PRIMARY SOURCES
American Psychological Association. “Intelligence: Knowns and Unknowns. Report of a Task Force Established by the Board of Scientific Affairs of the American Psychological Association.” Released August 7, 1995.
Ceci, S. J. On Intelligence: A Bio-ecological Treatise on Intellectual Development. Harvard University Press, 1996.
Cravens, H. “A scientific project locked in time: the Terman Genetic Studies of Genius.” American Psychologist 47, no. 2 (February 1992): 183– 89.
Dickens, William T., and James R. Flynn. “Heritability estimates versus large environmental effects: the IQ paradox resolved.” Psychological Review 108, no. 2 (2001): 346–69.
Dodge, Kenneth A. “The nature-nurture debate and public policy.” Merrill-Palmer Quarterly 50, no. 4 (2004): 418–27.
Flynn, J. R. “Beyond the Flynn Effect: Solution to All Outstanding Problems Except Enhancing Wisdom.” Lecture at the Psychometrics Centre, Cambridge Assessment Group, University of Cambridge, December 16, 2006.
Locurto, Charles. Sense and Nonsense about IQ. Praeger, 1991.
Risley, Todd R., and Betty Hart. Meaningful Differences in the Everyday Experience of Young American Children. Paul H. Brookes Publishing, 1995.
Schönemann, Peter H. “On models and muddles of heritability.” Genetica 99, no. 2/3 (March 1997): 97–108.
Sternberg, Robert J. “Intelligence, Competence, and Expertise.” In Handbook of Competence and Motivation, edited by A. J. Elliot and C. S. Dweck. Guilford Publications, 2005.
Sternberg, Robert J., and Janet E. Davidson. Conceptions of Giftedness. 1st ed. Cambridge University Press, 1986.
Sternberg, Robert J., and Elena Grigorenko. “The predictive value of IQ.” Merrill-Palmer Quarterly 47, no. 1 (2001): 1–41.
CHAPTER NOTES
[Some] assert that an individual’s intelligence is a fixed quantity.
Longer version: “[Some] assert that an individual’s intelligence is a fixed quantity which cannot be increased. We must protest and react against this brutal pessimism … With practice, training, and above all method, we manage to increase our attention, our memory, our judgment, and literally to become more intelligent than we were before.” (Binet, Les idées modernes sur les enfants; this work has been reprinted in Elliot and Dweck, eds., Handbook of Competence and Motivation; see p. 124.)
The good news is that, once learned, The Knowledge becomes literally embedded in the taxi driver’s brain.
Eleanor Maguire writes:
Our finding that the posterior hippocampus increases in volume when there is occupational dependence on spatial navigation is evidence for functional differentiation within the hippocampus. In humans, as in other animals, the posterior hippocampus seems to be preferentially involved when previously learned spatial information is used, whereas the anterior hippocampal region may be more involved (in combination with the posterior hippocampus) during the encoding of new environmental layouts.
A basic spatial representation of London is established in the taxi drivers by the time The Knowledge is complete. This representation of the city is much more extensive in taxi drivers than in the control subjects. Among the taxi drivers, there is, over time and with experience, a further fine-tuning of the spatial representation of London, permitting increasing understanding of how routes and places relate to each other. Our results suggest that the “mental map” of the city is stored in the posterior hippocampus and is accommodated by an increase in tissue volume. (Maguire et al., “Navigation-related structural change in the hippocampi of taxi drivers,” pp. 4398–403.)
Further, her conclusion was perfectly consistent with what others have discovered in recent studies of violinists, Braille readers, meditation practitioners, and recovering stroke victims: that specific parts of the brain adapt and organize themselves in response to specific experience.
Leon Eisenberg surveys the evidence:
Colleagues … compared magnetoencephalographic recordings from experienced violinists with those from nonmusicians and found a substantially larger cortical representation of the fingers of the left hand (the one used to play the strings) than of the fingers of the right (or bowing) arm and more brain area dedicated to representation of fingers in the musicians than in the corresponding recordings from the nonmusicians.
A second example … is that the planum temporale is larger on the left than on the right in the musicians; the asymmetry is most marked in those with perfect pitch.
[Another study] found a substantial enlargement of hand representation in the three-finger Braille readers.
The cortex has a remarkable capacity for remodeling after environmental change. (Italics mine.) (Eisenberg, “Nature, niche, and nurture,” 213–22.)
Eisenberg’s citations:
Schlaug G., L. Jancke, Y. Huang, et al. “Asymmetry in musicians.” Science 267 (1995): 699–701.
Elbert, Thomas, Christo Pantev, Christian Wienbruch, Brigitte Rockstroh, and Edward Taub. “Increased cortical representation of the fingers of the left hand in string players.” Science 270 (1995): 305–7.
Sterr, A., M. M. Muller, T. Elbert, et al. “Changed perceptions in Braille readers.” Nature 391 (1998): 134–35.
Yang, T. T., C. C. Gallen, and B. Schwartz. “Sensory maps in the human brain.” Nature 368 (1994): 592–93.
Yang T. T., C. C. Gallen, V. S. Ramachandran, et al. “Noninvasive detection of cerebral plasticity in adult human somatosensory cortex.” Neuroreport 5 (1994): 701–4.
Ramachandran, V. S., D. Rogers-Ramachandran, and M. Stewart. “Perceptual correlates of massive cortical reorganization.” Science 258 (1992): 1159–60.
Ramachandran, V. S. “Behavioral and magnetoencephalographic correlates of plasticity in the adult human brain.” Proceedings of the National Academy of Sciences 90 (1993): 10413–20.
Mogilner A., J. A. I. Grossman, and V. Ribary. “Somatosensory cortical plasticity in adult humans revealed by magnetoencephalography.” Proceedings of the National Academy of Sciences 90 (1993): 3593–97.
This is our famous “plasticity”: every human brain’s built-in capacity to become, over time, what we demand of it.
There are, of course, strict limits to plasticity. Every functioning human brain has an intricate and unchanging design, billions of years in the making. Various lobes and neural pathways are dedicated to specific functions: language, sensory input, consciousness, logical thought, abstract thought, spatial representation, and so on. The mind is not a blank slate. But this evolved design also includes an enormous capacity to learn and adapt, to hold specialized knowledge and wield specialized skills.
Psychological methods of measuring intelligence: Terman, Genetic Studies of Genius, vol. 1, p. v.
Terman was part of a well-established movement convinced that intelligence was an inborn asset, inherited through genes, fixed at birth, and stable throughout life.
Terman’s direct mentor was the prominent psychologist (and first president of the American Psychological Association) G. Stanley Hall. H. Cravens writes:
From his mentor, [G. Stanley] Hall, Terman learned that biological inheritance was all-powerful in determining the psyches and actions of animals and men … Hall’s genetic psychology was a grand vision; simply put, Hall taught that minds have evolved through definite stages or types, from those of the lowliest cockroach to those of comparatively intellectual mammals and, finally, to those of the lower races, of children, of women, and then of rational White men. Hallian genetic psychology offered an overall hypothesis for Terman during his scientific career. (Cravens, “A Scientific Project Locked in Time.”)
