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  1. Explanation and Understanding Through Scientific Models.Richard David-Rus - unknown
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  • Models and Fiction.Roman Frigg - 2010 - Synthese 172 (2):251-268.
    Most scientific models are not physical objects, and this raises important questions. What sort of entity are models, what is truth in a model, and how do we learn about models? In this paper I argue that models share important aspects in common with literary fiction, and that therefore theories of fiction can be brought to bear on these questions. In particular, I argue that the pretence theory as developed by Walton has the resources to answer these questions. I introduce (...)
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  • Models of’ Versus ‘Models For.Julia Gouvea & Cynthia Passmore - 2017 - Science & Education 26 (1-2):49-63.
    The inclusion of the practice of “developing and using models” in the Framework for K-12 Science Education and in the Next Generation Science Standards provides an opportunity for educators to examine the role this practice plays in science and how it can be leveraged in a science classroom. Drawing on conceptions of models in the philosophy of science, we bring forward an agent-based account of models and discuss the implications of this view for enacting modeling in science classrooms. Models, according (...)
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  • The Theory Theory Thrice Over: The Child as Scientist, Superscientist or Social Institution?Michael A. Bishop & Stephen M. Downes - 2002 - Studies in History and Philosophy of Science Part A 33 (1):117-132.
    Alison Gopnik and Andrew Meltzoff have argued for a view they call the ‘theory theory’: theory change in science and children are similar. While their version of the theory theory has been criticized for depending on a number of disputed claims, we argue that there is a fundamental problem which is much more basic: the theory theory is multiply ambiguous. We show that it might be claiming that a similarity holds between theory change in children and (i) individual scientists, (ii) (...)
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  • Models and Representation.Roman Frigg & James Nguyen - 2017 - In Lorenzo Magnani & Tommaso Bertolotti (eds.), Springer Handbook of Model-Based Science. pp. 49-102.
    Scientific discourse is rife with passages that appear to be ordinary descriptions of systems of interest in a particular discipline. Equally, the pages of textbooks and journals are filled with discussions of the properties and the behavior of those systems. Students of mechanics investigate at length the dynamical properties of a system consisting of two or three spinning spheres with homogenous mass distributions gravitationally interacting only with each other. Population biologists study the evolution of one species procreating at a constant (...)
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  • Metaphysics as Modeling: The Handmaiden’s Tale.L. A. Paul - 2012 - Philosophical Studies 160 (1):1-29.
    Critics of contemporary metaphysics argue that it attempts to do the hard work of science from the ease of the armchair. Physics, not metaphysics, tells us about the fundamental facts of the world, and empirical psychology is best placed to reveal the content of our concepts about the world. Exploring and understanding the world through metaphysical reflection is obsolete. In this paper, I will show why this critique of metaphysics fails, arguing that metaphysical methods used to make claims about the (...)
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  • Philosophy of Cell Biology.William Bechtel & Andrew Bollhagen - 2019 - Stanford Encyclopedia of Philosophy.
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  • Model Anarchism.Walter Veit - 2020
    This paper constitutes a radical departure from the existing philosophical literature on models, modeling-practices, and model-based science. I argue that the various entities and practices called 'models' and 'modeling-practices' are too diverse, too context-sensitive, and serve too many scientific purposes and roles, as to allow for a general philosophical analysis. From this recognition an alternative view emerges that I shall dub model anarchism.
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  • Models and the Semantic View.Martin Thomson-Jones - 2006 - Philosophy of Science 73 (5):524-535.
    I begin by distinguishing two notions of model, the notion of a truth-making structure and the notion of a mathematical model (in one specific sense). I then argue that although the models of the semantic view have often been taken to be both truth-making structures and mathematical models, this is in part due to a failure to distinguish between two ways of truth-making; in fact, the talk of truth-making is best excised from the view altogether. The result is a version (...)
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  • Mother Nature Kicks Back: Review of Sean B. Carroll’s 2016 The Serengeti Rules. [REVIEW]Lachlan Douglas Walmsley - 2017 - Biology and Philosophy 32 (1):133-146.
