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  1. Bohr's Atomic Model and Paraconsistent Logic.Pandora Hadzidaki -
    Bohr’s atomic model is one of the better known examples of empirically successful, albeit inconsistent, theoretical schemes in the history of physics. For this reason, many philosophers use this model to illustrate their position for the occurrence and the function of inconsistency in science. In this paper, I proceed to a critical comparison of the structure and the aims of Bohr’s research program – the starting point of which was the formulation of his model – with some of its contemporary (...)
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  2. Review of True Enough, by Catherine Z. Elgin.John Bengson - forthcoming - Mind:fzz003.
    Review of True Enough, by Catherine Elgin. Reconstructs three pillars of Elgin's view (focused on truth enough, understanding, and holism); summarizes the book's main arguments against veritism and factivism; presents a general recipe for responding to those arguments; raises several objections to the view.
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  3. Towards a Taxonomy of the Model-Ladenness of Data.Alisa Bokulich - forthcoming - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association.
    Model-data symbiosis is the view that there is an interdependent and mutually beneficial relationship between data and models, whereby models are not only data-laden, but data are also model-laden or model filtered. In this paper I elaborate and defend the second, more controversial, component of the symbiosis view. In particular, I construct a preliminary taxonomy of the different ways in which theoretical and simulation models are used in the production of data sets. These include data conversion, data correction, data interpolation, (...)
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  4. The Truth About Better Understanding?Lewis Ross - forthcoming - Erkenntnis:1-24.
    The notion of understanding occupies an increasingly prominent place in contemporary epistemology, philosophy of science, and moral theory. A central and ongoing debate about the nature of understanding is how it relates to the truth. In a series of influential contributions, Catherine Elgin has used a variety of familiar motivations for antirealism in philosophy of science to defend a non- factive theory of understanding. Key to her position are: (i) the fact that false theories can contribute to the upwards trajectory (...)
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  5. Mechanistic Idealization in Systems Biology.Dingmar van Eck & Cory Wright - forthcoming - Synthese.
    This paper adds to the philosophical literature on mechanistic explanation by elaborating two related explanatory functions of idealisation in mechanistic models. The first function involves explaining the presence of structural/organizational features of mechanisms by reference to their role as difference-makers for performance requirements. The second involves tracking counterfactual dependency relations between features of mechanisms and features of mechanistic explanandum phenomena. To make these functions salient, we relate our discussion to an exemplar from systems biological research on the mechanism for countering (...)
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  6. Making Confident Decisions with Model Ensembles.Joe Roussos, Richard Bradley & Roman Frigg - 2021 - Philosophy of Science 88 (3):439-460.
    Many policy decisions take input from collections of scientific models. Such decisions face significant and often poorly understood uncertainty. We rework the so-called confidence approach to tackl...
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  7. Why I Am Not a Literalist.Zoe Drayson - 2020 - Mind and Language 35 (5):661-670.
    Carrie Figdor argues for literalism, a semantic claim about psychological predicates, on the basis of a scientific claim about the nature of psychological properties. I argue that her scientific claim is based on controversial interpretations of scientific modelling, and that even if it were correct it would not justify her claims that psychological predicates are undergoing radical conceptual change.
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  8. Understanding Climate Change with Statistical Downscaling and Machine Learning.Julie Jebeile, Vincent Lam & Tim Räz - 2020 - Synthese:1-21.
    Machine learning methods have recently created high expectations in the climate modelling context in view of addressing climate change, but they are often considered as non-physics-based ‘black boxes’ that may not provide any understanding. However, in many ways, understanding seems indispensable to appropriately evaluate climate models and to build confidence in climate projections. Relying on two case studies, we compare how machine learning and standard statistical techniques affect our ability to understand the climate system. For that purpose, we put five (...)
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  9. Philosophical Dogmatism Inhibiting the Anti-Copernican Interpretation of the Michelson Morley Experiment.Spyridon Kakos - 2020 - Harmonia Philosophica 1.
    From the beginning of time, humans believed they were the center of the universe. Such important beings could be nowhere else than at the very epicenter of existence, with all the other things revolving around them. Was this an arrogant position? Only time will tell. What is certain is that as some people were so certain of their significance, aeons later some other people became too confident in their unimportance. In such a context, the Earth quickly lost its privileged position (...)
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  10. Descartes’ Man Under Construction: The Circulatory Statue of Salomon Reisel, 1680.Mattia Mantovani - 2020 - Early Science and Medicine 25 (2):101-134.
