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  1. Ernest W. Adams (1982). Approximate Generalizations and Their Idealization. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1982:199 - 207.
    Aspects of a formal theory of approximate generalizations, according to which they have degrees of truth measurable by the proportions of their instances for which they are true, are discussed. The idealizability of laws in theories of fundamental measurement is considered: given that the laws of these theories are only approximately true "in the real world", does it follow that slight changes in the extensions of their predicates would make them exactly true?
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  2. Alfonso Arroyo-Santos & Xavier de Donato-Rodríguez, Idealization and the Structure of Theories in Biololgy.
    In this paper we present a new framework of idealization in biology. We characterize idealizations as a network of counterfactual conditionals that can exhibit different degrees of contingency. We use the idea of possible worlds to say that, in departing more or less from the actual world, idealizations can serve numerous epistemic, methodological or heuristic purposes within scientific research. We defend that, in part, it is this structure what helps explain why idealizations, despite being deformations of reality, are so successful (...)
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  3. William F. Barr (1974). A Pragmatic Analysis of Idealizations in Physics. Philosophy of Science 41 (1):48-64.
    A brief discussion is offered of what it means to say that a set of statements provides D-N explanation with special emphasis given to approximative D-N explanation. An idealized theory is seen to provide approximative D-N explanation. An ideal case provides explanation only if postulates are offered which connect the ideal antecedent condition with actual conditions. Such postulates will help in accounting for deviations between what the consequent of the ideal case entails and what actually occurs. Three ways are presented (...)
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  4. Robert Batterman (2010). On the Explanatory Role of Mathematics in Empirical Science. British Journal for the Philosophy of Science 61 (1):1-25.
    This paper examines contemporary attempts to explicate the explanatory role of mathematics in the physical sciences. Most such approaches involve developing so-called mapping accounts of the relationships between the physical world and mathematical structures. The paper argues that the use of idealizations in physical theorizing poses serious difficulties for such mapping accounts. A new approach to the applicability of mathematics is proposed.
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  5. Robert W. Batterman (2009). Idealization and Modeling. Synthese 169 (3):427 - 446.
    This paper examines the role of mathematical idealization in describing and explaining various features of the world. It examines two cases: first, briefly, the modeling of shock formation using the idealization of the continuum. Second, and in more detail, the breaking of droplets from the points of view of both analytic fluid mechanics and molecular dynamical simulations at the nano-level. It argues that the continuum idealizations are explanatorily ineliminable and that a full understanding of certain physical phenomena cannot be obtained (...)
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  6. Nancy Cartwright (1995). False Idealisation: A Philosophical Threat to Scientific Method. Philosophical Studies 77 (2-3):339 - 352.
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  7. Nancy Cartwright, Stephan Hartmann, Carl Hoefer & Luc Bovens (eds.) (2008). Nancy Cartwright's Philosophy of Science. Routledge.
    Nancy Cartwright is one of the most distinguished and influential contemporary philosophers of science. Despite the profound impact of her work, there is neither a systematic exposition of Cartwright’s philosophy of science nor a collection of articles that contains in-depth discussions of the major themes of her philosophy. This book is devoted to a critical assessment of Cartwright’s philosophy of science and contains contributions from Cartwright's champions and critics. Broken into three parts, the book begins by addressing Cartwright's views on (...)
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  8. Michael A. Day (1990). The No-Slip Condition of Fluid Dynamics. Erkenntnis 33 (3):285 - 296.
    In many applications of physics, boundary conditions have an essential role. The purpose of this paper is to examine from both a historical and philosophical perspective one such boundary condition, namely, the no-slip condition of fluid dynamics. The historical perspective is based on the works of George Stokes and serves as the foundation for the philosophical perspective. It is seen that historically the acceptance of the no-slip condition was problematic. Philosophically, the no-slip condition is interesting since the use of the (...)
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  9. Xavier de Donato Rodríguez (2007). Idealization, Abduction, and Progressive Scientific Change. Theoria 22 (3):331-338.
