research analyses are based on data collected in the National Longitudinal Survey of Youth (NLSY). None of their research analyses on the relation between IQ, SES, and social behaviors has ever been published in peer-reviewed scientific journals. The Bell Curve is written for the general reader and does not assume that the reader has had a course in statistics. The authors have even included an appendix for those readers who are sure they can not learn statistics, titled "Statistics for People Who Are Sure They Can't Learn Statistics" (Appendix 1, pp. 553-567). Scientists first publish their research in peer-reviewed scientific journals, not in books written for the general reader who may not have the technical background needed to detect flaws in data and misinterpretations of data analyses. It is inappropriate for a scientist to do otherwise.

Herrnstein and Murray's research analyses--never published in peer-reviewed scientific journals--investigate the relation of IQ and SES to marriage, to divorce, to illegitimacy, to welfare dependency, and to parenting. They conclude that IQ is the primary problem, not SES: "People with low cognitive ability tend to be worse parents" (p. 232). The authors believe that low birth weight and high infant mortality are indications of poor parenting and are probably caused by "prenatal negligence" (p. 233) on the part of mothers with low cognitive ability rather than inadequate prenatal medical care on the part of society. They also present unpublished research analyses on the relation between crime and low cognitive intelligence, and between civility and high cognitive intelligence. "A smarter population is more likely to be, and more capable of being made into, a civil citizenry" (p. 266), according to the authors.

In the final part of The Bell Curve, titled "Living Together," Herrnstein and Murray propose a solution to the supposed dysgenic downward pressures on our national intelligence caused by the large number of children born to "low-IQ women," and to the recent large-scale Latino immigrations to the United States. They argue that America's current fertility policy "subsidizes births among poor women, who are disproportionately at the low end of the intelligence distribution" (p. 548). They seem to urge eugenic foresight to counteract dysgenic pressure: "We urge generally that these policies, represented by the extensive network of cash and services for low-income women who have babies, be ended" (p. 548). With regard to the supposed dysgenic effects of Latino immigration on national intelligence, their central thought about immigration "is that present policy assumes an indifference to the individual characteristics of immigrants that no society can indefinitely maintain without danger" (p. 549). "But," they conclude, "we believe that the main purpose of immigration law should be to serve America's interests" (p. 549). For those members of groups who will not be excluded from the American dream by eugenic foresight or new immigration laws, Herrnstein and Murray propose "that group differences in cognitive ability, so desperately denied for so long, can best be handled--can only be handled--by a return to individualism" (p. 550).

Who are the authors of The Bell Curve? Are they right? The first author, Richard Herrnstein, was a professor of psychology at Harvard University for 36 years. He died a very short time ago. One would presume that The Bell Curve represents Herrnstein's final summing up of a lifetime of objective scholarly research published in peer-reviewed scientific journals on the genetic basis of IQ. Regrettably, the media seem to be totally unaware of the fact that the deceased Harvard professor never published any scientific research on the genetic basis of IQ and its relation to race, poverty, or social class in peer-reviewed scientific journals in his entire 36-year academic career. Richard Herrnstein's actual area of expertise is the experimental analysis of decision making in pigeons and rats, and he never studied the genetic basis of any behavior in those laboratory animals. The first presentation of his theory on the genetic basis of IQ, social class, and poverty appeared in a magazine article titled "I.Q." published in the September 1971 issue of the Atlantic Monthly magazine. As we all know, scientists publish their data and theories in peer-reviewed scientific journals or in peer-reviewed technical books, not in popular magazines or in nontechnical books written for the general reader.

In 1973, Herrnstein published a nontechnical Atlantic Monthly Press book titled I.Q. in the Meritocracy that expanded on his theory of the genetic basis of IQ and poverty. Herrnstein had never collected data on IQ, so the book drew on the work of others, especially the "data" of Sir Cyril Burt. According to Leslie Hearnshaw (1979), Burt's biographer and distinguished historian of British psychology, Burt had probably invented much of his highly cited data on the genetic basis of IQ. While doing research on Burt's data for an article that I later published in Science (1978), I discovered that Herrnstein had in fact laundered Burt's own descriptions of Burt's widely publicized and highly cited study "Intelligence and Social Mobility" (Burt, 1961). Burt had described his own study "merely as a pilot inquiry" (p. 9) and his data as "crude and limited" (p. 9). Burt had not even reported the number of subjects he had tested in his crude and limited study. In describing Burt's study, however, Herrnstein (1973) failed to tell the reader about the deficiencies that Burt, himself, had mentioned. In addition, Herrnstein (1973) said Burt's sample size was "1,000" (p. 203), later revising that figure to "40,000" in response to criticism. In reply to a critical letter by Jerry Hirsch (1975), Herrnstein (1975) revised his 1973 figure: "It is true that Burt's sample was 40,000, not 1,000 as I said" (p. 436), while failing to acknowledge that Burt had never reported the number of subjects he had tested. Leon Kamin (1974) appears to have been the only psychologist to notice and publicly report that Burt had failed to give the sample size of his celebrated 1961 study of IQ and social mobility. Presumably, Herrnstein and other psychologists who had publicized the results of that study had never noticed that Burt had not reported the sample size of his famous study.

