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  1. Modeling Epistemic Communities.Samuli Reijula & Jaakko Kuorikoski - forthcoming - In Miranda Fricker, Peter J. Graham, David Henderson & Nikolaj Jang Lee Linding Pedersen (eds.), The Routledge Handbook of Social Epistemology. Routledge.
    We review the most prominent modeling approaches in social epistemology aimed at understand- ing the functioning of epistemic communities and provide a philosophy of science perspective on the use and interpretation of such simple toy models, thereby suggesting how they could be integrated with conceptual and empirical work. We highlight the need for better integration of such models with relevant findings from disciplines such as social psychology and organization studies.
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  2. From Galileo to Hubble: Copernican Principle as a Philosophical Dogma Defining Modern Astronomy.Spyridon Kakos - 2018 - International Journal of Theology, Philosophy and Science 2 (3):13-37.
    For centuries the case of Galileo Galilei has been the cornerstone of every major argument against the church and its supposedly unscientific dogmatism. The church seems to have condemned Galileo for his heresies, just because it couldn’t and wouldn’t handle the truth. Galileo was a hero of science wrongfully accused and now – at last – everyone knows that. But is that true? This paper tries to examine the case from the point of modern physics and the conclusions drawn are (...)
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  3. Metaphor in Science.Hossein Dabbagh - 2014 - Tehran, Tehran Province, Iran: Hermes Publisher.
    In this thesis I am going to explain the role of metaphor in articulation of new scientific theories, explicitly speaking, indeed, I have not a word about metaphorical thinking in theory invention, implicitly speaking. In fact, I talk about conceptual metaphor instead of linguistic metaphor. As another classification, this investigation belongs to “justification context”, rather than “discovery context”. Employing Boyd’ ideas on metaphor in science can lend a hand for acquiring this point. In Boyd’ set of beliefs; we need another (...)
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  4. Modelling Inequality.Karim Thébault, Seamus Bradley & Alexander Reutlinger - 2018 - British Journal for the Philosophy of Science 69 (3):691-718.
    Econophysics is a new and exciting cross-disciplinary research field that applies models and modelling techniques from statistical physics to economic systems. It is not, however, without its critics: prominent figures in more mainstream economic theory have criticized some elements of the methodology of econophysics. One of the main lines of criticism concerns the nature of the modelling assumptions and idealizations involved, and a particular target are ‘kinetic exchange’ approaches used to model the emergence of inequality within the distribution of individual (...)
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  5. Knowledge Transfer in Theoretical Ecology: Implications for Incommensurability, Voluntarism, and Pluralism.Justin Donhauser & Jamie Shaw - forthcoming - Studies in History and Philosophy of Science Part A.
    Well-known epistemologies of science have implications for how best to understand knowledge transfer (KT). Yet, to date, no serious attempt has been made explicate these particular implications. This paper infers views about KT from two popular epistemologies; what we characterize as incommensurabilitist views (after Devitt 2001; Bird 2002, 2008; Sankey and Hoyningen-Huene 2013) and voluntarist views (after van Fraassen 1984; Dupré 2001; Chakravartty 2015). We argue views of the former sort define the methodological, ontological, and social conditions under which research (...)
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  6. What Do Symmetries Tell Us About Structure?Thomas William Barrett - 2017 - Philosophy of Science (4):617-639.
    Mathematicians, physicists, and philosophers of physics often look to the symmetries of an object for insight into the structure and constitution of the object. My aim in this paper is to explain why this practice is successful. In order to do so, I present a collection of results that are closely related to (and in a sense, generalizations of) Beth’s and Svenonius’ theorems.
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  7. Philosophy of Science A to Z, Arabic Translation فلسفة العلم من الألف إلى الياء.Salah Osman - 2018 - Cairo, Cairo Governorate, Egypt: Ministry of Culture, National Center for Translation.