    After a brief comparison of Aliseda’s account with different approaches to abductive reasoning, I relate abduction, as studied by Aliseda, to idealization, a notion which also occupies a very important role in scientific change, as well as to different ways of dealing with the growth of scientific knowledge understood as a particular kind of non-monotonic process. A particularly interesting kind of abductive reasoning could be that of finding an appropriate concretization case for a theory, originally revealed as extraordinarily success-ful but (...)
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  10. David Eng, The Role of Idealizations in the Realism/Anti-Realism Debate.
    The thesis focuses on what impact the use of idealizations has on the realism/anti-realism debate concerning the fundamental laws of physics. My aim is modest. It is not to present an argument for either the realist or the anti-realist position but rather to show where the debate stands once we have considered recent arguments by Laymon and Cartwright which have made use of the notion of idealization assumptions. My intent is to point out the difficulties of Laymon's argument for realism (...)
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  11. Aldo Frigerio, Alessandro Giordani & Luca Mari (2010). Outline of a General Model of Measurement. Synthese 175 (2):123-149.
    Measurement is a process aimed at acquiring and codifying information about properties of empirical entities. In this paper we provide an interpretation of such a process comparing it with what is nowadays considered the standard measurement theory, i.e., representational theory of measurement. It is maintained here that this theory has its own merits but it is incomplete and too abstract, its main weakness being the scant attention reserved to the empirical side of measurement, i.e., to measurement systems and to the (...)
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  12. Roman Frigg, Fiction in Science.
    At first blush, the idea that fictions play a role in science seems to be off the mark. Realists and antirealists alike believe that science instructs us about how the world is (they part ways only over the question of what exactly science tells us about the world). Fiction not only seems to play no role in such an endeavour; it seems to detract from it. The aims of science and fiction seem to be (...)
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  13. Alessandro Giordani & Luca Mari (2014). Modeling Measurement: Error and Uncertainty. In Marcel Boumans, Giora Hon & Arthur Petersen (eds.), Error and Uncertainty in Scientific Practice. Pickering & Chatto 79-96.
    In the last few decades the role played by models and modeling activities has become a central topic in the scientific enterprise. In particular, it has been highlighted both that the development of models constitutes a crucial step for understanding the world and that the developed models operate as mediators between theories and the world. Such perspective is exploited here to cope with the issue as to whether error-based and uncertainty-based modeling of measurement are incompatible, and thus alternative with one (...)
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  14. Frank Hindriks (2008). False Models as Explanatory Engines. Philosophy of the Social Sciences 38 (3):334-360.
    Many models in economics are very unrealistic. At the same time, economists put a lot of effort into making their models more realistic. I argue that in many cases, including the Modigliani-Miller irrelevance theorem investigated in this paper, the purpose of this process of concretization is explanatory. When evaluated in combination with their assumptions, a highly unrealistic model may well be true. The purpose of relaxing an unrealistic assumption, then, need not be to move from a false model to a (...)
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  15. Steven Horst (forthcoming). Cognitive Pluralism. MIT Press.
    This book introduces an account of cognitive architecture, Cognitive Pluralism, on which the basic units of understanding are models of particular content domains. Having many mental models is a good adaptive strategy for cognition, but models can be incompatible with one another, leading to paradoxes and inconsistencies of belief, and it may not be possible to integrate the understanding supplied by multiple models into a comprehensive and self-consistent "super model". The book applies the theory to explaining intuitive reasoning and cognitive (...)
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  16. Nicholaos Jones (2013). Don't Blame the Idealizations. Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 44 (1):85-100.
    Idealizing conditions are scapegoats for scientific hypotheses, too often blamed for falsehood better attributed to less obvious sources. But while the tendency to blame idealizations is common among both philosophers of science and scientists themselves, the blame is misplaced. Attention to the nature of idealizing conditions, the content of idealized hypotheses, and scientists’ attitudes toward those hypotheses shows that idealizing conditions are blameless when hypotheses misrepresent. These conditions help to determine the content of idealized hypotheses, and they do so in (...)
