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  1. Scientific Theories and Empirical Significance.Peter Achinstein - 1965 - Review of Metaphysics 19:758-769.
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  2. Minnesota Studies in the Philosophy of Science. Volume IV: Analyses of Theories and Methods of Physics and Psychology.Volume V: Historical and Philosophical Perspectives of Science. [REVIEW]Robert Ackermann, Michael Radner, Stephen Winokur & Roger Stuewer - 1974 - Journal of Philosophy 71 (13):424.
  3. Recent Semantic Developments on Models.Agustín Adúriz-Bravo - 2015 - Science and Education 24 (9 - 10):1245-1250.
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  4. Embryos in Wax: Models From the Ziegler Studio. With a Reprint of Embryological Wax Models by Friedrich Ziegler. [REVIEW]Samuel Alberti - 2003 - British Journal for the History of Science 36 (3):372-373.
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  5. Idealization.Michael Weisberg Alkistis Elliott‐Graves - 2014 - Philosophy Compass 9 (3):176-185.
    This article reviews the recent literature on idealization, specifically idealization in the course of scientific modeling. We argue that idealization is not a unified concept and that there are three different types of idealization: Galilean, minimalist, and multiple models, each with its own justification. We explore the extent to which idealization is a permanent feature of scientific representation and discuss its implications for debates about scientific realism.
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  6. Models, Mechanisms, and Animal Minds.Colin Allen - 2014 - Southern Journal of Philosophy 52 (S1):75-97.
    In this paper, I describe grounds for dissatisfaction with certain aspects of the sciences of animal cognition and argue that a turn toward mathematical modeling of animal cognition is warranted. I consider some objections to this call and argue that the implications of such a turn are not as drastic for ordinary, commonsense understanding of animal minds as they might seem.
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  7. A Multiagent Approach to Modelling Complex Phenomena.Francesco Amigoni & Viola Schiaffonati - 2008 - Foundations of Science 13 (2):113-125.
    Designing models of complex phenomena is a difficult task in engineering that can be tackled by composing a number of partial models to produce a global model of the phenomena. We propose to embed the partial models in software agents and to implement their composition as a cooperative negotiation between the agents. The resulting multiagent system provides a global model of a phenomenon. We applied this approach in modelling two complex physiological processes: the heart rate regulation and the glucose-insulin metabolism. (...)
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  8. Model Validation: Perspectives in Hydrological Science.Malcolm G. Anderson & Paul D. Bates (eds.) - 2001 - Wiley.
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  9. Inverse Ontomimetic Simulation: A Window on Complex Systems.Claes Andersson - unknown -
    The present paper introduces "ontomimetic simulation" and argues that this class of models has enabled the investigation of hypotheses about complex systems in new ways that have epistemological relevance. Ontomimetic simulation can be differentiated from other types of modeling by its reliance on causal similarity in addition to representation. Phenomena are modeled not directly but via mimesis of the ontology (i.e. the "underlying physics", microlevel etc.) of systems and a subsequent animation of the resulting model ontology as a dynamical system. (...)
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  10. A Finite Memory Argument for an Axiomatic Conception of Scientific Theories.Holger Andreas - 2015 - International Studies in the Philosophy of Science 29 (2):113-127.
    This article concerns the split between syntactic and semantic approaches to scientific theories. It aims at showing that an axiomatic representation of a scientific theory is a precondition of comprehending if the models of contain infinite entities. This result is established on the basis of the proposition that the human mind—which is finitely bounded for all we know—is not capable of directly grasping infinite entities. In view of this cognitive limitation, an indirect and finite representation of possibly infinite components of (...)
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  11. Scientific Theories of Computational Systems in Model Checking.Nicola Angius & Guglielmo Tamburrini - 2011 - Minds and Machines 21 (2):323-336.
    Model checking, a prominent formal method used to predict and explain the behaviour of software and hardware systems, is examined on the basis of reflective work in the philosophy of science concerning the ontology of scientific theories and model-based reasoning. The empirical theories of computational systems that model checking techniques enable one to build are identified, in the light of the semantic conception of scientific theories, with families of models that are interconnected by simulation relations. And the mappings between these (...)
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  12. Towards the Formal Study of Models in the Non-Formal Sciences.Leo Apostel - 1960 - Synthese 12 (2-3):125 - 161.
    I. The function of models in the empirical sciencesII. Structure and purpose: conditions of a structural nature which models should satisfy in order to accomplish their function.III. Generalisation and specialisation of the classical definition of model, in view of the above requirements:the algebraic model conceptthe semantic model conceptthe syntactical model conceptIV. Attempt towards reunification: the concept of model on a pragmatic basis.