    This paper studies the “human circulatory statues” which Salomon Reisel designed in the 1670s in order to demonstrate the circulation of the blood and its effect on the brain. It investigates how Reisel intended this project to promote Descartes’ philosophy, and how it relates to contemporary diagrammatic schematizations of the blood circulation system. It further explores Reisel’s claims concerning the epistemological and practical advantages of working with a three-dimensional model and argues that Reisel intended his statua to address the concerns (...)
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  11. Physical Entity As Quantum Information.Vasil Penchev - 2020 - Philosophy of Science eJournal (Elsevier: SSRN) 13 (35):1-15.
    Quantum mechanics was reformulated as an information theory involving a generalized kind of information, namely quantum information, in the end of the last century. Quantum mechanics is the most fundamental physical theory referring to all claiming to be physical. Any physical entity turns out to be quantum information in the final analysis. A quantum bit is the unit of quantum information, and it is a generalization of the unit of classical information, a bit, as well as the quantum information itself (...)
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  12. Cybernetics for the Command Economy: Foregrounding Entropy in Late Soviet Planning.Diana Kurkovsky West - 2020 - History of the Human Sciences 33 (1):36-51.
    The Soviet Union had a long and complex relationship with cybernetics, especially in the domain of planning. This article looks at Soviet postwar efforts to draw up plans for the rapidly developing, industrializing, and urbanizing Siberia, where cybernetic models were used to develop a vision of cybernetic socialism. Removed from Moscow bureaucracy and politics, the various planning institutes of the Siberian Academy of Sciences became a key frontier for exploring the potential of cybernetic thinking to offer a necessary corrective to (...)
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  13. Computer Simulation Validation - Fundamental Concepts, Methodological Frameworks, and Philosophical Perspectives.Claus Beisbart & Nicole J. Saam - 2019 - Springer.
    This unique volume introduces and discusses the methods of validating computer simulations in scientific research. The core concepts, strategies, and techniques of validation are explained by an international team of pre-eminent authorities, drawing on expertise from various fields ranging from engineering and the physical sciences to the social sciences and history. The work also offers new and original philosophical perspectives on the validation of simulations. Topics and features: introduces the fundamental concepts and principles related to the validation of computer simulations, (...)
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  14. Interprétabilité et explicabilité pour l’apprentissage machine : entre modèles descriptifs, modèles prédictifs et modèles causaux. Une nécessaire clarification épistémologique.Christophe Denis & Franck Varenne - 2019 - Actes de la Conférence Nationale En Intelligence Artificielle - CNIA 2019.
    Le déficit d’explicabilité des techniques d’apprentissage machine (AM) pose des problèmes opérationnels, juridiques et éthiques. Un des principaux objectifs de notre projet est de fournir des explications éthiques des sorties générées par une application fondée sur de l’AM, considérée comme une boîte noire. La première étape de ce projet, présentée dans cet article, consiste à montrer que la validation de ces boîtes noires diffère épistémologiquement de celle mise en place dans le cadre d’une modélisation mathématique et causale d’un phénomène physique. (...)
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  15. Probing Possibilities: Toy Models, Minimal Models, and Exploratory Models.Axel Gelfert - 2019 - In Matthieu Fontaine, Cristina Barés-Gómez, Francisco Salguero-Lamillar, Lorenzo Magnani & Ángel Nepomuceno-Fernández (eds.), Model-Based Reasoning in Science and Technology. Springer Verlag.
    According to one influential view, model-building in science is primarily a matter of simplifying theoretical descriptions of real-world target systems using abstraction and idealization. This view, however, does not adequately capture all types of models. Many contemporary models in the natural and social sciences – from physics to biology to economics – stand in a more tenuous relationship with real-world target systems and have a decidedly stipulative element, in that they create, by fiat, ‘model worlds’ that operate according to some (...)
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  16. Epistemic Norms: Truth Conducive Enough.Lisa Warenski - 2019 - Synthese 198 (3):2721-2741.
    Epistemology needs to account for the success of science. In True Enough, Catherine Elgin argues that a veritist epistemology is inadequate to this task. She advocates shifting epistemology’s focus away from true belief and toward understanding, and further, jettisoning truth from its privileged place in epistemological theorizing. Pace Elgin, I argue that epistemology’s accommodation of science does not require rejecting truth as the central epistemic value. Instead, it requires understanding veritism in an ecumenical way that acknowledges a rich array of (...)
