Re-situations of scientific knowledge

A case study of a skirmish over clusters vs clines in human population genomics

Bibliographic Data

ID12028375
AuthorsJames Griesemer (0000-0001-8817-0407, University of California, Davis, corresponding author), Carlos Andrés Barragán (0000-0002-5480-9441, University of California, Davis)
Year2022
Volume44
Issue2
Pages16-16
Publication date2022-04-21
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueHistory & Philosophy of the Life Sciences (JOURNAL)
Journal identifiersISSN: 0391-9714 • E-ISSN: 1742-6316
PublisherSpringer Nature (PUBLISHER • SG)
DOI10.1007/s40656-022-00497-9
PMID35445860
OpenAlexW4224244569
LanguageEN
Citations received4
References cited72

We track and analyze the re-situation of scientific knowledge in the field of human population genomics ancestry studies. We understand re-situation as a process of accommodating the direct or indirect transfer of objects of knowledge from one site/situation to (one or many) other sites/situations. Our take on the concept borrows from Mary S. Morgan's work on facts traveling while expanding it to include other objects of knowledge such as models, data, software, findings, and visualizations. We structure a specific case study by tracking the re-situation of these objects between three research projects studying human population diversity reported in three articles in Science, Genome Research and PLoS Genetics between 2002 and 2005. We characterize these three engagements as a unit of analysis, a "skirmish," in order to compare: (a) the divergence of interests in how life-scientists answer similar research questions and (b) to track the challenging transformation of workflows in research laboratories as these scientific objects are re-situated individually or in bundles. Our analysis of the case study shows that an accurate understanding of re-situation requires tracking the whole bundle of objects in a project because they interact in particular key ways. The absence or dismissal of these interactions opens the door to unforeseen trade-offs, misunderstandings and misrepresentations about research design(s) and workflow(s) and what these say about the questions asked and the findings produced

Biology · Data science · Epistemology · Genome · Genomics · Knowledge management · Population · Population genomics · Social science · Sociology · Sociology of scientific knowledge · Workflow · Biomedical Text Mining and Ontologies · Computer Science · Forensic and Genetic Research · Race, Genetics, and Society · Genetics

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