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Scientific Models

Assistant editor: Guilherme Sanches De Oliveira (University of Cincinnati, Technische Universität Berlin)
About this topic
Summary Modeling is an increasingly important method in many fields of science. Scientific models are taken to be only partially similar to the phenomena they are used to study. Several philosophical questions result. For one, philosophers investigate how it is that models represent phenomena despite their differences, and what is responsible for models' epistemic success. This dovetails with questions about the nature of the representation relation. Philosophers also investigate abstraction and idealization in modeling, and some accord a further role to fictions. Finally, models are also significant in a different sense for the semantic view of theories. 
Key works Hesse 1963; Van Fraassen Bas 1980; Wimsatt (1987); Poland 1988; Morgan & Morrison 1999; Bailer-Jones 2009; Weisberg 2013.
Introductions Frigg and Hartmann (2006)
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  1. Sociologie fondamentale. Etude d'épistémologie.Dominique Raynaud - 2021 - Paris: Editions Matériologiques.
    Ce livre est un livre d’épistémologie de la sociologie. L’objectif est d’appliquer des méthodes analytiques pour clarifier le vocabulaire, expliciter des relations non-apparentes entre concepts, dégager la portée d’une méthode, ou souligner les incohérences d’un programme de recherche. Les questions épineuses ne sont pas écartéees: Comment clarifier des notions confuses? Peut-on mathématiser les concepts sociologiques? Peut-on pratiquer la sociologie comme on pratique les sciences naturelles? Quelle est la place du déterminisme? Chaque question est examinée à la fois dans sa structure (...)
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  2. The Epistemic Duties of Philosophers: An Addendum.Philippe van Basshuysen & Lucie White - forthcoming - Kennedy Institute of Ethics Journal.
    We were slightly concerned, upon having read Eric Winsberg, Jason Brennan and Chris Surprenant’s reply to our paper “Were Lockdowns Justified? A Return to the Facts and Evidence”, that they may have fundamentally misunderstood the nature of our argument, so we issue the following clarification, along with a comment on our motivations for writing such a piece, for the interested reader.
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  3. Taming the Tyranny of Scales: Models and Scale in the Geosciences.Alisa Bokulich - forthcoming - Synthese.
    While the predominant focus of the philosophical literature on scientific modeling has been on single-scale models, most systems in nature exhibit complex multiscale behavior, requiring new modeling methods. This challenge of modeling phenomena across a vast range of spatial and temporal scales has been called the tyranny of scales problem. Drawing on research in the geosciences, I synthesize and analyze a number of strategies for taming this tyranny in the context of conceptual, physical, and mathematical modeling. This includes several strategies (...)
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  4. Epistemic and Objective Possibility in Science.Ylwa Sjölin Wirling & Till Grüne-Yanoff - forthcoming - British Journal for the Philosophy of Science.
    Scientists regularly make possibility claims. While philosophers of science are well aware of the distinction between epistemic and objective notions of possibility, we believe that they often fail to apply this distinction in their analyses of scientific practices that employ modal concepts. We argue that heeding this distinction will help further progress in current debates in the philosophy of science, as it shows that the debaters talk about different things, rather than disagree on the same issue. We first discuss how (...)
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  5. Three Ways in Which Pandemic Models May Perform a Pandemic.Philippe van Basshuysen, Lucie White, Donal Khosrowi & Mathias Frisch - 2021 - Erasmus Journal for Philosophy and Economics 14 (1):110-127.
    Models not only represent but may also influence their targets in important ways. While models’ abilities to influence outcomes has been studied in the context of economic models, often under the label ‘performativity’, we argue that this phenomenon also pertains to epidemiological models, such as those used for forecasting the trajectory of the Covid-19 pandemic. After identifying three ways in which a model by the Covid-19 Response Team at Imperial College London may have influenced scientific advice, policy, and individual responses, (...)
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  6. Extending Similarity-Based Epistemology of Modality with Models.Ylwa Sjölin Wirling - forthcoming - Ergo: An Open Access Journal of Philosophy.
    Empiricist modal epistemologies can be attractive, but are often limited in the range of modal knowledge they manage to secure. In this paper, I argue that one such account – similarity-based modal empiricism – can be extended to also cover justification of many scientifically interesting possibility claims. Drawing on recent work on modelling in the philosophy of science, I suggest that scientific modelling is usefully seen as the creation and investigation of relevantly similar epistemic counterparts of real target systems. On (...)
