The Problem of Representation in Terms of Scientific Models
Keywords:
Representation, Scientific Representation, Scientific Model, Isomorphism, SimilarityAbstract
If one commonly held view of many philosophers of science is that
scientific models play a fundamental role in scientific activity, the other
is that they are representations of real-world systems. However, there is no unanimity on the nature of scientific representation. Most differ in terms of the necessary and sufficient conditions for a representation to be scientific in their effort to find a solution to this problem, which is called the problem of scientific representation. By adopting a kind of morphism, structuralists reduce scientific representation to the properties of the model and the target system. Structuralists argue that for a model to represent a target system, it must be either structurally isomorphic or partially isomorphic to that system. In contrast, the proponents of the similarity account argue that the model cannot represent the target system unless it resembles it. Others, on the other hand, understand representation in terms of the cognitive activities of those who use a model. However, as we shall see, both views run into many problems. Another view opposing these two views sees scientific representation as an example of representation in general that emerges in science and evaluates it under the category of representation. In the first part of this article, the first two views, which we will call strong and weak accounts, will be discussed, and it will be argued that these views do not solve the problem of scientific representation [...]
References
Boon, M., & Knuuttila, T. (2009). Models as Epistemic Tools in Engineering Sciences. A. Meijers (Ed.), Handbook of the Philosophy of Science Volume 9: Philosophy of Technology and Engineering Sciences (ss. 693-726). Amsterdam: Elsevier.
Boumans, M. (1999). Built-in Justification. M. S. Morgan & M. Morrison (Ed.), Models as Mediators (ss. 66-96). New York: Cambridge University Press.
Callender, C., & Cohen, J. (2006). There is No Special Problem about Scientific Representation. An International Journal for Theory, History and Foundations of Science. 21/1(55), 67-85.
Contessa, G. (2006). Scientific Models, Partial Structures and the New Received View of Theories. Studies in History and Philosophy of Science, 37, 370–377.
Da Costa, N., & French, S. Science and Partial Truth: A Unitary Approach to Models and Scientific Reasoning. Oxford: Oxford University Press, 2003.
Elgin, C. Z. (2009). Exemplification, Idealization, and Scientific Understanding. M. Suárez (Ed.), Fictions in Science: Philosophical Essays on Modeling and Idealization (ss. 77-90). New York: Routledge.
French, S., & Vickers, P. (2011). Are There No Things That are Scientific Theories?. British Journal of Philosophy of Science, 62, 771-804.
Frigg, R., & Nguyen J. (2017). Models and Representation. L. Magnani & T. Bertolotti (Ed.), Springer Handbook of Model-Based Science (ss. 49-102). Berlin: Springer.
Frigg, R., & Nguyen J. (2021). Scientific Representation. The Stanford Encyclopedia of Philosophy (Winter 2021 Edition), Edward N. Zalta (ed.), https://plato.stanford.edu/archives/win2021/entries/scientific-representation
Frigg, R., & Hartmann, S. (2012). Models in Science. E. N. Zalta (Ed.), The Stanford Encyclopedia of Philosophy. Erişim: https://plato.stanford.edu/archives/sum2018/entries/models-science/.
Frigg, R. (2010). Fiction and Scientific Representation. R. Frigg & M. C. Hunter (Ed.), Beyond Memesis and Convention: Representation in Art and Science (ss.97-138). New York: Springer.
Giere, R. N. (2010). An Agent-Based Conception of Models and Scientific Representation. Synthese, 172, 269-281.
Giere, R. N. (1988). Explaining Science: A Cognitive Approach. Chicago: The University of Chicago Press.
Goodman, N. (1968). Languages of Art. Indianapolis: The Bobbs-Merrill Company, Inc.
Humphreys, P., & Imbert, C. (2012). Models, Simulations and Representation. New York: Routledge.
Knuuttila, T. (2005). Models as Epistemic Artefacts: Toward a Non-Representationalist Account of Scientific Representation. Helsinki: University of Helsinki.
Morrison, M. (2015). Reconstructing Reality: Models, Mathematics and Simulations. New York: Oxford University Press.
Morrison, M. (2008). Models as Representational Structures. S. Hartmann, C. Hoefer, & L. Bovens (Ed.), Nancy Cartwright’s Philosophy of Science (ss. 67-88). New York: Routledge.
Peschard, I. (2011). Making Sense of Modeling: Beyond Representation. European Journal for Philosophy of Science, 1, 335-352.
Pincock, C. (2005). Overextending Partial Structures: Idealization and Abstraction. Philosophy of Science, 72(5), 1248-1259.
Suárez, M. (2004). An Inferential Conception of Scientific Representation. Philosophy of Science, 71(5), 767-779.
Suárez, M. (2003). Scientific Representation: Against Similarity and Isomorphism.
International Studies in the Philosophy of Science, 17(3), 225-244.
Suppe, F. (1977). The Structure of Scientific Theories. Urbana University of Illinois Press.
Suppes, P. (1960). A Comparison of the Meaning and Uses of Models in Mathematics and the Empirical Sciences. Synthese 12/2(3), 287-301.
Swoyer, C. (1991). Structural Representation and Surrogative Reasoning. Synthese, 87, 449-508.
Teller, P. (2001). Twilight of the Perfect Model Model. Erkenntnis, 55(3), 393-415.
Toon, A. (2012). Models as Make-Believe: Imagination, Fiction and Scientific Representation. Basingstoke: Palgrave-MacMillan.
Toon, A. (2010). Models as Make-Believe. R. Frigg & M. Hunter (Ed.), Beyond Mimesis and Convention: Representation in Science and Art (ss. 71-96). Dordrecht: Springer.
Van Fraassen, B. C. (2008). Scientific Representation: Paradoxes of Perspective. Oxford: Clarendon Press.
Weisberg, M. (2013). Simulation and Similarity: Using Models to Understand the World. New York: Oxford University Press.
Downloads
Published
Issue
Section
License
Copyright (c) 2022 Onur Kabil (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain copyright of their work.
All content published in this journal is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
This license permits unrestricted use, distribution, and reproduction in any medium, provided that the original work is properly cited.
https://creativecommons.org/licenses/by/4.0/
