Racial zigzags: Visualizing racial deviancy in German physical anthropology during the 20th century

Research output: Contribution to journalArticlepeer-review

Abstract

In 1907, German anthropologist Theodor Mollison invented a unique method for racial differentiation, called ‘deviation curves’. By transforming anthropometric data matrices into graphs, Mollison’s method enabled the simultaneous comparison of a large number of physical attributes of individuals and groups. However, the construction of deviation curves had been highly desultory, and their interpretation had been prone to various visual misjudgements. Despite their methodological shortcomings, deviation curves became very popular among racial anthropologists. This positive reception not only stemmed from the method’s utilities, but was related to additional interests of its protagonists which the method helped promote. Deviation curves provided a unique solution to the holistic–atomistic controversy in German anthropology. By giving separate measurements a consolidated visual form, they substantiated the idea that the attributes of certain social groups were part of distinct racial compounds. Deviation curves thus reinforced racial suppositions, in face of severe criticism on the ontological reality of race itself. Finally, deviation curves emphasized the biological singularity of disadvantaged human groups – Jews, Africans and also women – and of their divergence from ideologically defined physical norms. Disciplinary and social interests thus became intertwined in the formation of a scientific method, which is used to this day in physical anthropology.

Original languageEnglish
Pages (from-to)17-48
Number of pages32
JournalHistory of the Human Sciences
Volume28
Issue number5
DOIs
StatePublished - 1 Dec 2015
Externally publishedYes

Keywords

  • German
  • anthropology
  • graph
  • race
  • visual

Fingerprint

Dive into the research topics of 'Racial zigzags: Visualizing racial deviancy in German physical anthropology during the 20th century'. Together they form a unique fingerprint.

Cite this