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  7. Is Crediblity a Guide to Possibility? A Challenge for Toy Models in Science.Ylwa Sjölin Wirling - forthcoming - Analysis.
    Several philosophers of science claim that scientific toy models afford knowledge of possibility, but answers to the question of why toy models can be expected to competently play this role are scarce. The main line of reply is that toy models support possibility claims insofar as they are credible. I raise a challenge for this credibility-thesis, drawing on a familiar problem for imagination-based modal epistemologies, and argue that it remains unanswered in the current literature. The credibility-thesis has a long way (...)
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  8. How to Interpret Covid-19 Predictions: Reassessing the IHME’s Model.S. Andrew Schroeder - 2021 - Philosophy of Medicine 1 (2).
    The IHME Covid-19 prediction model has been one of the most influential Covid models in the United States. Early on, it received heavy criticism for understating the extent of the epidemic. I argue that this criticism was based on a misunderstanding of the model. The model was best interpreted not as attempting to forecast the actual course of the epidemic. Rather, it was attempting to make a conditional projection: telling us how the epidemic would unfold, given certain assumptions. This misunderstanding (...)
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  9. What Theoretical Equivalence Could Not Be.Trevor Teitel - 2021 - Philosophical Studies:1-31.
    Formal criteria of theoretical equivalence are mathematical mappings between specific sorts of mathematical objects, notably including those objects used in mathematical physics. Proponents of formal criteria claim that results involving these criteria have implications that extend beyond pure mathematics. For instance, they claim that formal criteria bear on the project of using our best mathematical physics as a guide to what the world is like, and also have deflationary implications for various debates in the metaphysics of physics. In this paper, (...)
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  10. Resenha do livro Imagens de natureza, imagens de ciência (2ª edição revista e ampliada. Rio de Janeiro: Eduerj, 2016), de Paulo C. Abrantes. [REVIEW]Bruno Camilo de Oliveira - 2020 - Revista Helius 3:1250-1263.
    The second edition of the work of the Brazilian physicist Paulo C. Abrantes (2016), entitled Images of nature, images of science, is a good alternative for students of history and philosophy of science. The reason is Abrantes' thesis in this work: to defend that the development of scientific knowledge is dependent on the influence of different images of "nature" and "science" existing during the history of Western scientific-philosophical thought; and an advocate for the historian of science Studying as reasons that (...)
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  11. The Dynamical Renaissance in Neuroscience.Luis H. Favela - 2020 - Synthese 1 (1):1-25.
    Although there is a substantial philosophical literature on dynamical systems theory in the cognitive sciences, the same is not the case for neuroscience. This paper attempts to motivate increased discussion via a set of overlapping issues. The first aim is primarily historical and is to demonstrate that dynamical systems theory is currently experiencing a renaissance in neuroscience. Although dynamical concepts and methods are becoming increasingly popular in contemporary neuroscience, the general approach should not be viewed as something entirely new to (...)
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  12. Disambiguation of Social Polarization Concepts and Measures.Aaron Bramson, Patrick Grim, Daniel J. Singer, Steven Fisher, William Berger, Graham Sack & Carissa Flocken - 2016 - Journal of Mathematical Sociology 40:80-111.
    ABSTRACT This article distinguishes nine senses of polarization and provides formal measures for each one to refine the methodology used to describe polarization in distributions of attitudes. Each distinct concept is explained through a definition, formal measures, examples, and references. We then apply these measures to GSS data regarding political views, opinions on abortion, and religiosity—topics described as revealing social polarization. Previous breakdowns of polarization include domain-specific assumptions and focus on a subset of the distribution’s features. This has conflated multiple, (...)
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  13. Philosophical Analysis in Modeling Polarization: Notes From a Work in Progress.Patrick Grim, Aaron Bramson, Daniel J. Singer, Stephen Fisher, Carissa Flocken & William Berger - 2013 - In Paul Youngman & Mirsad Hadzikadik (eds.), Complexity and the Human Experience: Modeling Complexity in the Humanities and Social Sciences. Pan Sanford.
  14. Estrategias tropológicas en ciencia.Israel Salas Llanas - 2019 - Dissertation, Universidad Autónoma de Madrid
    Para el constructivismo, la ciencia y la cognición comparten intereses similares. Ambos dominios pueden describirse como dos sistemas entrelazados que se activan mutuamente y se modulan entre sí a través de un lazo interno de retroalimentación, lazo que opera mediante la dinámica interna representativa en el caso de la cognición y mediante la dinámica del desarrollo teórico en el caso de la ciencia. Cada uno de estos dominios —ciencia y cognición— busca generar un marco de interacción adecuado que garantice, por (...)
