Bryan Caplan  

Analytical Egalitarianism and Truth-Seeking: Strain the Gnat, Swallow the Camel

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I've been beating up on Analytical Egalitarianism quite a bit lately (see here, here, and here). Now Sandra Peart, a leading proponent of this view, has risen to the challenge.

According to Peart, scholars should assume equal human abilities because otherwise they might give in to temptation to shade the truth:

Without AE, we wonder whether truth-seeking is incentive compatible...

[...]

Consider models with agents of different fixed types. Suppose a modeler proposes to pick who is in the “better” and who in the “worse” class. If the modeler can do this and policies follow from the exercise, the modeler may benefit. That’s one incentive issue. We consider rewards from both material sources and applause.

[...]

[O]nce we allow for difference to creep into the analysis, the incentives are asymmetric: the theorist gains more by showing difference than similarity.

As far as I can tell, Peart's argument boils down to: If researchers are allowed to claim they (or their group, or their sponsors, etc.) are somehow better than average, they have an incentive to do so. This leads them to err on the side of inegalitarianism.

So far, so good. But we have a standard toolkit for dealing with researcher bias: asking to see the evidence, double-checking the work, asking probing questions, looking around for contrary evidence, and so on. What makes the "vanity of the philosopher" such a special problem? Inquiring minds want to know.

Admittedly, the standard toolkit is not perfect. But imposing the plainly false assumption of Analytical Egalitarianism in the name of methodological hygiene is far worse. We could just as well argue for Analytical Hermaphrodism: "If we admit that there are two genders, researchers will argue that their gender is somehow better than average. Therefore, in the name of incentive compatibility, researchers should assume that there is only one gender." In both cases, we would be dogmatically embracing a massive falsehood to guard against a moderate potential bias.

Even if you reject this analogy, Peart seems to neglect the possibility that some people might be biased in an egalitarian direction. I find this extremely odd, because in the modern intellectual world, this is the standard bias! Look at all the "applause" Murray and Herrnstein got. The primary effect of Analytical Egalitarianism is not, therefore, to counteract our tendency to think we're better than other people. It is to make it even more costly to challenge popular egalitarian platitudes.


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COMMENTS (6 to date)
Randy writes:

Peart's article reminds me very much of the works of medieval philosophers. When first introduced to such writing, I often felt uneasy about the fact that I could not comprehend. But after working my way through a few, I quickly realized that overly complex writings are often not worth the effort of trying to comprehend. I realized that the primary objective, the reason for the complexity, was not to reveal the truth, but to get around it.

That said, the idea of analytical egalitarianism seems to be to reduce or eliminate bias in the creation of public policy - perhaps a worthy goal. But I'm not quite sure how that can work, as the concept is itself a form of bias.

Eric writes:

It reminds me of Derrida and Stanley Fish, who argue their words mean exactly what they want them to mean, no more no less. And since everything is contextual, you can't prove me otherwise. I don't think that kind of rhetoric takes you forward, but I suspect these people don't believe in 'truth' or 'value' or 'progress', so they don't care.

Steve Sailer writes:

Peart is being disingenuous, not the IQ researchers. Where is the evidence that, say, that white IQ researchers say that whites have higher average IQs than Northeast Asians? They don't. They all -- e.g., Richard Lynn, Charles Murray, Arthur Jensen, JP Rushton, etc. -- say that Northeast Asians have higher average IQs than whites, even though all the researchers are white.

bgrindle writes:

Frankly I'm only wondering whether or not she is related to Neil Peart of Rush. Same last name and she is from Canada...its possible.

Scott Clark writes:

Bryan mentions that "in the modern intellectual world, this (egalitariasm) is the standard bias!"

Let's not forget that Levy and Peart are writing on topics in the HISTORY of economic thought, and if egalitarism is now the standard bias in modern intellectual life, then Mill and Smith and others have finally gotten through to the social science community at large. Levy and Peart point to all the social scientists and would-be reformers who used models to show that other races were absolutely inferior to the modeler's race and sold those models to polically powerful groups who then used this "science" as an additional justification for discriminatory policies. If everybody has moved away from that, Levy and Peart want to make sure that economist's get the credit for that. That's why they pointed out the phenomenon.

Surely, in the academic world, you ask for the evidence, you test and retest, but when someone is making a political argument they seize onto whatever they can to support their predetermined position. It goes back to the point that lots of people argue on topics with no regard for what the truth actually is, but on what they want the prevailing viewpoint to be.

Steve Sailer writes:

"It goes back to the point that lots of people argue on topics with no regard for what the truth actually is, but on what they want the prevailing viewpoint to be."

Which would seem to be Levy and Peart's modus operandi. Bryan sent me a paper by them that was straight out of the Stephen Jay Gould "Mismeasure of Man" playbook -- attack a great scientist of the 19th century (in this case Karl Pearson, inventor of the correlation coefficient) for his shortcomings, as if that's terribly relevant to important issues of the 21st Century.

It's like saying astronomers are all wrong today because Ptolemy thought the sun went around the earth. But it sure made Stephen Jay Gould a lot of money!

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