After Darwin published On the Origin of Species in 1859, Galton immediately sought to further define natural selection: Galton, Hereditary Genius, p. 2.
Galton also wrote:
Biographies show [eminent men] to be haunted and driven by an incessant instinctive craving for intellectual work. They do not work for the sake of eminence, but to satisfy a natural craving for brain work, just as athletes cannot endure repose on account of their muscular irritability, which insists upon exercise. It is very unlikely that any conjunction of circumstances should supply a stimulus to brain work commensurate with what these men carry in their own constitutions. (Galton, Hereditary Genius, p. 80.)
In 1869, he published Hereditary Genius, arguing that smart, successful people were simply “gifted” with a superior biology: Galton, Hereditary Genius, p. 39.
“The range of mental power between the greatest and least of English intellects is enormous,” Galton wrote. “There is a continuity of natural ability reaching from one knows not what height, and descending to one can hardly say what depth.” (Galton, Hereditary Genius, p. 26.)
In 1874, he introduced the phrase “nature and nurture” (as a rhetorical device to favor nature).
“The phrase ‘nature and nurture’ is a convenient jingle of words,” Galton wrote, “for it separates under two distinct heads the innumerable elements of which personality is composed. Nature is all that a man brings with himself into the world. Nurture is every influence from without that affects him after his birth.” (Galton, English Men of Science, p. 112.)
Galton probably got the phrase from Shakespeare’s The Tempest.
Prospero: A devil, a born devil, on whose nature Nurture can never stick.
Judith Rich Harris suggests that Shakespeare may have gotten it from British writer Richard Mulcaster, who, thirty years earlier, had written, “Nature makes the boy toward, nurture sees him forward.” (Harris, The Nurture Assumption, p. 4.)
In 1883, he invented “eugenics,” his plan to maximize the breeding of biologically superior humans and minimize the breeding of biologically inferior humans.
Galton was an epic figure in the history of science. In his New Yorker review of Martin Brookes’s recent Galton biography, Jim Holt eloquently explains his importance in two fields: eugenics and statistics.
Jim Holt on Galton’s eugenics:
In his long career, Galton didn’t come close to proving the central axiom of eugenics: that, when it comes to talent and virtue, nature dominates nurture. Yet he never doubted its truth, and many scientists came to share his conviction. Darwin himself, in “The Descent of Man,” wrote, “We now know, through the admirable labours of Mr. Galton, that genius … tends to be inherited.” Given this axiom, there are two ways of putting eugenics into practice: “positive” eugenics, which means getting superior people to breed more; and “negative” eugenics, which means getting inferior ones to breed less. For the most part, Galton was a positive eugenicist. He stressed the importance of early marriage and high fertility among the genetic elite, fantasizing about lavish state-funded weddings in Westminster Abbey with the Queen giving away the bride as an incentive. Always hostile to religion, he railed against the Catholic Church for imposing celibacy on some of its most gifted representatives over the centuries. He hoped that spreading the insights of eugenics would make the gifted aware of their responsibility to procreate for the good of the human race. But Galton did not believe that eugenics could be entirely an affair of moral suasion. Worried by evidence that the poor in industrial Britain were breeding disproportionately, he urged that charity be redirected from them and toward the “desirables.” To prevent “the free propagation of the stock of those who are seriously afflicted by lunacy, feeble-mindedness, habitual criminality, and pauperism,” he urged “stern compulsion,” which might take the form of marriage restrictions or even sterilization.
Galton’s proposals were benign compared with those of famous contemporaries who rallied to his cause. H. G. Wells, for instance, declared, “It is in the sterilisation of failures, and not in the selection of successes for breeding, that the possibility of an improvement of the human stock lies.” Although Galton was a conservative, his creed caught on with progressive figures like Harold Laski, John Maynard Keynes, George Bernard Shaw, and Sidney and Beatrice Webb. In the United States, New York disciples founded the Galton Society, which met regularly at the American Museum of Natural History, and popularizers helped the rest of the country become eugenics-minded. “How long are we Americans to be so careful for the pedigree of our pigs and chickens and cattle—and then leave the ancestry of our children to chance or to ‘blind’ sentiment?” asked a placard at an exposition in Philadelphia. Four years before Galton’s death, the Indiana legislature passed the first state sterilization law, “to prevent the procreation of confirmed criminals, idiots, imbeciles, and rapists.” Most of the other states soon followed. In all, there were some sixty thousand court-ordered eugenically unfit. It was in Germany that eugenics took its most horrific form. Galton’s creed had aimed at the uplift of humanity as a whole; although he shared the prejudices that were common in the Victorian era, the concept of race did not play much of a role in his theorizing.
German eugenics, by contrast, quickly morphed into Rassenhygiene—race hygiene. Under Hitler, nearly four hundred thousand people with putatively hereditary conditions like feeblemindedness, alcoholism, and schizophrenia were forcibly sterilized. In time, many were simply murdered. The Nazi experiment provoked a revulsion against eugenics that effectively ended the movement. (Holt, “Measure for Measure,” p. 90.)
Jim Holt on Galton’s statistical inventions:
After obtaining height data from two hundred and five pairs of parents and nine hundred and twenty-eight of their adult children, Galton plotted the points on a graph, with the parents’ heights represented on one axis and the children’s on the other. He then penciled a straight line though the cloud of points to capture the trend it represented. The slope of this line turned out to be two-thirds. What this meant was that exceptionally tall (or short) parents had children who, on average, were only two-thirds as exceptional as they were. In other words, when it came to height children tended to be less exceptional than their parents. The same, he had noticed years earlier, seemed to be true in the case of “eminence”: the children of J. S. Bach, for example, may have been more musically distinguished than average, but they were less distinguished than their father. Galton called this phenomenon “regression toward mediocrity.”
Regression analysis furnished a way of predicting one thing (a child’s height) from another (its parents’) when the two things were fuzzily related. Galton went on to develop a measure of the strength of such fuzzy relationships, one that could be applied even when the things related were different in kind—like rainfall and crop yield. He called this more general technique “correlation.” The result was a major conceptual breakthrough. Until then, science had pretty much been limited to deterministic laws of cause and effect—which are hard to find in the biological world, where multiple causes often blend together in a messy way. Thanks to Galton, statistical laws gained respectability in science. His discovery of regression toward mediocrity—or regression to the mean, as it is now called—has resonated even more widely. (Holt, “Measure for Measure,” pp. 88–89.)
“[the word] ‘intelligence’ has become a mere vocal sound”: Spearman, The Abilities of Man, Their Nature and Measurement, cited in Schönemann, “On models and muddles of heritability.”
This was still the case in the 1980s. From the American Psychiatric Association report: “Indeed, when two dozen prominent theorists were recently asked to define intelligence, they gave two dozen somewhat different definitions.” (Hertzig and Farber, eds., Annual Progress in Child Psychiatry and Child Development 1997, p. 96.)
there must be a single “general intelligence” (g for short): Spearman, “General intelligence, objectively determined and measured,” pp. 201–93; Green, Classics in the History of Psychology Web site.