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  15. A Critical Look on Critical Realism.Agustina Borella - 2012 - Perspectives on Epistemology of Economics:183-207.
    Tony Lawson, founder of The Social Ontology Group and The Realist Workshop of Cambridge, has proposed critical realism to reorient economics. The transformation of the social world that Lawson tries, emerges from the adherence to critical realism, this is, from taking the transcendental realism of Roy Bhaskar to the social realm. With the purpose of deepening the criticisms to this movement, we will specify what is critical realism, and which are the philosophical assumptions of the mainstream according to this author. (...)
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  16. Modelar o no modelar: esa no es la cuestión. ¿Hay algo intermedio?Agustina Borella - 2017 - Revista Perspectivas de Las Ciencias Económicas y Jurídicas 7 (2):89-100.
    The present paper tries to show that in the discussion on whether it is better to model or not to capture truth in the social world, that is not what is mainly being discussed. We put forward that the main question in this discussion is, essentially, ontological, not methodological. As a representative of the “to model position” we will refer to Uskali Mäki’s Possible Realism, and as one ofthe “notto model position” we will consider Tony Lawson’s Critical Realism. What will (...)
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  17. Pinceladas de Realismo Finlandés. [REVIEW]Agustina Borella - 2013 - Filosofia de la Economia 1 (1):131-137.
    La presente obra ofrece un análisis crítico de la filosofía de la economía de Uskali Mäki; en particular de la consideración realista científica de la economía. Se intenta a lo largo del texto responder, de algún modo, a las preguntas que plantea Lehtinen en la introducción: “¿Están los economistas aspirando en absoluto a la verdad, o están solamente jugando un juego intelectual en que tales supuestos son aceptables por alguna razón misteriosa? ¿Están estudiando la economía en serio? ¿Están simplemente desinteresados (...)
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  18. Trazos- Ensayos de Filosofía para el Mundo Social.Agustina Borella (ed.) - 2020 - Buenos Aires, CABA, Argentina: Grupo Unión.
    Entender algo sobre un mundo que se nos presenta de modo desordenado e incompleto constituye buena parte de la tarea de la filosofía y de la ciencia. La racionalidad, los modelos, y el mundo social introducen preocupaciones propias de la filosofía de la ciencia en general y de la epistemología de la economía en particular. Los aportes de Popper, Lawson, Mäki, Hayek y Cartwright se expresan en estos trazos como intentos abiertos para alcanzar a comprender nuestro mundo.
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  19. Fundamento Ontológico del Modelo en Hayek.Agustina Borella - 2019 - Procesos de Mercado. Revista Europea de Economía Política 2 (XVI):103-124.
    In the debate on realism of models in economics, the Austrian School and Hayekin particular, seem to have, in a certain way, remained outside. Assuming neoclassical models asunrealistic, the theory of the market as a process looks like a more realistic proposal. However, oneof the fundamental issue s in Hayek’s dissent is not so much the unrealism of the assumptions, but that the market equilibrium theory was not correctly raised, especially with regards to the perfectknowledge assumption. Despite this, in this (...)
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  20. Policymaking Under Scientific Uncertainty.Joe Roussos - 2020 - Dissertation, London School of Economics
    Policymakers who seek to make scientifically informed decisions are constantly confronted by scientific uncertainty and expert disagreement. This thesis asks: how can policymakers rationally respond to expert disagreement and scientific uncertainty? This is a work of non-ideal theory, which applies formal philosophical tools developed by ideal theorists to more realistic cases of policymaking under scientific uncertainty. I start with Bayesian approaches to expert testimony and the problem of expert disagreement, arguing that two popular approaches— supra-Bayesianism and the standard model of (...)
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  21. Models, Information and Meaning.Marc Artiga - 2020 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 82:101284.
    There has recently been an explosion of formal models of signalling, which have been developed to learn about different aspects of meaning. This paper discusses whether that success can also be used to provide an original naturalistic theory of meaning in terms of information or some related notion. In particular, it argues that, although these models can teach us a lot about different aspects of content, at the moment they fail to support the idea that meaning just is some kind (...)
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  22. The Use and Limitations of Null-Model-Based Hypothesis Testing.Mingjun Zhang - 2020 - Biology and Philosophy 35 (2):1-22.
