Understanding race and human variation: why forensic anthropologists are good at identifying race

Abstract

American forensicanthropologists uncritically accepted the biological race concept from classic physical anthropology and applied it to methods of human identification. Why and how the biological race concept might work in forensic anthropology was contemplated by Sauer (Soc Sci Med 34 1992 107-111), who hypothesized that American forensic anthropologists are good at what they do because of a concordance between social race and skeletal morphology in American whites and blacks. However, Sauer also stressed that this concordance did not validate the classic biological race concept of physical anthropology that there are a relatively small number of discrete types of human beings. Results from Howells (Papers of the Peabody Museum of Archaeology and Ethnology 67 1973 1-259; Papers of the Peabody Museum of Archaeology and Ethnology 79 1989 1-189; Papers of the Peabody Museum of Archaeology and Ethnology 82 1995 1-108) and others using craniometric and molecular data show strong geographic patterning of human variation despite overlap in their distributions. However, Williams et al. (Curr Anthropol 46 2005 340-346) concluded that skeletal morphology cannot be used to accurately classify individuals. Williams et al. cited additional support from Lewontin (Evol Biol 6 1972 381-398), who analyzed classic genetic markers. In this study, multivariate analyses of craniometric data support Sauer's hypothesis that there are morphological differences between American whites and blacks. We also confirm significant geographic patterning in human variation but also find differences among groups within continents. As a result, if biological races are defined by uniqueness, then there are a very large number of biological races that can be defined, contradicting the classic biological race concept of physical anthropology. Further, our results show that humans can be accurately classified into geographic origin using craniometrics even though there is overlap among groups.