The second author of The Bell Curve, Charles Murray, has a doctorate in political science from the Massachusetts Institute of Technology and is currently a Bradley Fellow with the American Enterprise Institute, a conservative research group in Washington, DC. Murray often publishes his research and theories in The Public Interest (e.g., Murray, 1994), a neoconservative magazine edited by Irving Kristol, also a fellow of the American Enterprise Institute and sometimes considered the founding father of neoconservatism (Atlas, 1995). In an article recently published in The Public Interest, Murray listed the first priority of his political agenda: "And so I want to end welfare" (1994, p. 18). Inasmuch as the media sometimes refer to The Bell Curve as Murray's book, perhaps the book represents Murray's summing up of a body of objective scholarly research that he had published in scientific journals on the genetic basis of IQ and poverty. But like his coauthor Richard Herrnstein, Murray has never conducted or published any research in scientific journals on the genetic basis of IQ and poverty in his entire career.

The Bell Curve is not a scientific work. It was not written by experts, and it has a specific political agenda. Still, it is possible that the major scientific premises of the book may be correct. If two monkeys were put before a typewriter, it is theoretically possible for those two monkeys to produce a Shakespearean sonnet. Perhaps Herrnstein and Murray produced a valid scientific work. I will now evaluate the major premises of The Bell Curve.

The rewriting of history: The Burt affair

In 1972, Leon Kamin exposed the empirical unsoundness of the most important evidence in support of the IQ hereditarian position, Sir Cyril Burt's data (Hearnshaw, 1979). He later published his results in a book attacking Burt's data as well as the secondary sources who publicized those data (Kamin, 1974). In 1979, Leslie Hearnshaw (1979) published a biography of Burt in which he concluded on the basis of personal diaries and other material that it was highly likely that Burt had fabricated some of his most celebrated data. Hearnshaw, distinguished historian of British psychology, delivered the memorial address at Burt's Memorial Service and was later asked by Marion Burt, Burt's sister, to write a full-length biography of Burt. The result was the well-known Cyril Burt: Psychologist (1979). In their discussion of the Burt affair, Herrnstein and Murray suggest that some of Burt's "leading critics were aware that their accusations were inaccurate" (p. 12), suggesting a possible conspiracy against Burt. There is, however, no mention whatsoever of Hearnshaw's book in their half-page synopsis of the Burt affair, and Hearnshaw's book does not appear anywhere in their 57-page bibliography of references. This misrepresentation of the Burt affair by omission of important historical facts is not uniquely associated with The Bell Curve. In 1982, Richard Herrnstein published an article in The Atlantic Monthly in which he attacked the media for misrepresenting the evidence in the IQ controversy (Herrnstein, 1982). In that magazine article, the Harvard professor wrote "that most psychometricians had stopped trusting Burt's data years before, partly because of inconsistencies first noted in a 1974 article by Arthur Jensen" (p. 70), while omitting any mention of Leo Kamin, the psychologist who in reality first noted inconsistencies in Burt's data.

Does the distribution of IQs follow a bell curve?

The distribution of IQ test scores cannot be expected to follow a bell curve unless it is constructed by the tester to do so (Dorfman, 1978). The shape of the distribution of IQ test scores will depend on the average difficulty of the test items as well as their intercorrelations. The high item intercorrelations in IQ tests imply that the IQ distribution can take a variety of shapes. The central limit theorem does not apply to random variables with positive intercorrelations (Lamperti, 1966). Frederic Lord (1952), one of the fathers of modern test theory and former president of the Psychometric Society, gave results on this question: "The results given are sufficient to show that the distribution of test scores cannot in general be expected to be normal, or even approximately normal. The question naturally arises as to what possible shapes the frequency distribution fs, as given in (76) [Lord's Equation (76)], may assume. The answer is that this function may assume any shape whatsoever, provided the item intercorrelations are sufficiently high" (Lord, 1952, pp. 32-33). The symbol fs refers to the distribution of test scores.

Does cognitive ability consist of a single general factor?

The book uses factor analysis to infer the existence of a single hypothetical general factor of cognitive intelligence that is presumed to account for most of cognitive performance. One of the problems with factor analysis as a tool for determining the underlying structure of a system is that neither the factors nor the loadings are uniquely defined if you have more than one factor (Lawley & Maxwell, 1963), and it is difficult to determine if you have only one factor. In experimental cognitive psychology, factor analysis is virtually never used as a tool to determine the underlying cognitive structure. It is a tool for correlational cognitive psychology, not experimental cognitive psychology. I inspected the subject index of some well-known texts in experimental cognitive psychology and found that the term factor analysis never appears in the subject index (e.g., see Anderson, 1985; Matlin, 1994; Reed, 1982). Why not? Kendall and Stuart (1966) may provide the answer: "Application of the same technique [factor analysis] to physical systems very often results in weighted sums of variables to which no clear interpretation can be given" (p. 310). In short, "The main difficulty, as a rule, is to know what the results mean" (p. 310), Kendall and Stuart point out.

Can you measure the heritability of IQ?

The most direct way of estimating heritability is from data on monozygotic twins reared apart (MZA) and separated in early infancy (Bouchard, Lykken, McGue, Segal, & Tellegen, 1990). This MZA design allows for the estimation of heritability if the following major assumptions are met: (a) environments are a random sample from the population of environments, (b) genotypes are a random sample from the population of genotypes, (c) there is no genotype-environment correlation, and (d) there is no genotype-environment interaction. If the pairs of MZAs differ in age, then these assumptions will not be met. If these assumptions are met, then the intraclass correlation between IQ scores of MZA twin pairs directly measures heritability. Sir Cyril Burt's (1966) study of 53 MZAs appears to have met the first three assumptions. Unfortunately, Burt's data appear to have been invented (Hearnshaw, 1979). Bouchard et al.'s (Minnesota) survey of MZAs provides the next best data set. Unfortunately, to the best of my knowledge, the detailed case-study records of the Minnesota MZAs have never been released and have therefore not been subjected to public scrutiny to determine the degree to which assumptions have been met and the degree to which the MZAs told the truth to the Minnesota group. Finally, if there is genotype-environment interaction--then the fourth assumption is not met--and heritability is undefined. But this is the most controversial assumption underlying the MZA design. Herrnstein and Murray present no convincing evidence to justify the fourth assumption.