“G is, in the normal course of events, determined innately,” Spearman declared. “A person can no more be trained to have it in higher degree than he can be trained to be taller”: Deary, Lawn, and Bartholomew, “A conversation between Charles Spearman, Godfrey Thomson, and Edward L. Thorndike,” p. 128.
In the absence of any persuasive alternative, Spearman’s g resonated with the psychological community and proved quite resilient throughout the twentieth century. His g was further refined in the 1970s and ’80s by Berkeley psychologist Arthur Jensen and gained considerable traction in the psychological community.
That’s not to say that Jensen won over a clear majority of academic psychologists. But he clearly won over at least a large plurality. “Of the 60 papers in our sample, 29 cited Jensen’s article negatively. This number includes articles that took exception to almost every point presented in the paper. It also includes those in which the authors debated specific points Jensen made. Eight of the articles cited Jensen’s paper as an example of a controversy. Eight more used the article as a background reference. Only fifteen of the articles cited Jensen in agreement with his positions, and seven of them only on minor points. Further readings have confirmed that our sample is typical of the way authors have cited the Jensen work.” (“High Impact Science and the Case of Arthur Jensen,” pp. 652–62.)
In 1971, Raymond Cattell divided g into two independent subcomponents—fluid intelligence (gF) and crystallized intelligence (gC). Fluid intelligence was thought to be a fixed, innate ability to reason and conceptualize; crystallized intelligence was the school-influenced ability to draw on knowledge and experience.
Throughout the twentieth century, psychologists supporting general intelligence became naturally allied with the psychologists supporting “heritability” from twin studies, and together they painted a formidable neo-Galtonian portrait of humans with preset genetic capabilities. Collectively, these modern Galton disciples became known as “behavior geneticists.” In the 1980s and ’90s, they published a slew of studies aiming to solidify their position and influence policy. In short, they wanted to steer resources toward the innately superior and not waste much on the genetically inferior.
Kenneth A. Dodge writes: “The naïve hope that early environmentalists could be easily manipulated to alter long-term outcomes inspired a backlash of behavior-genetic studies in the 1980s and 1990s that championed the high percent of variance in behavior that is accounted for by genes. The legacy of this backlash is the argument that public and private resources (e.g., the best schools and highest incomes) should be administered according to the selection of those with the highest (presumably, genetically based) potential to achieve, rather than to compensate for biological or environmental disadvantage. The scholarly anchor or the policy conclusion was exemplified in the essays by Scarr (1992), Lytton (1990), and Harris (1995, 1998) which claimed that the environment accounts for very little influence on human behavior. After 50 years of study, it seemed that little had been learned.” (Dodge, “The nature-nurture debate and public policy,”. pp. 418–27)
In 1916, Stanford’s Lewis Terman produced a practical equivalent of g with his Stanford-Binet Intelligence Scales.
Excerpt from an excellent article by Mitchell Leslie:
In 1916, Terman sprang his test on America. He released The Measurement of Intelligence, a book that was half instruction manual and IQ test, half manifesto for universal testing. His little exam, which a child could complete in a mere 50 minutes, was about to revolutionize what students learned and how they thought of themselves.
Few American children have passed through the school system in the last 80 years without taking the Stanford-Binet or one of its competitors. Terman’s test gave U.S. educators the first simple, quick, cheap and seemingly objective way to “track” students, or assign them to different course sequences according to their ability. The following year, when the United States entered World War I, Terman helped design tests to screen Army recruits. More than 1.7 million draftees took his tests, broadening public acceptance of widespread IQ testing.
The Stanford-Binet made Terman a leader in a fervent movement to take testing far beyond the schoolhouse and Army base. Proponents considered intelligence the most valuable human quality and wanted to test every child and adult to determine their place in society. The “intelligence-testers”—a group that included many eugenicists—saw this as the tool for engineering a fairer, safer, fitter and more efficient nation, a “meritocracy” run by those most qualified to lead. In their vision of a vibrant new America, IQ scores would dictate not only what kind of education a person received but what work he or she could get. The most important and rewarding jobs in business, the professions, academia and government would go to the brightest citizens. People with very low scores—under about 75—would be institutionalized and discouraged or prevented from having children.
IQ tests and the social agenda of their advocates roused critics right from the start. To the journalist Walter Lippmann, the intelligence-testers were “the Psychological Battalion of Death,” seizing unparalleled power over every child’s future. Lippmann and Terman dueled in the pages of The New Republic in 1922 and 1923. “I hate the impudence of a claim that in 50 minutes you can judge and classify a human being’s predestined fitness in life,” Lippmann wrote. “I hate the sense of superiority which it creates, and the sense of inferiority which it imposes.” In a sarcastic rejoinder, Terman compared Lippmann to the creationist William Jennings Bryan and other opponents of scientific progress, then attacked Lippmann’s writing style as “much too verbose for literal quotation.” Though he could never match Lippmann’s eloquence, in the end Terman won the war: intelligence testing continued to spread. By the 1930s, kids with high IQs were being sent into more challenging classes to prepare for high-earning jobs or college, while low scorers got less demanding coursework, reduced expectations and dimmer job prospects. (Leslie, “The Vexing Legacy of Lewis Terman.”)
adapted from an earlier version by French psychologist Alfred Binet.
Ironically, IQ tests were not originally intended to measure a person’s intelligence at all. First invented in 1905 by psychologist Alfred Binet and physician Theodore Simon as an effort to identify French schoolchildren in need of most attention, the Binet-Simon test aimed to lift students up rather than assign them a permanent intellectual rank.
“The procedures which I have indicated will, if perfected, come to classify a person before or after such another person or such another series of persons,” wrote Binet. “But I do not believe that one may measure one of the intellectual aptitudes in the sense that one measures length or a capacity” (italics mine). (Varon, “Alfred Binet’s concept of intelligence,” p. 41.)
“With practice, training, and above all method,” Binet wrote in 1909, “we manage to increase our attention, our memory, our judgment, and literally to become more intelligent than we were before.” (A century later, the science of motivation and expert performance would validate this.) (Binet, Les idées modernes sur les enfants; this work has been reprinted in Elliot and Dweck, eds., Handbook of Competence and Motivation; see p. 124.)
Mitchell Leslie adds:
With questions ranging from mathematical problems to vocabulary items, the Americanized test was supposed to capture “general intelligence,” an innate mental capability that Terman felt was as measurable as height and weight. As a hardcore hereditarian, he believed that genetics alone dictated one’s level of general intelligence. This vital constant, which he called an “original endowment,” wasn’t altered by education or home environment or hard work, he maintained. To denote it, he selected the term “intelligence quotient.” (Leslie, “The Vexing Legacy of Lewis Terman.”)
the National Intelligence Test (a precursor to the SAT) was designed by Edward Lee Thorndike: Saretzky, “Carl Campbell Brigham, the Native Intelligence Hypothesis, and the Scholastic Aptitude Test.”
Princeton psychologist Carl Brigham disavowed his own creation, writing that all intelligence tests were based on “one of the most glorious fallacies in the history of science, namely that the tests measured native intelligence purely and simply without regard to training or schooling.”
