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Thicker Than Blood: How Racial Statistics Lie

Tukufu Zuberi


Thicker Than Blood: How Racial Statistics Lie

Author:Tukufu Zuberi
Publisher:University of Minnesota Press
Pages:193
Genre:Non-Fiction

By Loren Glass | Posted 10/31/2001

In the early 19th century, scientists measured intelligence by filling empty skulls with mustard seed. Using this method, the American physician and scientist Samuel George Morton tried to prove that the cranial capacity, and therefore the intelligence, of the light-skinned races was superior to that of the dark-skinned races. By packing the skulls with different densities of mustard seed, Morton was able to force his data to match his racist assumptions. His work was widely respected by scientists and scholars throughout the Western world.

The scientific study of human intelligence has advanced considerably since the early 19th century, but, according to University of Pennsylvania sociologist Tukufu Zuberi, the apparently objective science of social statistics remains hostage to the subjective assumptions of racist scientists. In Thicker Than Blood, Zuberi compellingly recounts the enduring connection between the eugenics movement--the now-forgotten effort to selectively breed human populations--and the development of racial statistics. He concludes that "eugenic attempts to explain racial differences have left an indelible mark on social statistics." His research proves that racial statistics continue to be contaminated by racist assumptions and that, therefore, we must strive to "deracialize" statistical analysis in the social sciences.

Zuberi's historical account begins in the 15th century with the European colonial expansion into Africa and the resulting enslavement of Africans. "Race," as a category for the classification of human populations, emerged as part of an effort to justify the practices of slavery and colonialism. Thus, racial classification and racial stratification are intimately linked at their origins. The abolition of slavery in the 19th century only intensified the need on the part of Western scientists to justify racial inequality. As Zuberi powerfully illustrates, the "science" of eugenics emerged in the late 19th century to explain and legitimize racial stratification in liberal democratic society.

The world's disgust with Nazism dealt a political deathblow to the "science" of eugenics. Furthermore, postwar genetic scientists were increasingly undermining the viability of race as a scientific category. However, as Zuberi shows, psychology picked up the ball that genetics had dropped; in the late 20th century, the IQ test emerged as the basis for a new eugenic movement. As the popularity of Richard Herrnstein and Charles Murray's 1994 book The Bell Curve attests, spurious statistical justifications of racial stratification will not die as long as racism remains a social problem.

Zuberi argues that if we alter our understanding of the relationship between race and statistics, social science can begin to solve, instead of perpetuate, this most intransigent of problems. Zuberi's solution is deceptively simple: If we use race as an indicator of prejudice and discrimination, instead of as a cause of stratification and inequality, then we can use racial statistics to battle, instead of perpetuate, racial injustice. Thus, Zuberi claims, "race is not a causal variable but rather an intrinsic property of the individual."

It is on this definition of race that Zuberi's argument founders. In his preface, he offers the following definitions: "race is a biological notion of physical difference grounded in ideology"; "race is a socially constructed process that produces subordinate and superordinate groups"; "race is . . . a system of ideas by which men and women imagine the human body and their relationships within society"; "race is an emblem of a population within racially stratified societies." After all this, how can race also be "an intrinsic property of the individual"? Thicker Than Blood reveals that the very incoherence of race as a concept might account for its power and persistence as a category of scientific analysis.

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