Does high within-group heritability of IQ imply between-group heritability of IQ?

The authors have made a fundamental error well-known by professional geneticists. It is sometimes called "Jensen's error." Jensen made that error in his famous 1969 Harvard Educational Review article. The critical importance of that error was first clearly illuminated by Roger Milkman, a professor of biology at the University of Iowa and a world authority on population genetics and evolutionary biology. The article, "A Simple Exposition of Jensen's Error," was published in the Journal of Educational Statistics in 1978 (Milkman, 1978). Melvin Novick was editor of that journal when Milkman's article was published. Novick, professor of statistics and education at the University of Iowa at the time, later became president of the Psychometric Society. What is Jensen's error? It is that within-race heritability has no implications for between-race heritability. The Bell Curve is therefore flawed with regard to inferring between-race heritability in IQ from within-race heritability in IQ.

Does IQ or SES cause socially undesirable behaviors?

Herrnstein and Murray use logistic regression to determine which is more important--IQ or SES--in determining socially undesirable behaviors. Logistic regression is a form of regression in which the dependent variable is binary. In all of their analyses, they assume a simple additive model in which the logit (a transform of the sample proportion) is assumed to equal B0 + B1IQ + B2SES + B3 age + random residual [numbers after Bs should read as subscripts]. They assume no IQ-SES interaction. They use the standardized beta weights to determine the relative importance of IQ and SES in determining the probability of various undesirable or desirable behaviors. Unfortunately, IQ and SES are highly intercorrelated (collinearity).

There are two major problems with Herrnstein and Murray's attempts to determine whether IQ or SES is more important. First, there is the collinearity problem. Weisberg (1985) describes the collinearity problem in linear regression: "When the predictors are related to each other, regression modeling can be very confusing. Estimated effects can change magnitude or even sign depending on the other predictors in the model" (p. 196). Next, there is the problem of deciding that the predictor with the largest standardized beta weight is the most important. Weisberg describes why this approach is faulty: "Unfortunately, this logic is faulty because the scaling depends on the range of values for the variables in the data" (p. 186). Perhaps these are the reasons why Herrnstein and Murray never published their logistic analyses in peer-reviewed journals.

Were Herrnstein and Murray as lucky as the proverbial monkeys at a typewriter? That depends on your point of view.


Anderson, J. R. (1985). Cognitive psychology and its implications (2nd ed.). New York: W. H. Freeman.

Atlas, J. (1995, February 12). The counter counterculture. The New York Times, pp. 32-39, 54, 61-62, 65.

Bouchard, T. J., Lykken, D. T., McGue, M., Segal, N. L., & Tellegen, A. (1990). Sources of human psychological differences: The Minnesota study of twins reared apart. Science, 250, 223-228.

Burt, C. (1961). Intelligence and social mobility. The British Journal of Statistical Psychology, 14, 3-24.

Burt, C. (1966). The genetic determination of differences in intelligence: A study of monozygotic twins reared together and apart. British Journal of Psychology, 57, 137-153.

Dorfman, D. D. (1978). The Cyril Burt question: New findings. Science, 201, 1177-1186.

Hearnshaw, L. S. (1979). Cyril Burt: Psychologist. London: Hodder & Staughton.

Herrnstein, R. J. (1971, September). I.Q. The Atlantic Monthly, 43-64.

Herrnstein, R. J. (1973). I.Q. in the meritocracy. Boston: Atlantic-Little, Brown.

Herrnstein, R. J. (1975). Herrnstein replies. Contemporary Psychology, 20, 436.

Herrnstein, R. J. (1982, August). IQ testing and the media. The Atlantic Monthly, 68-74.

Hirsch, J. (1975). Hirsch on Herrnstein and Jensen. Contemporary Psychology, 20, 436.

Jensen, A. R. (1969). How much can we boost IQ and scholastic achievement? Harvard Educational Review, 39, 1-123.

Kamin, L. J. (1974). The science and politics of I.Q. New York: Wiley.

Kendall, M. G., & Stuart, A. (1966). The advanced theory of statistics (Vol. 3). New York: Hafner.

Lamperti, J. (1966). Probability: A survey of the mathematical theory. New York: W. A. Benjamin.

Lawley, D. N., & Maxwell, A. E. (1963). Factor analysis as a statistical method. London: Butterworth.

Lord, F. M. (1952). A theory of test scores. Psychometric Monographs (Whole No. 7).

Matlin, M. W. (1994). Cognition (3rd ed.). Fort Worth, TX: Harcourt Brace.

Milkman, R. (1978). A simple exposition of Jensen's error. Journal of Educational Statistics, 3, 203-208.

Murray, C. (1994, Spring). Does welfare bring more babies? The Public Interest, 17-30.

Reed, S. K. (1982). Cognition: Theory and applications. Monterey, CA: Brooks/Cole.