    In this article I give a critical evaluation of the use and limitations of null-model-based hypothesis testing as a research strategy in the biological sciences. According to this strategy, the null model based on a randomization procedure provides an appropriate null hypothesis stating that the existence of a pattern is the result of random processes or can be expected by chance alone, and proponents of other hypotheses should first try to reject this null hypothesis in order to demonstrate their own (...)
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  23. From a Boson to the Standard Model Higgs: A Case Study in Confirmation and Model Dynamics.Cristin Chall, Martin King, Peter Mättig & Michael Stöltzner - 2019 - Synthese 198 (Suppl 16):3779-3811.
    Our paper studies the anatomy of the discovery of the Higgs boson at the Large Hadron Collider and its influence on the broader model landscape of particle physics. We investigate the phases of this discovery, which led to a crucial reconfiguration of the model landscape of elementary particle physics and eventually to a confirmation of the standard model. A keyword search of preprints covering the electroweak symmetry breaking sector of particle physics, along with an examination of physicists own understanding of (...)
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  24. Actual Causation and the Art of Modeling.Joseph Halpern & Christopher Hitchcock - 2010 - In Causality, Probability, and Heuristics: A Tribute to Judea Pearl. London: College Publications. pp. 383-406.
  25. Scientific Modelling in Generative Grammar and the Dynamic Turn in Syntax.Ryan Nefdt - 2016 - Linguistics and Philosophy 39 (5):357-394.
    In this paper, I address the issue of scientific modelling in contemporary linguistics, focusing on the generative tradition. In so doing, I identify two common varieties of linguistic idealisation, which I call determination and isolation respectively. I argue that these distinct types of idealisation can both be described within the remit of Weisberg’s :639–659, 2007) minimalist idealisation strategy in the sciences. Following a line set by Blutner :27–35, 2011), I propose this minimalist idealisation analysis for a broad construal of the (...)
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  26. Explanation and Understanding Through Scientific Models.Richard David-Rus - unknown
  27. Model Change and Reliability in Scientific Inference.Erich Kummerfeld & David Danks - 2014 - Synthese 191 (12):2673-2693.
    One persistent challenge in scientific practice is that the structure of the world can be unstable: changes in the broader context can alter which model of a phenomenon is preferred, all without any overt signal. Scientific discovery becomes much harder when we have a moving target, and the resulting incorrect understandings of relationships in the world can have significant real-world and practical consequences. In this paper, we argue that it is common (in certain sciences) to have changes of context that (...)
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  28. Environmental Risk Analysis: Robustness Is Essential for Precaution.Jan Sprenger - 2012 - Philosophy of Science 79 (5):881-892.
    Precaution is a relevant and much-invoked value in environmental risk analysis, as witnessed by the ongoing vivid discussion about the precautionary principle (PP). This article argues (i) against purely decision-theoretic explications of PP; (ii) that the construction, evaluation, and use of scientific models falls under the scope of PP; and (iii) that epistemic and decision-theoretic robustness are essential for precautionary policy making. These claims are elaborated and defended by means of case studies from climate science and conservation biology.
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  29. D. Rothbart, Editor, Modeling: Gateway to the Unknown. A Work by Rom Harré, Elsevier, London (2004) ISBN 0-444-51464-3 (300pp., US$ 119 Hardbound). [REVIEW]M. Morrison - 2005 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 36 (3):583-585.
  30. On Hodgkin and Huxley's Theory of Excitable Membranes.Ulrich Müller & Stephan Pilatus - 1982 - Theoretical Medicine and Bioethics 3 (2):193-208.
    Using Sneed's metatheory an attempt is made to reconstruct Hodgkin and Huxley's theory of excitation of cell membranes. The structure of this theory is uncovered by defining set-theoretical predicates for the partial potential models, potential models, and models of the theory. The function of permeability is said to be the only theoretical function with respect to this theory. The main underlying assumptions of the theory are briefly outlined.
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  31. Rejoinder.David Freedman - 1995 - Foundations of Science 1 (1):69-83.
    My favorite opponent in this debate once made a remarkable concession, not that it interfered with business as usual:No sensible social scientist believes any particular specification, coefficient estimate, or standard error. Social science theories ... imply that specifications and parameters constant over situations do not exist ... One searches for qualitative theory ... not for quantitative specifications Achen (1987, p.149). . With Hooke's law and the like, we are estimating parameters in specifications that are constant across time—at least to a (...)
