A critical/historical approach.
mike
>From owner-psyc@PUCC.PRINCETON.EDU Wed Jan 12 11:30:53 2000
Return-Path: <owner-psyc@PUCC.PRINCETON.EDU>
Received: from pucc.Princeton.EDU (SMTPE722-9024@pucc.Princeton.EDU [128.112.129.99])
by weber.ucsd.edu (8.9.3/8.9.3) with SMTP id LAA19034
for <mcole@WEBER.UCSD.EDU>; Wed, 12 Jan 2000 11:30:49 -0800 (PST)
Date: Wed, 12 Jan 2000 14:19:03 -0500
>From: PSYCOLOQUY <journal@princeton.edu>
To: PSYC@PUCC.PRINCETON.EDU
Status: RO
psycoloquy.99.10.079.intelligence-g-factor.18.harrington Fri Dec 31 2000
ISSN 1055-0143 (14 para, 21 refs, 327 lines)
PSYCOLOQUY is sponsored by the American Psychological Association (APA)
Copyright 1999 Gordon M. Harrington
BORN BEFORE GENES: THE g LEGACY
Book Review of Jensen on Intelligence-g-Factor
Gordon M. Harrington
Department of Psychology
University of Northern Iowa
Cedar Falls, IA 50614
gordon.harrington@uni.edu
ABSTRACT: Jensen (1998, 1999) offers a comprehensive presentation
of the argument that the g-factor, as defined by hierarchical
common factor models, constitutes the core and major component of
human intellective function. Its validity includes matters of
evolution and inheritance of g with attendant consequences for both
individual and group differences such as racial differences. The
future is envisioned as elucidating the details of the genetic and
brain elements of g. The uninformed reader would have no hint that
there is also a century of work which can be cited against the
argument. The g model is not consistent with mainstream twentieth
century work in evolution and in genetics. Some of the main points
of conflict are examined.
1. This magnum opus (Jensen 1998, 1999) is a comprehensive brief
presented to the world court of psychological opinion in a suit on
behalf of the corporate owners of factor analytic g, claiming title to
most of the intellective lands of the human brain. Like the best of
attorneys, Jensen thoroughly marshals - evidence, arguments, and
citations to authorities - to support his case for the plaintiffs while
avoiding, insofar as possible, even a hint that there might be
evidence, arguments, or authorities supporting the respondents. Title
to the intellective lands purportedly derives both from inheritance and
from original claims and grants to Charles Spearman (1904a). Since
Jensen's quite proper purpose is to make a case, not to present a
review of the literature, my role is cast as respondent or as amicus
curiae. A reasonable rebuttal is that g is not a psychological
phenomenon and is simply a statistical artifact derived from
assumptions of linearity in data arising from multiple interacting
causes.
I. THE RISE AND FALL AND RISE OF G
2. The core around which the book is built is the view that Spearman
discovered a general factor, g, and claimed that this was the major
element in all areas of human intellective function. It is held that,
with the research of an intervening century, the legacy of this view is
now largely uncontested. Hierarchical factor analysis has succeeded the
two-factor theory but g remains with us. Characterising all humans,
this general factor must be genetic and evolutionary in origin both on
theoretical and empirical grounds. It follows that the future of
research on intelligence lies in explicating the details of the gene
architecture and brain correlates for g.
3.The opening history chapter is limited to Spearman's contribution to
the g heritage. He generated a quarter of a century of vigorous
interest. Not mentioned is the following half a century of decline and
disinterest (Cronbach, 1990). Neisser and Bouchard (1999) correctly
credit the beginning of the resurrection of interest in g to Jensen and
his Harvard Educational Review paper (1969). Reviving an historic
concept calls for historic context.
4. For historical context, one should understand the milieu within
which g was conceived. The word "gene" did not exist in 1904. Just on
the verge of rediscovery, Mendel's ideas were generally unknown or
forgotten. Evolution was the great new concept of biological science.