    دليل مُرتَّب أبجديًا للمصطلحات الأساسية، وكذلك لأشهر الأعلام، في المجالات المختلفة لفلسفة العلم. يُغطي الكتاب أبرز المشكلات، والمواقف، والتصورات، والحجج التي كانت مثار مناقشات واسعة بين الفلاسفة. والهدف الأساسي له هو فهم المناقشات الحالية من خلال تتبع وتفسير تطوراتها التاريخية وارتباطاتها بالمسائل الفلسفية الأبعد. ومع أن الكتاب يفترض مسبقًا وجود خلفية معرفية بفلسفة العلم لدى القارئ، إلا أنه مفيد بالقدر ذاته لكل من المبتدئين من دارسي فلسفة العلم، والمتخصصين ذوي الخبرات الواسعة، فضلاً عن عامة القُراء. وسوف يجد القارئ من خلال (...)
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  8. Modelling in Applied Physics: The Case of Polymers.Towfic Shomar - 2006 - Dirasat, Pure Science 33 (2):241-250.
    Until recently philosophy of physics has been overshadowed by the idea that the important philosophical issues that can be derived from physics are related only to fundamental theories, such as quantum mechanics and relativity. Applied fields of physics were deemed as unimportant. The argument for such a position lays in thinking that these applied fields of physics depend in their theoretical representations on fundamental theories and hence are reducible to these fundamental theories. It would be hard to defend such a (...)
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  9. Modelling as Indirect Representation? The Lotka–Volterra Model Revisited.Tarja Knuuttila & Andrea Loettgers - 2017 - British Journal for the Philosophy of Science 68 (4):1007-1036.
    ABSTRACT Is there something specific about modelling that distinguishes it from many other theoretical endeavours? We consider Michael Weisberg’s thesis that modelling is a form of indirect representation through a close examination of the historical roots of the Lotka–Volterra model. While Weisberg discusses only Volterra’s work, we also study Lotka’s very different design of the Lotka–Volterra model. We will argue that while there are elements of indirect representation in both Volterra’s and Lotka’s modelling approaches, they are largely due to two (...)
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  10. Systems Biology and Mechanistic Explanation.Ingo Brigandt, Sara Green & Maureen O'Malley - 2018 - In Stuart Glennan & Phyllis McKay Illari (eds.), The Routledge Handbook of Mechanisms and Mechanical Philosophy. New York: Routledge. pp. 362–374.
    We address the question of whether and to what extent explanatory and modelling strategies in systems biology are mechanistic. After showing how dynamic mathematical models are actually required for mechanistic explanations of complex systems, we caution readers against expecting all systems biology to be about mechanistic explanations. Instead, the aim may be to generate topological explanations that are not standardly mechanistic, or to arrive at design principles that explain system organization and behaviour in general, but not specific mechanisms. These abstraction (...)
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  11. Make-Believe and Model-Based Representation in Science: The Epistemology of Frigg’s and Toon’s Fictionalist Views of Modeling.Poznic Michael - 2016 - Teorema: International Journal of Philosophy 35 (3):201-218.
    Roman Frigg and Adam Toon, both, defend a fictionalist view of scientific modeling. One fundamental thesis of their view is that scientists are participating in games of make-believe when they study models in order to learn about the models themselves and about target systems represented by the models. In this paper, the epistemology of these two fictionalist views is critically discussed. I will argue that both views can give an explanation of how scientists learn about models they are studying. However, (...)
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  12. Conceptualizing Fraudulent Studies as Viruses: New Models for Handling Retractions.Kathleen Montgomery & Amalya L. Oliver - 2017 - Minerva 55 (1):49-64.
    This paper addresses the growing problem of retractions in the scientific literature of publications that contain bad data, also called “false science.” While the problem is particularly acute in the biomedical literature because of the life-threatening implications when treatment recommendations and decisions are based on false science, it is relevant for any knowledge domain, including the social sciences, law, and education. Yet current practices for handling retractions are seen as inadequate. We use the metaphor of a virus to illustrate how (...)
