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The history of intelligence

New spectacles for developmental psychology

James R. Flynn

Clancy Blair

The best-known developmentally based theory of intelligence is that of the Swiss

psychologist Jean Piaget. He had little interest in individual differences. He illuminated

how intelligence developed, in all children, from initial cognitive structures to later ones.

These structures assimilated information and evolved to accommodate new information.

Piagets tests were designed to record the development of intelligence. For example, to

assess whether a child understood that the quantity of something was not altered by

change of shape, water was poured from a shallow beaker to a tall one and the child

asked whether there was more water than before.

The psychometric approach to the study of intelligence did not arise out of

developmental concerns but rather, focused on measuring intelligence differences

between individuals. Charles Spearman was the first to give it a theoretical foundation.

He identified the general factor of intelligence org. Its justification was empirical.

Individual performance across a wide range of cognitive tasks tends to be positively

correlated. Someone superior to the average person in classifying objects will tend to be

superior in identifying the missing piece of a matrix and so forth.

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However, right from the start, the psychometric tradition recognized that the

development of intelligence had a sociological dimension. Every individual is a member

of a group. For example, even within one nation, the social context in which a black

child develops may differ profoundly from that of a white child. It was inevitable that

scholars like Arthur Jensen would study group differences. The group differences of

greatest interest were the general skills to which the label intelligence is usually applied

and the two most important academic skills, namely, reading and mathematics.

We will try to show that writing cognitive history integrates the developmental

and psychometric approaches and therefore, sheds new light on cognitive abilities and

their development. To make our case, we will do seven things: discuss the psychometric

and developmental traditions; summarize the cognitive history of the 20th century in

America; distinguish cognitive history from the science of measuring intelligence;

illustrate how cognitive history can correct mistakes in applied psychology that are

difficult to self-correct; use it to clarify the roles of genes and environment; use it to show

that enhancing intelligence is a life time quest; show how it revolutionizes the task of

accounting for group differences.

The psychometric and developmental traditions

In combination, the psychometric (or differential) and developmental traditions cross-

fertilize and provide valuable information about intelligence. But they begin from very

different starting points and with different sets of assumptions. This is seen most clearly

in the idea that intelligence within the psychometric tradition does not really develop per

se. The emphasis is on the measurement of an underlying individual difference

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characteristic, one that is manifest in a variety of ways at different ages but is for the most

part stable from very early until very late in the lifespan (Deary, 2000).

The psychometric tradition recognizes that performance on the indicators used to

assess intelligence improves from childhood to adulthood, for example, the size and

extent of vocabulary knowledge, an indicator of what is referred to as crystallized

intelligence, and the ability to complete increasingly complex puzzles or patterns, an

indicator of what is referred to as fluid intelligence. But it does not treat this

development as equivalent to enhanced intelligence. Rather it posits a stable underlying

individual difference characteristic (IQ) and therefore, ranks the individuals scores on

tests like vocabulary and analyzing patterns by comparing them to the scores of the same

age individuals in the population from which that individual was drawn. These rankings

(deviation IQ scores) tend to have excellent psychometric properties. They are internally

very coherent, are remarkably similar from one time point to the next, and do about as

good a job as any other available measure in providing information about an individual's

level of competence relative to others, making them highly useful although rarified

indicators of psychological functioning.

This emphasis on stability over time and between-person (inter-individual)

variability in the measurement of intelligence in the psychometric tradition stands in

sharp contrast to an emphasis on change and within-person (intra-individual) variability

in the developmental tradition. In the developmental tradition, the emphasis is on the rate

and extent of change in the various indicators of intelligence, such as vocabulary or

pattern completion, and most importantly on the determinants of change (Ferrer &

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McArdle, 2004). Rates of change relative to group averages and inter-individual variation

are, of course, considered, but the primary interest is in the process of development, in

contexts and experiences and aspects of the individual that affect intelligence.

As a consequence, information about change and determinants of change in

mental abilities in the developmental tradition leads to questions about intelligence that

are essentially distinct from those of the psychometric tradition, which views intelligence

as a fixed entity attributable to a specific cause or causes, such as the ability to process

information quickly (Jensen, 1998) or the size and density of synaptic connections in the

brain (Garlick, 2002). In contrast, the developmental tradition views intelligence as a

malleable entity that is shaped during the course of development. Therefore, findings

from the two approaches to the study of intelligence sometimes seem at odds if not

antagonistic.

New habits of mind

In distinguishing the psychometric and developmental traditions, nothing brings them

into relief quite as clearly as the phenomenon of rising mean IQ. The identification of

population gains across successive cohorts of test takers on measures of fluid

intelligence, with only modest change in crystallized intelligence (at least over the last 60

years) amounts to one of the most surprising and challenging empirical findings of

psychological research in the twentieth century (Flynn, 1987). Until recently, the notion

of a unitary intelligence subject to the glacial pace of brain evolution held sway, with the

corollary that dysgenic reproduction was slowly eroding cognitive potential. Massive IQ

gains over time called this into question. Since the US data is most complete, we will

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make frequent use of it, but most of what we say applies to the West in general

First, the gains have been huge. Since 1947, American children have gained 24

points (SD = 15) on the Similarities subtest of the WISC (Wechsler Intelligence Test for

Children). Estimated gains on Raven's Progressive Matrices, the standard measure of

fluid intelligence, are even greater. Legitimate projections back to 1900, based on birth

dates, put 20th century gains on these two tests at 50 points (Flynn, 2009, p. 23). The

century saw Full Scale IQ gains of at least 30 points. On the other hand, gains were

differential. Excellent data since 1947 show that gains on WISC subtests like

Information, Arithmetic, and Vocabulary have been slight. We now know that society can

make differential progress without facing some kind of psychometric veto from theg

(general intelligence) factor.

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Insert Figure 1 about here

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The following traits allow us to solve problems with cognitive content: mental

acuity, habits of mind, attitudes, knowledge and information, efficiency of information

processing, and working memory. "Habits of mind" may need some explanation. Ten

years ago, one of us began to do crossword puzzles. He now does them much better, but

not because of increased mental acuity or even larger vocabulary or store of information.

The usual proclivity with words is to use them to say something as simply and directly as

possible. Crosswords require that this habit be modified to imagine secondary meanings,

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less literal meanings, reflect whether the clue word was being "used" as a noun or a verb,

and so forth. At first, it was an effort to do all of this. Now it has become automatic -- a

new habit of mind has replaced the old.

The inculcation of habits of mind, of making previously effortful thinking

automatic, makes reference to what are known as dual processing theories in cognitive

psychology. Dual-processing theories define the general hypothesis that there are (at

least) two primary ways in which the mind processes information. The first is relatively

fast, automatic, and effortless and may involve non-conscious information processing to

direct attention and behavior in specific ways. The second is relatively slow, complex,

and effortful and always involves conscious, deliberative processing of information and

direction of attention (Barrett, Tugade, & Engle, 2004; Evans, 2008). The idea that dual

processing theory could help to account for IQ gains is largely untested. But there is a

substantial body of data on the relation of beliefs and biases about thinking to intelligence

test performance (Stanovich & West, 2008; Steele & Aronson, 1995) and on the

malleability and cultural grounding of these beliefs (Nisbett. 2003). This suggests that

changing habits of mind may very well be a factor in population changes in intelligence

test performance.

The pattern of IQ gains

Evolution of our habits of mind since 1900 does much to explain the differential pattern

of IQ gains. Even in 1900, it was an asset to have mental acuity, a good everyday

vocabulary, a reasonable fund of general information, numeracy, and working memory

skills. Therefore, the habits of mind relevant to these were highly developed. However,

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the habits of mind necessary to classify the world using abstract categories (Similarities)

and to use logic to note sequences in shapes or anything else abstracted from the concrete

(Raven's) were in their infancy. Certain attitudes had to alter for the habits of mind to

alter. People had to supplement their desire to manipulate concrete reality with a concern

for classifying the world. They had to begin to take the hypothetical seriously to become

practiced in using logic as a tool detached from the concrete. In a word, they had to put

on scientific spectacles.