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  17. Nicholaos Jones, Resolving the Bayesian Problem of Idealization.
    In "Bayesian Confirmation of Theories that Incorporate Idealizations", Michael Shaffer argues that, in order to show how idealized hypotheses can be confirmed, Bayesians must develop a coherent proposal for how to assign prior probabilities to counterfactual conditionals. This paper develops a Bayesian reply to Shaffer's challenge that avoids the issue of how to assign prior probabilities to counterfactuals by treating idealized hypotheses as abstract descriptions. The reply allows Bayesians to assign non-zero degrees of confirmation to idealized hypotheses and to capture (...)
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  18. Martin King, Idealization and Structural Explanation in Physics.
  19. Robert Kowalenko (2009). How (Not) to Think About Idealisation and Ceteris Paribus -Laws. Synthese 167 (1):183 - 201.
    Semantic dispositionalism is the theory that a speaker’s meaning something by a given linguistic symbol is determined by her dispositions to use the symbol in a certain way. According to an objection by Saul Kripke, further elaborated in Kusch (2005), semantic dispositionalism involves ceteris paribus-clauses and idealisations, such as unbounded memory, that deviate from standard scientific methodology. I argue that Kusch misrepresents both ceteris paribus-laws and idealisation, neither of which factually approximate the behaviour of agents or the course of events, (...)
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  20. Ehud Lamm (2013). Theoreticians as Professional Outsiders: The Modeling Strategies of John von Neumann and Norbert Wiener. In Oren Harman & Michael Dietrich (eds.), Outsider Scientists: Routes to Innovation in Biology. Chicago University Press
    Both von Neumann and Wiener were outsiders to biology. Both were inspired by biology and both proposed models and generalizations that proved inspirational for biologists. Around the same time in the 1940s von Neumann developed the notion of self reproducing automata and Wiener suggested an explication of teleology using the notion of negative feedback. These efforts were similar in spirit. Both von Neumann and Wiener used mathematical ideas to attack foundational issues in biology, and the concepts they articulated had lasting (...)
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  21. Ehud Lamm (2008). Hopeful Heretic – Richard Goldschmidt’s Genetic Metaphors. History and Philosophy of the Life Sciences 30 (3-4):387-406.
    Richard Goldschmidt famously rejected the notion of atomic and corpuscular genes, arranged on the chromosome like beads-on-a-string. I provide an exegesis of Goldschmidt’s intuition by analyzing his repeated and extensive use of metaphorical language and analogies in his attempts to convey his notion of the nature of the genetic material and specifically the significance of chromosomal pattern. The paper concentrates on Goldschmidt’s use of metaphors in publications spanning 1940-1955. -/- .
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  22. Ronald Laymon (1989). Applying Idealized Scientific Theories to Engineering. Synthese 81 (3):353 - 371.
    The problem for the scientist created by using idealizations is to determine whether failures to achieve experimental fit are attributable to experimental error, falsity of theory, or of idealization. Even in the rare case when experimental fit within experimental error is achieved, the scientist must determine whether this is so because of a true theory and fortuitously canceling idealizations, or due to a fortuitous combination of false theory and false idealizations. For the engineer, the problem seems rather different. Experiment for (...)
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  23. Arnon Levy (2015). Modeling Without Models. Philosophical Studies 172 (3):781-798.
    Modeling is an important scientific practice, yet it raises significant philosophical puzzles. Models are typically idealized, and they are often explored via imaginative engagement and at a certain “distance” from empirical reality. These features raise questions such as what models are and how they relate to the world. Recent years have seen a growing discussion of these issues, including a number of views that treat modeling in terms of indirect representation and analysis. Indirect views treat the model as a bona (...)
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  24. Chuang Liu, Fictional Models in Science.