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  13. Theoretical Understanding in Science.Mark P. Newman - 2017 - British Journal for the Philosophy of Science 68 (2).
    In this article I develop a model of theoretical understanding in science. This is a philosophical theory that specifies the conditions that are both necessary and sufficient for a scientist to satisfy the construction ‘S understands theory T ’. I first consider how this construction is preferable to others, then build a model of the requisite conditions on the basis of examples from elementary physics. I then show how this model of theoretical understanding can be made philosophically robust and provide (...)
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  14. Annual Modulation Experiments, Galactic Models and WIMPs.Robert G. Hudson - 2006 - Studies in History and Philosophy of Modern Physics 38 (1):97-119.
  15. Commentary on “On Appeals to Models”: Appeals to Visual Models – An Epistemological Reconstruction of an Argument Type.Christoph Lumer - unknown
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  16. How Models Fail. A Critical Look at the History of Computer Simulations of the Evolution of Cooperation.Catrin Misselhorn (ed.) - 2015 - Springer.
    Simulation models of the Reiterated Prisoner's Dilemma have been popular for studying the evolution of cooperation since more than 30 years now. However, there have been practically no successful instances of empirical application of any of these models. At the same time this lack of empirical testing and confirmation has almost entirely been ignored by the modelers community. In this paper, I examine some of the typical narratives and standard arguments with which these models are justified by their authors despite (...)
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  17. The ‘Big Picture’: The Problem of Extrapolation in Basic Research.Tudor 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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  18. Pierre Duhem on the Testing of Hypotheses.Glen C. Joy - 1979 - Philosophy Research Archives 5:1-24.
    In this paper I examine Pierre Duhem's position on the problem of crucial experiments and the falsification of hypotheses. Duhem maintained that conclusive falsification of an isolated hypothesis is impossible; he maintained further that crucial experiments are impossible. But, I argue, this does not imply, as Adolf Grunbaum and others have taken Duhem to imply, that one could always save any hypothesis by making adjustments elsewhere in the system. By analyzing the logic of falsification, by examining the text of Duhem's (...)
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  19. Scientific Theories as Intervening Representations.Andoni Ibarra & Thomas Mormann - 2006 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 21 (1):21-38.
    In this paper some classical representational ideas of Hertz and Duhem are used to show how the dichotomy between representation and intervention can be overcome. More precisely, scientific theories are reconstructed as complex networks of intervening representations. The formal apparatus developed is applied to elucidate various theoretical and practical aspects of the in vivo/in vitro problem of biochemistry. Moreover, adjoint situations are used to explain the relation berween empirical facts and theoretical laws in a new way.
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  20. Scientific Representation and the Semantic View of Theories.Roman Frigg - 2006 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 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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  21. 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 debates in the literature are concerned with non-issues.
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  22. Fictions in Science. Philosophical Essays on Modeling and Idealization. [REVIEW]Xavier de Donato - 2010 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 25 (1):111-114.
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  23. Semiotic Foundation of Models and Modelling.Ladislav Tondl - 2000 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 15 (3):413-420.
    The paper analyses the model as an artefact sui generis establishing the role of semiosis, as a homomorphic representation, as an artefact securing the function of an interface between the author and the receiver. The receiver's ability of accepting the model and its interpretation possibility and/or quality depends on the receiver's competence including the linquistic competence, his knowledge of the represented sphere and the knowledge of the applied sign system and its rules.
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  24. Analogy and Understanding.Jiri Syrovatka - 2000 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 15 (3):435-450.
    Analogy is taken into consideration by its didactive and heuristic functions. Analogic changes are analyzed in the form of syntactic-semantic graphs. Their recognizable structural similarity corresponds to the syntax or semantics in the analogy. The concept of analogy has subjective and objective aspects. The explanation in analogies is a dynamic transition from one concept structure to another. The possibility of analogy in the world is a statement about the disposition of the world. The possibility of analogy asserts something about the (...)
