Must Read on Intelligence and g-factor : Pure Pedantry

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Jake Young is a MD/PhD student at Mount Sinai School of Medicine in NYC getting a PhD in Behavioral Neuroscience. He holds a BS and MS in Biological Sciences from Stanford University. If a volcano were to erupt Pompei-style in Central Park, his body would be preserved in a scoliotic posture over his lab desk. Archeaologists would later conclude that he spent most of his day training rats to perform tricks, until he went blind building electrical equipment by hand using a dissecting microscope. But, still, he died happy...because science is cool.

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Must Read on Intelligence and g-factor

Category: Intelligence • Other People's Work
Posted on: October 19, 2007 2:22 PM, by NotoriousLTP

Here is a must-read post on g-factor by Three Toed Sloth:

Anyone who wanders into the bleak and monotonous desert of IQ and the nature-vs-nurture dispute eventually gets trapped in the especially arid question of what, if anything, g, the supposed general factor of intelligence, tells us about these matters. By calling g a "statistical myth" before, I made clear my conclusion, but none of my reasoning. This topic being what it is, I hardly expect this will change anyone's mind, but I feel a duty to explain myself.

To summarize what follows below ("shorter sloth", as it were), the case for g rests on a statistical technique, factor analysis, which works solely on correlations between tests. Factor analysis is handy for summarizing data, but can't tell us where the correlations came from; it always says that there is a general factor whenever there only positive correlations. The appearance of g is a trivial reflection of that correlation structure. A clear example, known since 1916, shows that factor analysis can give the appearance of a general factor when there are actually many thousands of completely independent and equally strong causes at work. Heritability doesn't distinguish these alternatives either. Exploratory factor analysis being no good at discovering causal structure, it provides no support for the reality of g.
These purely methodological points don't, themselves, give reason to doubt the reality and importance of g, but do show that a certain line of argument is invalid and some supposed evidence is irrelevant. Since that's about the only case which anyone does advance for g, however, which accords very poorly with other evidence, from neuroscience and cognitive psychology, about the structure of the mind, it is very hard for me to find any reason to believe in the importance of g, and many to reject it. These are all pretty elementary points, and the persistence of the debates, and in particular the fossilized invocation of ancient statistical methods, is really pretty damn depressing.

Read the whole thing.

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