Disentangling scientific representation
| Abstract | The main aim of this paper is to disentangle three senses in which we can say that a model represents a system—denotation epistemic representation, and successful epistemic representation--and to individuate what questions arise from each sense of the notion of representation as used in this context. Also, I argue that a model is an epistemic representation of a system only if a user adopts a general interpretation of the model in terms of a system. In the process, I hope to clarify where those who, following Craig Callander and Jonathan Cohen, claim that there is no special problem about scientific representation go wrong. In the terminology adopted here, even if scientific representation is only an instance of epistemic representation, scientific representation should not be confounded with denotation. | |||||||||
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Tarja Knuuttila (2011). Modelling and Representing: An Artefactual Approach to Model-Based Representation. Studies in History and Philosophy of Science 42 (2):262-271.
Axel Gelfert (2011). Mathematical Formalisms in Scientific Practice: From Denotation to Model-Based Representation. Studies in History and Philosophy of Science 42 (2):272-286.
Mauricio Suarez (2003). Scientific Representation: Against Similarity and Isomorphism. International Studies in the Philosophy of Science 17 (3):225-244.
Adam Toon (2010). Models as Make-Believe. In Roman Frigg & Matthew Hunter (eds.), Beyond Mimesis and Convention: Representation in Art and Science. Boston Studies in Philosophy of Science.
Jonathan Cohen & Callender Craig (2006). There is No Special Problem About Scientific Representation. Theoria 55 (1):67-85.
Craig Callender & Jonathan Cohen (2006). There is No Special Problem About Scientific Representation. Theoria 21 (1):67-85.
Gabriele Contessa (2007). Scientific Representation, Interpretation, and Surrogative Reasoning. Philosophy of Science 74 (1):48-68.
Gabriele Contessa (2007). Representing Reality: The Ontology of Scientific Models and Their Representational Function. Dissertation, University of London
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