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  13. Is Discretization a Change in Mathematical Idealization ?Vincent Ardourel - unknown -
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  14. Methode, Statistik Und Modell in den Sozialwissenschaften.Gerhard Arminger - 1983 - Analyse & Kritik 5 (1):3-36.
    The relationship between methods, statistics and models in the social sciences is discussed. New models generalizing commonly used linear models to deal with qualitative and ordinal data are introduced; their basic similarity to linear models is pointed out. Rate models and stochastic linear differential equations to model social processes in continuous time are mentioned. The implications of weak substantial theory and the correct use of statistical significance tests for any kind of model are demonstrated.
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  15. Simulation Models of the Evolution of Cooperation as Proofs of Logical Possibilities: How Useful Are They?Eckhart Arnold - 2013 - Etica E Politica 15 (2):101-138.
    This paper discusses critically what simulation models of the evolution ofcooperation can possibly prove by examining Axelrod’s “Evolution of Cooperation” and the modeling tradition it has inspired. Hardly any of the many simulation models of the evolution of cooperation in this tradition have been applicable empirically. Axelrod’s role model suggested a research design that seemingly allowed to draw general conclusions from simulation models even if the mechanisms that drive the simulation could not be identified empirically. But this research design was (...)
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  16. The Dark Side of the Force: When Computer Simulations Lead Us Astray and ``Model Think'' Narrows Our Imagination --- Pre Conference Draft for the Models and Simulation Conference, Paris, June 12-14 ---. [REVIEW]Eckhart Arnold - unknown -
    This paper is intended as a critical examination of the question of when the use of computer simulations is beneficial to scientific explanations. This objective is pursued in two steps: First, I try to establish clear criteria that simulations must meet in order to be explanatory. Basically, a simulation has explanatory power only if it includes all causally relevant factors of a given empirical configuration and if the simulation delivers stable results within the measurement inaccuracies of the input parameters. If (...)
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  17. On William A. Wallace, O.P., The Modeling of Nature.Benedict Ashley & Eric Reitan - 1997 - The Thomist 61:625-640.
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  18. Are (the Log‐Odds of) Hospital Mortality Rates Normally Distributed? Implications for Studying Variations in Outcomes of Medical Care.Peter C. Austin - 2009 - Journal of Evaluation in Clinical Practice 15 (3):514-523.
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  19. Creating Analogies-on Aspects of the Mapping Process Between Knowledge Domains.Thomas Bachmann - 1997 - Poznan Studies in the Philosophy of the Sciences and the Humanities 56:75-96.
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  20. Economic Models and Reality: The Role of Informal Scientific Methods.Roger E. Backhouse - 2002 - In Uskali Mäki (ed.), Fact and Fiction in Economics: Models, Realism and Social Construction. Cambridge University Press. pp. 202--213.
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  21. The ‘Big Picture’: The Problem of Extrapolation in Basic Research.T. M. Baetu - 2016 - British Journal for the Philosophy of Science 67 (4):941-964.
    Both clinical research and basic science rely on the epistemic practice of extrapolation from surrogate models, to the point that explanatory accounts presented in review papers and biology textbooks are in fact composite pictures reconstituted from data gathered in a variety of distinct experimental setups. This raises two new challenges to previously proposed mechanistic-similarity solutions to the problem of extrapolation: one pertaining to the absence of mechanistic knowledge in the early stages of research and the second to the large number (...)
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  22. Creative Strategies Employed in Modelling: A Case Study. [REVIEW]D. M. Bailer-Jones - 1999 - Foundations of Science 4 (4):375-388.
    This paper examines creative strategies employed inscientific modelling. It is argued that being creativepresents not a discrete event, but rather an ongoingeffort consisting of many individual `creative acts''.These take place over extended periods of time andcan be carried out by different people, working ondifferent aspects of the same project. The example ofextended extragalactic radio sources shows that, inorder to model a complicated phenomenon in itsentirety, the modelling task is split up into smallerproblems that result in several sub-models. This is away (...)
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  23. Operationalism, Logical Empiricism and the Murkiness of Models.Daniela M. Bailer-Jones - 2007 - Revista Portuguesa de Filosofia 63 (1/3):145 - 167.
    In the first half of the 20th century, scientific models were hardly mentioned in philosophy of science. Models were not thought to be central elements of science, in contrast to theories. This attitude can be better understood when considering philosophical trends - Operationalism and Logical Empiricism - and scientific developments - the advent of quantum theory and relativity theory. This paper traces the philosophical currents and positions that prevented models from being recognized as playing an important role in science. It (...)