Weisberg, S. (1985). Applied linear regression (2nd ed.). New York: Wiley.


Richard J. Herrnstein (deceased) was Edgar Pierce Professor of Psychology at Harvard University (Cambridge, Massachusetts) and is author of IQ in the Meritocracy and coauthor, with J. Q. Wilson, of Crime and Human Nature and, with E. G. Boring, of A Sourcebook in the History of Psychology. Herrnstein is coeditor, with R. C. Atkinson, G. Lindzey, and R. D. Luce, of Stevens' Handbook of Experimental Psychology, Vol. 1: Perception and Motivation, and Vol. 2: Learning and Cognition (2nd ed.); and, with M. L. Commons, S. M. Kosslyn, and D. B. Mumford, of Quantitative Analyses of Behavior, Vol. 8: Behavioral Approaches to Pattern Recognition and Concept Formation, and Vol. 9: Computational and Clinical Approaches to Pattern Recognition and Concept Formation.

Charles Murray, currently a Bradley Fellow at the American Enterprise Institute, is author of Losing Ground: American Social Policy 1950-1980.

Thomas J. Bouchard, Jr., professor of psychology at the University of Minnesota (Minneapolis) and director of the Minnesota Center for Twin and Adoption Research, is immediate past president of the Behavior Genetics Association and American Psychological Association Distinguished Scientist Lecturer for 1995. Bouchard is author of the chapter "The Genetic Architecture of Human Intelligence" in P. E. Vernon (Ed.) Biological Approaches in the Study of Human Intelligence and of the chapter "IQ Similarity in Twins Reared Apart: Findings and Responses to Critics" in the forthcoming R. J. Sternberg and E. L. Grigorenko (Eds.) Intelligence: Heredity and Environment. Bouchard is coeditor, with P. Propping, of Twins as a Tool of Behavior Genetics.

Donald D. Dorfman, professor of psychology and radiology and faculty member in the graduate program in applied mathematical and computational sciences at the University of Iowa (Iowa City), is author of the chapter "Group Testing" in S. Kotz and N. L. Johnson (Eds.) Encyclopedia of Statistical Sciences, Vol. 3 and coauthor, with J. T. Cacioppo, of the chapter "Waveform Moment Analysis: Topographical Analysis of Nonrhythmic Waveforms" in J. T. Cacioppo and L. G. Tassinary (Eds.) Principles of Psychophysiology: Physical, Social, and Inferential Elements.


Published Tuesday, January 18, 2005
Harvard Chief Defends His Talk on Women

New York Times

The president of Harvard University, Lawrence H. Summers, who offended some women at an academic conference last week by suggesting that innate differences in sex may explain why fewer women succeed in science and math careers, stood by his comments yesterday but said he regretted if they were misunderstood.

"I'm sorry for any misunderstanding but believe that raising questions, discussing multiple factors that may explain a difficult problem, and seeking to understand how they interrelate is vitally important," Dr. Summers said in an interview.

Several women who participated in the conference said yesterday that they had been surprised or outraged by Dr. Summers's comments, and Denice D. Denton, the chancellor designate of the University of California, Santa Cruz, questioned Dr. Summers sharply during the conference, saying she needed to "speak truth to power."

Nancy Hopkins, a professor of biology at the Massachusetts Institute of Technology who once led an investigation of sex discrimination there that led to changes in hiring and promotion, walked out midway through Dr. Summers's remarks.

"When he started talking about innate differences in aptitude between men and women, I just couldn't breathe because this kind of bias makes me physically ill," Dr. Hopkins said. "Let's not forget that people used to say that women couldn't drive an automobile."
The Boston Globe first reported yesterday about Dr. Summers's remarks and the stir they created.

Not all reactions were negative. Some female academics and the organizer of the two-day conference that Dr. Summers addressed on Friday at the National Bureau of Economic Research, a nonprofit economic research organization in Cambridge, defended the remarks as a well-intentioned effort to speak candidly about the persistent underrepresentation of women in university departments of mathematics, engineering and physical sciences.

"A lot of people who absolutely disagreed with him were not irritated, and he said again and again, 'I'm here to provoke you,' " said Richard Freeman, an economics professor at Harvard who directs the bureau's labor studies program and invited Dr. Summers to speak. "He's very good at stimulating debate, but he cares deeply about increasing diversity in the science and engineering workforces, especially since we have many more women getting Ph.D.'s in science and engineering than ever before."

About 50 academics from across the nation, many of them economists, participated in the conference, "Diversifying the Science and Engineering Workforce: Women,


Underrepresented Minorities, and their S. & E. Careers." Dr. Summers arrived after a morning session and addressed a working lunch, speaking without notes. No transcript was made because the conference was designed to be off-the-record so that participants could speak candidly without fear of public misunderstanding or disclosure later.

In his presentation, Dr. Summers addressed the question of why so few women were on math and engineering faculties at top research universities.

"I began by saying that the whole issue of gender equality was profoundly important and that we are taking major steps at Harvard to combat passive discrimination," he recalled in yesterday's interview. "Then I wanted to add some provocation to what I understand to be basically a social science discussion."

He discussed several factors that could help explain the underrepresentation of women. The first factor, he said, according to several participants, was that top positions on university math and engineering faculties require extraordinary commitments of time and energy, with many professors working 80-hour weeks in the same punishing schedules pursued by top lawyers, bankers and business executives. Few married women with children are willing to accept such sacrifices, he said.