Take a typical similarities item, "what do dogs and rabbits have in common?" A

child in 1900, with a utilitarian attitude to the world, will say that you use dogs to hunt

rabbits. A child in 2000, who accepts that it is of fundamental importance to classify the

world, will give the "right" answer", namely, that they are both mammals. Note this

interview from Luria (1976. P. 82) with a rural Russian in the 1920s:

Fish and crows

Q: What do a fish and a crow have in common?

A: A fish -- it lives in water. A crow flies. If the fish just lays on top of the water, the crow

could peck at it. A crow can eat a fish but a fish can't eat a crow.

Q: Could you use one word for them both?

A: If you call them "animals", that wouldn't be right. A fish isn't an animal and a crow

isn't either. A crow can eat a fish but a fish can't eat a bird. A person can eat a fish but not

a crow.

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Turning to Raven's and the habit of detaching logic from the concrete to deal with

the hypothetical, Luria (1976, p.112) shows how uncongenial this once was:

Camels and Germany

Q: There are no camels in Germany; the city of B is in Germany; are there camels there

or not?

A: I don't know, I have never seen German villages. If B is a large city, there should be

camels there.

Q: But what if there aren't any in all of Germany?

A: If B is a village, there is probably no room for camels.

It may be that the attitudes and habits of mind relevant to WISC subtests like

Information, Arithmetic, and Vocabulary were much the same in 1900 and 2000 and

therefore, small score gains, at least as far back as we can measure. The attitudes and

habits of mind relevant to WISC Similarities and Raven's show a yawning gap between

1900 and 2000 and therefore, huge gains. If we flesh out our account of recent cognitive

history, it will become clear that this change had important consequences that

transcended the testing room. In addition, the influence of changing habits of mind on

intelligence, particularly aspects of intelligence relating to performance on similarities,

reasoning, and general problem solving types of tasks, gains plausibility from a growing

body of evidence that indicates a sizable gap between the conclusions of the

psychometric and developmental traditions in intelligence research.

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Over the past 100 years, psychometric research has demonstrated time and

again that general fluid reasoning skills are the very foundation of individual differences

in general intelligence. In numerous factor analytic studies, fluid skills have been the

best indicators ofgand tests of fluid abilities have tended to demonstrate higher loadings

on the general factor than have tests assessing primarily crystallized abilities (Jensen,

1998). Indeed, confirmatory factor analyses of relations between fluid cognitive abilities,

variously referred to as working memory, working memory capacity, executive functions,

or cognitive control abilities, have indicated latent variable correlations with the general

factor that are at or near unity (> .95) and that are at the very least in the range of .70(Kane, Hambrick, & Conway, 2005; Ackerman, Beier, & Boyle, 2005).

How fluid aspects of human mental ability could be so central to individual

differences in intelligence on the one hand and show such massive increases over time on

the other is a puzzle. From the psychometric perspective, humankind should either be

experiencing a massive cultural and intellectual flowering or at the very least our not too

distance ancestors should have generally functioned in the low normal range of

intelligence. However, no evidence suggests that either of these holds true and in this,

something fundamental about the nature of human mental ability is revealed.

Liberation of the human mind

The cognitive history of the 20th century is a great romance. Science altered our lives

and then liberated our minds from the concrete. As children of our time, we do not

perceive the gulf that separates us from our distant ancestors: the difference between their

world and the world seen through scientific spectacles. Moreover, because our ability to

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cope with the concrete demands of everyday life has not been much changed, our distant

ancestors appear fully human.

Before 1900, most Americans had a few years of school and then worked long

hours in factories, shops, or agriculture. The only artificial images they saw were

drawings or photographs both of which tended to be representational. Aside from basic

Arithmetic, non-verbal symbols were restricted to musical notation (for an elite) and

playing cards (except for the religious). Their minds were focused on ownership, the

useful, the beneficial, and the harmful. Kinship and church provided identity. Slowly

society began to demand that the mass of people come to terms with the cognitive

demands of secondary education and contrary to the confident predictions of the

privileged, they met that challenge to a large degree. Mass graduation from secondary

school had profound real-world effects. The search for identity became a more individual

quest. Education created a mass clientele for books, plays, and the arts, and culture was

enriched by contributions from those whose talents had hitherto gone undeveloped.

Why such historical changes did not lead to increases in crystallized (or

knowledge-based) rather than fluid (reasoning-based) aspects of intelligence is thought-

provoking. We cannot speak with assurance of the period before 1947 because prior to

the WISC and its subtests, data specific to crystallized intelligence is scant. But the

record since 1947 is clear. The schools children attended were better financed and better

staffed, and we would expect that levels of population ability in mathematics, vocabulary,

and related aspects of knowledge would show distinct upward trends. That this was not

the case might suggest that enhanced schooling had a different influence. It is worth

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considering that the impact of schooling was not necessarily related to increasing a

specific knowledge base, which has been quite stable in populations over time, but rather

to a different sort of influence on trends in mental ability.

After World War II, the emergence of a new visual culture (and perhaps a

resistance to the ever-enhanced demands of classroom subjects) may have inhibited

progress in areas like school mathematics and the interpretation of serious literature. In

contrast, the gains on fluid g have been highly significant. As use of logic and analysis

of the hypothetical moved beyond the concrete, people have become practiced at solving

problems with abstract or visual content and more innovative at solving novel problems.

The scientific ethos provided the prerequisites for this advance. However, once

minds were prepared to attack these new problems, certain social triggers and multipliers

enhanced performance greatly. Post-war affluence meant that people sought cognitive

stimulation from leisure. It meant parents had to rear fewer children and they became pre-

occupied with affording their children a cognitively stimulating environment. Schools

became filled with children and teachers less friendly to rote learning and the world of

work offered more and more professional and managerial jobs. These jobs both required

and stimulated the new habits of mind.

The expanded population of secondary school graduates was a prerequisite for

the chief educational advance of the post-1950 era, that is, the huge increase in the

number of university graduates. These graduates have gone the farthest towards viewing

the world through scientific spectacles. They are more likely to be innovative and

independent and therefore, can meet professional and managerial demands. A greater

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pool of those suited by temperament and therefore inclination to be mathematicians or

theoretical scientists or even philosophers, more contact with people who enjoy playing

with ideas for its own sake, the enhancement of leisure, these things are not to be

despised. And all of this has come about without an upgrading of the human brain

through better genes or environmental factors that have a direct impact on brain

physiology.

The habit of taking hypothetical situations seriously has laid the foundation for

a new level of moral and political debate. Flynn offers an anecdote from his youth:

When I used to argue with my father, who was born in 1885, about race, I would say

"But what if your skin turned black?" His response was, "That is the dumbest thing you

have ever said -- who has ever heard of anyone's skin turning black?" In other words, he

was not in the habit of taking the hypothetical seriously, so the argument could not get off

the ground. Today, even someone with a powerful bias against blacks would accept that

the hypothetical question was one he could not evade. He would see it as a challenge to

show that his views about the treatment of blacks could be made logically consistent.

There is some evidence that members of Congress are less obtuse in debate

today, at least when they give speeches designed for their peers. Thus far, studies have

been limited to debates about women's rights (Rosenau & Fagan, 1997). But we would

anticipate a general trend among opinion leaders toward elementary market analysis of

economic proposals and higher standards of evidence, particularly in regard to medical

claims and claims about the state of public opinion. Someone should do a systematic

analysis of editorials and essays in leading newspapers and periodicals aimed at a mass

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but educated readership.