    Sean B. Carroll’s new book, The Serengeti Rules: The Quest to Discover How Life Works and Why it Matters, is a well-written mix of history of science and philosophy of biology. In his book, Carroll articulates a set of ecological generalisations, the Serengeti Rules, which are supposed to make salient the structures in ecosystems that ensure the persistence of those ecosystems. In this essay review, I evaluate Carroll’s use of the controversial concept of regulation and his thesis that ecosystems have (...)
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  • An Inferential Account of Model Explanation.Wei Fang - 2019 - Philosophia 47 (1):99-116.
    This essay develops an inferential account of model explanation, based on Mauricio Suárez’s inferential conception of scientific representation and Alisa Bokulich’s counterfactual account of model explanation. It is suggested that the fact that a scientific model can explain is essentially linked to how a modeler uses an established model to make various inferences about the target system on the basis of results derived from the model. The inference practice is understood as a two-step activity, with the first step involving making (...)
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  • Explanation and Description in Computational Neuroscience.David Michael Kaplan - 2011 - Synthese 183 (3):339-373.
    The central aim of this paper is to shed light on the nature of explanation in computational neuroscience. I argue that computational models in this domain possess explanatory force to the extent that they describe the mechanisms responsible for producing a given phenomenon—paralleling how other mechanistic models explain. Conceiving computational explanation as a species of mechanistic explanation affords an important distinction between computational models that play genuine explanatory roles and those that merely provide accurate descriptions or predictions of phenomena. It (...)
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  • Imagination in Scientific Modeling.Adam Toon - 2016 - In Amy Kind (ed.), The Routledge Handbook of Philosophy of Imagination. Routledge. pp. 451-462.
    Modeling is central to scientific inquiry. It also depends heavily upon the imagination. In modeling, scientists seem to turn their attention away from the complexity of the real world to imagine a realm of perfect spheres, frictionless planes and perfect rational agents. Modeling poses many questions. What are models? How do they relate to the real world? Recently, a number of philosophers have addressed these questions by focusing on the role of the imagination in modeling. Some have also drawn parallels (...)
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  • Modeling Evolution in Theory and Practice.Anya Plutynski - 2001 - Proceedings of the Philosophy of Science Association 2001 (3):S225-.
    This paper uses a number of examples of diverse types and functions of models in evolutionary biology to argue that the demarcation between theory and practice, or "theory model" and "data model," is often difficult to make. It is shown how both mathematical and laboratory models function as plausibility arguments, existence proofs, and refutations in the investigation of questions about the pattern and process of evolutionary history. I consider the consequences of this for the semantic approach to theories and theory (...)
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  • Defending the Semantic View: What It Takes.Soazig Le Bihan - 2012 - European Journal for Philosophy of Science 2 (3):249-274.
    In this paper, a modest version of the Semantic View is motivated as both tenable and potentially fruitful for philosophy of science. An analysis is proposed in which the Semantic View is characterized by three main claims. For each of these claims, a distinction is made between stronger and more modest interpretations. It is argued that the criticisms recently leveled against the Semantic View hold only under the stronger interpretations of these claims. However, if one only commits to the modest (...)
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  • Modeling Practical Thinking.Matthew Mosdell - 2019 - Mind and Language 34 (4):445-464.
    Intellectualists about knowledge how argue that knowing how to do something is knowing the content of a proposition (i.e, a fact). An important component of this view is the idea that propositional knowledge is translated into behavior when it is presented to the mind in a peculiarly practical way. Until recently, however, intellectualists have not said much about what it means for propositional knowledge to be entertained under thought's practical guise. Carlotta Pavese fills this gap in the intellectualist view by (...)
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  • Microbes, Mathematics, and Models.Maureen A. O'Malley & Emily C. Parke - 2018 - Studies in History and Philosophy of Science Part A 72:1-10.
    Microbial model systems have a long history of fruitful use in fields that include evolution and ecology. In order to develop further insight into modelling practice, we examine how the competitive exclusion and coexistence of competing species have been modelled mathematically and materially over the course of a long research history. In particular, we investigate how microbial models of these dynamics interact with mathematical or computational models of the same phenomena. Our cases illuminate the ways in which microbial systems and (...)
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  • Who is a Modeler?M. Weisberg - 2007 - British Journal for the Philosophy of Science 58 (2):207-233.