    In this paper, I begin with a discussion of Giere’s recent work arguing against taking models as works of fiction. I then move on to explore a spectrum of scientific models that goes from the obviously fictional to the not so obviously fictional. And then I discuss the modeling of the unobservable and make a case for the idea that despite difficulties of defining them, unobservable systems are modeled in a fundamentally different way than the observable systems. While idealization and (...)
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  25. Chuang LIu, Re-Inflating the Conception of Scientific Representation.
    This paper argues for an anti-deflationist view of scientific representation. Our discussion begins with an analysis of the recent Callender-Cohen deflationary view on scientific representation. We then argue that there are at least two radically different ways in which a thing can be used to represent: one is purely symbolic and therefore conventional, and the other is epistemic. The failure to recognize that scientific models are epistemic vehicles rather than symbolic ones has led to the mistaken (deflationary) view that whatever (...)
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  26. Chuang Liu, Symbols Versus Models.
    In this paper I argue against a deflationist view that as representational vehicles symbols and models do their jobs in essentially the same way. I argue that symbols are conventional vehicles whose chief function is denotation while models are epistemic vehicles whose chief function is showing what their targets are like in the relevant aspects. It is further pointed out that models usually do not rely on similarity or some such relations to relate to their targets. For that referential relation (...)
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  27. Chuang Liu, Confirming Idealized Theories and Scientific Realism.
    Two types of idealization in theory construction are distinguished, and the distinction is used to give a critique of Ron Laymon's account of confirming idealized theories and his argument for scientific realism.
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  28. Chuang Liu (2004). Approximations, Idealizations, and Models in Statistical Mechanics. Erkenntnis 60 (2):235-263.
    In this paper, a criticism of the traditional theories of approximation and idealization is given. 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 in thermostatistical physics. After a brief (...)
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  29. Chuang Liu (2004). Laws and Models in a Theory of Idealization. Synthese 138 (3):363 - 385.
    I first give a brief summary of a critique of the traditional theories of approximation and idealization; and after identifying one of the major roles of idealization as detaching component processes or systems from their joints, a detailed analysis is given of idealized laws – which are discoverable and/or applicable – in such processes and systems (i.e., idealized model systems). Then, I argue that dispositional properties should be regarded as admissible properties for laws and that such an inclusion supplies the (...)
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  30. Chuang Liu (2004). Laws and Models in a Theory of Idealization. Synthese 138 (3):363 - 385.
    I first give a brief summary of a critique of the traditional theories of approximation and idealization; and after identifying one of the major roles of idealization as detaching component processes or systems from their joints, a detailed analysis is given of idealized laws -- which are discoverable and/or applicable -- in such processes and systems (i.e., idealized model systems). Then, I argue that dispositional properties should be regarded as admissible properties for laws and that such an inclusion supplies the (...)
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  31. Chuang Liu (2004). Approximations, Idealizations, and Models in Statistical Mechanics. 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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  32. Robert W. P. Luk (2010). Understanding Scientific Study Via Process Modeling. Foundations of Science 15 (1):49-78.
    This paper argues that scientific studies distinguish themselves from other studies by a combination of their processes, their (knowledge) elements and the roles of these elements. This is supported by constructing a process model. An illustrative example based on Newtonian mechanics shows how scientific knowledge is structured according to the process model. To distinguish scientific studies from research and scientific research, two additional process models are built for such processes. We apply these process models: (1) to argue that scientific progress (...)
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  33. Uskali Mäki (2009). Models and Truth: The Functional Decomposition Approach. In Mauricio Suárez, Miklós Rédei & Mauro Dorato (eds.), EPSA Epistemology and Methodology of Science: Launch of the European Philosophy of Science Association. Springer
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  34. Uskali Mäki (2009). MISSing the World. Models as Isolations and Credible Surrogate Systems. Erkenntnis 70 (1):29 - 43.
