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  1. G. W. R. Ardley (1965). Models and Analogies in Science. Philosophical Studies 14:231-232.
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  2. P. Auger & C. Bougarel (1965). Models in Science. Diogenes 13 (52):1-13.
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  3. William F. Barr (1971). A Syntactic and Semantic Analysis of Idealizations in Science. Philosophy of Science 38 (2):258-272.
    Various laws and theories in the natural and social sciences are presented with a view to discerning the syntactic and semantic characteristics of many idealizations in science. Three different kinds of idealizations are discussed: ideal conditions, ideal cases, and idealized theories. An ideal condition is a formula in which state variables occur, whose existential closure is false, and for which there is another formula that can be constructed out of the original formula such that the existential closure of the new (...)
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  4. Jeffrey A. Barrett (2009). Scientific Representation. Journal of Philosophy 106 (11):634-639.
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  5. Michael Baur (1990). On the Aim of Scientific Theories in Relating to the World: A Defence of the Semantic Account. Dialogue 29 (03):323-.
  6. John Beatty (1987). On Behalf of the Semantic View. Biology and Philosophy 2 (1):17-23.
    responses to Sloep and Van der Steen, Biol. Philos. 1987 (2)33.
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  7. Yemima Ben-Menahem (1988). Models of Science: Fictions or Idealizations? Science in Context 2 (1).
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  8. William F. Brewer (2001). Models in Science and Mental Models in Scientists and Nonscientists. Mind and Society 2 (2):33-48.
    This paper examines the form of mental representation of scientific theories in scientists and nonscientists. It concludes that images and schemas are not the appropriate form of mental representation for scientific theories but that mental models and perceptual symbols do seem appropriate for representing physical/mechanical phenomena. These forms of mental representation are postulated to have an analogical relation with the world and it is this relationship that gives them strong explanatory power. It is argued that the construct of naïve theories (...)
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  9. Harold I. Brown (1979). A Functional Analysis of Scientific Theories. Journal for General Philosophy of Science 10 (1):119-140.
    Scientific theories are analyzed in terms of the role that they play in science rather than in terms of their logical structure. It is maintained that theories: provide descriptions of the fundamental features of their domains; on the basis of 1, explain non-fundamental features of their domains; provide a guide for further research in their domains. Any set of propositions that carries out these functions with respect to some domain counts as a theory. This view of theories is developed and (...)
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  10. Fernando Flores Camacho & Leticia Gallegos Cazares (1998). Partial Possible Models: An Approach to Interpret Students' Physical Representation. Science Education 82 (1):15-29.
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  11. Stephen M. Downes (2011). Scientific Models. Philosophy Compass 6 (11):757-764.
    This contribution provides an assessment of the epistemological role of scientific models. The prevalent view that all scientific models are representations of the world is rejected. This view points to a unified way of resolving epistemic issues for scientific models. The emerging consensus in philosophy of science that models have many different epistemic roles in science is presented and defended.
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  12. Steffen Ducheyne (2012). Scientific Representations as Limiting Cases. Erkenntnis 76 (1):73-89.
    In this essay, I shall show that the so-called inferential (Suárez 2003 and 2004 ) and interpretational (Contessa 2007 ) accounts of scientific representation are respectively unsatisfactory and too weak to account for scientific representation ( pars destruens ). Along the way, I shall also argue that the pragmatic similarity (Giere 2004 and Giere 2010 ) and the partial isomorphism (da Costa and French 2003 and French 2003 ) accounts are unable to single out scientific representation. In the pars construens (...)
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  13. Steffen Ducheyne (2005). Lessons From Galileo: The Pragmatic Model of Shared Characteristics of Scientific Representation. Philosophia Naturalis 42 (2):213-234.
    In this paper I will defend a new account of scientific representation. I will begin by looking at the benefits and drawbacks of two recent accounts on scientific representation: Hughes’ DDI account and Suárez’ inferential account. Next I use some of Galileo’s models in the Discorsi as a heuristic tool for a better account of scientific representation. Next I will present my model. The main idea of my account, which I refer to as the pragmatic model of shared characteristics (PMSC), (...)
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  14. Bruce Edmonds, Bootstrapping Knowledge About Social Phenomena Using Simulation Models.
    Formidable difficulties face anyone trying to model social phenomena using a formal system, such as a computer program. The differences between formal systems and complex, multi-facetted and meaning-laden social systems are so fundamental that many will criticise any attempt to bridge this gap. Despite this, there are those who are so bullish about the project of social simulation that they appear to believe that simple computer models, that are also useful and reliable indicators of how aspects of society works, are (...)
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  15. Bruce Edmonds, The Use of Models.