Genetics was a lesser and only remotely, if at all, related field. It
would be a quarter of a century before Fisher (1930) would bring them
together. Genetic phenomena were understood to be governed by "blended
inheritance" where the genotype was the mid-parent value; offspring
inherited the average of their parents' characteristics. Given this
linear model, the genetic or "factor" structure of inherited
characteristics could be inferred from the correlation matrix of
measures of the phenotype. Karl Pearson's Biometrika, was the leading
journal for disseminating work following the "biometric" model.
Spearman's model followed directly from this "biometric" model.
Galton's original concept of a quantitative model for the life sciences
- "anthropometrics" - had led to a model more focused on biological
processes - "biometrics" - and had now spawned "psychometrics",
extending the biometric genetics model to psychological processes.
Correlation analysis has remained the core of psychological measurement
ever since. The first book on psychological measurement (Thorndike,
1904) confirmed psychometrics as its own field in the same year as
Spearman's (1904a,b) basic papers. Thereafter psychometrics developed
independently of biometrics.
5. Meanwhile, in genetics, Mendel was rediscovered and the nature of
his theory began to be recognised. In what has generally been
considered one of the half dozen most important papers in the history
of science, Fisher (1918) asked what would be the consequences for
quantitative genetic analysis if inheritance were Mendelian rather than
biometric. He proved that if inheritance is Mendelian one cannot infer
genetic structure from the correlation matrix but one can deduce the
correlation matrix if genetic structure is known. With only minor
modifications, the analyses of that paper still define the main
concepts of population genetics today. The linear models of
correlational analysis and their underlying assumptions were replaced
by Fisher's analysis of variance model with its components of variance
and with the nonlinear concept of interaction necessary to account for
such phenomena as dominance, epistasis, maternal effects, and
genetic-environmental interaction and correlation effects. The impact
went far beyond genetics as correlational analyses of experimental data
were rejected to be replaced by components of variance methods ranging
from t-tests to MANOVA. Despite Jensen's belief in the genetic basis of
g the fact remains that a genetic foundation for g cannot be inferred
from any correlational structure, including the correlational structure
which defines g.
6. The term factor analysis usually is restricted to the common factor
model. This is a linear model of estimates of underlying hypothetical
error free variables. It is not a model of the actual empirical data.
Present day factor analysis is oriented toward confirmatory analysis
which tests whether an hypothesised factor structure is consistent with
observed data. Fisher's demonstration that one cannot infer genetic
structure from the correlation matrix proved the matrix is not unique.
An infinite number of genetic structures are consistent with any given
matrix. Confirmatory is a misnomer. The usual logic of hypothesis
testing is to frame the hypothesis of interest against the null
hypothesis. Rejecting the null confirms the substantive. Factor
analysis reverses this logic by interpreting acceptance of the null as
confirmation of the substantive hypothesis.
II. FACTORS AS PSYCHOMETRIC ARTIFACTS
7. In defining terms, Jensen notes an essential empirical data
precondition for the estimates of factor analysis: "Factors arise only
from the reliable or nonchance correlation between abilities. Now if it
were the case that tests were constructed of only those items that
happened to be correlated with one another (and items that did not were
discarded), factors would indeed be mere psychometric artifacts. That
is, factors would be no more than a product of the arbitrary way that
ability items are devised or selected for inclusion in psychometric
tests (p. 56)." But this is exactly what one does in item analysis! The
success of the Stanford-Binet approach is attributable to Terman's
(1916) careful attention to internal consistency, making it one of the
cornerstones of psychometrics. Trying out items with selection and
discard based on item correlations is a major part of the standardised
test construction enterprise.
8. Tests are intended to sample performance in some aspect of the test
taker's environment. Evolution occurs because individuals with
different characteristics perform differently in different
environments. Natural selection reflects an advantage for a particular
characteristic in a particular environment. For genetic characteristics
then, the necessary condition for natural selection is the existence of
such genetic-environmental interactions. Thus, from a genetics
perspective, a test item samples the performance of an individual in
some niche of her world. Accordingly, if performance has any hereditary
component then one expects genetic-environmental interactions. In
theory, it is possible that some performances have no such
interactions, but those of us who work with infrahumans would be hard
put to identify a characteristic that has not been found susceptible to
some degree of selective breeding. The existence of
genetic-environmental (item x genotype) interactions implies that item
selection will be weighted by the genetic interactions of the tested
population. This has been verified experimentally.
