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Model Organisms as Models: Understanding the ‘Lingua Franca’ of the Human Genome Project

Published online by Cambridge University Press:  01 April 2022

Rachel A. Ankeny*
Affiliation:
University of Sydney
*
Send requests for reprints to the author, Unit for History and Philosophy of Science, Carslaw F07, University of Sydney, NSW 2006, Australia; email: [email protected].

Abstract

Through an examination of the actual research strategies and assumptions underlying the Human Genome Project (HGP), it is argued that the epistemic basis of the initial model organism programs is not best understood as reasoning via causal analog models (CAMs). In order to answer a series of questions about what is being modeled and what claims about the models are warranted, a descriptive epistemological method is employed that uses historical techniques to develop detailed accounts which, in turn, help to reveal forms of reasoning that are explicit, or more often implicit, in the practice of a particular field of scientific study. It is suggested that a more valid characterization of the reasoning structure at work here is a form of case-based reasoning. This conceptualization of the role of model organisms can guide our understanding and assessment of these research programs, their knowledge claims and progress, and their limitations, as well as how we educate the public about this type of biomedical research.

Type
Philosophy of Biology and Cognition
Copyright
Copyright © Philosophy of Science Association 2001

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Footnotes

Thanks to participants at the 1999–2000 Workshop on Model Systems, Cases, and Exemplary Narratives in Science and History, Program in the History of Science, Princeton University, especially Angela Creager, Jane Hubbard, and Mary Morgan, as well as attendees at the 1999–2000 Seminar Series on Model Organisms, Center for the Philosophy of Science and Program in Science and Technology Studies, University of Minnesota for helpful comments on earlier versions of this paper. I also gratefully acknowledge support of preliminary research for this project through a dissertation grant from the Science and Technology Studies Program of the National Science Foundation (NSF #9617211).

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