Justin’s Notes

Anti-Racist Science Can Fail by the Same Statistical Move It Condemns

2026-08-23 · AI-generated insight

These two notes describe what look like separate controversies—Gould's Mismeasure of Man and Lewontin's argument against biological race—but the alleged errors share a common statistical shape: ignoring the structure that only appears when correlated variables are considered together.

Winegard and Carl's point about Lewontin is explicitly about aggregation: any single genetic locus varies more within populations than between them, just as nose size alone can't sort faces by sex. The signal lives in the correlations across many loci. Meanwhile, Carroll's critique of Gould (as Warne recounts it) is that Gould misunderstood factor analysis—which is precisely the tool for extracting a common signal from many correlated measurements. In both cases, a celebrated anti-racist argument allegedly worked by decomposing an aggregate into pieces, showing each piece was individually weak, and declaring the whole an illusion. Whether or not one accepts the critics' conclusions, the parallel suggests this isn't a coincidence of two careless scholars but a rhetorically attractive fallacy: disaggregation always makes patterns look smaller, so it's the natural move for anyone motivated to dissolve a category.

The Morton affair adds a darker recursive twist. Gould's central claim was that Morton's racist priors unconsciously bent his measurements—and the 2011 re-analysis accused Gould of exactly the same unconscious bending, in the opposite moral direction. Bias in measurement, it turns out, is not a property of villains; it's a property of having priors. Kaplan's position in the follow-up debate may be the wisest of the lot: Morton's interpretations were flawed, and Gould was wrong to think he could read Morton's motivations from the data. That's a general lesson for the whole "Politics Shaping Science" file—we're usually on firmer ground auditing the statistics than auditing the soul of the statistician. The statistics here suggest a symmetric failure mode: virtue is no vaccine against motivated aggregation errors; it just changes which direction the error points.

Woven from these notes

Many scholars have criticized The Mismeasure of Man periodically throughout its 38-year history. For example, James T. Sanders stated that Gould’s attempt to link his argument to anti-racism was a ploy to smear intelligence scholars and Gould’s enemies as evil people. Arthur Jensen argued in 1982 that Gould misrepresented Jensen’s ideas and often demolished strawmen that no intelligence scholar believes, including the boogeyman of “biological determinism.” John Carroll showed that Gould understood neither the purpose nor interpretation of factor analysis (a statistical procedure often used to evaluate data from psychological tests) and that Gould’s attacks on factor analysis do nothing to alter the importance of intelligence tests, nor the mass of evidence—impossible to dispute—that they predict real-life outcomes. Most criticism of The Mismeasure of Man was confined to the recherché world of psychologists who study intelligence. However, a new debate opened up in 2011 when a team of anthropologists argued that Gould’s analysis of the data on cranium measurements from 19th century scientist Samuel George Morton was flawed. Gould cast Morton as a racist who fudged his data to match his beliefs about white racial superiority because of a supposed larger skull capacity. Instead, the anthropologists argued, it was Gould who manipulated the data to support his biases. This ignited a series of follow-up articles in the scholarly literature by authors taking a variety of positions regarding Morton’s data and Gould’s interpretations. Weisberg believed that the re-analysis was flawed and Gould was mostly correct. Kaplan and his colleagues claimed that Morton’s interpretations were flawed, but that Gould was incorrect in believing that he could discern Morton’s actions and motivations. Finally, Mitchell believed that Morton’s data were accurate and that the interpretations were colored by the racism of the era, but the claim that Morton subtly manipulated the data was a fiction created by Gould.
— Russell T. Warne The Mismeasurements of Stephen Jay Gould

In brief, Lewontin ignored the fact that differences among human populations are correlated. Although population variation at any one genetic locus tends to be small, global population structure becomes clear if one examines correlated differences across loci. For a simple analogy, consider men and women’s faces. If one takes any particular characteristic, say nose size, there is likely to be more variation within a sex than between the sexes (and it would be nearly impossible to classify faces by sex with any accuracy using only nose size). However, if one considers all facial characteristics together (which is, after all, how we actually experience human faces), then sex differences become sufficiently clear that an observer can guess the correct sex more than 95 percent of the time.

— Bo Winegard, Noah Carl Superior: The Return of Race Science—A Review