Matt Pacenza writes:
In an unpublished manuscript which Lemann unearthed, Brigham wrote that the standardized testing movement was based on “one of the most glorious fallacies in the history of science, namely that the tests measured native intelligence purely and simply without regard to training or schooling. The test scores very definitely are a composite including schooling, family background, familiarity with English and everything else. (Pacenza, “Flawed from the Start”; Lemann, The Big Test.)
diagram illustrating Distribution of IQ Scores: Locurto, Sense and Nonsense About IQ, p. 5.
As Stephen Jay Gould outlines, Terman assigned a protégée, Catherine Cox, to look back in time and assign IQs to dead geniuses—a logical farce considering what the IQ is supposed to do. They assigned a score of 200 to Terman’s hero Galton. (Gould, The Mismeasure of Man, pp. 213–17.)
At the time it was introduced, Terman’s test filled a particular need in American schools and society. In that age of standardization and mechanization, American culture was obsessed with establishing consistent measures in all walks of life. IQ scores provided an easy way to separate the most promising students from the least promising, to identify and nurture future leaders in business, government, the military, and so on. “Tests of ‘general intelligence,’ given as early as six, eight, or ten years,” Terman insisted with pride, “tell a great deal about the ability to achieve either presently or 30 years hence.”
Terman was correct to suggest a strong connection between academic skills and success in modern, industrialized society. Someone who performs well in school and in abstract intellectual tests is generally (albeit with many obvious exceptions) more likely to succeed in business, law, journalism, and of course academia—any profession that puts a premium on any of those same skills. For that reason, IQ scores have proven to be generally predictive of success in Western societies where success is sufficiently based on education.
Sternberg and Grigorenko add:
IQ seems to be predictive of the reaching of all steps of career life in a stable society, where Western schooling is valued and rewarded, income is scaled in rough correspondence to years of education, and highly-skilled labor is needed. (Sternberg and Grigorenko, “The predictive value of IQ,” p. 9.)
at its core, IQ was merely a population-sorting tool.
Just as Binet had originally intended.
Lewis Terman and colleagues actually recommended that individuals identified as “feebleminded” by his test be removed from society and that anyone scoring less than 100 be automatically disqualified from any prestigious position.
Bonnie Strickland writes:
Terman (1916) actually appealed for universal intelligence testing, believing that the enormous costs of crime and vice could be reduced by removing the feebleminded from society. Further, theorizing that employment opportunities should be determined by intelligence, Terman proposed a social order that would close prestigious and rewarding professions to people with IQs under 100. (Strickland, “Misassumptions, misadventures, and the misuse of psychology,” p. 333—citing Terman, The Intelligence of School Children.)
The Terman book is fascinating reading. Although Terman’s IQ test could not really prove either fixed or innate intelligence, he maintained that it had proved both and proceeded accordingly. Terman’s logic was simple: since his tests showed a reasonable consistency over the years, they revealed that intelligence was innate and fixed. (Terman, The Intelligence of School Children.)
The French did not share this leave-them-behind approach, and to this day they largely ignore modern IQ tests. (Sternberg and Grigorenko, “The predictive value of IQ,” p. 2.)
“does not imply unchangeability”: Howe, “Can IQ Change?” p. 71.
“IQ scores,” explains Cornell University’s Stephen Ceci, “can change quite dramatically as a result of changes in family environment (Clarke, 1976; Svendsen, 1982), work environment (Kohn, 1981), historical environment (Flynn, 1987), styles of parenting (Baumrind, 1967; Dornbusch, 1987), and, most especially, shifts in level of schooling”: Ceci, On Intelligence, p. 73.
Ceci’s Citations
Family environment
Clarke, Ann M., and Alan D. Clarke. Early Experience and the Life Path. Somerset, 1976.
Svendsen, Dagmund. “Factors related to changes in IQ: a follow-up study of former slow learners.” Journal of Child Psychology and Psychiatry 24, no. 3 (1983): 405–13.
Work environment
Kohn, Melvin, and Carmi Schooler. “The Reciprocal Effects of the Substantive Complexity of Work and Intellectual Flexibility: A Longitudinal Assessment.” American Journal of Sociology 84 (July 1978): 24–52.
Historical environment
Flynn, J. R. “Massive IQ gains in 14 nations: what IQ tests really measure.” Psychological Bulletin 101 (1987): 171–91.
Styles of parenting
Baumrind, D. “Child care practices anteceding three patterns of preschool behavior.” Genetic Psychology Monographs 75 (1967): 43–88.
Dornbusch, Sanford M., Philip L. Ritter, P. Herbert Leiderman, Donald F. Roberts, and Michael J. Fraleigh. “The relation of parenting style to adolescent school performance.” Child Development 58, no. 5 (October 1987): 1244–57.
Lewis Terman’s most important claim for IQ—that it reveals a person’s fixed, innate intelligence—relies entirely on the assertion that individual IQ scores remain the same throughout people’s lives. This simply is not true. While one study reported a majority of people’s scores changing relatively little over time, that same study reported that, “in a nontrivial minority of children, naturalistic IQ change is marked and real.” Other large studies showed a significant majority of students experiencing an IQ swing of 15 points or more over time. (Sternberg and Grigorenko, “The predictive value of IQ,” p. 13.)
It also means that Spearman’s IQ test has ironically sowed the seeds of its own destruction. In so efficiently documenting narrow bands of academic achievement decade after decade, the test that he devised to prove the fixedness of intelligence inadvertently demonstrated how flexible and buildable intelligence really is.
James Flynn: “At any particular time, factor analysis will extract g(iQ)—and intelligence appears unitary. Over time, real-world cognitive skills assert their functional autonomy and swim freely of g—and intelligence appears multiple. If you want to see g, stop the film and extract a snap shot; you will not see it while the film is running. Society does not do factor analysis.” (Flynn, What Is Intelligence? p. 18.)
IQ is as changeable as much as 30 points, as reported in Sherman and Key; and as much as 18 points, as reported in Jones and Bayley. (Sherman and Key results reported in Ceci, On Intelligence, chapter 5; Jones and Bayley, “The Berkeley Growth Study,” pp. 167–73.)
Their unavoidable conclusion was that “children develop only as the environment demands development”: Sherman and Key, “The intelligence of isolated mountain children,” pp. 279–90.
Other studies have demonstrated that IQ scores drift lower during the summer months (except for those attending an academic camp) and that they rise steadily as the school year progresses. In other words, schooling itself has a direct effect on IQ scores. “Contrary to the traditional belief that information contained on IQ tests is potentially available to all children, regardless of environmental conditions,” writes Stephen Ceci, “it has been known for many decades that a child’s experience of schooling exerts a strong influence on intelligence test performance … This relationship is still substantial after potentially confounding variables, such as the tendency for the most intelligent children to begin schooling earlier and remain there longer, are controlled.” (Ceci, On Intelligence, chapter 5.)
