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  1. Why a Diagram is (Sometimes) Worth Ten Thousand Words.Jill H. Larkin & Herbert A. Simon - 1987 - Cognitive Science 11 (1):65-100.
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  • A comparison of the meaning and uses of models in mathematics and the empirical sciences.Patrick Suppes - 1960 - Synthese 12 (2-3):287--301.
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  • (1 other version)There Is No Special Problem About Scientific Representation.Craig Callender & Jonathan Cohen - 2006 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 21 (1):67-85.
    We propose that scientific representation is a special case of a more general notion of representation, and that the relatively well worked-out and plausible theories of the latter are directly applicable to thc scientific special case. Construing scientific representation in this way makes the so-called “problem of scientific representation” look much less interesting than it has seerned to many, and suggests that some of the (hotly contested) debates in the literature are concerned with non-issues.
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  • (1 other version)Models and fiction.Roman Frigg - 2007 - Synthese 172 (2):251-268.
    Most scientific models are not physical objects, and this raises important questions. What sort of entity are models, what is truth in a model, and how do we learn about models? In this paper I argue that models share important aspects in common with literary fiction, and that therefore theories of fiction can be brought to bear on these questions. In particular, I argue that the pretence theory as developed by Walton (1990, Mimesis as make-believe: on the foundations of the (...)
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  • Second thoughts on paradigms.Thomas Samuel Kuhn - 1981 - In David Zaret (ed.), Review of Thomas S. Kuhn The Essential Tension: Selected Studies in Scientific Tradition and Change. Duke University Press. pp. 293--319.
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  • Formats of representation in scientific theorizing.Marion Vorms - 2011 - In Paul Humphreys & Cyrille Imbert (eds.), Models, Simulations, and Representations. New York: Routledge. pp. 250-273.
    This paper is intended to sketch the definition of a methodological tool -- the notion of a format of representation -- for the study of scientific theorising. One of its main assumption is that a philosophical study of theorising needs to pay attention to other types of units of analysis than the traditional ones, namely, theories and models approached in a logical and structural way, since scientific reasoning is always led on concrete representational devices and depends upon their specific properties. (...)
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  • (2 other versions)Scientific representation and the semantic view of theories.Roman Frigg - 2006 - Theoria 21 (1):49-65.
    It is now part and parcel of the official philosophical wisdom that models are essential to the acquisition and organisation of scientific knowledge. It is also generally accepted that most models represent their target systems in one way or another. But what does it mean for a model to represent its target system? I begin by introducing three conundrums that a theory of scientific representation has to come to terms with and then address the question of whether the semantic view (...)
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  • Scientific representation: Against similarity and isomorphism.Mauricio Suárez - 2003 - International Studies in the Philosophy of Science 17 (3):225-244.
    I argue against theories that attempt to reduce scientific representation to similarity or isomorphism. These reductive theories aim to radically naturalize the notion of representation, since they treat scientist's purposes and intentions as non-essential to representation. I distinguish between the means and the constituents of representation, and I argue that similarity and isomorphism are common but not universal means of representation. I then present four other arguments to show that similarity and isomorphism are not the constituents of scientific representation. I (...)
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  • (3 other versions)Models and Representation: Why Structures Are Not Enough.Roman Frigg - manuscript
    Models occupy a central role in the scientific endeavour. Among the many purposes they serve, representation is of great importance. Many models are representations of something else; they stand for, depict, or imitate a selected part of the external world (often referred to as target system, parent system, original, or prototype). Well-known examples include the model of the solar system, the billiard ball model of a gas, the Bohr model of the atom, the Gaussian-chain model of a polymer, the MIT (...)
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  • Why a diagram is (sometimes) worth 10, 000 word.Jill H. Larkin & Herbert A. Simon - 1987 - Cognitive Science 11 (1):65-99.
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  • (4 other versions)Conceptual role semantics.Mark Greenberg & Gilbert Harman - 2005 - In Ernie Lepore & Barry C. Smith (eds.), The Oxford Handbook of Philosophy of Language. Oxford, England: Oxford University Press.
    CRS says that the meanings of expressions of a language or other symbol system or the contents of mental states are determined and explained by the way symbols are used in thinking. According to CRS one.
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  • The strategy of model-based science.Peter Godfrey-Smith - 2006 - Biology and Philosophy 21 (5):725-740.
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  • (4 other versions)(Nonsolipsistic) conceptual role semantics.Gilbert Harman - 1987 - In Ernest LePore (ed.), New directions in semantics. Orlando: Academic Press. pp. 55–81.
    CRS says that the meanings of expressions of a language or other symbol system or the contents of mental states are determined and explained by the way symbols are used in thinking. According to CRS one.
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  • Knowing with images: Medium and message.John Kulvicki - 2010 - Philosophy of Science 77 (2):295-313.
    Problems concerning scientists’ uses of representations have received quite a bit of attention recently. The focus has been on how such representations get their contents and on just what those contents are. Less attention has been paid to what makes certain kinds of scientific representations different from one another and thus well suited to this or that epistemic end. This article considers the latter question with particular focus on the distinction between images and graphs on the one hand and descriptions (...)
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  • Reflections on my critics.Ts Khn - 1970 - In Imre Lakatos & Alan Musgrave (eds.), Criticism and the growth of knowledge. Cambridge [Eng.]: Cambridge University Press.
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  • (1 other version)There Is No Special Problem About Scientific Representation.Craig Callender & Jonathan Cohen - 2006 - Theoria 21 (1):67-85.
    We propose that scientific representation is a special case of a more general notion of representation, and that the relatively well worked-out and plausible theories of the latter are directly applicable to the scientific special case.
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  • Theories, models, and representations.Mauricio Suárez - 1999 - In L. Magnani, Nancy Nersessian & Paul 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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  • (1 other version)Models and fiction.Roman Frigg - 2010 - Synthese 172 (2):251-268.
    Most scientific models are not physical objects, and this raises important questions. What sort of entity are models, what is truth in a model, and how do we learn about models? In this paper I argue that models share important aspects in common with literary fiction, and that therefore theories of fiction can be brought to bear on these questions. In particular, I argue that the pretence theory as developed by Walton (1990, Mimesis as make-believe: on the foundations of the (...)
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