    The use of MABS (Multi-Agent Based Simulations) is analysed as the modelling of distributed (usually social) systems using MAS as the model structure. It is argued that rarely is direct modelling of target systems attempted but rather an abstraction of the target systems is modelled and insights gained about the abstraction then applied back to the target systems. The MABS modelling process is divided into six steps: abstraction, design, inference, analysis, interpretation and application. Some types of MABS papers are characterised (...)
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  16. James H. Fetzer (1999). The Role Of Models In Computer Science. The Monist 82 (1):20-36.
    Taking Brian Cantwell Smith’s study, “Limits of Correctness in Computers,” as its point of departure, this article explores the role of models in computer science. Smith identifies two kinds of models that play an important role, where specifications are models of problems and programs are models of possible solutions. Both presuppose the existence of conceptualizations as ways of conceiving the world “in certain delimited ways.” But high-level programming languages also function as models of virtual (or abstract) machines, while low-level programming (...)
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  17. Steven French (2003). A Model‐Theoretic Account of Representation (or, I Don't Know Much About Art…but I Know It Involves Isomorphism). Philosophy of Science 70 (5):1472-1483.
    Discussions of representation in science tend to draw on examples from art. However, such examples need to be handled with care given a) the differences between works of art and scientific theories and b) the accommodation of these examples within certain philosophies of art. I shall examine the claim that isomorphism is neither necessary nor sufficient for representation and I shall argue that there exist accounts of representation in both art and science involving isomorphism which accommodate the apparent counterexamples and, (...)
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  18. Mathias Frisch (2014). Models and Scientific Representations Or: Who is Afraid of Inconsistency? Synthese 191 (13):3027-3040.
    I argue that if we make explicit the role of the user of scientific representations not only in the application but also in the construction of a model or representation, then inconsistent modeling assumptions do not pose an insurmountable obstacle to our representational practices.
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  19. Ronald Giere (2011). Representing with Physical Models. In Paul Humphreys & Cyrille Imbert (eds.), Models, Simulations, and Representations. Routledge.
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  20. Ronald N. Giere (1994). The Cognitive Structure of Scientific Theories. Philosophy of Science 61 (2):276-296.
    This paper explores a new reason for preferring a model-theoretic approach to understanding the nature of scientific theories. Identifying the models in philosophers' model-theoretic accounts of theories with the concepts in cognitive scientists' accounts of categorization suggests a structure to families of models far richer than has commonly been assumed. Using classical mechanics as an example, it is argued that families of models may be "mapped" as an array with "horizontal" graded structures, multiply hierarchical "vertical" structures, and local "radial" structures. (...)
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  21. Erik Götlind (1961). Two Views About the Function of Models in Empirical Theories. Theoria 27 (2):58-69.
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  22. James Griesemer (1984). Presentations and the Status of Theories. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1984:102 - 114.
    The concept of a presentation of a theory is often introduced in discussions of the "semantic view" of theories to characterize the way in which models for a theory are specified. Presentations are most often thought of as definitions of the kinds of systems represented in the models. It is argued that the concept of a presentation can be widened to permit consideration of the links between epistemologically motivated accounts of theory structure and some metaphysically motivated accounts of the growth (...)
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  23. Philip P. Hallie (1971). Models, Burglary, and Philosophy. Philosophy and Rhetoric 4 (4):215 - 229.
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  24. B. Hart, A. Pillay & S. Starchenko (1995). 1-Based Theories — the Main Gap for a -Models. Archive for Mathematical Logic 34 (5):285-300.
    We prove the Main Gap for the class of a -models (sufficiently saturated models) of an arbitrary stable 1-based theory T . We (i) prove a strong structure theorem for a -models, assuming NDOP, and (ii) roughly compute the number of a -models of T in any given cardinality. The analysis uses heavily group existence theorems in 1-based theories.
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  25. Michael Heidelberger (2006). Applying Models in Fluid Dynamics. International Studies in the Philosophy of Science 20 (1):49 – 67.
    The following article treats the 'applicational turn' of modern fluid dynamics as it set in at the beginning of the 20th century with Ludwig Prandtl's concept of the boundary layer. It seeks to show that there is much more to applying a theory in a highly mathematical field like fluid dynamics than deriving a special case from a general explanatory theory under particular antecedent conditions. In Prandtl's case, the decisive move was to introduce a model that provided a physical/causal conception (...)
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  26. Paul Humphreys, The Truth of False Idealizations in Modeling.
    Modeling involves the use of false idealizations, yet there is typically a belief or hope that modeling somehow manages to deliver true information about the world. The paper discusses one possible way of reconciling truth and falsehood in modeling. The key trick is to relocate truth claims by reinterpreting an apparently false idealizing assumption in order to make clear what possibly true assertion is intended when using it. These include interpretations in terms of negligibility, applicability, tractability, early-step, and more. Elaborations (...)
