Hostname: page-component-76fb5796d-vvkck Total loading time: 0 Render date: 2024-04-28T18:20:30.640Z Has data issue: false hasContentIssue false

Modeling without Mathematics

Published online by Cambridge University Press:  01 January 2022

Abstract

Inquiries into the nature of scientific modeling have tended to focus their attention on mathematical models and, relatedly, to think of nonconcrete models as mathematical structures. The arguments of this article are arguments for rethinking both tendencies. Nonmathematical models play an important role in the sciences, and our account of scientific modeling must accommodate that fact. One key to making such accommodations, moreover, is to recognize that one kind of thing we use the term ‘model’ to refer to is a collection of propositions.

Type
Fictions, Models and Representation
Copyright
Copyright © The Philosophy of Science Association

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

I am especially indebted to Arnon Levy and Edouard Machery for helpful correspondence on the chemoton model and on modeling in cognitive neuropsychology, respectively. Thanks also to Isabelle Peschard, Bas van Fraassen, and Michael Weisberg, my cosymposiasts; to Roman Frigg, Peter Godfrey-Smith, Mathias Frisch, and Phil Ehrlich for discussion at the PSA; and to Michael Strevens, Stephen Barker, Felipe De Brigard, Felipe Romero, and the other audience members at the Second Colombian Congress on Logic, Epistemology, and Philosophy of Science in Bogotá in 2012.

References

Achinstein, Peter. 1968. Concepts of Science: A Philosophical Analysis. Baltimore: Johns Hopkins Press.Google Scholar
Downes, Stephen M. 1992. “The Importance of Models in Theorizing: A Deflationary Semantic View.” In PSA 1992: Proceedings of the 1992 Biennial Meeting of the Philosophy of Science Association, Vol. 1, ed. Hull, David, Forbes, Micky, and Okruhlik, Kathleen, 142–53. East Lansing, MI: Philosophy of Science Association.Google Scholar
Gánti, Tibor. 2003. The Principles of Life. Commentary by James Griesemer and Eörs Szathmáry. Oxford: Oxford University Press.CrossRefGoogle Scholar
Giere, Ronald N. 1988. Explaining Science: A Cognitive Approach. Chicago: University of Chicago Press.CrossRefGoogle Scholar
Jones, Martin R. 2005. “Idealization and Abstraction: A Framework.” In Idealization XII: Correcting the Model—Idealization and Abstraction in the Sciences, ed. Jones, Martin R. and Cartwright, Nancy, 173217. Amsterdam: Rodopi.CrossRefGoogle Scholar
Kuhn, Thomas S. 1970. The Structure of Scientific Revolutions. 2nd ed. Chicago: University of Chicago Press.Google Scholar
Maynard Smith, John, and Szathmáry, Eörs. 1995. The Major Transitions in Evolution. Oxford: W. H. Freeman.Google Scholar
McMullin, Ernan. 1985. “Galilean Idealization.” Studies in History and Philosophy of Science 16:247–73.CrossRefGoogle Scholar
Redhead, Michael. 1980. “Models in Physics.” British Journal for the Philosophy of Science 31:145–63.CrossRefGoogle Scholar
Thomson-Jones, Martin. 1997. “Models and the Semantic View.” PhilSci Archive, University of Pittsburgh. http://philsci-archive.pitt.edu/8994/.Google Scholar
Thomson-Jones, Martin. 2006. “Models and the Semantic View.” Philosophy of Science 73 (Proceedings): 524–35.CrossRefGoogle Scholar
Thomson-Jones, Martin. 2011. “Structuralism about Scientific Representation.” In Scientific Structuralism, ed. Bokulich, Alisa and Bokulich, Peter, 119–41. Boston Studies in the Philosophy of Science 281. Dordrecht: Springer.Google Scholar
van Fraassen, Bas C. 2008. Scientific Representation: Paradoxes of Perspective. Oxford: Clarendon.CrossRefGoogle Scholar
Weisberg, Michael. Forthcoming. Simulation and Similarity: Using Models to Understand the World. Oxford: Oxford University Press.CrossRefGoogle Scholar