    Many standard philosophical accounts of scientific practice fail to distinguish between modeling and other types of theory construction. This failure is unfortunate because there are important contrasts among the goals, procedures, and representations employed by modelers and other kinds of theorists. We can see some of these differences intuitively when we reflect on the methods of theorists such as Vito Volterra and Linus Pauling on the one hand, and Charles Darwin and Dimitri Mendeleev on the other. Much of Volterra's and (...)
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  • Idealized, Inaccurate but Successful: A Pragmatic Approach to Evaluating Models in Theoretical Ecology. [REVIEW]Jay Odenbaugh - 2005 - Biology and Philosophy 20 (2-3):231-255.
    Ecologists attempt to understand the diversity of life with mathematical models. Often, mathematical models contain simplifying idealizations designed to cope with the blooming, buzzing confusion of the natural world. This strategy frequently issues in models whose predictions are inaccurate. Critics of theoretical ecology argue that only predictively accurate models are successful and contribute to the applied work of conservation biologists. Hence, they think that much of the mathematical work of ecologists is poor science. Against this view, I argue that model (...)
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  • The Mental States of Persons and Their Brains.Tim Crane - 2015 - Royal Institute of Philosophy Supplement 76:253-270.
    Cognitive neuroscientists frequently talk about the brain representing the world. Some philosophers claim that this is a confusion. This paper argues that there is no confusion, and outlines one thing that might mean, using the notion of a model derived from the philosophy of science. This description is then extended to make apply to propositional attitude attributions. A number of problems about propositional attitude attributions can be solved or dissolved by treating propositional attitudes as models.
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  • The Structure of Tradeoffs in Model Building.John Matthewson & Michael Weisberg - 2009 - 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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  • Missing Systems and the Face Value Practice.Martin Thomson-Jones - 2010 - Synthese 172 (2):283-299.
    Call a bit of scientific discourse a description of a missing system when (i) it has the surface appearance of an accurate description of an actual, concrete system (or kind of system) from the domain of inquiry, but (ii) there are no actual, concrete systems in the world around us fitting the description it contains, and (iii) that fact is recognised from the outset by competent practitioners of the scientific discipline in question. Scientific textbooks, classroom lectures, and journal articles abound (...)
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  • Semblance or Similarity? Reflections on Simulation and Similarity: Michael Weisberg: Simulation and Similarity: Using Models to Understand the World. Oxford University Press, 2013. 224pp. ISBN 9780199933662, $65.00.Jay Odenbaugh - 2015 - Biology and Philosophy 30 (2):277-291.
    In this essay, I critically evaluate components of Michael Weisberg’s approach to models and modeling in his book Simulation and Similarity. First, I criticize his account of the ontology of models and mathematics. Second, I respond to his objections to fictionalism regarding models arguing that they fail. Third, I sketch a deflationary approach to models that retains many elements of his account but avoids the inflationary commitments.
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  • Modeling Minimal Conditions for Inequity.Cailin O'Connor - unknown
    This paper describes a class of idealized models that illuminate minimal conditions for inequity. Some such models will track the actual causal factors that generate real world inequity. Others may not. Whether or not these models do track these real-world factors is irrelevant to the epistemic role they play in showing that minimal commonplace factors are enough to generate inequity. In such cases, it is the fact that the model does not fit the world that makes it a particularly powerful (...)
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  • Theoretical Equivalence in Physics.James Owen Weatherall - unknown
    I review the philosophical literature on the question of when two physical theories are equivalent. This includes a discussion of empirical equivalence, which is often taken to be necessary, and sometimes taken to be sufficient, for theoretical equivalence; and "interpretational" equivalence, which is the idea that two theories are equivalent just in case they have the same interpretation. It also includes a discussion of several formal notions of equivalence that have been considered in the recent philosophical literature, including definitional equivalence (...)
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  • Reinflating the Semantic Approach.Steven French & James Ladyman - 1999 - International Studies in the Philosophy of Science 13 (2):103 – 121.
    The semantic, or model-theoretic, approach to theories has recently come under criticism on two fronts: (i) it is claimed that it cannot account for the wide diversity of models employed in scientific practice—a claim which has led some to propose a “deflationary” account of models; (ii) it is further contended that the sense of “model” used by the approach differs from that given in model theory. Our aim in the present work is to articulate a possible response to these claims, (...)