    This article shows how the MISS account of models—as isolations and surrogate systems—accommodates and elaborates Sugden’s account of models as credible worlds and Hausman’s account of models as explorations. Theoretical models typically isolate by means of idealization, and they are representatives of some target system, which prompts issues of resemblance between the two to arise. Models as representations are constrained both ontologically (by their targets) and pragmatically (by the purposes and audiences of the modeller), and these relations are coordinated by (...)
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  35. Hans Martens & Willem M. De Muynck (1990). Nonideal Quantum Measurements. Foundations of Physics 20 (3):255-281.
    A partial ordering in the class of observables (∼ positive operator-valued measures, introduced by Davies and by Ludwig) is explored. The ordering is interpreted as a form of nonideality, and it allows one to compare ideal and nonideal versions of the same observable. Optimality is defined as maximality in the sense of the ordering. The framework gives a generalization of the usual (implicit) definition of self-adjoint operators as optimal observables (von Neumann), but it can, in contrast to this latter definition, (...)
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  36. John Matthewson & Michael Weisberg (2009). The Structure of Tradeoffs in Model Building. Synthese 170 (1):169 - 190.
    Despite their best efforts, scientists may be unable to construct models that simultaneously exemplify every theoretical virtue. One explanation for this is the existence of tradeoffs: relationships of attenuation that constrain the extent to which models can have such desirable qualities. In this paper, we characterize three types of tradeoffs theorists may confront. These characterizations are then used to examine the relationships between parameter precision and two types of generality. We show that several of these relationships exhibit tradeoffs and discuss (...)
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  37. Boaz Miller (2012). The Rationality Principle Idealized. Social Epistemology 26 (1):3-30.
    According to Popper's rationality principle, agents act in the most adequate way according to the objective situation. I propose a new interpretation of the rationality principle as consisting of an idealization and two abstractions. Based on this new interpretation, I critically discuss the privileged status that Popper ascribes to it as an integral part of all social scientific models. I argue that as an idealization, the rationality principle may play an important role in the social sciences, but it also has (...)
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  38. Moti Mizrahi (2012). Idealizations and Scientific Understanding. Philosophical Studies 160 (2):237-252.
    In this paper, I propose that the debate in epistemology concerning the nature and value of understanding can shed light on the role of scientific idealizations in producing scientific understanding. In philosophy of science, the received view seems to be that understanding is a species of knowledge. On this view, understanding is factive just as knowledge is, i.e., if S knows that p, then p is true. Epistemologists, however, distinguish between different kinds of understanding. Among epistemologists, there are those who (...)
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  39. Marcin Miłkowski (forthcoming). Explanatory Completeness and Idealization in Large Brain Simulations: A Mechanistic Perspective. Synthese:1-22.
    The claim defended in the paper is that the mechanistic account of explanation can easily embrace idealization in big-scale brain simulations, and that only causally relevant detail should be present in explanatory models. The claim is illustrated with two methodologically different models: Blue Brain, used for particular simulations of the cortical column in hybrid models, and Eliasmith’s SPAUN model that is both biologically realistic and able to explain eight different tasks. By drawing on the mechanistic theory of computational explanation, I (...)
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  40. Ryan Muldoon (2007). Robust Simulations. Philosophy of Science 74 (5):873-883.
    As scientists begin to study increasingly complex questions, many have turned to computer simulation to assist in their inquiry. This methodology has been challenged by both analytic modelers and experimentalists. A primary objection of analytic modelers is that simulations are simply too complicated to perform model verification. From the experimentalist perspective it is that there is no means to demonstrate the reality of simulation. The aim of this paper is to consider objections from both of these perspectives, and to argue (...)
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  41. Izabella Nowakowa (1994). Idealization V: The Dynamics of Idealizations: Translated by Katarzyna Paprzycka and Marek Kwiek. Rodopi.
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  42. John Pemberton (2005). Why Idealized Models in Economics Have Limited Use. Poznan Studies in the Philosophy of the Sciences and the Humanities 86 (1):35-46.
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  43. Demetris Portides (2011). Seeking Representations of Phenomena: Phenomenological Models. Studies in History and Philosophy of Science 42 (2):334-341.
