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Kathryne Metcalf

PhD Student, Communication and Science Studies

Kate Metcalf is a Jacobs Fellow and doctoral student at UCSD in Communication and Science Studies. Her work examines genomic biobanks as a diverse class of scientific and cultural actors that form the infrastructure for particular kinds of knowledge-making practices. She is broadly interested in the political economy of biomedical research, tissue economies, issues of privacy and health data, and futures of big data biology. Along with Magdalena Donea and Stuart Geiger, Kate co-organizes the Critical Data Studies Working Group at UCSD.

Before coming to San Diego, Kate was a science writer and outreach specialist at the Carl R. Woese Institute for Genomic Biology. Her work there included the development of The World of Genomics, a travelling museum exhibit that has been shown at Chicago’s Field Museum of Natural History, the Saint Louis Science Center, and the National Academy of Sciences in Washington DC. She also holds an MA in American Culture Studies from Bowling Green State University.

PhD Student, Communication and Science Studies
University of California San Diego, 2019-present

MA, American Culture Studies
Bowling Green State University, 2019

BA, Literary Studies
Beloit College, 2015


Original Research

  • Metcalf, K., Irani, L., and Uribe del Aguila, V. (2023). “Contested Care: COVID Surveillance and Health Data in the Workplace.” Surveillance and Society, 21(2), pp. 139-153. doi: 10.24908/ss.v21i2.15819
  • Rosati, C., James, A., Metcalf, K. (2023). “Data Plantation: Northern Virginia and the Territorialization of Digital Civilization in ‘The Internet Capital of the World.’” Online Media and Global Communication. doi: 10.1515/omgc-2023-0017
  • Metcalf, K. (2022). “Affective Economies in Blood Banks and Biobanks: Vital Accounting from US Transfusion Medicine to Genetic Research, 1935-1990.” Social History of Medicine, 35(2), pp. 369-388. doi: 10.1093/shm/hkab091


  • Metcalf, K. (2022). “Accounting for Complexity: Thinking with Idealisations, Models, and Data.” Medicine Anthropology Theory, 9(3), pp. 1-9. doi: 10.17157/mat.9.3.7290