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  27. Paul Humphreys & Cyrille Imbert (eds.) (2011). Models, Simulations, and Representations. Routledge.
    Although scientific models and simulations differ in numerous ways, they are similar in so far as they are posing essentially philosophical problems about the nature of representation. This collection is designed to bring together some of the best work on the nature of representation being done by both established senior philosophers of science and younger researchers. Most of the pieces, while appealing to existing traditions of scientific representation, explore new types of questions, such as: how understanding can be developed within (...)
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  28. Colin Klein, Idealization in Cognitive Psychology: A Case Study.
    develops themes from the dissertation. I argue that two models of prosopagnosia are best understood as idealizing models, and as such are subject to importantly different methodological constraints from non-idealized theories of face recognition.
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  29. Noretta Koertge, A Methodological Critique of the Semantic Conception of Theories.
    A new PhD slated to teach a beginning undergraduate course on scientific reasoning recently asked me to recommend topics. I launched into a description of my “baby-Popper-plus-statistics” class – give them enough deductive logic to understand the Duhemian problem, do the Galileo case study, use the notion of severe test to introduce a bit of probability theory, then segue to the problem of testing statistical hypotheses…. My interlocutor was looking impatient. “But I’m a strong adherent of the Semantic Conception of (...)
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  30. Ronald Laymon (1987). Using Scott Domains to Explicate the Notions of Approximate and Idealized Data. Philosophy of Science 54 (2):194-221.
    This paper utilizes Scott domains (continuous lattices) to provide a mathematical model for the use of idealized and approximately true data in the testing of scientific theories. Key episodes from the history of science can be understood in terms of this model as attempts to demonstrate that theories are monotonic, that is, yield better predictions when fed better or more realistic data. However, as we show, monotonicity and truth of theories are independent notions. A formal description is given of the (...)
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  31. Ronald Laymon (1980). Idealization, Explanation, and Confirmation. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1980:336 - 350.
    The use of idealizations and approximations in scientific explanations poses a problem for traditional philosophical theories of confirmation since, strictly speaking, these sorts of statements are false. Furthermore, in several central cases in the history of science, theoretical predictions seen as confirmatory are not, in any usual sense, even approximately true. As a means of eliminating the puzzling nature of these cases, two theses are proposed. First, explanations consist of idealized deductive-nomological sketches plus what are called modal auxiliaries, i.e., arguments (...)
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  32. Jean Leroux (2001). "Picture Theories" as Forerunners of the Semantic Approach to Scientific Theories. International Studies in the Philosophy of Science 15 (2):189 – 197.
  33. Elisabeth A. Lloyd (1988). The Semantic Approach and Its Application to Evolutionary Theory. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1988:278 - 285.
    In this talk I do three things. First, I review what I take to be fruitful applications of the semantic view of theory structure to evolutionary theory. Second, I list and correct three common misunderstandings about the semantic view. Third, I evaluate the weaknesses and strengths of Horan's paper in this symposium. Specifically, I argue that the criticisms leveled against the semantic view by Horan are inappropriate because they incorporate some basic misconceptions about the semantic view itself.
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  34. Michael Lynch & Ruth McNally, Encadenando a Un Monstruo : La Produccion de Representaciones En Un Campu Impuro.
    This paper analyses the topic of representation since the point of view of ethnomethodology and sociology of scientific knowledge. It starts out by discussing the “standard image of representation” and the constructivist proposition of that image. Then, a case of study is presented to suggest how practices for collecting and analyzing forensic evidence in criminal law, can contribute to understand representational adequacy. The aim of this paper is to think differently about representantion considering how it is produced, managed and deconstructed. (...)
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  35. Robert Mellert (1973). Models and Metanoia. Proceedings of the American Catholic Philosophical Association 47:142-152.
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  36. Kathleen Okruhlik (2009). Scientific Representation. Canadian Journal of Philosophy 39 (4):671-694.
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  37. Steven L. Peck (2008). The Hermeneutics of Ecological Simulation. Biology and Philosophy 23 (3):383-402.
    Computer simulation has become important in ecological modeling, but there have been few assessments on how complex simulation models differ from more traditional analytic models. In Part I of this paper, I review the challenges faced in complex ecological modeling and how models have been used to gain theoretical purchase for understanding natural systems. I compare the use of traditional analytic simulation models and point how that the two methods require different kinds of practical engagement. I examine a case study (...)
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  38. Christopher Pincock (2014). How to Avoid Inconsistent Idealizations. Synthese 191 (13):2957-2972.
    Idealized scientific representations result from employing claims that we take to be false. It is not surprising, then, that idealizations are a prime example of allegedly inconsistent scientific representations. I argue that the claim that an idealization requires inconsistent beliefs is often incorrect and that it turns out that a more mathematical perspective allows us to understand how the idealization can be interpreted consistently. The main example discussed is the claim that models of ocean waves typically involve the false assumption (...)