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  17. Models in Search of Targets: Exploratory Modelling and the Case of Turing Patterns.Axel Gelfert - 2018 - In A. Christian, David Hommen, N. Retzlaff & Gerhard Schurz (eds.), Philosophy of Science. European Studies in Philosophy of Science, vol 9. Springer International Publishing. pp. 245-269.
    Traditional frameworks for evaluating scientific models have tended to downplay their exploratory function; instead they emphasize how models are inherently intended for specific phenomena and are to be judged by their ability to predict, reproduce, or explain empirical observations. By contrast, this paper argues that exploration should stand alongside explanation, prediction, and representation as a core function of scientific models. Thus, models often serve as starting points for future inquiry, as proofs of principle, as sources of potential explanations, and as (...)
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  18. Why Experiments Matter.Arnon Levy & Adrian Currie - 2018 - Inquiry: An Interdisciplinary Journal of Philosophy 62 (9-10):1066-1090.
    ABSTRACTExperimentation is traditionally considered a privileged means of confirmation. However, why and how experiments form a better confirmatory source relative to other strategies is unclear, and recent discussions have identified experiments with various modeling strategies on the one hand, and with ‘natural’ experiments on the other hand. We argue that experiments aiming to test theories are best understood as controlled investigations of specimens. ‘Control’ involves repeated, fine-grained causal manipulation of focal properties. This capacity generates rich knowledge of the object investigated. (...)
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  19. Scientific Realism and the Earth Sciences.Teru Miyake - 2018 - In Juha Saatsi (ed.), The Routledge Handbook of Scientific Realism. New York, USA: Routledge. pp. 333-344.
  20. From Models to Simulations.Franck Varenne - 2018 - London, UK: Routledge.
    This book analyses the impact computerization has had on contemporary science and explains the origins, technical nature and epistemological consequences of the current decisive interplay between technology and science: an intertwining of formalism, computation, data acquisition, data and visualization and how these factors have led to the spread of simulation models since the 1950s. -/- Using historical, comparative and interpretative case studies from a range of disciplines, with a particular emphasis on the case of plant studies, the author shows how (...)
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  21. Meta-Theoretical Contributions to the Constitution of a Model-Based Didactics of Science.Yefrin Ariza, Pablo Lorenzano & Agustín Adúriz-Bravo - 2016 - Science & Education 25 (7-8):747-773.
    There is nowadays consensus in the community of didactics of science regarding the need to include the philosophy of science in didactical research, science teacher education, curriculum design, and the practice of science education in all educational levels. Some authors have identified an ever-increasing use of the concept of ‘theoretical model’, stemming from the so-called semantic view of scientific theories. However, it can be recognised that, in didactics of science, there are over-simplified transpositions of the idea of model. In this (...)
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  22. Modeling Organs with Organs on Chips: Scientific Representation and Engineering Design as Modeling Relations.Michael Poznic - 2016 - Philosophy and Technology 29 (4):357-371.
    On the basis of a case study in bioengineering, this paper proposes a novel perspective on models in science and engineering. This is done with the help of two notions: representation and design. These two notions are interpreted as referring to modeling relations between vehicles and targets that differ in their respective directions of fit. The representation relation has a vehicle-to-target direction of fit and the design relation has a target-to-vehicle direction of fit. The case study of an organ on (...)
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  23. Scientific Misrepresentation and Guides to Ontology: The Need for Representational Code and Contents.Elay Shech - 2015 - Synthese 192 (11):3463-3485.
    In this paper I show how certain requirements must be set on any tenable account of scientific representation, such as the requirement allowing for misrepresentation. I then continue to argue that two leading accounts of scientific representation— the inferential account and the interpretational account—are flawed for they do not satisfy such requirements. Through such criticism, and drawing on an analogy from non-scientific representation, I also sketch the outline of a superior account. In particular, I propose to take epistemic representations to (...)
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  24. 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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  25. Seeing the Oceans in the Shadow of Bergen Values.Jacob Darwin Hamblin - 2014 - Isis 105 (2):352-363.
    Although oceanographers such as Roger Revelle are typically associated with key indicators of anthropogenic change, he and other scientists at midcentury had very different scientific priorities and ways of seeing the oceans. How can we join the narrative of the triumph of mathematical, dynamic oceanography with the environmental narrative? Dynamic methods entailed a broad set of values that touched the professional lives of marine scientists in a variety of disciplines all over the world, for better or for worse. The present (...)
