Free The Genius in All of Us: New Insights Into Genetics, Talent, and IQ by David Shenk Page A

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 intelligencetest 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