    A distinction is made between theory-driven and phenomenological models. It is argued that phenomenological models are significant means by which theory is applied to phenomena. They act both as sources of knowledge of their target systems and are explanatory of the behaviors of the latter. A version of the shell-model of nuclear structure is analyzed and it is explained why such a model cannot be understood as being subsumed under the theory structure of Quantum Mechanics. Thus its representational capacity does (...)
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  44. Xavier Donato Rodríguedez (2007). Idealization, Abduction, and Progressive Scientific Change. Theoria 22 (3):331-338.
    After a brief comparison of Aliseda’s account with different approaches to abductive reasoning, I relate abduction, as studied by Aliseda, to idealization, a notion which also occupies a very important role in scientific change, as well as to different ways of dealing with the growth of scientific knowledge understood as a particular kind of non-monotonic process. A particularly interesting kind of abductive reasoning could be that of finding an appropriate concretization case for a theory, originally revealed as extraordinarily success-ful but (...)
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  45. Xavier Donato Rodríguedez & Jesús Zamora Bonilla (2009). Credibility, Idealisation, and Model Building: An Inferential Approach. Erkenntnis 70 (1).
    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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  46. Darrell P. Rowbottom (2011). Approximations, Idealizations and 'Experiments' at the Physics-Biology Interface. Studies in History and Philosophy of Biological and Biomedical Sciences 42 (2):145-154.
    This paper, which is based on recent empirical research at the University of Leeds, the University of Edinburgh, and the University of Bristol, presents two difficulties which arise when condensed matter physicists interact with molecular biologists: (1) the former use models which appear to be too coarse-grained, approximate and/or idealized to serve a useful scientific purpose to the latter; and (2) the latter have a rather narrower view of what counts as an experiment, particularly when it comes to computer simulations, (...)
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  47. Erdinc Sayan (1994). Idealizations, Approximations and Confirmation in Science. Dissertation, The Ohio State University
    Despite the pervasive use of idealizations and approximations in science, the issue of their role has been neglected or misunderstood by philosophers. Idealizations enter into a scientific analysis or explanation in at least two ways. First, they may be embodied in the very statement or formulation of laws and theories; I call such laws idealizational laws. Second, they may be conjoined to a theory as extraneous assumptions, mainly to make it easier to work with the theory. I first examine the (...)
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  48. Michael J. Shaffer (2001). Bayesian Confirmation of Theories That Incorporate Idealizations. Philosophy of Science 68 (1):36-52.
    Following Nancy Cartwright and others, I suggest that most (if not all) theories incorporate, or depend on, one or more idealizing assumptions. I then argue that such theories ought to be regimented as counterfactuals, the antecedents of which are simplifying assumptions. If this account of the logic form of theories is granted, then a serious problem arises for Bayesians concerning the prior probabilities of theories that have counterfactual form. If no such probabilities can be assigned, the the posterior probabilities will (...)
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  49. Eran Tal (2012). The Epistemology of Measurement: A Model-Based Account. Dissertation, University of Toronto
    This work develops an epistemology of measurement, that is, an account of the conditions under which measurement and standardization methods produce knowledge as well as the nature, scope, and limits of this knowledge. I focus on three questions: (i) how is it possible to tell whether an instrument measures the quantity it is intended to? (ii) what do claims to measurement accuracy amount to, and how might such claims be justified? (iii) when is disagreement among instruments a sign of error, (...)
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  50. Eran Tal (2011). How Accurate Is the Standard Second? Philosophy of Science 78 (5):1082-1096.
    Contrary to the claim that measurement standards are absolutely accurate by definition, I argue that unit definitions do not completely fix the referents of unit terms. Instead, idealized models play a crucial semantic role in coordinating the theoretical definition of a unit with its multiple concrete realizations. The accuracy of realizations is evaluated by comparing them to each other in light of their respective models. The epistemic credentials of this method are examined and illustrated through an analysis of the contemporary (...)
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