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Scientific fictions as rules of inference

In Fictions in Science: Philosophical Essays on Modeling and Idealization. Routledge. pp. 158--178 (2009)

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  1. Theories, models, and representations.Mauricio Suárez - 1999 - In L. Magnani, N. J. Nersessian & P. Thagard (eds.), Model-Based Reasoning in Scientific Discovery. Kluwer/Plenum. pp. 75--83.
    I argue against an account of scientific representation suggested by the semantic, or structuralist, conception of scientific theories. Proponents of this conception often employ the term “model” to refer to bare “structures”, which naturally leads them to attempt to characterize the relation between models and reality as a purely structural one. I argue instead that scientific models are typically “representations”, in the pragmatist sense of the term: they are inherently intended for specific phenomena. Therefore in general scientific models are not (...)
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  • A companion to cognitive science.William Bechtel & George Graham - 1996 - In Dennis M. Patterson (ed.), A Companion to Philosophy of Law and Legal Theory. Blackwell.
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  • General Propositions and Causality.Frank Plumpton Ramsey - 1929 - In The Foundations of Mathematics and other Logical Essays. Kegan Paul, Trench, Trübner. pp. 237-255.
    This article rebuts Ramsey's earlier theory, in 'Universals of Law and of Fact', of how laws of nature differ from other true generalisations. It argues that our laws are rules we use in judging 'if I meet an F I shall regard it as a G'. This temporal asymmetry is derived from that of cause and effect and used to distinguish what's past as what we can know about without knowing our present intentions.
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  • Language, truth and reason.Ian Hacking - 1982 - In Martin Hollis & Steven Lukes (eds.), Rationality and Relativism. MIT Press. pp. 48--66.
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  • Built-in justification.Marcel J. Boumans - unknown
    In several accounts of what models are and how they function a specific view dominates. This view contains the following characteristics. First, there is a clear-cut distinction between theories, models and data and secondly, empirical assessment takes place after the model is built. This view in which discovery and justification are disconnected is not in accordance with several practices of mathematical business-cycle model building. What these practices show is that models have to meet implicit criteria of adequacy, such as satisfying (...)
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  • Models: The Third Dimension of Science.Soraya de Chadarevian & Nick Hopwood - 2006 - Journal of the History of Biology 39 (1):224-226.
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  • Economics as robustness analysis.Jaakko Kuorikoski, Aki Lehtinen & Caterina Marchionni - unknown
    All economic models involve abstractions and idealisations. Economic theory itself does not tell which idealizations are truly fatal or harmful for the result and which are not. This is why much of what is seen as theoretical contribution in economics is constituted by deriving familiar results from different modelling assumptions. If a modelling result is robust with respect to particular modelling assumptions, the empirical falsity of these particular assumptions does not provide grounds for criticizing the result. In this paper we (...)
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  • Remarks on models and their truth.Uskali Mäki - 2006 - Storia Del Pensiero Economico. Nuova Serie 3 (1):7-19.
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  • On the method of isolation in economics.Uskali Mäki - 1992 - Poznan Studies in the Philosophy of the Sciences and the Humanities 26:19-54.
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  • Explaining Explanation: A Realist Account of Scientific Explanation and Understanding.Peter Railton - 1980 - Dissertation, Princeton University
    The orthodox, empiricist covering-law account of scientific explanation, as developed by C. G. Hempel and others, has long dominated philosophical discussions of scientific explanation. In recent years it has met overwhelming critical resistance. We should give up this account of scientific ex.
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  • Problems in the History of Fictionalism.Gideon Rosen - 2005 - In Mark Eli Kalderon (ed.), Fictionalism in Metaphysics. Oxford University Press. pp. 14--64.
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  • 15 Scientific cognition as distributed cognition.Ronald Giere - 2002 - In Peter Carruthers, Stephen P. Stich & Michael Siegal (eds.), The Cognitive Basis of Science. Cambridge University Press. pp. 285.
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  • Models of data.Patrick Suppes - 1962 - In Ernest Nagel, Patrick Suppes & Alfred Tarski (eds.), Logic, Methodology and Philosophy of Science Proceedings of the 1960 International Congress.
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  • Bell's Theorem, Ideology, and Structural Explanation.R. I. G. Hughes - 1989 - In James T. Cushing & Ernan McMullin (eds.), Philosophical Consequences of Quantum Theory. University of Notre Dame Press. pp. 195--207.
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  • The Right Tools for the Job: At Work in Twentieth-Century Life Sciences.Adele E. Clarke & Joan H. Fujimura - 1994 - Journal of the History of Biology 27 (1):172-174.
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  • The Methodology of Positive Economics.Milton Friedman - 1953 - In Essays in Positive Economics. University of Chicago Press. pp. 3-43.
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  • Meaning and Interpretation: Wittgenstein, Henry James, and Literary Knowledge.G. L. Hagberg - 1997 - Philosophical Quarterly 47 (186):106-108.
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  • The sturdy protestants of science: Larmor, Trouton, and the earth's motion through the ether.Andrew Warwick - 1995 - In Jed Z. Buchwald (ed.), Scientific Practice: Theories and Stories of Doing Physics. University of Chicago Press. pp. 300--343.
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  • Representation in science.Paul Teller - 2008 - In Stathis Psillos & Martin Curd (eds.), Routledge Companion to the Philosophy of Science. Routledge.
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  • How do Scientists Think? Capturing the Dynamics of Conceptual Change in Science.Nancy Nersessian - 1992 - In R. Giere & H. Feigl (eds.), Cognitive Models of Science. University of Minnesota Press. pp. 3--45.
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