Dr. Hopkins said, "I didn't disagree, but didn't like the way he presented that point because I like to work 80 hours a week, and I know a lot of women who work that hard."
In citing a second factor, Dr. Summers cited research showing that more high school boys than girls tend to score at very high and very low levels on standardized math tests, and that it was important to consider the possibility that such differences may stem from biological differences between the sexes.

Dr. Freeman said, "Men are taller than women, that comes from the biology, and Larry's view was that perhaps the dispersion in test scores could also come from the biology."
Dr. Summers said, "I was trying to provoke discussion, and I certainly believe that there's been some move in the research away from believing that all these things are shaped only by socialization."

It was at this point in his presentation that Dr. Hopkins walked out, and shortly thereafter, Dr. Denton told the Harvard president that she believed his assertions had been contradicted by research materials presented at the conference. Dr. Summers said he responded that "I didn't think for a moment that I had proven anything, but only that these are things that need to be studied."

A late phone call yesterday to Dr. Denton at the University of Washington, where she is the dean of engineering, was not returned.

Paula E. Stephan, a professor of economics at Georgia State University, said Dr. Summers's remarks offended some participants, but not her. "I think if you come to participate in a research conference," Dr. Stephan said, "you should expect speakers to present hypotheses that you may not agree with and then discuss them on the basis of research findings."

Catherine Didion, a director of the International Network of Women Engineers and Scientists, said she was "surprised by the provocation in tone and manner" of Dr. Summers's remarks.

"Initially all of the questions were from women, and I think there was definitely a gender component to how people interpreted his remarks," Dr. Didion said. "Male colleagues didn't say much afterwards and later said they felt his comments were being blown out of context. Female colleagues were on the whole surprised by his comments."




Amr.Ren. April 1995

Three Words and You're Out


Poor Francis Lawrence. Last November, the president of Rutgers University said the following at a faculty meeting:


"The average S.A.T. for African-Americans is 750 [out of 1600]. Do we set standards in the future so that we don't admit anybody with the national test? Or do we deal with a disadvantaged population that doesn't have the genetic hereditary background to have a higher average?"

Someone was recording his remarks – which went unchallenged at the time – and leaked them to the press in January. Dr. Lawrence has been apologizing and backpedaling ever since. "What I intended to say," he now explains, "was that standardized tests should not be used to exclude disadvantaged students on the trumped-up grounds that such tests measure inherent ability." [John Nordheimer, Rutgers Leader disavows linking race and ability,
NYT, 2/1/95, p. B5.]


There is much to ponder here. First, non-whites at Rutgers have been baying for his head, despite the fact that Dr. Lawrence has been one of the most ardent advocates of racial preferences, speech codes, and multiculturalism on any American campus. His record and his abject apologies meant nothing; he had to be fired. Thus do non-whites reward their benefactors. In February, when the university's Board of Governors announced that Dr. Lawrence would be kept on, some black activists shed tears of grief.


Clearly, many blacks believe that Dr. Lawrence meant what he said at the faculty meeting. It would be significant if, indeed, he believes that blacks do not have the same genetic endowments as whites, but still deserve affirmative action. This might become the fallback position for the defenders of racial preferences, once the facts about IQ have become too well known to be ignored. Race-based handouts are all the more necessary, it might be argued, if some races face built-in limitations.




Harvard Chief Says His Remarks on Women Were Wrong


Jan 20, 11:12 AM (ET)

By Greg Frost


CAMBRIDGE, Mass. (Reuters) - Harvard University President Lawrence Summers has written a lengthy apology, admitting he was wrong to suggest women do not have the same natural ability in math and sciences as men.


In his third and most repentant statement this week, the Ivy League school chief sought to make amends to faculty not just at Harvard but across the country who were offended by his remarks at a conference last Friday.


"I deeply regret the impact of my comments and apologize for not having weighed them more carefully," Summers said in a letter to the Harvard community posted on his Web site and dated Wednesday. "I was wrong to have spoken in a way that has resulted in an unintended signal of discouragement to talented girls and women."


Earlier this week, a Harvard faculty committee told Summers he may have damaged the school's efforts to attract more top female scholars with his suggestion that innate differences between the sexes may help explain why fewer women succeed in math and science careers.


In his most recent statement -- the third in as many days -- the former Treasury secretary said the human potential to excel in science is not dictated by gender, as evidenced by the distinguished careers of many women scientists.


Summers spoke of having learned much in recent days from a number of e-mails and calls that he said "made vivid the very real barriers faced by women in pursuing scientific and other academic careers."


He acknowledged there had been "frustratingly uneven and slow" progress made in luring more women to the sciences.


"As a university president, I consider nothing more important than helping to create an environment, at Harvard and beyond, in which every one of us can pursue our intellectual passions and realize our aspirations to the fullest possible extent," he said.


It is not the first time Summers' sensitivity has come into question since he became Harvard president in 2001. Early in his tenure, Summers upset black professors by questioning the academic output of star professor Cornel West, who then left Harvard for Princeton University.


There was no transcript available for Summers' comments to the National Bureau of Economic Research in Cambridge.


During the conference, Summers sought to explain why fewer women work in academic sciences, offering three suggestions -- the reluctance or inability of women to work 80-hour weeks, that boys outscore girls on math and science tests during the final years of high school and the possibility of discrimination, The Boston Globe reported.


One biologist in the audience, Nancy Hopkins, walked out on Summers' talk, while five others said they were deeply offended, the Globe reported this week. Four other participants said they were not offended.