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  32. Natural Science as a Hermeneutic of Instrumentation.Patrick Heelan - 1983 - Philosophy of Science 50 (2):181-204.
    The author proposes the thesis that all perception, including observation in natural science, is hermeneutical as well as causal; that is, the perceiver (or observer) learns to 'read' instrumental or other perceptual stimuli as one learns to read a text. This hermeneutical aspect at the heart of natural science is located where it might be least expected, within acts of scientific observation. In relation to the history of science, the question is addressed to what extent the hermeneutical component within scientific (...)
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  33. Model Selection and the Multiplicity of Patterns in Empirical Data.James W. McAllister - 2007 - Philosophy of Science 74 (5):884-894.
    Several quantitative techniques for choosing among data models are available. Among these are techniques based on algorithmic information theory, minimum description length theory, and the Akaike information criterion. All these techniques are designed to identify a single model of a data set as being the closest to the truth. I argue, using examples, that many data sets in science show multiple patterns, providing evidence for multiple phenomena. For any such data set, there is more than one data model that must (...)
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The Nature of Models
  1. Exploring Minds: Modes of Modeling and Simulation in Artificial Intelligence.Hajo Greif - 2021 - Perspectives on Science 29 (4):409-435.
  2. Cognitive Pluralism.Steven Horst - 2016 - 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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  3. La surprise comme mesure de l'empiricité des simulations computationnelles.Franck Varenne - 2015 - In Natalie Depraz & Claudia Serban (eds.), La surprise. A l'épreuve des langues. Paris: Hermann. pp. 199-217.
    This chapter elaborates and develops the thesis originally put forward by Mary Morgan (2005) that some mathematical models may surprise us, but that none of them can completely confound us, i.e. let us unable to produce an ex post theoretical understanding of the outcome of the model calculations. This chapter intends to object and demonstrate that what is certainly true of classical mathematical models is however not true of pluri-formalized simulations with multiple axiomatic bases. This chapter thus proposes to show (...)
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  4. Ecological-Enactive Scientific Cognition: Modeling and Material Engagement.Giovanni Rolla & Felipe Novaes - 2020 - Phenomenology and the Cognitive Sciences 1:1-19.
    Ecological-enactive approaches to cognition aim to explain cognition in terms of the dynamic coupling between agent and environment. Accordingly, cognition of one’s immediate environment (which is sometimes labeled “basic” cognition) depends on enaction and the picking up of affordances. However, ecological-enactive views supposedly fail to account for what is sometimes called “higher” cognition, i.e., cognition about potentially absent targets, which therefore can only be explained by postulating representational content. This challenge levelled against ecological-enactive approaches highlights a putative explanatory gap between (...)
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  5. Laws, Models, and Theories in Biology: A Unifying Interpretation.Pablo Lorenzano - 2020 - In Lorenzo Baravalle & Luciana Zaterka (eds.), Life and Evolution, History, Philosophy and Theory of the Life Sciences. pp. 163-207.
    Three metascientific concepts that have been object of philosophical analysis are the concepts oflaw, model and theory. The aim ofthis article is to present the explication of these concepts, and of their relationships, made within the framework of Sneedean or Metatheoretical Structuralism (Balzer et al. 1987), and of their application to a case from the realm of biology: Population Dynamics. The analysis carried out will make it possible to support, contrary to what some philosophers of science in general and of (...)
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  6. Prefacio.Daniel Blanco, Santiago Ginnobili & Pablo Lorenzano - 2016 - Metatheoria – Revista de Filosofía E Historia de la Ciencia 6:1--2.
  7. Introducción: Modelos y teorías en biología.Pablo Lorenzano - 2016 - Metatheoria – Revista de Filosofía E Historia de la Ciencia 6:5--46.
    Two metascientific concepts that have been ― and still are ― object of philosophical analysis are the concepts of model and theory. But while the concept of scientific theory was one of the concepts to which philosophers of science devoted most attention during the 20th century, it is only in recent decades that the concept of scientific model has come to occupy a central position in philosophical reflection. However, it has done so in such a way that, at present, as (...)
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  8. What Experimental Economics Teaches Us About Models. [REVIEW]Anna Alexandrova - 2008 - Journal of Economic Methodology 15:197-204.
  9. Philosophical Perspectives on Earth System Modeling: Truth, Adequacy and Understanding.G. Gramelsberger, J. Lenhard & Wendy Parker - 2020 - Journal of Advances in Modeling Earth Systems 12 (1):e2019MS001720.
