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Isolation-by-distance models are part of the institutional creed of antiracialism used to critique claims of biological race concepts (BRCs). Proponents of antiracialism appeal to isolation-by-distance models to describe patterns of human genetic differences among and between groups as a function of distance. Isolation by distance has been referred to as the pattern that human genetic variation fits, distributing the differences we see as race throughout geographic space as a series of Gaussian gradients. Contemporary scientific critiques of BRCs fuse social constructionist race concepts with a description of the distribution of proportions of human genetic variation in geographic space as a function of distance. These two points are often followed by statements noting that there is only one human race. How these two concepts connect to each other, and whether or not they connect at all, is unclear in both academic and nonacademic spaces. Consequently, scientists and the public lack an understanding of human population structure and its relationships to varying systems of human interactions. This article reviews isolation-by-distance models in population genetics and the use of these models in the modern problem of human difference. The article presents a historical and conceptual review of isolation-by-distance models and contemporary scientific critiques of BRCs, followed by examples of the use of isolation-bydistance models in studies of human genetic variation. To address the shortcomings in the scientific critique of race, the author proposes combining Du Boisian demography with Darwinian evolutionary biology. From a Du Boisian demographic perspective, race is a product of racism, or race/ism, and is a heredity and inheritance system based on rules of partus sequitur ventrem and hypodescent. Race marks individuals and groups them to reproduce unequal relationships into which Europeans co-opted them. This synthesis propounds a new racial formation theory to understand the more general consequences of racism on genes and health outcomes.