9. The genetic controls necessary for an experimental study are
attainable only with infrahuman species. (Some who have proposed human
racial groupings for the purpose have not appreciated the fact that
racial definition is not genetic definition.) Using six well defined
genotypes of rats we formed multiple mixed populations differing in
proportions of the six in each (Harrington, 1975/1982, 1984, 1988).
Maze performance tests were developed separately for each population
using conventional item analysis for selection. New samples from each
genotype were tested on all of the tests and also on a set of maze
tests defined as the criterion to be predicted. Performance of each
genotype on each test was correlated with the representation of the
genotype in the test base population. This was true not only for mean
performance level but also for predictive validity, which is, of
course, statistically independent. From Jensen's statement above, the
results are empirical evidence that factors are artifacts.
10. The laboratory experiments have a second implication that is notworthy.
Test performance is correlated with genotype membership in the test
base population. Then all tests developed on a given or comparable test
base population will share a common genotype representation effect and
must be positively correlated with each other. The tests would yield a
general factor on factor analysis. Thus standard psychometric test
construction procedures create a general factor as an artifact.
III. SAMPLING OR REDUCTIONISM?
11. Jensen sees g as a product of human evolution and inheritance. He
observes that behavioural functions involving g involve more brain
processes organised in more complex ways than other processes. Both in
factor analysis and in neurophysiological organisation, g is a higher
order function. In noting the role of intelligence in determining man's
place in nature, the message is clear that it is g which has emerged as
the higher order function. Jensen seems reluctant to think of it as
occurring in lower species at times. At other times he recognises that
if it evolved there had to be precursors in other species. A species
unique higher intellect function engages a century old argument
originally espoused by creationists in opposition to Darwinian theory.
When Fisher (1918) showed that correlational analysis failed for
Mendelian Inheritance, there ensued a quarter of a century of
controversy with Pearson and other defenders of biometric inheritance.
One argument was that the higher mental functions of humans were not
subject to Mendelian inheritance but to biometric inheritance, and thus
subject to correlation matrix analysis. In general the biometricians
argued that complex mental functions were higher order functions
requiring complex tests and subject to different mechanisms of
inheritance requiring different modes of analysis.
12. The chapter on heritability is technically accurate. However it
perpetuates the use of heritability coefficients for human data, an
inappropriate usage. Read Kempthorne (1978) for the authoritative
geneticist's critique of application of the heritability coefficient to
human data. Jensen is to be congratulated for making clear the
difference between hereditary and heritability - hereditary referring
to the biological source of a characteristic and heritability to its
variance. He uses the example I thought I had originated: number of
heads, hands, or feet is inherited but, since the variability is near
zero the heritability is near zero.
13. All but the very careful reader may miss the significance of the
coverage of assortative mating as a component of heritability. Whether
or not this usage is appropriate, any heritability coefficient for IQ
will be high because of the assortative mating component. The place of
genetics in evolution was first set forth by Fisher (1930). High
selection for one head, two hands, or two feet eliminates other numbers
of extremities reducing the associated variance. The "Fundamental
Theorem of Natural Selection" is that heritability varies inversely
with evolutionary fitness. Jensen believes g is a broad fitness factor
too recently evolved to show reduction of variance by selection.
Prediction of future evidence of fitness strikes me as soothsaying and
as ignoring the question of how it evolved to this point.
