
Is Psychometric g a Myth? - gwern
http://humanvarieties.org/2013/04/03/is-psychometric-g-a-myth/?2
======
verteu
The scientific consensus on intelligence in 1997 was quite clear on this
issue:
[http://en.wikipedia.org/wiki/Mainstream_Science_on_Intellige...](http://en.wikipedia.org/wiki/Mainstream_Science_on_Intelligence)
. (See conclusion #3.)

Has the consensus changed since '97? I frequently hear people dispute #2
("Intelligence can be measured, and intelligence tests measure it well") and
#5 ("Intelligence tests are not culturally biased"). However, I'm not aware of
a revolution in IQ testing which overturns the old findings.

~~~
pessimizer
That was the consensus of scientists who specialized in studying general
intelligence, not the consensus of scientists, and was controversial at the
time. It did help to fight myths that were being promulgated by popular
writers and politically-motivated cranks about what the consensus of
scientists who studied general intelligence actually was.

Asking scientists who specialize in Spearman's g whether g is real is like
asking astrologers whether astrology works.

~~~
verteu
> Asking scientists who specialize in Spearman's g whether g is real is like
> asking astrologers whether astrology works.

Climate change deniers use the same argument -- "Of course people who
professionally study global warming will claim it's real!"

Why is your claim valid while the above is specious? It depends on the rigor
of the subfield in question.

------
avatarlite
tl;dr - a refutation of statistician Cosma Shalizi’s essay at
[http://vserver1.cscs.lsa.umich.edu/~crshalizi/weblog/523.htm...](http://vserver1.cscs.lsa.umich.edu/~crshalizi/weblog/523.html)
in three parts:

(1) "Shalizi’s first error is his assertion that cognitive tests correlate
with each other because IQ test makers exclude tests that do not fit the
positive [correlation matrix]. In fact, more or less the opposite is true. ...
Cognitive tests correlate because all of them truly share one or more sources
of variance."

(2) "Shalizi’s second error is to disregard the large body of evidence that
has been presented in support of g as a unidimensional scale of human
psychological differences. The g factor is not just about the positive
[correlation matrix]. A broad network of findings related to both social and
biological variables indicates that people do in fact vary, both
phenotypically and genetically, along this continuum that can be revealed by
psychometric tests of intelligence and that has has widespread significance in
human affairs."

(3) "Shalizi’s third error is to think that were it shown that g is not a
unitary variable neurobiologically, it would refute the concept of g. However,
for most purposes, brain physiology is not the most relevant level of analysis
of human intelligence. What matters is that g is a remarkably powerful and
robust variable that has great explanatory force in understanding human
behavior. Thus g exists at the behavioral level regardless of what its
neurobiological underpinnings are like."

Conclusion: "In many ways, criticisms of g like Shalizi’s amount to “sure, it
works in practice, but I don’t think it works in theory”. Shalizi faults g for
being a “black box theory” that does not provide a mechanistic explanation of
the workings of intelligence, disparaging psychometric measurement of
intelligence as a mere “stop-gap” rather than a genuine scientific
breakthrough. However, the fact that psychometricians have traditionally been
primarily interested in validity and reliability is a feature, not a bug.
Intelligence testing, unlike most fields of psychology and social science, is
highly practical, being widely applied to diagnose learning problems and
medical conditions and to select students and employees. What is important is
that IQ tests reliably measure an important human characteristic, not the
particular underlying neurobiological mechanisms."

~~~
andreasvc
Please, can we just call it a "summary" instead of invoking the anti-
intellectual air of "tl;dr"?

------
nhoven
There is a good discussion of the relative merits of both articles(the linked
blog post, and the post it criticizes) on the LessWrong forums:
[http://lesswrong.com/r/discussion/lw/h6p/g_a_statistical_myt...](http://lesswrong.com/r/discussion/lw/h6p/g_a_statistical_myth/)