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  25. AFOS 1994 Workshop: Foundations of Science, Madralin , August 1994. IUHPS 1994 Conference: Theories and Models in Scientific Processes, Warsaw, August 1994. [REVIEW]Władysław Krajewski - 1995 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 10 (2):245-246.
  26. An Outline of the Idealizational Theory of Science.Andrzej Kupracz - 1994 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 9 (1):7-18.
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  27. Testing Through Realizable Models.Ruey-Lin Chen - 2004 - NTU Philosophical Review 27:67-117.
    How is a scientific theory, especial a classical physical theory, tested? This problem has a long history. In this paper I’ll propose a theory of testing based on but differentiated from Giere’s studies on the structure of scientific theories. I will show, from both theoretical and historical perspectives, that a scientific theory can always be understood as one contains a classified model population, including both higher-level models and realizable models, and that scientists always test a theory through its realizable models. (...)
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  28. Capturing the Scientific Imagination.Fiora Salis & Roman Frigg - forthcoming - In Peter Godfrey-Smith & Arnon Levy (eds.), The Scientific Imagination. Oxford University Press.
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  29. Multiple Roles for Analogies in the Genesis of Fluid Mechanics: How Analogies Can Cooperate with Other Heuristic Strategies.Alain Ulazia - 2016 - Foundations of Science 21 (4):543-565.
    When Johann and Daniel Bernoulli founded fluid dynamics they encountered several problems. To go beyond the vision of Newtonian particles, a new set of images was needed in order to deal with the spatial extensibility and lack of form of fluids. I point to evidence that analogy was an essential abductive strategy in the creation of this imagery. But its heuristic behavior is complex: analogy can provide an initial model or proto-model that establishes the starting point of a theoretical process, (...)
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  30. 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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  31. Explaining with Models: The Role of Idealizations.Julie Jebeile & Ashley Graham Kennedy - 2015 - International Studies in the Philosophy of Science 29 (4):383-392.
    Because they contain idealizations, scientific models are often considered to be misrepresentations of their target systems. An important question is therefore how models can explain the behaviours of these systems. Most of the answers to this question are representationalist in nature. Proponents of this view are generally committed to the claim that models are explanatory if they represent their target systems to some degree of accuracy; in other words, they try to determine the conditions under which idealizations can be made (...)
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  32. Representation and Similarity: Suárez on Necessary and Sufficient Conditions of Scientific Representation.Michael Poznic - 2016 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 47 (2):331-347.
    The notion of scientific representation plays a central role in current debates on modeling in the sciences. One or maybe the major epistemic virtue of successful models is their capacity to adequately represent specific phenomena or target systems. According to similarity views of scientific representation, models should be similar to their corresponding targets in order to represent them. In this paper, Suárez’s arguments against similarity views of representation will be scrutinized. The upshot is that the intuition that scientific representation involves (...)
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  33. Creating Scientific Concepts.Nancy Nersessian - unknown
    How do novel scientific concepts arise? In Creating Scientific Concepts, Nancy Nersessian seeks to answer this central but virtually unasked question in the problem of conceptual change. She argues that the popular image of novel concepts and profound insight bursting forth in a blinding flash of inspiration is mistaken. Instead, novel concepts are shown to arise out of the interplay of three factors: an attempt to solve specific problems; the use of conceptual, analytical, and material resources provided by the cognitive-social-cultural (...)
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  34. How to Talk About Physical Reality? Other Models, Other Questions.Benjamin B. Olshin - 2014 - Journal of Philosophy and Culture 5 (1).
    Investigating the nature of our apparent physical reality is a profound challenge. Our models from physics, while powerful, do not treat reality per se. The famous painter Paul Gaugin articulated the relevant existential questions famously in a grand painting - questions that also give the painting its title: D’où venons-nous? Que sommes-nous? Où allons-nous? People of religious faith, of course, assume that one can know the ultimate truth of reality, and, then, know the answers to these questions. But even in (...)
