David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Models are generally used by scientists to obtain predictions and to provide explanations about phenomena. Their predictive and explanatory power is generally thought of as depending on their representative power. It is still not clear, though, in virtue of which features models allow scientists to draw inferences about the system they stand for. In this paper, I focus on a special kind of models, namely imaginary models (I-models) such as the simple pendulum. The main question I address is: how do scientists use I-models in representing target systems? First, I propose a clarification of the very notion of representation, by emphasizing the importance of what I call the format of a representation to the inferences cognitive agents can draw from it. Then, I analyze the various representational relationships that are in play in the use of I-models. I finally conclude that there is no special semantics to be applied to I-models, and that the study of the representational power of models in general should instead focus on the variety of the formats that are used in scientific practice.
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library||
References found in this work BETA
No references found.
Citations of this work BETA
Jaakko Kuorikoski & Aki Lehtinen (2009). Incredible Worlds, Credible Results. Erkenntnis 70 (1):119 - 131.
Similar books and articles
Roman Frigg (2006). Scientific Representation and the Semantic View of Theories. Theoria 21 (1):49-65.
Ronald N. Giere (2004). How Models Are Used to Represent Reality. Philosophy of Science 71 (5):742-752.
Alisa Bokulich (2011). How Scientific Models Can Explain. Synthese 180 (1):33 - 45.
Tarja Knuuttila (2011). Modelling and Representing: An Artefactual Approach to Model-Based Representation. Studies in History and Philosophy of Science 42 (2):262-271.
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.
Gabriele Contessa (2007). Representing Reality: The Ontology of Scientific Models and Their Representational Function. Dissertation, University of London
Tarja Knuuttila (2005). Models, Representation, and Mediation. Philosophy of Science 72 (5):1260-1271.
Marion Vorms (2011). Formats of Representation in Scientific Theorizing. In Paul Humphreys & Cyrille Imbert (eds.), Models, Simulations, and Representations. Routledge.
Marion Vorms (2011). Representing with Imaginary Models: Formats Matter. Studies in History and Philosophy of Science 42 (2):287-295.
Added to index2009-01-28
Total downloads45 ( #37,792 of 1,102,738 )
Recent downloads (6 months)2 ( #182,643 of 1,102,738 )
How can I increase my downloads?