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  • Keeping Quiet on the Ontology of Models.Steven French - 2010 - Synthese 172 (2):231-249.
    Stein once urged us not to confuse the means of representation with that which is being represented. Yet that is precisely what philosophers of science appear to have done at the meta-level when it comes to representing the practice of science. Proponents of the so-called ‘syntactic’ view identify theories as logically closed sets of sentences or propositions and models as idealised interpretations, or ‘theoruncula, as Braithwaite called them. Adherents of the ‘semantic’ approach, on the other hand, are typically characterised as (...)
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  • The Strategy of Model-Based Science.Peter Godfrey-Smith - 2006 - Biology and Philosophy 21 (5):725-740.
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  • Holistic Modeling: An Objection to Weisberg’s Weighted Feature-Matching Account.Wei Fang - 2017 - Synthese 194 (5):1743–1764.
    Michael Weisberg’s account of scientific models concentrates on the ways in which models are similar to their targets. He intends not merely to explain what similarity consists in, but also to capture similarity judgments made by scientists. In order to scrutinize whether his account fulfills this goal, I outline one common way in which scientists judge whether a model is similar enough to its target, namely maximum likelihood estimation method. Then I consider whether Weisberg’s account could capture the judgments involved (...)
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  • Part 2: Theoretical Equivalence in Physics.James Owen Weatherall - 2019 - Philosophy Compass 14 (5).
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  • Empirical Adequacy: A Partial Structures Approach.Otávio Bueno - 1997 - Studies in History and Philosophy of Science Part A 28 (4):585-610.
    Based on da Costa's and French's notions of partial structures and pragmatic truth, this paper examines two possible characterizations of the concept of empirical adequacy, one depending on the notion of partial isomorphism, the other on the hierarchy of partial models of phenomena, and both compatible with an empiricist view. These formulations can then be employed to illuminate certain aspects of scientific practice.An empirical theory must single out a specific part of the world, establish reference to that part, and say—by (...)
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  • A ‘Semantic’ View of Scientific Models for Science Education.Agustín Adúriz-Bravo - 2013 - Science & Education 22 (7):1593-1611.
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  • Models, Models, Models: A Deflationary View.Jay Odenbaugh - forthcoming - Synthese:1-16.
    In this essay, I first consider a popular view of models and modeling, the similarity view. Second, I contend that arguments for it fail and it suffers from what I call “Hughes’ worry.” Third, I offer a deflationary approach to models and modeling that avoids Hughes’ worry and shows how scientific representations are of apiece with other types of representations. Finally, I consider an objection that the similarity view can deal with approximations better than the deflationary view and show that (...)
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  • Interweaving Categories: Styles, Paradigms, and Models.Rasmus Grønfeldt Winther - 2012 - Studies in History and Philosophy of Science Part A 43 (4):628-639.
    Analytical categories of scientific cultures have typically been used both exclusively and universally. For instance, when styles of scientific research are employed in attempts to understand and narrate science, styles alone are usually employed. This article is a thought experiment in interweaving categories. What would happen if rather than employ a single category, we instead investigated several categories simultaneously? What would we learn about the practices and theories, the agents and materials, and the political-technological impact of science if we analyzed (...)
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  • Modeling Without Models.Arnon Levy - 2015 - 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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  • The Structure of Scientific Theories.Rasmus Grønfeldt Winther - 2015 - Stanford Encyclopedia of Philosophy.
    Scientific inquiry has led to immense explanatory and technological successes, partly as a result of the pervasiveness of scientific theories. Relativity theory, evolutionary theory, and plate tectonics were, and continue to be, wildly successful families of theories within physics, biology, and geology. Other powerful theory clusters inhabit comparatively recent disciplines such as cognitive science, climate science, molecular biology, microeconomics, and Geographic Information Science (GIS). Effective scientific theories magnify understanding, help supply legitimate explanations, and assist in formulating predictions. Moving from their (...)
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  • The Strategies of Modeling in Biology Education.Julia Svoboda & Cynthia Passmore - 2013 - Science & Education 22 (1):119-142.
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