History and the developmental approach

Our emphasis on the impact of changing social structures and experiences on population

trends in fluid cognitive abilities is highly consistent with the developmental approach to

the study of intelligence. For example, it is well established in research on a number of

aspects of human behavior, not only intelligence but also personality, that social and

historical context and individual experience combine to shape development (Elder, 1996;

Magnusson & Cairns, 1996).

The developmental approach to the study of intelligence has always regarded the

fluid aspects of mental ability as central. Piaget (1952) himself posited hierarchically

organized mental abilities that allow for an increasingly abstract and differentiated view

of the world. (Almost as if the process of mental development in the child was one of

coming to view the world with scientific spectacles.)

In what came to be called the information processing approach to cognitive

development, those who followed in the Piagetian tradition sought to identify specific

cognitive processes that might underlie the emergence of reasoning ability in children. In

doing so, they found support for the theory that the cognitive abilities that underlie fluid

intelligence, namely executive function skills such as working memory and inhibitory

control are important contributors to cognitive development (Case, 1996; Houde &

Tzourio-Mazoye, 2003). Further research has indicated that fluid cognitive abilities,

working memory and inhibitory control included, demonstrate a pronounced change

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across the lifespan, increasing rapidly in childhood and decreasing in old age.

Data on rising mean IQ suggest that just as fluid cognitive abilities develop and

change across childhood, so they have developed in the population as a whole.

Successive generations have become increasingly good at tasks that require the holding

of information in mind in working memory, at resisting distraction from conflicting or

extraneous information, and solving problems and puzzles that require multiple,

sometimes conflicting steps for successful completion.

For the moment, we will postpone the solemn question of whether massive IQ

gains should be called intelligence gains. Massive IQ gains are what they are and do not

become another thing thanks to a particular label. The best shorthand description we can

offer is this. During the 20th century, people developed new habits of mind as they

invested their intelligence in the solution of new cognitive problems. Formal education

played a proximate causal role but a full appreciation of causes involves grasping the

total impact of modern society.

What cognitive history is all about

It is important to be clear about the task of the cognitive historian. Piagetians like

Oesterdiekhoff (2008) have written about the transition from the minds of pre-industrial

peoples and medieval people to the modern mind. Calhoun (1973) tried to estimate to

measure the intelligence of 19th-century Americans on the basis of what various sources

can tell us about what they were expected to know or to be able to learn. Flynn (2009)

attempted something new: to write the cognitive history of a nation in the 20th century

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based on performance trends on IQ tests.

The use of trends on IQ tests as the artifacts of history poses a problem of

communication with psychometricians. The fact that they are accustomed to using IQ

tests as measures of intelligence orgcreates a mindset that is a-historical. Perhaps an

analogy will help.

Imagine an archeologist from the distant future who excavates our civilization

and finds a record of performances over time on measures of marksmanship. The test is

always the same, that is, how many bullets you can put in a target 100 meters away in a

minute. Records from 1865 (the US Civil War) show the best scoring 5 with a median of

3 and a low score of 1. Records from 1898 (Spanish-American War) show 10, 6, and 2,

while records from 1918 (World War I), show 50, 30, and 10.

A group of "marksmanship-metricians" look at this data and find it worthless

for measuring marksmanship. They make two points. First, they distinguish between the

measure and the trait being measured. The mere fact that performance on the test has

risen in terms of "items" correct does not mean that marksmanship ability has increased.

All we know is that the test has gotten easier. Many things might account for that.

Second, they stress that we have only relative and no absolute scales of measurement. We

can rank soldiers against one another at each of the three times. But we have no measure

that would bridge the transition from one shooting instrument to another. How could you

rank the best shot with a rifle against the best shot with a bow and arrow? At this point,

the marksmanship-metrician either gives up or looks for something that would allow him

to his job, perhaps some new data that would afford an absolute measure of

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marksmanship over time.

However, a group of military historians are also present it is at this point they

become excited. They want to know why the test got easier irrespective of whether the

answer aids or undermines the measurement of marksmanship over time. They go to

archeologists for help, and if they are lucky, battlefields specific to each time will be

discovered. The 1865 battlefields will disclose the presence of non-repeating rifles, the

1898 ones of repeating rifles, and the 1918 ones of machine guns. Now we know why it

was easier to get more bullets into the target over time and we can confirm that this was

no measure of enhanced marksmanship. But it was of enormous historical and social

significance: the human costs of battle, the industries needed to arm the troops, and so

forth had altered dramatically.

Any confusion about the two roles has been dispelled. If the battlefields had been

the artifacts first discovered, there would have been no confusion because no one uses

battlefields as instruments for measuring marksmanship. It was the fact that the first

artifacts were also instruments of measurement that put historians and metricians at cross-

purposes. Now they see that different concepts dominate their two spheres: social

evolution in weaponry -- whose significance is that we have become much better at

solving the problem of how to kill people quickly; marksmanship -- whose significance is

who has the ability to kill people more skillfully than other people can. The metrician

would not deny that the historian's account is important. The historian has done nothing

to undermine what the metrician does. Results on his tests have great external validity.

They tell us who is likely to be promoted in each of the three wars (insofar as

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marksmanship is a criterion) and which of two armies equal in other respects is likely to

win a battle (the one with the best marksmen).

When Flynn amassed and assessed a large body of data showing that IQ tests

had gotten much easier over the 20th century, he was playing the role of an archeologist.

The response of intelligence- org-metricians was dual.

First, to distinguish IQ tests as measuring instruments from the trait being

measured, that is, from intelligence org(if you will). Second, to note that in the absence

of an absolute scale of measurement, the mere fact that the tests had got easier told us

nothing about whether the trait was being enhanced. The difficulty was inherent. IQ tests

were only relative scales of measurement ranking the members of a group in terms of

items they found easy to items they found difficult. A radical shift in the ease/difficulty of

items meant all bets were off. At this point, theg-metrician decides that he cannot do his

job of measurement and begins to look for some absolute measure that would allow him

to do so.

However, this is where the cognitve historian begins to get excited: Why had

the items got so much easier over time? Where was the alteration in our mental weaponry

that was analogous to the transition from the rifle to the machine gun?

This meant returning to the role of archeologist and finding battlefields of the

mind that distinguished 1900 from the year 2000. Flynn found evidence of a profound

shift from a merely utilitarian attitude to concrete reality towards assuming it was

important to classify it in terms the more abstract the better; and that the taking of

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hypothetical situations seriously had freed logic from the concrete to deal with not only

hypothetical questions but symbols that had no concrete referents.

The new artifacts came from reading Luria, reading the scoring directions of the

IQ tests, reading Schooler on the correlation between the modern habits of mind and

professional job roles, analysis of change in the temper of political debate in Congress

over the century, and so forth. Another piece of evidence has fallen into place. Genovese

(2002) compared the exams the state of Ohio gave to 14-year old schoolchildren between

1902-1913 and between 1997-1999. The former tested for in-depth knowledge of

culturally valued information; the latter expected only superficial knowledge of such

information and tested for understanding complex relationships between concepts.

Genovese (2002, p. 101) concludes: "These finding suggest that there have been

substantial changes in the cognitive skills valued by Ohio educators over the course of the

20th century."

But it was the initial artifacts that caused all of the trouble. Since they were

performances on IQ tests, and IQ tests are instruments of measurement, the roles of the

cognitive historian and theg-metrician were confused. Finding the causes and developing

the implications of a shift in habits of mind over time is simply not equivalent to a task of

measurement, even the measurement of intelligence. And just as theg-metrician should

not underestimate the non-measurement task of the historian, so the historian does

nothing to devalue the measurement of which individuals are most likely to learn fastest

and best when in competition with one another.

If one person has a general cognitive advantage over another, he or she will

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enjoy real-world benefits. No historical narrative can liquidate the evidence that showsg-

loaded tests have predictive validity in the realm of individual differences. Only evidence

that other measures are better predictors can challenge them (Sternberg, 2006). If the

individuals who make up one group have an IQ advantage over those of another, and all

compete in the same job market, they will have a higher occupational profile. Lynn and

Vanhanan (2002) have shown that if the people of one nation have a higher mean IQ than

those of another, that nation is likely to be more prosperous and more highly

industrialized.