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  24. Modelling Extended Extragalactic Radio Sources.Daniela M. Bailer-Jones - 2000 - Studies in History and Philosophy of Science Part B 31 (1):49-74.
    This paper examines the process of modelling a complex empirical phenomenon in modern astrophysics: extended extragalactic radio sources. I show that modelling is done piecemeal, addressing selected striking or puzzling features of that phenomenon separately and individually. The result is various independent and separate sub-models concerned only with limited aspects of the same phenomenon. Because the sub-models represent features of the same physical phenomenon, they need to be reasonably consistent with each other - a criterion not always fully adhered to (...)
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  25. Tracing the Development of Models in the Philosophy of Science.Daniela M. Bailer-Jones - 1999 - In L. Magnani, N. J. Nersessian & P. Thagard (eds.), Model-Based Reasoning in Scientific Discovery. Kluwer/Plenum. pp. 23--40.
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  26. Christopher Pincockmathematics and Scientific Representation.Alan Baker - 2015 - British Journal for the Philosophy of Science 66 (3):695-699.
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  27. Structuralist Theory of Science.Wolfgang Balzer & C. Ulises Moulines - 1999 - Erkenntnis 51 (2):353-356.
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  28. Steiner on the Applicability of Mathematics and Naturalism.S. Bangu - 2006 - Philosophia Mathematica 14 (1):26-43.
    Steiner defines naturalism in opposition to anthropocentrism, the doctrine that the human mind holds a privileged place in the universe. He assumes the anthropocentric nature of mathematics and argues that physicists' employment of mathematically guided strategies in the discovery of quantum mechanics challenges scientists' naturalism. In this paper I show that Steiner's assumption about the anthropocentric character of mathematics is questionable. I draw attention to mathematicians' rejection of what Maddy calls ‘definabilism’, a methodological maxim governing the development of mathematics. I (...)
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  29. The Applicability of Mathematics in Science: Indispensability and Ontology.Sorin Bangu - 2012 - Palgrave-Macmillan.
  30. Wigner's Puzzle for Mathematical Naturalism.Sorin Bangu - 2009 - International Studies in the Philosophy of Science 23 (3):245-263.
    I argue that a recent version of the doctrine of mathematical naturalism faces difficulties arising in connection with Wigner's old puzzle about the applicability of mathematics to natural science. I discuss the strategies to solve the puzzle and I show that they may not be available to the naturalist.
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  31. Beyond Mimesis and Convention: Representation in Art and Science.Katerina Bantinaki - 2012 - International Studies in the Philosophy of Science 26 (1):114 - 118.
    International Studies in the Philosophy of Science, Volume 26, Issue 1, Page 114-118, March 2012.
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  32. The Diversity of Models in Statistical Mechanics: Views About the Structure of Scientific Theories.Anouk Barberousse - 2003 - In Benedikt Löwe, Thoralf Räsch & Wolfgang Malzkorn (eds.), Foundations of the Formal Sciences Ii. Kluwer Academic Publishers. pp. 1--23.
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  33. New Mathematics for Old Physics: The Case of Lattice Fluids.Anouk Barberousse & Cyrille Imbert - 2013 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 44 (3):231-241.
    We analyze the effects of the introduction of new mathematical tools on an old branch of physics by focusing on lattice fluids, which are cellular automata -based hydrodynamical models. We examine the nature of these discrete models, the type of novelty they bring about within scientific practice and the role they play in the field of fluid dynamics. We critically analyze Rohrlich's, Fox Keller's and Hughes' claims about CA-based models. We distinguish between different senses of the predicates “phenomenological” and “theoretical” (...)
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  34. About the Warrants of Computer-Based Empirical Knowledge.Anouk Barberousse & Marion Vorms - 2014 - Synthese 191 (15):3595-3620.
    Computer simulations are widely used in current scientific practice, as a tool to obtain information about various phenomena. Scientists accordingly rely on the outputs of computer simulations to make statements about the empirical world. In that sense, simulations seem to enable scientists to acquire empirical knowledge. The aim of this paper is to assess whether computer simulations actually allow for the production of empirical knowledge, and how. It provides an epistemological analysis of present-day empirical science, to which the traditional epistemological (...)
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  35. Models: The Third Dimension of Science (Review).Jonathan Bard - 2006 - Perspectives in Biology and Medicine 49 (2):299-303.
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  36. The Explanatory Dispensability of Idealizations.Sam Baron - 2016 - Synthese 193 (2):365-386.