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  35. The Alternative Mathematical Models of the World.Salahaddin Khalilov - 2014 - Philosophy Study 4 (5).
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  36. Models and Theories in Physics.Gen-Ichiro Nagasaka - 1976 - Annals of the Japan Association for Philosophy of Science 5 (1):21-36.
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  37. Ray-Based Seismic Modeling of Geologic Models: Understanding and Analyzing Seismic Images Efficiently.Isabelle Lecomte, Paul Lubrano Lavadera, Ingrid Anell, Simon J. Buckley, Daniel W. Schmid & Michael Heeremans - 2015 - Interpretation: SEG 3 (4):SAC71-SAC89.
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  38. 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.
  39. Common Cause Abduction: The Formation of Theoretical Concepts and Models in Science.Gerhard Schurz - 2016 - Logic Journal of the IGPL 24 (4).
  40. I—Elisabeth A. Lloyd: Varieties of Support and Confirmation of Climate Models.Elisabeth A. Lloyd - 2009 - Aristotelian Society Supplementary Volume 83 (1):213-232.
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  41. Modeling the Impact of Microcracking on the Thermoelasticity of Porous and Microcracked Ceramics.Alexander M. Efremov & Giovanni Bruno - 2013 - Philosophical Magazine 93 (7):691-717.
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  42. Computer Simulation Study of the Role of Cross-Slip in the Formation of Textures in F.C.C. Metals.P. Gangli & P. Arató - 1976 - Philosophical Magazine 34 (3):465-478.
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  43. The Cosmic Web: Scientific Field Models and Literary Strategies in the Twentieth CenturyN. Katherine Hayles.G. S. Rousseau - 1988 - Isis 79 (2):322-323.
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  44. Models and Analogies in Science: Duhem Versus Campbell?D. H. Mellor - 1968 - Isis 59 (3):282-290.
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  45. How Do PDP Models Learn Quasiregularity?Woojae Kim, Mark A. Pitt & Jay I. Myung - 2013 - Psychological Review 120 (4):903-916.
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  46. More Modeling but Still No Stages: Reply to Borowsky and Besner.David C. Plaut & James R. Booth - 2006 - Psychological Review 113 (1):196-200.
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  47. Multiscale Modeling in Nanoscience: Beyond Hierarchical Relations.Julia Bursten - unknown
    Winsberg's "handshaking" account of inter-model relations is a well-known theory of multiscale modeling in physical systems. Winsberg argues that relations among the component models in a multiscale modeling system are not related mereologically, but rather by empirically determined algorithms. I argue that while the handshaking account does demonstrate the existence of non-mereological relationships among component models, Winsberg does not attend to the different ways in which handshaking algorithms are developed. By overlooking the distinct strategies employed in different handshake models, Winsberg's (...)
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  48. Models in Biology and Physics : What's the Difference?Darrell Patrick Rowbottom - unknown
    In Making Sense of Life, Keller emphasizes several differences between biology and physics. Her analysis focuses on significant ways in which modelling practices in some areas of biology, especially developmental biology, differ from those of the physical sciences. She suggests that natural models and modelling by homology play a central role in the former but not the latter. In this paper, I focus instead on those practices that are importantly similar, from the point of view of epistemology and cognitive science. (...)
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  49. A Study of the Discursive Aspect of Scientific Theorizing and Modeling.Micheal Joseph McEwan - unknown
    My dissertation contributes to the study of scientific theories and models by using a speech-act-theoretic framework to investigate the discursive aspect of theorizing and modeling practices. In the philosophical study of science some of the central questions concern the nature of theories and models and how they are used by scientists. There is debate about whether theories are best understood as representations or as tools useful for non-representational purposes, and among those that think they are representations there is disagreement about (...)
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  50. 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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