To the extent that scores did show some stability across a large population, it seemed largely a function not of innate intelligence but population inertia. Inertia is the tendency for things to remain in their same relative state—of rest or motion—unless and until something comes along to change the dynamic. It’s true of molecular physics and it’s equally true of human action and populations. Most people performing at the middle of the intellectual pack at age ten are going to be performing at the middle of the intellectual pack at age twenty or thirty. This observation says nothing about intelligence; it’s simple population dynamics. You could say the same thing about almost any trait: by and large, the funniest ten-year-olds are also going to be the funniest twenty-year-olds, the fastest ten-year-olds are also going to be the fastest twenty-year-olds; the biggest-toed ten-year-olds are also going to be the biggest-toed twenty-year-olds. There will be plenty of individual exceptions, but in a large group, this consistency of order is always going to be the norm.
Another way of illustrating population inertia is to consider the annual New York City marathon, with its ninety thousand runners. If one were to list the order of runners at the ten-mile mark, and then compare that order to the order at the finish line, you would find a very solid correlation. Almost none of the runners at the finish would be in exactly the same position as before, and of course some would be way off, but on the whole, the correlation of runners’ ten-mile positions to twenty-six-mile positions would be very high. Why? Because by mile ten, runners have already established their pace, their level of endurance, their level of competitiveness, and so on; the pack has taken shape and will keep roughly the same shape throughout the race. Obviously, this correlation has absolutely nothing to do with the underlying cause of each runner’s performance. It simply reflects the dynamic of any competition.
So it is with IQ. Without question, there are wide differences in intellectual abilities throughout life, and if you test one hundred thousand kids at age ten and then test them again at age twenty-six, you’re going to find that, on average, they remain in roughly the same intellectual pecking order. Many individual scores will diverge—IQ scores are known to swing as much as thirty points over time in individuals with changing circumstances—but as a group, the age-ten numbers will correlate rather well with the age-twenty-six numbers.
Surprise, surprise: most people who are pretty good at academics at age ten (compared to others the same age) are also pretty good at age twenty-six; most who are excellent at age ten are also excellent at age twenty-six. That’s what IQ stability tells us—and that’s all it tells us. It does not suggest inborn limits, and it doesn’t even hint at the extraordinary power of individuals to change their own circumstances and lift their intellectual performance.
Intelligence scores of infants are not predictive of future scores or life success. That population is still too much in flux; individuals have not yet hit their stride; the pack has not yet taken shape; population inertia has not yet set in.
Comparing raw IQ scores over nearly a century, Flynn saw that they kept going up: Nippert, “Eureka!”
IQ test takers improved over their predecessors by three points every ten years.
These comparisons draw on the raw scores—not the weighted scores that are annually recalibrated so that the average is always 100.
Using a late-twentieth-century average score of 100, the comparative score for the year 1900 was calculated to be about 60—leading to the truly absurd conclusion, acknowledged Flynn, “that a majority of our ancestors were mentally retarded.”
This retroactive analysis illustrates the logical flaw in continually using a curved IQ score to dismiss the competence of anyone scoring below 100.
“[The intelligence of] our ancestors in 1900 was anchored in everyday reality,” explains Flynn. “We differ from them in that we can use abstractions and logic and the hypothetical.”
Flynn adds:
When [asked]: “What do dogs and rabbits have in common,” Americans in 1900 would be likely to say, “You use dogs to hunt rabbits.” The correct [contemporary test] answer, that both are mammals, assumes that the important thing about the world is to classify it in terms of the taxonic categories of science … Our ancestors found pre-scientific spectacles more comfortable than post-scientific spectacles, [because that’s what] showed them what they considered to be most important about the world … (Flynn, “Beyond the Flynn Effect.”)
Examples of abstract notions that simply didn’t exist in the minds of our nineteenth-century ancestors include the theory of natural selection (formulated in 1864), and the concepts of control group (1875) and random sample (1877).
This comes from a 2006 lecture by James Flynn. An extended excerpt:
Over the last century and a half, science and philosophy have expanded the language of educated people, particularly those with a university education, by giving them words and phrases that greatly increase their critical acumen. Each of these terms stands for a cluster of interrelated ideas that virtually spell out a method of critical analysis applicable to social and moral issues. I will call them “shorthand abstractions” (or SHAs), it being understood that they are abstractions with peculiar analytic significance.
I will name [some] SHAs followed by the date they entered educated usage (dates all from the Oxford English Dictionary on line):
(1) Market (1776: economics). With Adam Smith, this term altered from the merely concrete (a place where you bought something) to an abstraction (the law of supply and demand). It provokes a deeper analysis of innumerable issues. If the government makes university education free, it will have to budget for more takers. If you pass a minimum wage, employers will replace unskilled workers with machines, which will favor the skilled. If you fix urban rentals below the market price, you will have a shortage of landlords providing rental properties. Just in case you think I have revealed my politics, I think the last a strong argument for state housing.
(2) Percentage (1860: mathematics). It seems incredible that this important SHA made its debut into educated usage less than 150 years ago. Its range is almost infinite. Recently in New Zealand, there was a debate over the introduction of a contraceptive drug that kills some women. It was pointed out that the extra fatalities from the drug amounted to 50 in one million (or 0.005 %) while without it, an extra 1000 women (or 0.100 %) would have fatal abortions or die in childbirth.
(3) Natural selection (1864: biology). This SHA has revolutionized our understanding of the world and our place in it. It has taken the debate about the relative influences of nature and nurture on human behavior out of the realm of speculation and turned it into a science. Whether it can do anything but mischief if transplanted into the social sciences is debatable. It certainly did harm in the 19th century when it was used to develop foolish analogies between biology and society. Rockefeller was acclaimed as the highest form of human being that evolution had produced, a use denounced even by William Graham Sumner, the great “Social Darwinist.” I feel it made me more aware that social groups superficially the same were really quite different because of their origins. Black unwed mothers who are forced into that status by the dearth of promising male partners are very different from unwed mothers who choose that status because they genuinely prefer it.
(4) Control group (1875: social science). Recognition that before and after comparisons of how interventions affect people are usually flawed. We introduce an enrichment program in which pre-school children go to a “play center” each day. It is designed to raise the IQ of children at risk of being diagnosed as mentally retarded. Throughout the program we test their IQs to monitor progress. The question arises, what has raised their IQs? The enrichment program, getting out of a dysfunctional home for 6 hours each day, the lunch they had at the play center, the continual exposure to IQ tests. Only a control group selected from the same population and subjected to everything but the enrichment program can suggest an answer.
(5) Random sample (1877: social science). Today, the educated public is much more likely to spot biased sampling than they were a few generations ago. In 1936, the Literary Digest telephone poll showed that Landon was going to beat Roosevelt for President and was widely believed, even though few had telephones except the more affluent.
(6) Naturalistic fallacy (1903: moral philosophy). That one should be wary of arguments from facts to values, for example, an argument that because something is a trend in evolution it provides a worthy goal for human endeavor.
(7) Charisma effect (1922: social science). Recognition that when a technique is applied by a charismatic innovator or disciples fired by zeal, it may be successful for precisely that reason. For example, a new method of teaching mathematics often works until it is used by the mass of teachers for whom it is merely a new thing to try.