In passing, they have not shown that developing nations are doomed to

permanent inferiority. There are signs that IQ gains may cease in developed nations in the

21st century but may take off in the developing world (Daley et al., 2003; Meisenberg et

al., 2005; Schneider, 2006). This would eliminate the IQ gap that separates those two

worlds and refute those who see the lower IQs of developing nations as a largely fixed

cause of lack of economic progress. It would show that industrialization and IQ rise in

tandem and boost one another in a cycle of reciprocal causation. We suspect that a

nation's degree of modernity determines both its mean IQ and economic maturity (Flynn,

2009, pp. 143 -144). Hopes for the next century assume, of course, that problems of food

supply, water supply, energy supply, and climate do starve the poor and debase the rich.

An item that got easier

As to how new habits of mind (the cognitive machine guns) explain why the IQ tests got

easier over time, take the item about what dogs and rabbits have in common. In 1900, for

a schoolchild for whom utility rather than classification was a natural response, getting

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the right answer required great ingenuity. Something like: "Mainly we use dogs to hunt

rabbits, but that is more what we do with them rather than what they have in common.

They certainly don't look much alike but they are both rather furry. However, they must

want something more important than how they feel. Perhaps it is what our teacher was

talking about last year when she told us that mammals were different from reptiles

because they are warm-blooded. I will take a chance and say that they are both

mammals."

In 2000, for schoolchildren for whom classification is an established habit of

mind, "both are mammals" will be an almost automatic response and will come not only

from the brightest child but also from the average child. The item has lost most of its

cognitive complexity and suffered a loss ingloading and has become much easier. And

theg-metrician is correct: the fact that the item is easier tells us nothing about whether

children in 2000 were brighter than children in 1900. The absence of an absolute scale is

fatal. But merely because the artifacts have lost measurement value hardly means they

have no historical value.

The fact that the item had got easier from 1900 and 2000 does not mean that it

was inappropriate, as part of a measuring instrument, at either time. In 1900, it would

draw a line between the best and the rest; in 2000, it would draw a line between the

average and the below average (those who despite living in a scientific age, did not see

the importance of the difference between mammals and reptiles). So it would

discriminate at both times, just at different levels of difficulty on the scale.

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Digging deep

The most important lesson this example teaches is this: when the cognitive historian

looks for new artifacts, it is important to dig deep. Let us go back to the discovery of

marksmanship tests that show that shooters put more bullets into the target from one time

to another. Some might say that enhanced nutrition over time had produced better eyes;

others might say that better training must have enhanced skills. But whatever the

plausibility of these hypotheses, they offer nothing specific as to just why the best

shooters went from putting 5 to 10 to 50 bullets in the target. We would not have a full

and fecund causal chain until we discovered the rifles and the machine guns.

Similarly, those who debate whether nutrition or schooling or both explain

massive gains on Raven's and Similarities are not digging deep enough. Better nutrition

may produce better brains and better schooling better educated people. But neither brains

nor some abstraction called "better schooled" take IQ tests. Minds take IQ tests. Until

we have found just what new weaponry minds got that made the items so much easier, we

do not have a full and fecund causal chain. Quite possibly people could not have

developed news habits of thought without formal schooling. It is likely that over the first

half of the century better-nourished children got more out of school. But just what did

they get? Thinking through the specific items of IQ tests focuses us on that question. A

cognitive historian of the 20th century who was ignorant of the IQ data would be likely to

miss something. For example, they might miss our new habit of taking the hypothetical

seriously and therefore, might not look for enhanced moral debate.

Currently, Must, te Nijenhuis, and Must (under review) are beginning to dig

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into the minds of Estonian children. Trends on a variety of subtests from 1933-1936 to

2006 suggest that today's children are less adept at arithmetical calculations but much the

same for arithmetical reasoning, that their fund of general information shows a radical

shift from a rural to urban ethos, and that computer games have made them more at home

with symbol-number relations. The most interesting hypothesis is that the scoring

protocol for perceiving similarities and differences between concepts was appropriate for

children in the 1930s but is no longer so. Contemporary children offer reasons for

regarding more than one answer as correct and test administrators consider these reasons

valid. The authors note that the meaning of words may have become more ambiguousover time. However, we believe it shows more acute logical analysis of concepts, another

sign of the trend towards a wider scope for logic.

Jelte Wicherts (2008) notes that Dutch adults had unusually large gains on two

subtests of the WAIS (Wechsler Adult Intelligence Scale), namely, Similarities and

Comprehension. By way of explanation, he dons the cap of a cognitive historian. He

notes that these two subtests are unique in that if subjects talk a lot, the scorer is more

likely to conclude that they have hit on the correct answer. He speculates that these gains

signal an important change in the Dutch character over time. The older generation lacked

the self-confidence to say much unless they were certain of their ground, while the new

generation feel free to cast about for a good answer. Here is a hypothesis with wide

ramifications for Dutch social historians to examine.

Wicherts, like Must, has begun to dig deeper by asking historical questions in

conjunction with a functional analysis of just what you have to do to get more items

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correct. His speculation does not apply very well to American gains. There gains on

Similarities have been over double those on Comprehension, so something extra has been

at work (Flynn, 2009, pp. 8 & 180). Only gains on Raven's rival those on Similarities

and, of course, talking does not affect Raven's performance. But his historical/functional

approach is identical to our own. Faced with huge gains on both of these tests, we

hypothesize that the common factor is a historical one. Those who have absorbed the

scientific ethos the most will do better on both tests. However, we also argue that a

functional analysis reveals that what must done to score well on the two tests differs.

Someone must find it natural to classify to do well on Similarities, while someone musthabitually take the hypothetical seriously to do well on Raven's (Flynn, 2009, pp. 34-35).

Our account of cognitive history shows that the mere fact that IQ tests have

become easier over time does not show that intelligence has increased. Once we

understand why they have become easier, we cannot make some kind of absolute

judgment. Recall the fact that in 1865, only a wonderful marksman could hit a target 5

times in a minute and that in 1918, practically anyone could. One had a machinegun and

the other did not. The issue of whether IQ gains are intelligence gains has been drained of

significance. It has become a matter of definition. If we define intelligence as better

shooting skills, almost certainly not. If we define intelligence as having a mental tool

kit that allows us to address a wider range of cognitive problems, yes. But now that we

know what happened, the label "intelligence" adds nothing to what we know.

The tension between cognitive history and pychometrics is a misunderstanding

that arises from historical accident. As young scholars replace old warriors, peaceful co-

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existence will become an axiom remarkable only because once it was not self-evident to

all.

Structure and function

The developmental tradition in intelligence research offers scientific explanations of

either personal or social change. The well-known structure-function problem in

evolutionary biology provides a straightforward way to characterize the distinction

between the developmental and psychometric traditions. That problem is created by the

difficulty of determining the extent to which the structure of a given system (an

appendage, a sensory organ, etc.) gives rise to its function versus the extent to which the

function of that system gives rise to its structure.

After defining the structure of intelligence, the psychometric tradition draws

conclusions about its function, as an individual differences construct. That is, the

psychometric tradition identifies a core set of cognitive abilities and demonstrates that

these abilities can be grouped in a set of second order abilities that can be further grouped

or subsumed under general cognitive ability org(Carroll, 1993). Given evidence for this

structure of intelligence, the psychometric tradition posits that knowledge ofgis essential

for understanding the function of intelligence, i.e., the relation of intelligence to various

life outcomes.