    We explore three questions about Earth system modeling that are of both scientific and philosophical interest: What kind of understanding can be gained via complex Earth system models? How can the limits of understanding be bypassed or managed? How should the task of evaluating Earth system models be conceptualized?
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  10. 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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  11. Битие и наука.Vasil Penchev - 1996 - Sofia: "Дамян Яков".
    The book suggests a "phenomological" philosophy of science, in the sense of Husserl and Heidegger. Reality is consideried as continuity. The scientific model is entangled into reality by many links in a single context rather than to redlect a certain separate part of reality studied by a scientific discipline as an "image of reality", A coherent, rather than correspondent, concept of truth is relevant to that kind of philosophy of science.
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  12. Getting Serious About Shared Features.Donal Khosrowi - 2020 - British Journal for the Philosophy of Science 71 (2):523-546.
    In Simulation and Similarity, Michael Weisberg offers a similarity-based account of the model–world relation, which is the relation in virtue of which successful models are successful. Weisberg’s main idea is that models are similar to targets in virtue of sharing features. An important concern about Weisberg’s account is that it remains silent on what it means for models and targets to share features, and consequently on how feature-sharing contributes to models’ epistemic success. I consider three potential ways of concretizing the (...)
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  13. Metafore, modelli, linguaggio scientifico: il dibattito postempirista.Sergio Volodia Marcello Cremaschi - 1988 - In Melchiorre Virgilio (ed.), Simbolo e conoscenza. Milan, Italy: VIta e Pensiero. pp. 31-102.
    I discuss Mary Hess’s interaction-view of scientific metaphor, outline an alternative view and show how it may prove fruitful when applied to chapters of the history of science. I start with a reconstruction of the discussion on the nature of scientific models and on their relationship to metaphors that has taken place in the Anglo-Saxon philosophy of Science starting from the Fifties; the discovery started with Stephen Pepper and Kenneth Burke, reaching Thomas Kuhn, Marx Wartofsky, and George Lakoff via Max (...)
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  14. Concrete Scale Models, Essential Idealization, and Causal Explanation.Christopher Pincock - forthcoming - British Journal for the Philosophy of Science:000-000.
    This paper defends three claims about concrete or physical models: these models remain important in science and engineering, they are often essentially idealized, in a sense to be made precise, and despite these essential idealizations, some of these models may be reliably used for the purpose of causal explanation. This discussion of concrete models is pursued using a detailed case study of some recent models of landslide generated impulse waves. Practitioners show a clear awareness of the idealized character of these (...)
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  15. Unifying the Essential Concepts of Biological Networks: Biological Insights and Philosophical Foundations.Daniel Kostic, Claus Hilgetag & Marc Tittgemeyer - forthcoming - Philosophical Transactions of the Royal Society B: Biological Sciences.
    Over the last decades, network-based approaches have become highly popular in diverse fields of biology, including neuroscience, ecology, molecular biology and genetics. While these approaches continue to grow very rapidly, some of their conceptual and methodological aspects still require a programmatic foundation. This challenge particularly concerns the question of whether a generalized account of explanatory, organisational and descriptive levels of networks can be applied universally across biological sciences. To this end, this highly interdisciplinary theme issue focuses on the definition, motivation (...)
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  16. Integración de analogías en la investigación científica (Integration of Analogies in Scientific Modeling).Natalia Carrillo-Escalera - 2019 - Revista Colombiana de Filosofía de la Ciencia 37 (18):318-335.
    Discussion of modeling within philosophy of science has focused in how models, understood as finished products, represent the world. This approach has some issues accounting for the value of modeling in situations where there are controversies as to which should be the object of representation. In this work I show that a historical analysis of modeling complements the aforementioned representational program, since it allows us to examine processes of integration of analogies that play a role in the generation of criteria (...)
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  17. Models as Signs: Extending Kralemann and Lattman’s Proposal on Modeling Models Within Peirce’s Theory of Signs.Sergio Gallegos - 2019 - Synthese 196 (12):5115-5136.
    In recent decades, philosophers of science have devoted considerable efforts to understand what models represent. One popular position is that models represent fictional situations. Another position states that, though models often involve fictional elements, they represent real objects or scenarios. Though these two positions may seem to be incompatible, I believe it is possible to reconcile them. Using a threefold distinction between different signs proposed by Peirce, I develop an argument based on a proposal recently made by Kralemann and Lattman (...)
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