(8) Placebo (1938: medicine). The recognition that merely being given something apparently endorsed by authority will often have a salutary effect for obvious psychological reasons. Without this notion, a rational drugs policy would be overwhelmed by the desperate desire for a cure by those stricken with illness.
(9) Falsifiable/tautology (1959: philosophy of science). The stipulation that a factual claim is bankrupt (a mere tautology or closed circle of definitions) unless it is testable against evidence. It can be used to explode: a theory of motivation that asserts all human acts are selfish and yet rules out every possible counterexample; the claim that “real” workers by definition have a revolutionary psychology; that “real” Christians are always charitable; and so forth. (Flynn, “Beyond the Flynn Effect.”)
Flynn and his colleague William Dickens add:
Thanks to industrialization, it is likely that the cognitive complexity of the average person’s job has increased over the last century. There is no doubt that more-demanding educational credentials control access to a wide range of jobs. There are far more people in scientific, managerial, and technical positions than ever before. Increased leisure time is another possible trigger for IQ gains, as some activities undertaken during extended leisure (reading, puzzles, games such as chess) may be honing people’s facilities. Radio and television may be factors. It is possible that the machinery we increasingly surround ourselves with (e.g., cars, phones, computers, and VCRs) have increased the demands on our cognitive capacities. The shift to fewer children in each family, affording more time to cater to children’s curiosity and richer individual interactions, may have played a role. Some or all of these may have contributed to a significant attitude shift: The current generation may take abstract problem solving far more seriously than preceding generations did. The direct effects of these changes need not be large. But because they are widespread and persistent trends, they could loom large relative to the many less-constant environmental influences that produce most differences between people. (Dickens and Flynn, “Heritability estimates versus large environmental effects,” pp. 346–69.)
Perhaps the most striking of Flynn’s observations is this: 98 percent of IQ test takers today score better than the average test taker in 1900.
Flynn writes:
The Wechsler-Binet rate of gain (0.3 points per year) entails that the school children of 1900 would have had a mean IQ just under 70. The Raven-Similarities rate (0.5 points per year) yields a mean IQ of 50 (against current norms). (Flynn, “Beyond the Flynn Effect.”)
This is arguably the most important observation in this book.
“Our ability to improve the academic accomplishment of students”: Murray, “Intelligence in the Classroom.”
“Even the best schools under the best conditions cannot repeal the limits”: Charles Murray, “Intelligence in the Classroom.”
Is Charles Murray a straw man? This question was raised by some draft readers of this book. Aren’t his views so ridiculous and outside the mainstream that they aren’t worth critiquing?
Actually, Murray’s views on this subject command a good deal of respect and mainstream attention. He is a fellow at the widely respected American Enterprise Institute in Washington, D.C. He continues to write for the Wall Street Journal, the New York Times, and the Weekly Standard and appears on C-SPAN.
“small to moderate”: “Head Start Impact Study, First Year Findings,” June 2005, Prepared for Office of Planning, Research and Evaluation Administration for Children and Families, U.S. Department of Health and Human Services, Washington, D.C., Westat, The Urban Institute Chesapeake Research Associates Decision Information Resources Inc., and American Institutes for Research.
Children in professionals’ homes were exposed to an average of more than fifteen hundred more spoken words per hour than children in welfare homes.
And more than three times the children of parents on welfare. Actual numbers: welfare children 616 words per hour; professionals’ kids 2,153 words per hour. Estimate based on fourteen-hour day. Words were spoken live in person—not on TV or radio. (Hart and Risley, “The early catastrophe.”)
Not surprisingly, the psychological community responded with a mixture of interest and deep caution. In 1995, an American Psychological Association task force wrote that “such correlations may be mediated by genetic as well as (or instead of) environmental factors.” Note “instead of.” In 1995, it was still possible for leading research psychologists to imagine that better-off kids could be simply inheriting smarter genes from smarter parents, that spoken words could be merely a genetic effect and not a cause of anything.
From the APA report:
There is no doubt that such variables as resources of the home and parents’ use of language are correlated with children’s IQ scores, but such correlations may be mediated by genetic as well as (or instead of) environmental factors. Behavior geneticists frame such issues in quantitative terms. As noted in Section 3, environmental factors certainly contribute to the overall variance of psychometric intelligence. But how much of that variance results from differences between families, as contrasted with the varying experiences of different children in the same family? Between-family differences create what is called “shared variance” or c2 (all children in a family share the same home and the same parents). Recent twin and adoption studies suggest that while the value of c2 (for IQ scores) is substantial in early childhood, it becomes quite small by late adolescence. These findings suggest that differences in the life styles of families, whatever their importance may be for many aspects of children’s lives, make little long-term difference for the skills measured by intelligence tests. We should note, however, that low-income and non-white families are poorly represented in existing adoption studies as well as in most twin samples. Thus it is not yet clear whether these surprisingly small values of (adolescent) c2 apply to the population as a whole. It remains possible that, across the full range of income and ethnicity, between-family differences have more lasting consequences for psychometric intelligence. (APA, “Stalking the Wild Taboo.”)
Now we know better. We know that genetic factors do not operate “instead of” environmental factors, they interact with them: GxE.
Recall Massimo Pigliucci’s observation: “Biologists have come to realise that if one changes either the genes or the environment, the resulting behaviour can be dramatically different. The trick, then, is not in partitioning causes between nature and nurture, but in [examining] the way genes and environments interact dialectically to generate an organism’s appearance and behaviour.” (Pigliucci, “Beyond nature and nurture,” pp. 20–22.)
Speaking to children early and often. This trigger was revealed in Hart and Risley’s incontrovertible study and reinforced by the University of North Carolina’s Abecedarian Project, which provided environmental enrichment to children from birth, with the study subjects showing substantial gains compared with a control group.
For example, in the North Carolina “Abecedarian Project”—an all-day program that provided various forms of environmental enrichment to fifty-seven children from infancy onward (mean starting age 4.4 months) and compared their test performance to a matched control group—differences between groups became apparent before the end of the first year. The difference did not diminish over time; the IQ difference between the groups was still present at age twelve. (Neisser, “Rising Scores on Intelligence Tests.”)
Reading early and often. In 2003, a national study reported the positive influence of early parent-to-child reading, regardless of parental education level. In 2006, a similar study again found the same thing about reading, this time ruling out any effects of race, ethnicity, class, gender, birth order, early education, maternal education, maternal verbal ability, and maternal warmth.
Helen Raikes and colleagues write:
A national study of preschool-aged children participating in Head Start demonstrated that, compared with parents who read less frequently, more frequent reading in the fall was associated with both higher concurrent scores on literacy measures and larger gains during the year, even after controlling for parental education level, parental literacy level, and the presence of books in the home. Children of parents who reported reading to them “not at all” or “only once or twice a week” had receptive vocabulary scores that were lower than those of children whose parents reported reading “three to six times a week.” Reading three to six times per week was associated with greater fall-to-spring vocabulary gains than was reading less frequently, and children whose parents reported reading daily had even larger gains. In addition, some research suggests that earlier regular experience with bookreading, beginning as young as 14 months, is particularly beneficial.