In contrast, the developmental tradition emphasizes the various mental abilities

of which intelligence is composed. It raises the possibility that the structure of

intelligence may follow from rather than precede function. Here, the emphasis is on

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specific cognitive abilities and influences on these abilities, which then influence the

development of intelligence (Piaget, 1952). In the developmental tradition, questions

about intelligence are best addressed by focusing on the process of development. It is by

understanding how intelligence develops, that practical conclusions about it and about its

relation to specific life outcomes can be reached. Here the concern is with the various

mental abilities that are required for competence, in school or in the workplace, etc., and

ways that they can best be fostered and developed.

Consideration of the relation between structure and function in intelligence

research provides a way around the seeming impasse of rising mean fluid IQ. For the

psychometric tradition with its emphasis on structure, the phenomenon is artifact, plain

and simple: the fact it has occurred in no way changes the structure of intelligence at a

given point in time. And it does not obviate the fact that within a group of individuals at

any given time point, those with high IQ are better at solving fluid cognitive tasks, such

as Raven's problems, than are people with low or average IQ. Nor does it change that

fact that performance on fluid cognitive tests, such as Raven's, loads more highly on the

general factor of intelligence than do other types of cognitive tests.

However, for the developmental tradition, the phenomenon of rising mean fluid

IQ is a substantive and affirmative empirical finding. It indicates, along with a

considerable body of evidence from neuropsychological and clinical research, that fluid

cognitive abilities are clearly distinguishable from other aspects of mental ability (Blair,

2006). And in doing so, it suggests that the close relation between fluid abilities and

general intelligence is to some extent artifact itself. It suggests that the function of fluid

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abilities, in abstracting and conceptualizing information, in resisting distracting or

extraneous information, etc., may give rise to a structure of general intelligence that

appears to be more hierarchical and necessary than it really is.

At its extreme, the phenomenon of rising mean fluid IQ identifies fluid

intelligence as a malleable entity that broadly influences human behavior. However, the

fact of radically higher levels of population fluid IQ over time raises very important

questions as to what are the discernable net impacts of these changes on culture and

society? Clearly, the gains are not gains ingand fluid cognitive abilities are not identical

to the general factor. They may, however, be of strong interest in their own right. We

will sketch their implications for education, for the role of genes in mental ability and

cognitive development, and for explaining group differences in IQ.

Second guessing the educators

One of the goals of developmental psychology has been to equalize educational

opportunity by promoting the ability of children to succeed in school. Here

psychometrics may have led developmental psychologists astray in a way that cognitive

history can correct. Recent innovations in teaching mathematics illustrate a misguided

application of psychometric understanding of the structure of mental abilities to a

practical problem. The rationale behind the mistake: reasoning skills are needed for

mathematical problem solving; reasoning skills and mathematical problem solving are

linked through the general factor of intelligence: therefore, increases in reasoning skills

should lead to increases in mathematics ability.

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As for the reasoning skills that were most relevant, educators turned to factor

analysis. It shows that performance on Raven's is highly correlated with performance on

the Arithmetic subtest of the WISC. Moreover, the relevance of Ravens skills has an

intuitive appeal. Raven's demands that you think out problems on the spot without a

previously learned method for doing so; and Mathematics requires mastering new proofs

dealing with non-verbal material. The two appear to require similar cognitive skills,

which suggested that we should teach young children Raven's-type problems in the hope

that they will become better mathematics problem solvers. It is not surprising that U.S.

schools have been introducingreasoning-based activities in mathematics instruction eversince the launching of Sputnik created a crisis of confidencein U.S. education (Blair,

Gamson, Thorne, & Baker, 2005).

IQ gains over time anticipated the educators by accomplishing what they hoped

to achieve: huge gains on Raven's Progressive Matrices. And these gains occurred during

a period in which gains on Arithmetic were virtually nil. If gains on the one have no

effect on the other, the relationship between the two can hardly be functional. Sadly, our

understanding of the functional process for learning Arithmetic is rudimentary. Some

speculation: except for mathematicians who link the formulae with proofs, mathematics

is less a logical enterprise than a separate reality with its own laws that are at variance

with those of the natural world. Therefore just as infants explore the natural world,

children must explore the world of mathematics themselves and become familiar with its

"objects" by self-discovery.

Michael Shayer is breaking new ground using teaching techniques based on

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self-discovery within small groups. In addition, he may have found cognitive skills that

have genuine functional links to arithmetical reasoning. In Britain from 1975 to 2003,

performance among schoolchildren on the Piagetian tasks of conceptualizing Volume and

Heaviness declined by 0.8 SDs. Flynn (in preparation) has analyzed British WISC data

covering the latter half of that period. From 1990 to 2003, British children lost 0.4 SDs

on the WISC Arithmetic subtest. The rates of loss are of course identical (Shayer &

Adhami, 2003: Shayer & Adhami, in press; Shayer, Ginsberg, & Coe, in press).

In America, despite time wasted on Raven's, it may seem that the schools are

doing something right. The National Association of Educational Progress (NAEP) tests

are called the nation's report card. They are administered to large representative samples

of 4th, 8th, and 12 graders. From 1973 to 2000, the Nation's Report Card shows 4th and

8th graders making mathematics gains equivalent to almost 7 IQ points. These put the

young children of today at the 68th percentile of their parents' generation. However, the

gain falls off at the 12th grade to nothing (U.S. Department of Education, 2000, pp. 54 &

60-61; 2001, p. 24). And trends over time on a WISC subtest suggest why.

The Arithmetic subtest and the NAEP mathematics tests present a composite

picture. An increasing percentage of young children have been mastering the

computational skills the Nation's Report Card emphasizes at those ages. However, WISC

Arithmetic measures both computational skills and something extra. The questions are

put verbally and often in a context that requires more than a times-table-type answer. For

example, take an item like: 'if 4 toys cost 6 dollars, how much do 7 cost?' Many subjects

who can do straight paper calculations cannot diagnose the two operations required: that

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you must first divide and then multiply. Others cannot do mental arithmetic involving

fractions. In other words, WISC Arithmetic also tests for the kind of mind that is likely

to be able to reason mathematically.

As Table 1 shows, between 1972 and 2002, American children gained almost

nothing on WISC Arithmetic. This suggests that although they were mastering

calculating skills at an earlier age, they made no progress in acquiring mathematical

reasoning skills. Mathematical reasoning skills are essential for higher mathematics.

Therefore, by the 12th grade, as the NAEP data show, the failure to develop enhanced

mathematical problem-solving strategies begins to bite. American schoolchildren cannot

do Algebra and Geometry any better than the previous generation. Although the previous

generation was slower to master computational skills, they were no worse off at

graduation.

------------------------------

Insert Table 1 about here

------------------------------

Table 1 also shows that Information and Vocabulary resemble Arithmetic as

subtests on which IQ gains have been minimal. General information and everyday

vocabulary are what we use when we read. The Nation's Report Card shows that from

1971 to 2002, 4th and 8th graders (average age 11 years old) made a reading gain

equivalent to almost 4 IQ points. However, once again, by the 12th grade, the reading

gain drops off to almost nothing (U.S. Department of Education, 2000, pp. 104 & 110;

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2003, p. 21).

The IQ data suggest an interesting possibility. For the sake of comparability, we

will focus on WISC trends from 1972 to 2002, rather than on the full period beginning in

1947. Between 1972 and 2002, U.S. schoolchildren made no gain in their store of

general information and only minimal vocabulary gains. Therefore, while today's

children may learn to master pre-adult literature at a younger age, they are no better

prepared for reading more demanding adult literature. You cannot enjoy War and Peace

if you have to run to the dictionary or encyclopedia every other paragraph.

Take a poem by Browning:

Over the Kremlins pavement bright

With serpentine and syenite

Step five generals

That simultaneously take snuff,

For each to have pretext enough

And kerchiefwise unfold his sash

Which, softness' self, is yet the stuff

To hold fast where a steel chain snaps,

And leave the grand white neck no gash

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If you do not know what the Kremlin is, or what "serpentine" means, or that

taking snuff involves using a snuff rag, you will hardly realize that these generals caught

the Czar unaware and strangled him.