Making Harvard Crimson with Rage

By Michael M. Rosen


Harvard's Lawrence Summers makes for an unlikely hero of the conservative movement. His liberal credentials are impeccable: president of an Ivy League university, Secretary of the Treasury under President Clinton, and economic adviser to Michael Dukakis.

But Summers has gained notoriety among progressives, and won plaudits from conservatives, for eschewing the liberal pieties of academia and speaking out clearly on issues from which most university presidents quietly shy away.


Take the most recent flap over comments Summers made last Friday at an off-the-record conference hosted by the National Bureau of Economic Research. In an interview with the New York Times, Summers recounted that he was speculating as to why so few women can be found on math and science faculties at major research universities.


Introducing his remarks with the phrase "I'm going to provoke you," Summers offered several reasons for disproportionately male science faculties. First, he stated that attaining a tenured professorship in the sciences often requires eighty-hour-workweeks, a commitment that most women with children could not make.


He then reportedly asserted that it was important to consider the possibility, proffered by several social scientists, that differential performance in math and science could stem from biological differences between the sexes. Summers told the Times that "there's been some move in the research away from believing that all these things are shaped only by socialization" and that fundamental differences between men and women could account for some of the discrepancy.


For entertaining these thoughts and airing them publicly, Summers has been skewered by Harvard-Radcliffe alumnae and female members of science faculties nationwide. Nancy Hopkins, a Massachusetts Institute of Technology (MIT) biologist, walked out of the talk because otherwise "I would've either blacked out or thrown up."


Harvard's Standing Committee on Women, citing an overall decline in female tenureships during Summers' reign, asserted that the president's comments "reinforce an institutional culture at Harvard that erects numerous barriers to improving the representation of women on the faculty."


Yet Summers remained steadfast, apologizing for any offense but maintaining his belief that "raising questions, discussing multiple factors that may explain a difficult problem, and seeking to understand how they interrelate is vitally important."


This episode, in which Summers refused to shrink from raising unpopular but legitimate hypotheses, represents only one more link in a chain of conduct that has established the president's reputation as a maverick unafraid to shake things up when appropriate.


In a September 2002 address at Harvard's Memorial Church, Summers famously tackled the delicate issue of anti-Semitism on college campuses. Citing an odious campaign to encourage the university to withdraw its investments from companies that do business in Israel, Summers, the first Harvard president to identify as a Jew, averred that "serious and thoughtful people are advocating and taking actions that are anti-Semitic in their effect if not their intent." He also stated that while he has never been one to cry "Holocaust," concerns that global anti-Semitism is on the rise "seem rather less alarmist in the world of today than they did a year ago."


The address immediately triggered near-parodic outbursts of indignation from the anti-Israel left on campus, which thundered that the president was seeking to squelch academic freedom. This could hardly have been further from the truth.  Dr. Bernard Steinberg, executive director of Harvard Hillel, the Jewish student organization, wrote, in praise of Summers, that we "strengthen free speech when we expose the illogic, ignorance, and injustice of the divestment campaign."


Summers took action in order to drain the swamps of bilious and hateful rhetoric that threatened to overwhelm any honest discussion of the Arab-Israeli conflict. Contrast his approach with that of beleaguered San Francisco State University president Robert Corrigan who has become infamous for his benign neglect of violent intimidation by Palestinian students on his campus.


Summers also made waves with a controversial encounter with Cornel West, then a professor of African-American studies at Harvard. Accounts of this meeting vary but Summers apparently attempted to encourage West to raise his level of serious scholarship -- according to some, West has not written so much as an academic article in over ten years -- and the professor did not take kindly to the president's counsel. After referring to Summers as a "bull in a China shop" and dubbing him "the Ariel Sharon of American higher education," West decamped for Princeton.


And the list goes on. In the wake of the September 11th attacks, Summers told an audience at the university's John F. Kennedy School of Government that he would like to see 9/11 spark "a greatly increased sense of patriotism." He later bolstered this call to duty with action when he declined to allow Harvard Law School to participate in a lawsuit that sought to compel the federal government to fund universities that refused to allow military recruiters on campus.


All this earned him the high praise of the Harvard Salient, the conservative campus newspaper, one of whose staff writers attested that "if there is one thing Summers has brought to the Kremlin on the Charles, it is a sense of order -- of morality, purpose and forthrightness -- that has long been lacking." While Summers is not likely to identify himself as a conservative, his tenure as president has inspired many on campus and elsewhere.


As famed Harvard linguist Steven Pinker put it, describing the scholarly debate over innate gender differences: "the truth cannot be offensive. Perhaps the hypothesis is wrong, but how would we ever find out whether it is wrong if it is 'offensive' even to consider it? People who storm out of a meeting at the mention of a hypothesis, or declare it taboo or offensive without providing arguments or evidence, don't get the concept of a university or free inquiry."


Summers' vision of a university comports with the best traditions of academia as a bastion of honest debate and openness to ideas. Sadly, these traditions have ebbed on today's campuses to the point where the mere attempt to restore them spawns furious resistance.


The University of Washington's dean of engineering criticized Summers because his remarks on gender "provoked an intellectual tsunami." But what in the name of academic inquiry could be wrong with that?


Michael M. Rosen, a TCS contributor, is a graduate of Harvard College and Harvard Law School.







Posted on Fri, Jan. 21, 2005


Harvard Chief Sorry for Remark on Women


Associated Press

BOSTON - Lawrence Summers' bluntness has earned him both enemies and admirers in several top Treasury Department jobs and now as president of Harvard.