In regression analyses to examine relations between reading and child outcomes, we controlled for the variables of race/ethnicity, demographic risk, maternal education and verbal ability, gender, birth order, Early Head Start enrollment, and maternal warmth. In the English-speaking group, at 14 months, reading several times weekly or reading daily was significantly related to vocabulary and comprehension. Findings were similar for vocabulary and MDI scores at 24 months, even after controlling for children’s 14-month vocabulary. A pattern of daily reading over three data points significantly related to child language and cognitive outcomes at 36 months. Reading daily at a minimum of one of the periods predicted language outcomes for Spanish-speaking children. Regression path analyses showed paths from early reading to later reading, early vocabulary to later child language outcomes, and 14-month vocabulary to 24-month reading. Paths for concurrent reading revealed associations with vocabulary at 14 and 24 months. (Raikes et al., “Mother-child bookreading in low-income families,” pp. 940–43.)
Nurturance and encouragement. Hart and Risley also found that, in the first four years after birth, the average child from a professional family receives 560,000 more instances of encouraging feedback than discouraging feedback; a working-class child receives merely 100,000 more encouragements than discouragements; a welfare child receives 125,000 more discouragements than encouragements.
Hart and Risley write:
But the children’s language experience did not differ just in terms of the number and quality of words heard. We can extrapolate similarly the relative differences the data showed in children’s hourly experience with parent affirmatives (encouraging words) and prohibitions. The average child in a professional family was accumulating 32 affirmatives and five prohibitions per hour, a ratio of 6 encouragements to 1 discouragement. The average child in a working-class family was accumulating 12 affirmatives and seven prohibitions per hour, a ratio of 2 encouragements to 1 discouragement. The average child in a welfare family, though, was accumulating five affirmatives and 11 prohibitions per hour, a ratio of 1 encouragement to 2 discouragements. In a 5,200-hour year, that would be 166,000 encouragements to 26,000 discouragements in a professional family, 62,000 encouragements to 36,000 discouragements in a working-class family, and 26,000 encouragements to 57,000 discouragements in a welfare family.
Extrapolated to the first four years of life, the average child in a professional family would have accumulated 560,000 more instances of encouraging feedback than discouraging feedback, and an average child in a working-class family would have accumulated 100,000 more encouragements than discouragements. But an average child in a welfare family would have accumulated 125,000 more instances of prohibitions than encouragements. By the age of 4, the average child in a welfare family might have had 144,000 fewer encouragements and 84,000 more discouragements of his or her behavior than the average child in a working-class family. Extrapolating the relative differences in children’s hourly experience allows us to estimate children’s cumulative experience in the first four years of life and so glimpse the size of the problem facing intervention. Whatever the inaccuracy of our estimates, it is not by an order of magnitude such that 60,000 words becomes 6,000 or 600,000. Even if our estimates of children’s experience are too high by half, the differences between children by age 4 in amounts of cumulative experience are so great that even the best of intervention programs could only hope to keep the children in families on welfare from falling still further behind the children in the working-class families. (Hart and Risley, “The early catastrophe.”)
Setting high expectations.
Studies validating this finding:
Edmonds, R. “Characteristics of Effective Schools.” In The School Achievement of Minority Children: New Perspectives, edited by U. Neisser. Lawrence Erlbaum, 1986, pp. 93–104
Rutter, M., B. Maughan, P. Mortimore, J. Ouston, and A. Smith. Fifteen Thousand Hours. Harvard University Press, 1979.
Slavin, R., N. Karweit, and N. Madden. Effective Programs for Students at Risk. Allyn and Bacon, 1989.
Ellen Winner: “Parents of gifted children typically have high expectations, and also model hard work and high achievement themselves.” (Winner, “The origins and ends of giftedness,” pp. 159–69.)
Winner’s Citations
Bloom, B. Developing Talent in Young People. Ballantine, 1985.
Csikszentmihályi, Mihály, Kevin Rathunde, and Samuel Whalen. Talented Teenagers. Cambridge University Press, 1993.
Gardner, H. Creating Minds: An Anatomy of Creativity Seen Through the Lives of Freud, Einstein, Picasso, Stravinsky, Eliot, Graham, and Gandhi. Basic Books, 1993.
Embracing failure.
“Deliberate practice does not involve a mere execution or repetition of already attained skills but repeated attempts to reach beyond one’s current level which is associated with frequent failures.” (Ericsson et al., “Giftedness and evidence for reproducibly superior performance,” pp. 3–56.)
Encouraging a “growth mindset”: Dweck, Mindset: The New Psychology of Success.
phenomenon that we might call “carton calculus”: Ceci, On Intelligence, p. 33.
Halfway around the world, in Kisumu, Kenya, Yale psychologist Robert Sternberg stumbled on exactly the same phenomenon in 2001 when studying the intelligence of Dholuo schoolchildren.
Surprisingly, Sternberg found a “significantly negative” correlation between his herbal medicine test and an English language test and no significant correlation between his test and the Raven Coloured Progressive Matrices (a multiple-choice IQ test probing abstract reasoning skills). (Sternberg, “Intelligence, Competence, and Expertise,” p. 21.)
As Robert Sternberg watched studies like these pile up—documenting the unusual, sometimes even untestable intelligence traits of Yup’ik Eskimo children, !Kung San hunters of the Kalahari Desert, Brazilian street youth, American horse handicappers, and Californian grocery shoppers—he realized that the lack of correlation between their expertise and IQ scores demanded nothing less than a whole new definition of intelligence.
Sternberg concludes: “Abilities as developing forms of expertise [result from] interaction with the demands of the environment.” This was more than seven decades after Sherman and Key had concluded, “Children develop only as the environment demands development.” (Sternberg, “Intelligence, Competence, and Expertise,” p. 21.)
!Kung San hunters of the Kalahari Desert: Ceci, On Intelligence, p. 35.
Brazilian street youth: Sternberg, “Intelligence, Competence, and Expertise,” p. 22.
American horse handicappers.
In an utterly fascinating study, Stephen Ceci and his colleague Jeff Liker studied expert and nonexpert horse handicappers at a racetrack. There were two extraordinary findings:
1. “Even though the greater use of complex, interactive thinking was causally related to success at the racetrack, there was no relation between such complex thinking and IQ or between IQ and success at estimating odds.”
2. Analysis “was shown to be under the influence of ecological variables such as the sex-role expectations of the task, the physical setting in which the task was performed, the motivational level of the task, and the performance context (game vs. laboratory task).” In other words, environmental variables really mattered. (Ceci, On Intelligence, pp. 41–44)
Californian grocery shoppers: Sternberg, “Intelligence, Competence, and Expertise,” p. 22.
He saw another problem, too, that reinforced this conclusion: the increasingly flimsy distinction between “intelligence” tests and so-called achievement tests like the SAT II. The more Sternberg compared the two, the harder it was for him to find any real difference between them.
Some choice quotes from Sternberg:
There is no qualitative distinction between various kinds of assessments. The main thing that distinguishes ability tests from achievement tests is not the tests themselves, but rather how psychologists, educators, and others interpretthe scores on these tests. (Italics mine.)