In other words, today's schoolchildren opened up an early lead on their

grandparents by learning the mechanics of reading at an earlier age. But by age 17, they

were no more advanced than their grandparents were by that age. And since current

students are no better than their grandparents in terms of vocabulary and general

information, the two generations at 17 are dead equal in their ability to read the adult

literature expected of a senior in high school.

Educational practice

One of the educational implications of the finding of rising mean fluid IQ is the need to

educate broadly and integratively. There are no short cuts to increasing expertise in math

and reading. Children must gain expertise in both the knowledge based aspects of each

subject (e.g., the meaning of serpentine, the times tables) and the reasoning skills that are

embedded in this knowledge, the skills that make use of it for problem solving and

reasoning in the application of previously acquired knowledge to the acquisition of new

knowledge. For emphasis: genuine learning entails the acquisition of both knowledge

and reasoning ability. Time and again developmental psychologists and educators have

been drawn to polarized positions at one end or the other of the reasoning-knowledge

continuum.

On the reasoning end of the spectrum, psychologists have made numerous

attempts to raise IQ, both as a means to equalize educational opportunity and eliminate

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disparities imposed by social class (Ramey & Campbell, 1991). The goal is worthy and

one essential to social, political and economic wellbeing. However, the efficacy of the

means chosen, i.e., increases in IQ, seems to be in doubt. There have been substantial

positive long-term effects on educational achievement and attainment as well as a number

of indicators of social and psychological competence (Campbell, Pungello, Miller-

Johnson, Burchinal, & Ramey, 2001; Reynolds, Temple, Robertson, & Mann, 2001).

And yet, initial IQ gains begin to decline shortly after programs end. Clearly the

programs changed something for recipients, but very likely this something had less to do

with enhanced general cognitive ability than with enhanced abilities to manage one'sbehavior, to exhibit self-control, and self-regulation (Heckman, 2006, 2007).

At the knowledge end of the spectrum, the temptation to believe that a relatively

narrow training of cognitive skills will confer broad psychological benefits remains a

siren song for psychologists and the general public alike. A recent example is instructive.

In a training study in which participants were randomly assigned to undergo repeated

training on a fluid cognitive working memory task over many days or to a control

condition, the training was shown to increase performance on Ravens, used as a measure

of fluid intelligence (Jaeggi, Buschkuelh, Jonides, & Perrig, 2008).

In the absence of any indication of the extent to which the training and its related

increase in intelligence test performance generalized beyond the testing environment,

however, no actual increase in intelligence can be assumed to have occurred. In the

absence of such evidence, it seems more likely that what occurred was a micro-genetic

version of the phenomenon of rising mean fluid IQ over time. That is, there was a change

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in specific cognitive abilities important for intelligence test performance without

immediately apparent broad implications for general cognitive abilities and everyday

functioning.

IQ gains over time did, of course, signal something that affected everyday life,

namely, new habits of mind. But this was specific to their cause: they were the result of

a profound evolution that affected the whole of society as the scientific ethos and

scientific technology slowly came to dominate. When IQ gains are the result of some

sort of narrowly focused mental exercise, the skills learned lack social context and are

unlikely to signal a significant cognitive event.

Genes and environment

The solution to one of the most baffling problems posed by IQ gains over time has a

direct input into cognitive psychology because it helps to clarify the relation between

genes and environment. Many TV documentaries tell about identical twins both of

whom, despite being separated at birth, have had amazingly similar life experiences and

grow up to have similar IQs. These studies are sometimes interpreted as showing that

genetic influences on IQ are potent and environmental influences feeble. Studies of

identical twins raised apart are only one component of a wide variety of kinship studies.

There have been comparisons of identical and fraternal twins each brought up by their

own parents, comparisons of adopted children with natural children, and so forth.

Jensen (1998) concludes that while environment may have some potency at

earlier ages, IQ differences between adults are overwhelmingly determined by genetic

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differences. Others have disputed this on evidential grounds arguing that differences

between rearing environments account for a substantial variance in intelligence in

adulthood (Brooks-Gunn & Duncan, 1997; Sameroff, Seifer, Baldwin, & Baldwin, 1993).

But let us assume that Jensen eventually wins the evidential argument. Would this show

that environmental factors simply lack potency?

In the light of trends over time, how could that be possible? As we have seen,

there are massive IQ differences between the generations and these manifest themselves

at all ages. No one has been selectively breeding human beings for high IQ, so it looks as

if genetic differences between the generations would be trivial. If that is so,

environmental factors must cause IQ gains over time and given the size of those gains,

those environmental factors must have enormous potency.

Jensen (1973a, 1973b) made the paradox all the more acute by using a

mathematical model. He plugged in two pieces of data: a 15-point IQ difference between

two groups; and a low estimate of the influence of environment on IQ (a correlation

between environment and IQ of about 0.33). These implied that for environment to

explain the IQ gap between those groups, the environmental gap between them would

have to be immense. One group would have to have an average environment so bad as to

be worse than 99% of the environments among the other group. Just to sharpen the

paradox, Dutch males of 1982 were 20 IQ points above the previous generation on

Ravens. According to Jensen's mathematics, the average environment of the previous

generation would have to be worse than 99.99% of the 1982 environments. How could

anyone make a case for something apparently so implausible?

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Lewontin (1976a, 1976b) tried to solve the paradox. He distinguished the role

of genes within groups from the role of genes between groups. He imagined a sack of

seed corn with plenty of genetic variation randomly divided into two batches, each of

which would therefore be equal for overall genetic quality. Batch A is grown in a

uniform and optimal environment, so within that group all height differences at maturity

are due to genetic variation; batch B is grown in a uniform environment which lacks

enough nitrates, so within that group all height differences are also genetic. However, the

difference in average height between the two groups will, of course, be due entirely to the

unequal quality of their two environments.

So now we seemed to have a solution. The present generation has some potent

environmental advantage absent from the last generation that explains its higher average

IQ. Let us call it Factor X. Factor X will simply not register in twin studies. After all, the

two members of a twin pair are by definition of the same generation. Since Factor X was

completely missing within the last generation, no one benefited from it at all and

therefore, it can hardly explain any IQ differences within the last generation. It will not

dilute the dominance of genes. Since Factor X is completely uniform within the present

generation, everyone benefits from it to the same degree and it cannot explain IQ

differences within the present generation. Once again, the dominance of genes will be

unchallenged. Therefore, twin studies could show that genes explain 100% of IQ

differences within generations and yet, environment might explain 100% of the average

IQ difference between generations.

However, Lewontin offers us a poisoned apple. History has not experimented

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with the last two generations as we might experiment with plants in a laboratory.

Consider the kind of factors that might explain massive IQ gains, such as better nutrition,

more education, more liberal parenting, and the slow spread of the scientific ethos. It is

quite unreal to imagine any of these affecting two generations with uniformity. Certainly,

everyone was not badly nourished in the last generation, everyone well nourished at

present; everyone without secondary school in the last generation, everyone a graduate at

present; everyone raised traditionally in the last generation, everyone raised liberally at

present; everyone bereft of the scientific ethos in the last generation, everyone permeated

with it at present. If the only solution to our paradox is to posit a Factor X or a collectionof such, it seems even more baffling than before. We should shut this particular door as

follows: A solution is plausible only if it does not posit a Factor X.

Eight years ago, William Dickens of the Brookings Institution, decided to do

some modeling of his own with help from Flynn in applying it to real-world situations

(Dickens & Flynn, 2001a; 2001b). We believe that it solves the identical twins paradox

without positing a Factor X. It makes an assumption that may seem commonplace but

which has profound implications, namely: that those who have an advantage for a

particular trait will become matched with superior environments for that trait.

