The Bell Curve, 20 years after

Or nearly so. I was planning to publish that blog article for the 31th December 2014. As you can see, I failed in this task, and didn’t finish in the right time. Anyway, I wrote this article, mainly because I am bothered that when people cite The Bell Curve the typical opponent responds with a link toward Wikipedia, specifically the part related to the “controversy” of The Bell Curve. It goes without saying that these persons did not read the books written in response to The Bell Curve. In fact, they have certainly read none of them. It is ridiculous to cite a book you didn’t read, but apparently, it does not bother many people, as I see.

For the 20 years of the book, I found appropriate to write a defense of the book. Or more precisely, a critical comment on the critics. I have decided to read carefully one of these books I can have access, and for what I have read here and there, it is probably the best book ever written against The Bell Curve. I know that Richard Lynn (1999) has already written a review before. But I wanted to go into the details. The title of the book I’m reviewing is :

Devlin, B. (1997). Intelligence, Genes and Success: Scientists Respond to the Bell Curve. Springer.

In fact, I have read that book some time ago, but didn’t find the need to read everything in detail. And I was unwilling to write a lengthy review. But I have changed my mind because of some nasty cowards.
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MH’s book review of Deafness, Deprivation, and IQ (Braden 1994)

Jeffery P. Braden. (1994). Deafness, deprivation, and IQ. Springer.

The book is a compilation of studies on deaf people, which concludes that cultural deprivation due to deafness lowers verbal IQ but not nonverbal IQ. Braden sought to prove Arthur Jensen wrong about his conclusions on the genetic component in racial differences in IQ. At the end, his research culminated in a trauma well known to scientific history, namely, his perfectly good theory was ruined by his data. Being born deaf does not affect g. And genetic theories are the most powerful arguments to account for the pattern of the data.
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