    Enhanced indispensability arguments seek to establish realism about mathematics based on the explanatory role that mathematics plays in science. Idealizations pose a problem for such arguments. Idealizations, in a similar way to mathematics, boost the explanatory credentials of our best scientific theories. And yet, idealizations are not the sorts of things that are supposed to attract a realist attitude. I argue that the explanatory symmetry between idealizations and mathematics can potentially be broken as follows: although idealizations contribute to the explanatory (...)
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  37. Glymour and Quine on Theoretical Equivalence.Thomas William Barrett & Hans Halvorson - 2016 - Journal of Philosophical Logic 45 (5):467-483.
    Glymour and Quine propose two different formal criteria for theoretical equivalence. In this paper we examine the relationships between these criteria.
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  38. Analogical Reasoning and Plausibility in the Sciences.Paul Frank Andrew Bartha - 1994 - Dissertation, University of Pittsburgh
    Analogical reasoning plays a significant role in the evolution of scientific thought. Not only is analogy extensively used in the early stages of investigation to demonstrate the plausibility of hypotheses, but in some fields, such as archaeology and evolutionary biology, it is often the strongest possible form of theoretical confirmation. This widely used form of reasoning, however, has seldom been subjected to rigorous examination by philosophers of science. Not surprisingly, there is a notable absence of standards for distinguishing between 'good' (...)
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  39. Science and Fiction: Analysing the Concept of Fiction in Science and its Limits.Ann-Sophie Barwich - 2013 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 44 (2):357-373.
    A recent and growing discussion in philosophy addresses the construction of models and their use in scientific reasoning by comparison with fiction. This comparison helps to explore the problem of mediated observation and, hence, the lack of an unambiguous reference of representations. Examining the usefulness of the concept of fiction for a comparison with non-denoting elements in science, the aim of this paper is to present reasonable grounds for drawing a distinction between these two kinds of representation. In particular, my (...)
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  40. Abstractions and Scientific Knowledge Representation.Valentin Bazhanov - 2013 - Epistemologia 1 (1):74-80.
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  41. Models of Madness, Models of Medicine By Miriam Siegler and Humphry Osmond.William B. Bean - 1975 - Perspectives in Biology and Medicine 18 (4):573-575.
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  42. Testing Bottom-Up Models of Complex Citation Networks.Mark A. Bedau - 2014 - Philosophy of Science 81 (5):1131-1143.
    The robust behavior of the patent citation network is a complex target of recent bottom-up models in science. This paper investigates the purpose and testing of three especially simple bottom-up models of the citation count distribution observed in the patent citation network. The complex causal webs in the models generate weakly emergent patterns of behavior, and this explains both the need for empirical observation of computer simulations of the models and the epistemic harmlessness of the resulting epistemic opacity.
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  43. Models of Critique: Introduction.Yemima Ben-Menahem & Adi Ophir - 1997 - Science in Context 10 (1).
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  44. On Physicalistic Models of Non-Physical Terms.Gustav Bergmann - 1940 - Philosophy of Science 7 (2):151-158.
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  45. Underdetermination, Model-Ensembles and Surprises: On the Epistemology of Scenario-Analysis in Climatology.Gregor Betz - 2009 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 40 (1):3-21.
    As climate policy decisions are decisions under uncertainty, being based on a range of future climate change scenarios, it becomes a crucial question how to set up this scenario range. Failing to comply with the precautionary principle, the scenario methodology widely used in the Third Assessment Report of the International Panel on Climate Change (IPCC) seems to violate international environmental law, in particular a provision of the United Nations Framework Convention on Climate Change. To place climate policy advice on a (...)
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  46. Causal Models as Multiple Working Hypotheses About Environmental Processes.Keith Beven - unknown -
    The environmental modeller faces a dilemma. Science often demands that more and more process representations are incorporated into models. Testing the causal representations in environmental models then depends on specifying boundary conditions and model parameters adequately. This will always be difficult in applications to a real system because of the heterogeneities, non-stationarities, complexities and epistemic uncertainties inherent in environmental prediction. Thus, it can be difficult to define the information content of a data set used in model evaluation and any consequent (...)
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  47. RS: Kaushal's Structural Analogies in Understanding Nature.V. K. Bharadvaj - 2005 - Indian Philosophical Quarterly 32 (1/2).
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  48. Simulating Closed Regimes with Agent Based Models.R. Bhavnani, D. Backer & R. Riolo - 2008 - Complexity 14 (1):36-44.
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  49. Idealizations and the Development of Capital Theory.Jack Birner - 1990 - Poznan Studies in the Philosophy of the Sciences and the Humanities 16:127-149.
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  50. Models: Representation and the Scientific Understanding. By Marx W. Wartofsky.Richard J. Blackwell - 1982 - Modern Schoolman 60 (1):69-69.
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