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  1. (1 other version)Models in Science (2nd edition).Roman Frigg & Stephan Hartmann - 2021 - The Stanford Encyclopedia of Philosophy.
    Models are of central importance in many scientific contexts. The centrality of models such as inflationary models in cosmology, general-circulation models of the global climate, the double-helix model of DNA, evolutionary models in biology, agent-based models in the social sciences, and general-equilibrium models of markets in their respective domains is a case in point (the Other Internet Resources section at the end of this entry contains links to online resources that discuss these models). Scientists spend significant amounts of time building, (...)
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  • The Scientific Image.William Demopoulos & Bas C. van Fraassen - 1982 - Philosophical Review 91 (4):603.
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  • Models of data.Patrick Suppes - 2009 - In Ernest Nagel, Patrick Suppes & Alfred Tarski (eds.), Provability, Computability and Reflection. Stanford, CA, USA: Elsevier.
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  • Intrinsic Motivation and Self-Determination in Human Behavior.Edward L. Deci & Richard M. Ryan - 2013 - Springer Verlag.
    Early in this century, most empirically oriented psychologists believed that all motivation was based in the physiology of a set of non-nervous system tissue needs. The theories of that era reflected this belief and used it in an attempt to explain an increasing number of phenomena. It was not until the 1950s that it became irrefutably clear that much of human motivation is based not in these drives, but rather in a set of innate psychological needs. Their physiological basis is (...)
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  • (1 other version)La théorie physique: son objet et sa structure.P. Duhem - 1906 - Revue Philosophique de la France Et de l'Etranger 61:324-327.
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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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  • 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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  • Multiple factor analysis.L. L. Thurstone - 1931 - Psychological Review 38 (5):406-427.
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  • Reflections on the revolution at Stanford.F. A. Muller - 2011 - Synthese 183 (1):87--114.
    We inquire into the question whether the Aristotelean or classical \emph{ideal} of science has been realised by the Model Revolution, initiated at Stanford University during the 1950ies and spread all around the world of philosophy of science --- \emph{salute} P.\ Suppes. The guiding principle of the Model Revolution is: \emph{a scientific theory is a set of structures in the domain of discourse of axiomatic set-theory}, characterised by a set-theoretical predicate. We expound some critical reflections on the Model Revolution; the conclusions (...)
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  • The Duhem thesis.Roger Ariew - 1984 - British Journal for the Philosophy of Science 35 (4):313-325.
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  • The theoretical status of latent variables.Denny Borsboom, Gideon J. Mellenbergh & Jaap van Heerden - 2003 - Psychological Review 110 (2):203-219.
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  • Understanding Scientific Theories: An Assessment of Developments, 1969–1998.Frederick Suppe - 2000 - Philosophy of Science 67 (3):115.
    The positivistic Received View construed scientific theories syntactically as axiomatic calculi where theoretical terms were given a partial semantic interpretation via correspondence rules connecting them to observation statements. This paper assesses what, with hindsight, seem the most important defects in the Received View; surveys the main proposed successor analyses to the Received View--various Semantic Conception versions and the Structuralist Analysis; evaluates how well they avoid those defects; examines what new problems they face and where the most promising require further development (...)
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  • The New Experimentalism, Topical Hypotheses, and Learning from Error.Deborah G. Mayo - 1994 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1994:270-279.
    An important theme to have emerged from the new experimentalist movement is that much of actual scientific practice deals not with appraising full-blown theories but with the manifold local tasks required to arrive at data, distinguish fact from artifact, and estimate backgrounds. Still, no program for working out a philosophy of experiment based on this recognition has been demarcated. I suggest why the new experimentalism has come up short, and propose a remedy appealing to the practice of standard error statistics. (...)
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  • Statistical concepts in philosophy of science.Patrick Suppes - 2007 - Synthese 154 (3):485--496.
    This article focuses on the role of statistical concepts in both experiment and theory in various scientific disciplines, especially physics, including astronomy, and psychology. In Sect. 1 the concept of uncertainty in astronomy is analyzed from Ptolemy to Laplace and Gauss. In Sect. 2 theoretical uses of probability and statistics in science are surveyed. Attention is focused on the historically important example of radioactive decay. In Sect. 3 the use of statistics in biology and the social sciences is examined, with (...)
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  • Exploratory factor analysis, instruments and the logic of discovery.Davis Baird - 1987 - British Journal for the Philosophy of Science 38 (3):319-337.
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  • Old and New Ideas for Data Screening and Assumption Testing for Exploratory and Confirmatory Factor Analysis.David B. Flora, Cathy LaBrish & R. Philip Chalmers - 2012 - Frontiers in Psychology 3.
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  • From probability to causality.Peter Spirtes, Clark Glymour & Richard Scheines - 1991 - Philosophical Studies 64 (1):1 - 36.
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  • Factor analysis, information-transforming instruments, and objectivity: A reply and discussion.Stanley A. Mulaik - 1991 - British Journal for the Philosophy of Science 42 (1):87-100.
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