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  39. Demetris P. Portides (2005). A Theory of Scientific Model Construction: The Conceptual Process of Abstraction and Concretisation. [REVIEW] Foundations of Science 10 (1):67-88.
    The process of abstraction and concretisation is a label used for an explicative theory of scientific model-construction. In scientific theorising this process enters at various levels. We could identify two principal levels of abstraction that are useful to our understanding of theory-application. The first level is that of selecting a small number of variables and parameters abstracted from the universe of discourse and used to characterise the general laws of a theory. In classical mechanics, for example, we select position and (...)
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  40. Marian Przełęcki (1974). On Model Theoretic Approach to Empirical Interpretation of Scientific Theories. Synthese 26 (3-4):401 - 406.
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  41. Stathos Psillos, 102 Book Reviews. [REVIEW]
    idea of a mechanical balance, described the volume of exchange of various aggregated commodities, weighted by their price, balanced against the quantity of money in the economy, weighted by the money’ s rate of circulation. Another family of models addressed issues about the gold standard and bimetallism by thinking of quantities of gold and silver as liquids in different connected reservoirs representing, alternatively, bullion and minted coin, and the way the liquids/metal/currency in one reservoir will ¯ ow into others if (...)
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  42. Alexander Razin (2006). Models of Moral Activity. Philosophy Now 54:16-17.
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  43. A. Ritterbusch (1981). Komparative Aussagemuster in Bezug Zu Komplementären Und Enkaptischen Modellen der Morphologie. Acta Biotheoretica 30 (1):49-66.
    The unity of organisms can be viewed in terms of the concepts of enkapsis and complementarity. A model (or a type) represents those properties (of elements, structure, and system) which renders cases - the organisms under consideration — comparable. Comparability is established by operations (or metamorphoses) which relate a case to a model. Therefore, the model and the operations must be enumerated together, if a certain morphology is to be established and applied. Two models, which in some way are related, (...)
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  44. Xavier de Donato Rodríguez & Jesús Zamora Bonilla (2009). Credibility, Idealisation, and Model Building: An Inferential Approach. [REVIEW] Erkenntnis 70 (1):101 - 118.
    In this article we defend the inferential view of scientific models and idealisation. Models are seen as "inferential prostheses" (instruments for surrogative reasoning) construed by means of an idealisation-concretisation process, which we essentially understand as a kind of counterfactual deformation procedure (also analysed in inferential terms). The value of scientific representation is understood in terms not only of the success of the inferential outcomes arrived at with its help, but also of the heuristic power of representation and their capacity to (...)
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  45. Alexander Rueger (2014). Idealized and Perspectival Representations: Some Reasons for Making a Distinction. Synthese 191 (8):1831-1845.
    I argue that an adequate understanding of the practice of constructing models in physics requires a distinction between two strategies that are commonly both labeled ‘idealization’. The formal characteristic of both methods is to let a parameter in the equations for a target system go to zero. But the discussion of examples from various applications of perturbation theory shows that there is in general a difference with respect to the aims such limiting procedures are supposed to serve; and with different (...)
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  46. Robert John Schwartz (1978). Idealizations and Approximations in Physics. Philosophy of Science 45 (4):595-603.
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  47. K. S. Shrader-Frechette (1989). Idealized Laws, Antirealism, and Applied Science: A Case in Hydrogeology. Synthese 81 (3):329 - 352.
    When is a law too idealized to be usefully applied to a specific situation? To answer this question, this essay considers a law in hydrogeology called Darcy''s Law, both as it is used in what is called the symmetric-cone model, and as it is used in equations to determine a well''s groundwater velocity and hydraulic conductivity. After discussing Darcy''s law and its applications, the essay concludes that this idealized law, as well as associated models and equations in hydrogeology, are not (...)
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  48. Michelle R. Silva (2005). The Aerodynamics of Insects: The Role of Models and Matter in Scientific Experimentation. Social Epistemology 19 (4):325 – 337.
    Historians and philosophers of science have examined the relationship between language and practice for a long time. Scholars have made important contributions to the field by attending to the social, cultural and economic contexts in which scientific paradigms are created and re-created. However, this article posits that while it is true that scientific practice and the artifacts they generate are both socially and discursively constructed and therefore, inextricable from the human contexts that produce them, these artifacts are not only texts (...)
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  49. Frederick Suppe (1999). The Positivist Model of Scientific Theories. In Robert Klee (ed.), Scientific Inquiry: Readings in the Philosophy of Science. Oxford University Press. 16.
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  50. Patrick Suppes (2002). Representation and Invariance of Scientific Structures.
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