He's rarely been one to apologize for his directness - until this week. Summers has spent much of the last few days saying sorry following a tumult over comments he made at a conference on women in science that he thought were off the record.


Summers insists his remarks about possible biological differences in scientific ability between men and women have been misrepresented - that he wasn't endorsing a position, just stating there is research that suggests such a difference may exist. But his words have sparked wide discussion on Harvard's campus and a string of angry calls and e-mails.


In a letter to the Harvard community posted late Wednesday on the university Web site, Summers wrote: "I deeply regret the impact of my comments and apologize for not having weighed them more carefully."


"I was wrong to have spoken in a way that was an unintended signal of discouragement to talented girls and women," he added in what was his third statement expressing contrition since the conference last Friday.


Summers, an economist by training, said in a telephone interview that he hopes he'll be able to participate in academic discussions in the future. "But particularly on sensitive topics, I will speak in much less spontaneous ways and in ways that are much more mindful of my position as president," he said.


Some academics think that's too bad. They say it's important for college presidents to be engaged in debating important issues, and worry this episode will discourage them.


"It's rare that a university president comes and offers provocative ideas," said Richard Freeman, an economist at Harvard and the National Bureau of Economic Research, the Cambridge research institute that hosted the conference where Summers spoke. "All too often in universities somebody comes and it's like cutting a ribbon, and they mouth some platitudes."


Summers already had a reputation as brilliant but indelicate, and drew attention in 2002 when a prominent black studies professor, Cornel West, left Harvard after a dispute with Summers.

But Freeman and several other participants at last Friday's conference say Summers has been portrayed unfairly. They say he was simply outlining possible reasons why women aren't filling as many top science jobs as men.


"He didn't say anything that people in that room didn't have in their own minds," said Claudia Goldin, another Harvard and NBER economist who attended the conference. Goldin said Summers simply summarized research from papers presented at the conference. "Why can they say them and he can't?"


The short answer - because Summers is president of Harvard. Summers acknowledged the rules are different for him, and critics say Summers' influential position is precisely why they were so offended.


"We need to be drawing on all of the talent of our population," University of Washington engineering school dean Denise Denton, who confronted Summers about his comments, said in a telephone interview. "The notion that half the population may not be up to the task, even remotely getting that idea out there, especially from the leader of a major university in the United States, that's of concern."


Women comprise a majority of American undergraduates, but they have lagged in ascending to top university science jobs. The debate over why this is so was renewed at Harvard this year after only a few female scientists were put forward for tenure. Summers said bringing more women into the sciences is a top priority.


But MIT biologist Nancy Hopkins, who walked out of Summers' talk and said it made her "nauseous," said the president was expressing his own views at the conference - and setting an unacceptable tone for Harvard.


"(We can't) start to say to young people, 'From the day you get to Harvard University your chances of making to the top aren't very good, because you're a woman,'" said Hopkins, a Harvard alumna.

Summers reiterated to the AP that he "was not expressing convictions" but avoided apologizing for raising the issue at all. "I certainly believe that every subject should be brought to bear in research on vitally important problems," he said.


As Treasury secretary under President Clinton, Summers held the power to move markets with an offhand comment, and was accustomed to having every utterance scrutinized. But in this case, he believed the conference proceedings would remain private. An account was of the meeting was first published in The Boston Globe.


Goldin said it's distressing the comments were leaked.

"Academic conferences are always off the record," she said. "They are places to voice concerns, to provoke, so that you promote further research in areas, to ask your colleagues 'What do you think about this hypothesis?'"


But Summers said, as president of Harvard, he should have known "that some would put more than academic interpretations on my comments, even in a research setting."







Harvard Crimson

Published on Wednesday, January 19, 2005
PSYCHOANALYSIS Q-and-A: Steven Pinker, author of ‘The Blank Slate: The Modern Denial of Human Nature’

No writer attributed  [very wise]



an e-mail exchange with The Crimson yesterday, Johnstone Professor of Psychology Steven Pinker, who teaches the popular spring core class “The Human Mind,” opined on the latest flap over President Summers’ comments on women in science.

CRIMSON: From what psychologists know, is there ample evidence to support the hypothesis that a difference in “innate ability” accounts for the under-representation of women on science faculties?


PINKER: First, let’s be clear what the hypothesis is—every one of Summers’ critics has misunderstood it. The hypothesis is, first, that the statistical distributions of men’s and women’s quantitative and spatial abilities are not identical—that the average for men may be a bit higher than the average for women, and that the variance for men might be a bit higher than the variance for women (both implying that there would be a slightly higher proportion of men at the high end of the scale). It does not mean that all men are better at quantitative abilities than all women! That’s why it would be immoral and illogical to discriminate against individual women even if it were shown that some of the statistidcal differences were innate.


Second, the hypothesis is that differences in abilities might be one out of several factors that explain differences in the statistical representation of men and women in various professions. It does not mean that it is the only factor. Still, if it is one factor, we cannot reflexively assume that different statistical representation of men and women in science and engineering is itself proof of discrimination. Incidentally, another sign that we are dealing with a taboo is that when it comes to this issue, ordinarily intelligent scientists suddenly lose their ability to think quantitatively and warp statistical hypotheses into crude dichotomies.


As far as the evidence is concerned, I’m not sure what “ample” means, but there is certainly enough evidence for the hypothesis to be taken seriously.


