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  1. The Structure of Scientific Theories.Rasmus Grønfeldt Winther - 2015 - Stanford Encyclopedia of Philosophy.
    Scientific inquiry has led to immense explanatory and technological successes, partly as a result of the pervasiveness of scientific theories. Relativity theory, evolutionary theory, and plate tectonics were, and continue to be, wildly successful families of theories within physics, biology, and geology. Other powerful theory clusters inhabit comparatively recent disciplines such as cognitive science, climate science, molecular biology, microeconomics, and Geographic Information Science (GIS). Effective scientific theories magnify understanding, help supply legitimate explanations, and assist in formulating predictions. Moving from their (...)
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  • Modelle.Stephan Hartmann & Daniela Bailer-Jones - 2010 - In Hans Jörg Sandkühler & Others (eds.), Enzyklopädie Philosophie. Meiner Verlag. pp. 1627-1632.
    Der Begriff ‘Modell’ leitet sich vom Lateinischen ‘modulus’ (das Maß) ab, im Italienischen existiert seit dem 16. Jh. ‘modello’ und R. Descartes verwendet im 17. Jh. ‘modèlle’. Während der Begriff in Architektur und Kunst schon seit der Renaissance gängig ist, wird er in den Naturwissenschaften erst im 19. Jh. verwendet.1 Dort greifen wissenschaftliche Modelle die für eine gegebene Problemstellung als wesentlich erachteten Charakteristika (Eigenschaften, Beziehungen, etc.) eines Untersuchungsgegenstandes heraus und machen diesen so einem Verständnis bzw. einer weiterführenden Untersuchung zugänglich. Es (...)
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  • Mathematical Modeling in Biology: Philosophy and Pragmatics.Rasmus Grønfeldt Winther - 2012 - Frontiers in Plant Evolution and Development 2012:1-3.
    Philosophy can shed light on mathematical modeling and the juxtaposition of modeling and empirical data. This paper explores three philosophical traditions of the structure of scientific theory—Syntactic, Semantic, and Pragmatic—to show that each illuminates mathematical modeling. The Pragmatic View identifies four critical functions of mathematical modeling: (1) unification of both models and data, (2) model fitting to data, (3) mechanism identification accounting for observation, and (4) prediction of future observations. Such facets are explored using a recent exchange between two groups (...)
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  • Mathematical models and reality: A constructivist perspective. [REVIEW]Christian Hennig - 2010 - Foundations of Science 15 (1):29-48.
    To explore the relation between mathematical models and reality, four different domains of reality are distinguished: observer-independent reality, personal reality, social reality and mathematical/formal reality. The concepts of personal and social reality are strongly inspired by constructivist ideas. Mathematical reality is social as well, but constructed as an autonomous system in order to make absolute agreement possible. The essential problem of mathematical modelling is that within mathematics there is agreement about ‘truth’, but the assignment of mathematics to informal reality is (...)
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  • (1 other version)The philosophy of computer science.Raymond Turner - 2013 - Stanford Encyclopedia of Philosophy.
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  • Approximations, idealizations, and models in statistical mechanics.Chuang Liu - 2004 - Erkenntnis 60 (2):235-263.
    In this paper, a criticism of the traditional theories of approximation and idealization is given as a summary of previous works. After identifying the real purpose and measure of idealization in the practice of science, it is argued that the best way to characterize idealization is not to formulate a logical model – something analogous to Hempel's D-N model for explanation – but to study its different guises in the praxis of science. A case study of it is then made (...)
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  • How minds can be computational systems.William J. Rapaport - 1998 - Journal of Experimental and Theoretical Artificial Intelligence 10 (4):403-419.
    The proper treatment of computationalism, as the thesis that cognition is computable, is presented and defended. Some arguments of James H. Fetzer against computationalism are examined and found wanting, and his positive theory of minds as semiotic systems is shown to be consistent with computationalism. An objection is raised to an argument of Selmer Bringsjord against one strand of computationalism, namely, that Turing-Test± passing artifacts are persons, it is argued that, whether or not this objection holds, such artifacts will inevitably (...)
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  • Introducción: Modelos y teorías en biología.Pablo Lorenzano - 2016 - Metatheoria – Revista de Filosofía E Historia de la Ciencia 6:5--46.
    Two metascientific concepts that have been ― and still are ― object of philosophical analysis are the concepts of model and theory. But while the concept of scientific theory was one of the concepts to which philosophers of science devoted most attention during the 20th century, it is only in recent decades that the concept of scientific model has come to occupy a central position in philosophical reflection. However, it has done so in such a way that, at present, as (...)