Recall studies of identical twins separated at birth and reared by different

families. When they grow up, they are very similar and this is supposed to be due solely

to the fact that they have identical genes. But for that to be true, they must not be

atypically similar in environment, indeed, the assumption is that they have no more

environment in common than randomly selected individuals (see Gottlieb, 1998). To

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show how unlikely this is, let us look at the life history of a pair of identical twins.

John and Joe are separated at birth. Both live in an area (a place like the state

of Indiana) that is basketball-mad. Their identical genes make them both taller and

quicker than average to the same degree. John goes to school in one city, plays basketball

a bit better on the playground, enjoys it more, practices more than most, catches the eye

of the grade-school coach, plays on a team, goes on to play in high school where he gets

really professional coaching. Joe goes to school in a city a hundred miles away.

However, precisely because his genes are identical to John's, precisely because his is

taller and quicker than average to exactly the same degree, he is likely to have a very

similar life history. After all, this is an area in which no talent for basketball is likely to

go unnoticed.

On the other hand, Mark and Allen have identical genes that make them both a

bit shorter and stodgier than average. They too are separated and go to different schools.

However, they too have similar basketball life histories except in their case, both play

very little, develop few skills, and become mainly spectators.

In other words, genetic advantages that may have been quite modest at birth

have a huge effect on eventual basketball skills by getting matched with better

environments -- and genes thereby get credit for the potency of powerful environmental

factors, such as more practice, team play, professional coaching. It is not difficult to

apply the analogy to IQ. One child is born with a slightly better brain than another.

Which of them will tend to like school, be encouraged, start haunting the library, get into

top stream classes, and attend university? And if that child has a separated identical twin

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that has much the same academic history, what will account for their similar adult IQs?

Not identical genes alone -- the ability of those identical genes to co-opt environments of

similar quality will be the missing piece of the puzzle.

Note that genes have profited from seizing control of a powerful instrument that

multiplies causal potency, namely, feedback loops that operate between performance and

its environment. A gene-caused performance advantage causes a more-homework-done

environment; the latter magnifies the academic performance advantage, which upgrades

the environment further by entry into a top stream; which magnifies the performance

advantage once again; which gets access to a good university environment. Since these

feedback loops so much influence the fate of individuals throughout their life histories,

the Dickens/Flynn model calls them "individual multipliers".

Understanding how genes gain dominance over environment in kinship studies

provides the key to how environment emerges with huge potency between generations.

There must be persistent environmental factors that bridge the generations; and those

factors must seize control of a powerful instrument that multiplies their causal potency.

The industrial revolution has persisted for 200 years and it affects every aspect

of our lives. For example, look at what the industrial revolution did to basketball by the

invention of TV. It gave basketball a mass audience and it increased the pay a

professional player could expect. Basketball also had the advantage that ghetto blacks

without access to playing fields could play it on a small concrete court with a minimum

of equipment. Wider and keener participation raised the general skill level, you had to

shoot more and more accurately to excel. That higher average performance fed back into

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play: Those who learned to shoot with either hand became the best -- and then they

became the norm -- which meant you had to be able to pass with either hand to excel --

and then that became the norm -- and so forth. Every escalation of the average

population performance raised individual performance, which escalated the average

performance further, and you get a huge escalation of basketball skills in a single

generation.

The advent of TV set into motion a new set of feedback loops that

revolutionized the game. To distinguish these society-driven feedback loops from those

gene-driven feedback loops that favor one individual over another, Dickens and Flynn

call them "the social multiplier". Its essence is that rising average performance becomes

a potent causal factor in its own right. The concept applies equally well to IQ gains over

time.

The industrial revolution is both the child of the scientific revolution and the

parent of the spread of the scientific world-view. It has changed every aspect of our lives.

It demands and rewards additional years of education. When a grade-school education

became the norm, everyone with middle-class aspirations wanted a high-school diploma.

When their efforts made a high-school diploma the norm, everyone began to want a B.A.

Economic progress creates new expectations about parents stimulating children, highly

paid professional jobs in which we are expected to think for ourselves, more cognitively

demanding leisure activities. No one wants to seem deficient as a parent, unsuited for

promotion, boring as a companion. Everyone responds to the new milieu by enhancing

their performance, which pushes the average higher, so they respond to that new average,

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which pushes the average higher still. You get a huge escalation of cognitive skills in a

single generation.

So now, everything is clear. Within a generation, genes drive feedback

processes, namely, the individual multiplier. Genetic differences are matched to

environmental differences and magnify IQ differences between individuals. Between

generations, environmental trends drive feedback processes -- environment uses social

multipliers to raise the average IQ over time. Twin studies, despite their evidence for

feeble environmental factors, and IQ trends over time, despite their revelation of potent

environmental factors, present no paradox. What dominates depends on what seizes

control of powerful multipliers. Without the concept of multipliers, all is confusion.

There is nothing more certain than this. If twin studies of basketball were done, they

would show the separated twins growing up with very similar skills. And Jensen's

mathematics would "show" that environment was far too weak to cause massive gains in

basketball performance over time. Which is to say we would demonstrate the

impossibility of what we know to be true.

Best of all, our solution posits no Factor X. Nothing said assumes that social

changes from one time to another were uniform in their impact on individuals. Better

education, better parent-child relationships, better work, better leisure, all may raise the

quality of the range of environments available from one generation to another. But the

magnitude of the differences between the quality of various environments from best to

worse can remain the same. Genetic differences between individuals can continue to

match people with better or worse environments to the same degree they always did.

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Even though slam dunks and passing behind the back become common, being tall and

quick will still co-opt a better basketball environment. Even though people in general get

better at solving intellectually demanding problems, being born with a bit better brain

will still co-opt a better than average school environment. In a word, the operation of

social multipliers over time does not abolish the operation of individual multipliers in the

life histories of individuals.

As we shall see, the concept of multipliers raises important questions about the

ways in which they can, and perhaps should be, established or manipulated to increase

opportunities and equalize outcomes across the range of socioeconomic classes.

The matching of individual differences between genes with individual

differences between environments is consistent with a scientifically informed

understanding of how genes and environments act in combination to influence behavior.

Evidence has been accumulating for some time that genes and environments cannot be

neatly parceled into components of variance but jointly and interactively determine

developmental outcomes (Wahlsten & Gottlieb, 1997; Meaney & Szfe, 2005). However,

only recently has any factual understanding of gene activity emerged in scientific

theorizing about the role of genes in complex psychological traits (Meaney, 2001;

Wahlsten, 1999).

Brains and muscles

The implications of the Dickens/Flynn model provide an answer to the question that

dominates the mind of parents and every developmental psychologist who tries to come

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to their aid. How can we enhance the intelligence and IQs of our children? The quick

answer is that a child must have good luck or becomes the sort of person who makes his

or her own luck. This advice rests on two pillars: the plasticity of our brains; and the

nature of the effects of environment.

Our brains are much more like our muscles than we once believed. The brain does

not stop developing in youth but shows a protracted developmental course of progressive

gray and white matter increase and decline throughout the lifespan (Toga, Thompson, &

Sowell, 2006). It is well established that physical health and regular mental stimulation,

well-educated companions, etc., protect against the typical cognitive declines (Schaie).

Cognitively complex activities give some protection even against dementia and

Alzheimer's (Andel et al., 2005). Richard Wetherill played chess in retirement and could

think 8 moves ahead. In 2001, he was alarmed because he could only think 4 moves

ahead and took a battery of tests designed to spot early dementia. He passed them all

easily and continued an active mental life until his death in 2003. Autopsy showed that

his brain was riddled with the plaques and tangles that are characteristic of Alzheimer's.

Most people would have been reduced to a state of total confusion (Melton, 2005).