For example, quantitative and spatial skills vary within a gender according to levels of sex hormones. And in samples of gifted students who are given every conceivable encouragement to excel in science and math, far more men than women expressed an interest in pursuing science and math.


CRIMSON: Were President Summers’ remarks within the pale of legitimate academic discourse?


PINKER: Good grief, shouldn’t everything be within the pale of legitimate academic discourse, as long as it is presented with some degree of rigor? That’s the difference between a university and a madrassa.


CRIMSON: Would it be normal to hear a similar set of hypotheses presented and considered at a conference of psychologists?


PINKER: Some psychologists are still offended by such hypotheses, but yes, they could certainly be considered at most major conferences in scientific psychology.


CRIMSON: Finally, did you personally find President Summers’ remarks (or what you’ve heard/read of them) to be offensive?


PINKER: Look, the truth cannot be offensive. Perhaps the hypothesis is wrong, but how would we ever find out whether it is wrong if it is “offensive” even to consider it? People who storm out of a meeting at the mention of a hypothesis, or declare it taboo or offensive without providing arguments or evidence, don’t get the concept of a university or free inquiry.




Genes determine the funniest things (Just don't tell Larry Summers' enemies)
Jonah Goldberg

June 24, 2005



Here are some recent headlines from the world of science:

"Researchers Say Intelligence and Diseases May Be Linked in Ashkenazic [Jewish] Genes" - New York Times

"Some Politics May Be Etched in the Genes" - The New York Times

"Feminists Feed on Lawrence Summers' Flesh, Vital Organs; Pancreas Swallowed Whole, 'like a Cocktail Peanut.' " - New York Times

OK, I made the last one up. Feminists didn't actually feed on the president of Harvard University, but it's certainly been all-you-can-eat-at-Sizzler night, metaphorically speaking. In January, you might recall, Larry Summers raised the possibility - nay, the hypothesis! - that as a statistical matter biological differences may partially account for the disproportionately low number of women at the top ranks of science. In response, an activist feminist professor from MIT contracted a case of the vapors, and when she arose from her fainting couch she was on the "Today Show" complaining to a supportive Katie Couric about what a bigot Summers is. Fast forward from her Café Vienna moment with Katie, through more groveling than Jake Blues offered to Carrie Fisher at the end of "The Blues Brothers," and we have the recent announcement that Summers will spend an additional 50 million of someone's tuition dollars over the next 10 years to atone for his - and Harvard's - alleged bigotry toward (just-as-smart-as-you-Mister-Man) female scientists.

The flames of the Summers' auto-da-fe cast a useful light on the cognitive dissonance, schizophrenia and bad faith dotting the intellectual and political landscape today when it comes to genetics.

Consider the other headlines I mentioned above. One paper by a respected independent researcher suggests that Jews from Northern Europe (aka Ashkenazi Jews) are more likely to get certain diseases, like Tay Sachs, in part because Jews have been selectively breeding for intelligence for centuries. Central to the theory is the fact that Jews have been middleman traders, financiers and bankers since the Middle Ages - occupations that require high levels of intelligence.

Or consider the new study that claims, as reported just this week in The New York Times, that political attitudes are in some part genetically determined. The study itself, which appeared in the American Political Science Review, is far more cautious than the Times' coverage of it. But the basic gist is that studies of twins have revealed that genetics plays a significant, but far from ironclad, role in political attitudes. Identical twins are more likely to see politics through a similar prism than other siblings. Or so the authors claim.

"It is not that opinions on specific issues are written into a person's DNA," the Times's Benedict Carey reassures readers. "Rather, genes prime people to respond cautiously or openly to the mores of a social group."

Sounds plausible, but there's good reason to be skeptical. Since the 1930s, the Left has offered a string of theories suggesting that conservatives are simply wired "wrong" and that our views can be ascribed to mental defects rather than conviction. It was this thinking that prompted 1,189 psychiatrists in 1964 to take out newspaper ads declaring Barry Goldwater to be "psychologically unfit" to be president. Just two summers ago, a Berkeley study claimed to prove that conservatism was more akin to a personality disorder than an actual political philosophy.

Indeed, one gets a whiff of this sort of thinking in Carey's coverage . The most ominous concern he raises at the end is that the study calls into doubt "the future of bipartisan cooperation or national unity." Why? "Because men and women tend to seek mates with a similar ideology . the two gene pools are becoming, if anything, more concentrated, not less."

This last bit strikes me as piffle. Did mates select for bipartisanship more during the Bronze Age?

Here's how I read Carey: The bipartisan divide exists because those chromosomally damaged right-wingers aren't going away until we can find a cure.

In other words, the Times is showing it's biases.

Which brings us back to the mortification of Larry Summers. Is it so unreasonable to assume there are greater genetic cognitive and behavioral differences between men and women than between, say, Jews and gentiles - never mind conservatives and liberals? If genes make us more open to some group mores, why can't they make one gender more open to one field of study? The animal kingdom is replete with enormous male-female disparities. Even among the branch of humans we call feminists, it's a widely held view that men and women think and behave differently.

Such views only become controversial when some aggrieved group's self-esteem is on the line - and the possibility of extortion is in play. Then, suddenly, Dr. Summers' pancreas becomes a cocktail peanut.

The problem is these sorts of stories are going to be pouring forth daily for the next 20 years, and there's just not enough of Summers for everybody with low self-esteem to feed on.

Jonah Goldberg is editor-at-large of, a member group.

©2005 Tribune Media Service

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