Conventional tests of intelligence and related abilities measure achievement that individuals should have accomplished several years back. In other words, the tests are measuring competencies at a somewhat less developed level. Tests such as vocabulary, reading comprehension, verbal analogies, arithmetic problem solving, and the like, are all, in part, tests of achievement. Even abstract reasoning tests measure achievement in dealing with geometric symbols taught in Western schools. One might as well use academic performance to predict ability test scores. The conventional view infers some kind of causation (abilities cause achievement) from correlation, but the inference is not justified from the correlational data.
There is nothing mystical or privileged about the intelligence tests. One could as easily use, say, academic or job performance to predict intelligence-related scores and vice-versa. (Sternberg, “Intelligence, Competence, and Expertise.”)
“Intelligence,” he declared profoundly in 2005, “represents a set of competencies in development.”
Sternberg calls it “the model of developing expertise.” (Sternberg, “Intelligence, Competence, and Expertise,” p. 18.)
In other words, intelligence isn’t fixed. Intelligence isn’t general. Intelligence is not a thing. Intelligence is a dynamic, diffuse, and ongoing process.
Sternberg argues that no current tests actually measure such built-in intelligence and that intelligence testers are instead relying on a dangerous circular logic: “Some intelligence theorists point to the stability of the alleged general (g) factor of human intelligence as evidence for the existence of some kind of stable and overriding structure of human intelligence. But … [w]ith different forms of schooling, g could be made either stronger or weaker. In effect, Western forms and related forms of schooling may, in part, create the g phenomenon by providing a kind of schooling that teaches in conjunction the various kinds of skills measured by tests of intellectual abilities.”
In other words: we are teaching certain skills in our schools—skills that do correlate reasonably well with Western job performance—and then measuring how well kids learn these skills. Then we pretend that the results reveal a person’s raw intelligence, when all they actually reveal is how well a child learned those skills. All we’re really learning from intelligence tests is that some kids do better than others in school. We are not, as intelligence testers claim, uncovering the innate cause of these differences.
Is Sternberg saying there’s no such thing as innate intelligence?
No. But he is saying that such intelligence is “not directly measurable,” that it is not one general ability which can be scored, and that it is not inherently limiting. The evidence shows that skills and abilities are inextricably interwoven and that all skills are modifiable.
“The main constraint in achieving expertise,” says Sternberg, “is not some fixed prior level of capacity, but purposeful engagement involving direct instruction, active participation, role modeling, and reward.”
What about the famous correlation between intelligence test scores on the one hand and job performance/life success on the other?
It’s a mirage. The correlation does exist, says Sternberg, but not because one causes the other; rather, it’s because they both measure the same abilities.
Or as Sternberg puts it: “Such correlations represent no intrinsic relation between intelligence and other kinds of performance, but rather overlap in the kinds of competencies needed to perform well under different kinds of circumstances. The greater the overlap in skills, in general, the higher the correlations.”
Sternberg then points to a series of studies demonstrating that practical expertise does not correlate well with analytical (“intelligence”) tests but does correlate very nicely with job performance and life success:
· The Yup’ik Eskimo children of Alaska have “extremely impressive competencies and even expertise for surviving in a difficult environment, but because these skills are not ones valued by teachers” they tend to do very poorly in school. (Grigorenko et al.)
· In Brazil, street children who are extremely successful in running street businesses, and highly expert in math skills necessary for those affairs, do very poorly in abstract, pencil-and-paper math problems. (Nunes)
· In Berkeley, California, there is “no correlation” between housewives’ impressive abilities in comparison shopping math and scores on pencil-and-paper math tests. (Lave)
The essential point being that whatever our innate abilities—which clearly exist but are still far from being understood and specified—they do not limit us in a way that IQ scores imply. Ultimately, life success is a function not of inherent abilities, but of highly developed skills.
Sternberg depicts a Western society having painted itself into a logical corner: as we’ve succeeded with our own brand of academia, we’ve devised tests—g, IQ, SAT, etc.—which we’ve convinced ourselves show actual innate intelligence, when all they show is achievements according to those particular standards. When you look around the world, you see there are all different kinds of intelligence. Western societies have nothing to be ashamed of in having created successful academies and economies, but we can’t let that success corrupt our judgment of where abilities actually come from.
Sternberg: “Skills develop as results of gene-environment covariation and interaction. If we wish to call them intelligence, that is certainly fine, so long as we recognize that what we are calling intelligence is a form of development competencies that can lead to expertise.”
Robert Sternberg, “Intelligence, Competence, and Expertise.” In Handbook of Competence and Motivation, edited by A. J. Elliot and C. S. Dweck, Guilford Publications, 2005.
Grigorenko, Elena. “The relationship between academic and practical intelligence: a case study of the tacit knowledge of native American Yup’ik people in Alaska.” Office of Educational Research and Improvement, December 2001.
Nunes, T. “Street Intelligence.” In Encyclopedia of Human Intelligence, edited by R. J. Sternberg. Macmillan, 1994, pp. 1045–49.
Lave, J. Cognition in Practice: Mind, Mathematics, and Culture in Everyday Life. Cambridge University Press, 1988.
Along the way, a person is not developing a single intelligence, but many different types of intelligence. How many are there? Harvard’s Howard Gardner has famously suggested that there are eight different types of intelligence:
Linguistic: the spoken and written word
Logical/mathematical: numbers and reasoning
Musical: rhythm and melody
Spatial intelligence: the ability to form a picture or mental model (highly developed in sailors, engineers, surgeons, sculptors, and painters)
Bodily kinesthetic: intuition and control over one’s own body (dancers, athletes, surgeons, craftspeople)
Interpersonal: the ability to understand other people
Intrapersonal: the ability to understand oneself
Naturalist: appreciation and understanding of nature
“Intelligence,” writes Gardner, “is a biopsychological potential.” It’s not an entity, but a living thing. (Gardner, Intelligence Reframed, p 34.)
Or, as Alfred Binet said in 1909: “With practice, training, and above all method, we manage to increase our attention, our memory, our judgment, and literally to become more intelligent than we were before.” (Binet, Les idées modernes sur les enfants, pp. 105–6; this work has been reprinted in Elliot and Dweck, eds., Handbook of Competence and Motivation; see p. 124.)
“high academic achievers are not necessarily born ‘smarter’”: Csikszentmihályi, Rathunde, and Whalen, Talented Teenagers, p. 6.
How will that child measure up tomorrow?
“One moves along the continuum,” says Sternberg, “as one acquires a broader range of skills, a deeper level of the skills one already has, and increased efficiency in the utilization of these skills.”
Sternberg recalibrated it, in other words, from a thing to a process. The word “intelligence,” he realized, is only a crude symbol for a snapshot of the process in motion. Like any still photograph, it can capture some truth, but it fundamentally misses the ongoing procedure, which is driven, explains Sternberg, by five key elements: metacognitive skills (control of one’s own cognition), learning skills, thinking skills, knowledge, and motivation.
Intelligence is not how good you are at something. It’s how good you are on your way to becoming.
“At the center, driving the elements,” observed Sternberg, “is motivation.” (Sternberg, “Intelligence, Competence, and Expertise.”)