14. Brown and Thomson (1921) showed a general factor will occur in a
correlation analysis if the observed effects are attributable to a
large number of underlying causal influences. Similar views were
championed by Tryon (1932a,b, 1935). Guilford (1954, p.476) explained
that the sampling theory alternative to g never gained acceptance among
psychometricians because: "In criticism of the sampling theory, it may
be said that there seems to be little likelihood of demonstrating
experimentally the existence of the elements hypothesized. . . It is in
repeated compounds that we find the invariances such as we seek in
science." That anti-reductionist view was reinforced by the abject
failure of an almost monolithic investment of many years of the
research resources of the entire psychological community in
sensori-motor elements - a disaster in that it yielded nothing
(Wissler, 1901). Global approaches carried the day and only a minority
followed Brown or Tryon in a belief in many factors or elements. Today
the Human Genome Project reflects a massive investment in a pursuit of
elements. A third or more of those elements are thought to be related
to brain processes. Because of current successes in illuminating many
disease and other processes, contemporary neurobiology is driven by
molecular biological concepts and research strategies which are
diametrically opposed to those global approaches which Guilford saw as
dominant in psychometrics.
REFERENCES
Brown, W., & Thomson, G. H. (1921). The essentials of mental
measurement. Cambridge: Cambridge University Press.
Cronbach, L. J. (1990). Essentials of psychological testing (5th ed.).
New York: Harper & Row.
Fisher, R. A. (1918). The correlation between relatives on the
supposition of Mendelian inheritance. Transactions of the Royal Society
(Edinburgh), 52, 399-433.
Fisher, R. A. (1930). The genetical theory of natural selection.
Oxford: Clarendon Press
Guilford, J. P. (1954). Psychometric methods (2nd ed.). New York:
McGraw-Hill.
Harrington, G. M. (1982). Intelligence tests may favour the majority
groups in a population. In J. Hirsch & T. R. McGuire (Eds.), Benchmark
papers in behaviour . Vol. 16. , Behaviour-genetic analysis. New York:
Academic Press. (Reprinted from Nature , 1975, 258 , 708-709)
Harrington, G. M. (1984). An experimental model of bias in mental
testing. In C. R. Reynolds & R. T. Brown (Eds.), Perspectives on bias
in mental testing (p. 101-138). New York: Plenum Press.
Harrington, G. M. (1988). Two forms of minority test bias as
psychometric artifacts with an animal model. Journal of Comparative
Psychology, 102, 400-407.
Jensen, A. R. (1969). How much can we boost IQ and scholastic
achievement? Harvard Educational Review, 39, 1-123.
Jensen, A. (1998). The g Factor: The Science of Mental Ability. Praeger
Jensen, A. (1999). Precis of: The g Factor: The Science of Mental
Ability. PSYCOLOQUY 10(23).
ftp://ftp.princeton.edu/pub/harnad/Psycoloquy/1999.volume.10/
psyc.99.10.023.intelligence-g-factor.1.jensen
http://www.cogsci.soton.ac.uk/cgi/psyc/newpsy?10.023
Kempthorne, O. (1978). Logical, epistemological and statistical aspects
of nature-nurture data interpretation. Biometrics, 34, 1-23.
Neisser, U., & Bouchard, T. J. (1999). Two views about the g factor.
Contemporary Psychology, 44(2), 131-135.
Spearman, C. (1904a). "General intelligence" objectively determined and
measured. American Journal of Psychology, 15, 201-292.
Spearman, C. (1904b). The proof and measurement of association between
two things. American Journal of Psychology, 15, 72-101.
Terman, L. M. (1916). The measurement of intelligence. Boston:
Houghton-Mifflin
Thorndike, E. L. (1904). An introduction to the theory of mental and
social measurements. New York: Science Press.
Tryon, R. C. (1932a). Multiple factors vs two factors as determiners of
ability. Psychological Review, 39, 324-351.
Tryon, R. C. (1932b). So-called group factors as determiners of
ability. Psychological Review, 39, 403-439.
Tryon, R. C. (1935). A theory of psychological components-an
alternative to mathematical factors. Psychological Review, 42,
425-454.
Wissler, C. (1901). The correlation of mental and physical tests. New
York: Columbia University.
This archive was generated by hypermail 2b29 : Tue Feb 01 2000 - 01:01:57 PST