Cognitive exercise benefits all ages and the benefit accrues even if the exercise

regime is postponed until later life. But we do not wish to raise false hopes. Wetherill's

high level of cognitive exercise did not keep his cognitive abilities from declining with

age and declines in fluid cognitive abilities are the norm. In contrast, crystallized aspects

of mental ability show relative stability well into old age (Schaie, 1994). Possible

reasons for the decline of fluid but not crystallized abilities are varied. However, one of

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the primary reasons appears to be a decline in the speed at which individuals process

information (Salthouse, 1996; 2006).

Different areas of the brain are surprisingly independent. Damage to the brain is

often localized in its effects. Trauma to prefontal cortex vetoes a normal level of on-the-

spot problem solving ability, but other undamaged areas allow normal levels of other

cognitive abilities (Blair, 2006).

Just as you can develop the muscles of a swimmer or a runner, you can improve

spatial ability without improving verbal ability and memory without improving your

mental agility. London taxi-drivers, a least those who are both expert and experienced,

have brains that are peculiar. They have an enlarged hippocampus, which is the area used

for navigating three-dimensional space (Maguire et al., 2000). To develop a wide variety

of cognitive skills you need a wide variety of exercise. It will be interesting when

someone assesses the effects of Kawashima's brain training regime. A variety of mini-

games include solving simple math problems, counting people going in and out of a

house, drawing pictures on the Nintendo DS touch screen, and reading classical literature

aloud into a microphone (Kawashima & Matsuyama, 2005).

The Dickens/Flynn model does not deny that certain environmental experiences

for example, brain trauma or chronic neglect in early childhood have a long-term effect

on intelligence The association between socioeconomic status and intelligence, as

mediated by a host of risk factors is well established (Brooks-Gunn & Duncan, 1997;

McLoyd, 1998; Sameroff, Seifer, Baldwin, & Baldwin, 1993).

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Genes and fate

Nothing we have said re-imposes the sterile concept of nature versus nurture. Neither

genes nor environment determine ones fate, rather causal interaction between the two

affects individual development. Nothing we have said implies that IQ is the sole or

dominant trait in individual development. A wide range of scholars have shown that non-

cognitive traits, such as persistence and self-control, are at least as potent in predicting

social outcomes (Duckworth & Seligman, 2005; Heckman & Rubenstein, 2001;

Heckman, Stixrud, & Urzua, 2006).

In other words, the fate of an individual is not written in his or her genes, not even

as far as IQ is concerned You may have a genotype such that if all members of your

society lived their lives in a cognitive environment of average quality, you would have an

IQ of 100. But interventions that enhance your environment may favor you. Setting

aside experimental interventions, every person experiences natural interventions

throughout life. You and your sibling will not have identical genotypes and we will

assume that yours is inferior. Despite this, most parents try to give all their children a

good pre-school environment and you may internalize self-control to a greater degree

than the average person. Note that even experimental intervention like Head Start had

persistent non-cognitive effects even if their effects on IQ proved transitory. You may

even internalize a delight in accepting and seeking out cognitive challenges that is well

above average.

Schooling and university education are later natural interventions that give you

second chances, that is, both give all those you experience them a more equal chance at

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an enriched environment than they would otherwise get. An inspiring teacher at either,

or being exposed to a subject that delights, may instill above-average non-cognitive traits

relevant to exercising you mind or a love of that exercise for its own sake. If so, despite

your average genotype, you may qualify for a cognitively demanding profession, marry

someone who is intellectually lively, and welcome cognitively demanding leisure activity.

In sum, you may live out you entire life in an enriched environment that raises you IQ

well above average.

We all know that this is true in areas like sporting excellence. I may be born with

an average physiology for running. But compared to other non-professional runners, I

jog regularly as a means toward better health, while they know they should but have less

self-discipline than I do. Indeed, I may eventually be able to beat someone born with the

physiology of a potential Olympic champion. If I love running and he or she does it only

for the money, after the age of 35, I will keep exercising my body and he or she will not.

These traits will not override physiology entirely, of course. There are runners I cannot

beat even when I train more than they do. But I can run rings around every couch potato

within 20 years of my age. Our genes do not fix us to a particular level in a hierarchy

even for height (Weedon et al., 2008)

No one can keep you from falling in love with ideas, and serious literature, and

conversation with other critical minds. No one can deep you from developing an

expert mind that makes an unceasing effort to better understand the world around you

(Ross, 2006). In addition, remember that the brain is a physical organ. Its efficiency can

be enhanced by nutrition and aerobic exercise. Rhythmic use of large muscle groups

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occupying army in Germany. Eyferth selected a representative sample of the children

black servicemen fathered with German women and a matching group (matched for the

SES of the mothers) of the children of white servicemen. He collected IQ data for 170

of the former and 69 of the latter on the HAWIK or the German version of the WISC.

The mean IQs of the two groups were virtually identical implying that there was no

advantage in having a white father rather than a black one (Flynn, 1980, pp. 84-102).

This study by no means settles the race and IQ debate. The numbers are too small

and there is the problem that the black fathers were elite: men had to pass a mental test to

enter the army and far more blacks failed than whites. Flynn (1980) calculated that

representative samples of American men would have left 3 points of the 15-point IQ gap

of that time unexplained. On the other hand, the racial attitudes of Germans made it

likely that the half-black children experienced overt discrimination. The real lesson of

Eyferth is not that its results are decisive but the clues they give us to the causes operative

in America in the post-war era: that 3 points of the IQ gap were due to the effects on

blacks of racial profiles; and that the remaining 12 point were due to the historical

experience of black Americans something that was nullified in Germany. This four to

one ratio is not to be taken literally, of course. But it is indicative that any explanation of

the racial IQ gap must not omit an analysis of the cognitive environments that separate

black and white Americans.

The other salient fact is that over the last 30 years, blacks have gained on whites

and the average gap between black and white school children is now about 10 points.

But much more important is the discovery that black infants have virtually no IQ deficit,

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that is, the back IQ deficit is a phenomenon that arises as black and white children age

and follow different paths of development.

-------------------------------

Insert Figure 2 about here

-------------------------------

Figure 2 provides the latest data as to where black IQ stands today (Dickens &

Flynn, 2006). At every age, blacks are normed on whites (not including Hispanics) set at

an IQ of 100. The solid vertical line just before 0 represents conception, 0 represents

birth, and the broken vertical line just after 0 represents 10 months old.

The virtual absence of a black IQ deficit in infancy is tentative. Frier and Levitt

(2006) report results from the Early Childhood Longitudinal Survey Birth Cohort (ECLS-

B). Representative samples of black and white infants (aged 8 to 12 months) were given

the BSF-R, a shortened version of the Bayley Scale of Infant Development. This test has

a higher correlation with later IQ than any other infant intelligence test, but the

correlation is still modest (it stabilizes at 0.30 at about 5 years of age). It "tests" for

babbling, reaching for and holding objects, using another object to get a toy that is out of

reach, using words, and trying to discover what makes the ringing sound in a bell. The

difference between black and white children was too small to be statistically significant

but black children were slightly below at an "IQ" of 99.04.

The values beginning from ages 4 to 24 are based on the results of standard IQ

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is, those with better minds tend to gravitate to the more cognitively demanding peer

groups and this happens irrespective of family.

But would anyone say that the difference between rural Nigeria and New York

City would not afford US blacks a higher mean IQ? The fact that family environment

fades in both places as a determinant of individual differences in IQ does not affect the

fact that the two groups live in very different cultures; and that Nigerian rural culture

offers a less enriched spectrum of cognitive environments all the way from infancy to

adulthood. It would not even mean we could ignore the early childhood environment of

Nigerians. Their childhoods have a causal affect on the kind of peers they encounter post-

childhood. The fact that Nigerian children are not groomed for life in a modern society

means that as they age, they are surrounded with peers none of whom make the cognitive

demands characteristic of that kind of society.

Note how this example focuses us on the contention that Bla

flynn blair

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