I looked at the above link, and it’s actually a fairly heavily referenced book review written by Richard Lynn, a professor of psychology. The subject matter of the book is heavily within Lynn’s area of expertise and stays focused on the substance. The guy is both a prominent academic in the psychology of intelligence, and willing to affiliate with publications, organizations, and events associated with nasty and silly ethnocentrism. Some possible heuristics we could apply here:
1) Read everything Lynn writes, both in academic journals and books, and in articles written for non-academic political publications, since he’s an academic with relevant expertise.
2) Read everything Lynn writes, both in academic journals and books, and in articles written for non-academic political publications, but exclude things written for political publications where strongly disapproved writings appear (even if the Lynn article itself is unobjectionable).
3) Only read his academic articles and books, and not popularizations or other writings.
4) Don’t read anything by this guy, either because his associations indicate his academic work is bad, or accepting any lost opportunities to learn as a legitimate cost of supporting norms of tolerance among majorities.
5) Don’t read anything by people with Lynn’s associations, but also extend one more level to exclude people who have associated with them, e.g. Arthur Jensen. Only read people who have political associations for which their research is inconvenient.
What are you thinking of?
Remember that too far down the list, one would also wind up excluding many of the arguments in the scientific literature against hereditarianism, at least on race, as the well-known anti-hereditarian authors often have strong Marxist, socialist and related commitments, e.g. Stephen J. Gould. In some cases, such as Gould’s, that would be justified: Gould was caught in numerous errors and falsehoods skewed in the direction of his politics. But this would still slice away vast swathes of the relevant literature, if not the raw data.
I looked at the above link, and it’s actually a fairly heavily referenced book review written by Richard Lynn, a professor of psychology. The subject matter of the book is heavily within Lynn’s area of expertise and stays focused on the substance. The guy is both a prominent academic in the psychology of intelligence, and willing to affiliate with publications, organizations, and events associated with nasty and silly ethnocentrism. Some possible heuristics we could apply here:
1) Read everything Lynn writes, both in academic journals and books, and in articles written for non-academic political publications, since he’s an academic with relevant expertise.
2) Read everything Lynn writes, both in academic journals and books, and in articles written for non-academic political publications, but exclude things written for political publications where strongly disapproved writings appear (even if the Lynn article itself is unobjectionable).
3) Only read his academic articles and books, and not popularizations or other writings.
4) Don’t read anything by this guy, either because his associations indicate his academic work is bad, or accepting any lost opportunities to learn as a legitimate cost of supporting norms of tolerance among majorities.
5) Don’t read anything by people with Lynn’s associations, but also extend one more level to exclude people who have associated with them, e.g. Arthur Jensen. Only read people who have political associations for which their research is inconvenient.
What are you thinking of?
Remember that too far down the list, one would also wind up excluding many of the arguments in the scientific literature against hereditarianism, at least on race, as the well-known anti-hereditarian authors often have strong Marxist, socialist and related commitments, e.g. Stephen J. Gould. In some cases, such as Gould’s, that would be justified: Gould was caught in numerous errors and falsehoods skewed in the direction of his politics. But this would still slice away vast swathes of the relevant literature, if not the raw data.