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  • Philosophy of Modeling: Neglected Pages of History.Karlis Podnieks - 2018 - Baltic Journal of Modern Computing 6 (3):279–303.
    The work done in the philosophy of modeling by Vaihinger (1876), Craik (1943), Rosenblueth and Wiener (1945), Apostel (1960), Minsky (1965), Klaus (1966) and Stachowiak (1973) is still almost completely neglected in the mainstream literature. However, this work seems to contain original ideas worth to be discussed. For example, the idea that diverse functions of models can be better structured as follows: in fact, models perform only a single function – they are replacing their target systems, but for different purposes. (...)
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  • Models and theories I: The semantic view revisited.Chuang Liu - 1997 - International Studies in the Philosophy of Science 11 (2):147 – 164.
    The paper, as Part I of a two-part series, argues for a hybrid formulation of the semantic view of scientific theories. For stage-setting, it first reviews the elements of the model theory in mathematical logic (on whose foundation the semantic view rests), the syntactic and the semantic view, and the different notions of models used in the practice of science. The paper then argues for an integration of the notions into the semantic view, and thereby offers a hybrid semantic view, (...)
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  • Holism, conceptual-role semantics, and syntactic semantics.William J. Rapaport - 2002 - Minds and Machines 12 (1):3-59.
    This essay continues my investigation of `syntactic semantics': the theory that, pace Searle's Chinese-Room Argument, syntax does suffice for semantics (in particular, for the semantics needed for a computational cognitive theory of natural-language understanding). Here, I argue that syntactic semantics (which is internal and first-person) is what has been called a conceptual-role semantics: The meaning of any expression is the role that it plays in the complete system of expressions. Such a `narrow', conceptual-role semantics is the appropriate sort of semantics (...)
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  • Models and theories II: Issues and applications.Chuang Liu - 1998 - International Studies in the Philosophy of Science 12 (2):111 – 128.
    This paper is the second of a two-part series on models and theories, the first of which appeared in International Studies in the Philosophy of Science, Vol. 11, No. 2, 1997. It further explores some of themes of the first paper and examines applications, including: the relations between “similarity” and “isomorphism”, and between “model” and “interpretation”, and the notion of structural explanation.
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  • (1 other version)Explanation and Understanding through Scientific Models.Richard David-Rus - 2009 - Dissertation, University Munich
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  • Discussion of David Freedman's “some issues in the foundations of statistics”.James Berger - 1995 - Foundations of Science 1 (1):41-67.
    While results from statistical modelling too often receive blind acceptance, we question whether there is any real alternative to use of modelling. This does not diminish the main point of Professor Freedman, which is that healthy scepticism towards models is needed. While agreeing with many of Professor Freedman's points concerning the objectivist debate, we argue that there is a Bayesian school of objectivists that possesses considerable advantages over the classical objectivist school. At the least, the debate needs to be enlarged (...)
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  • Searches for the origins of the epistemological concept of model in mathematics.Gert Schubring - 2017 - Archive for History of Exact Sciences 71 (3):245-278.
    When did the concept of model begin to be used in mathematics? This question appears at first somewhat surprising since “model” is such a standard term now in the discourse on mathematics and “modelling” such a standard activity that it seems to be well established since long. The paper shows that the term— in the intended epistemological meaning—emerged rather recently and tries to reveal in which mathematical contexts it became established. The paper discusses various layers of argumentations and reflections in (...)
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  • Naturalizing Theorizing: Beyond a Theory of Biological Theories. [REVIEW]Werner Callebaut - 2013 - Biological Theory 7 (4):413-429.
    Although “theory” has been the prevalent unit of analysis in the meta-study of science throughout most of the twentieth century, the concept remains elusive. I further explore the leitmotiv of several authors in this issue: that we should deal with theorizing (rather than theory) in biology as a cognitive activity that is to be investigated naturalistically. I first contrast how philosophers and biologists have tended to think about theory in the last century or so, and consider recent calls to upgrade (...)
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  • Quantification and Realism: Locating Semiosis in the Description of Biological Systems.Claudio J. Rodríguez Higuera - 2021 - Biosemiotics 14 (2):241-252.
    What do we quantify when we attempt to quantify semiotic systems and theories? How sound are potential quantifications in terms of interpretive values within some varieties of semiotic theory? We will make a distinction between formalization and quantification in order to understand what to quantify, how to quantify it and why quantification may be a desirable outcome for semiotic theory. The implications of this stance may be relevant and philosophically interesting in light of the naturalized project of biosemiotics. In this (...)
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