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  26. Humanities’ Metaphysical Underpinnings of Late Frontier Scientific Research.Alcibiades Malapi-Nelson - 2014 - Humanities 214 (3):740-765.
    The behavior/structure methodological dichotomy as locus of scientific inquiry is closely related to the issue of modeling and theory change in scientific explanation. Given that the traditional tension between structure and behavior in scientific modeling is likely here to stay, considering the relevant precedents in the history of ideas could help us better understand this theoretical struggle. This better understanding might open up unforeseen possibilities and new instantiations, particularly in what concerns the proposed technological modification of the human condition. The (...)
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  27. Things and the Archives of Recent Sciences.Soraya de Chadarevian - 2013 - Studies in History and Philosophy of Science Part A 44 (4):634-638.
    With the interest in studying science as practice came an interest in the material artefacts and things that form part of scientific activities in the laboratory, the field, the classroom, or the political arena. This shift in interest in connection with new modes of knowledge production raises new questions regarding the “archive” of science: what should be preserved and where to make it possible to reconstruct scientific practices in the desired detail? While digital media may be able to bridge some (...)
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  28. Models, Simulations, and the Reduction of Complexity.Ulrich Gähde, Stephan Hartmann & Jörn Henning Wolf (eds.) - 2013 - De Gruyter.
    Modern science is, to a large extent, a model-building activity. But how are models contructed? How are they related to theories and data? How do they explain complex scientific phenomena, and which role do computer simulations play here? These questions have kept philosophers of science busy for many years, and much work has been done to identify modeling as the central activity of theoretical science. At the same time, these questions have been addressed by methodologically-minded scientists, albeit from a different (...)
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  29. Abstraction and the Organization of Mechanisms.Arnon Levy & William Bechtel - 2013 - Philosophy of Science 80 (2):241-261.
  30. Refounding of the Activity Concept? Towards a Federative Paradigm for Modeling and Simulation.Alexandre Muzy, Franck Varenne, Bernard P. Zeigler, Jonathan Caux, Patrick Coquillard, Luc Touraille, Dominique Prunetti, Philippe Caillou, Olivier Michel & David R. C. Hill - 2013 - Simulation - Transactions of the Society for Modeling and Simulation International 89 (2):156-177.
    Currently, the widely used notion of activity is increasingly present in computer science. However, because this notion is used in specific contexts, it becomes vague. Here, the notion of activity is scrutinized in various contexts and, accordingly, put in perspective. It is discussed through four scientific disciplines: computer science, biology, economics, and epistemology. The definition of activity usually used in simulation is extended to new qualitative and quantitative definitions. In computer science, biology and economics disciplines, the new simulation activity definition (...)
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  31. Introducción a “Nuevas contribuciones iberoamericanas a la metateoría estructuralista”.José A. Díez, José L. Falguera & Pablo Lorenzano - 2012 - Agora 31 (2).
    This is the introduction to the special issue of the Spanish journal Ágora-Papeles de Filosofía (31/2, 2012) devoted to new Ibero-American contributions to metatheoretical structuralism.
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  32. Models, Fictions, and Realism: Two Packages.Arnon Levy - 2012 - Philosophy of Science 79 (5):738-748.
    Some philosophers of science – the present author included – appeal to fiction as an interpretation of the practice of modeling. This raises the specter of an incompatibility with realism, since fiction-making is essentially non-truth-regulated. I argue that the prima facie conflict can be resolved in two ways, each involving a distinct notion of fiction and a corresponding formulation of realism. The main goal of the paper is to describe these two packages. Toward the end I comment on how to (...)
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  33. Complessità in fisica: che cos’è il cambiamento?Ignazio Licata - 2012 - Nuova Civiltà Delle Macchine 10 (4):59-76.
    IN FISICA LA COMPLESSITÀ FA IL SUO INGRESSO NELLA FISICA STATISTICA PER POI APPARIRE NELLO STUDIO DEI COMPORTAMENTI COLLETTIVI NELLA MATERIA CONDENSATA E DELLA SOFT MATTER, E DA ULTIMO NELLA NUOVA TEORIA DEL CAMBIAMENTO. RIDUZIONISMO ED EMERGENZA NON SONO APPROCCI OPPOSTI BENSÌ COMPLEMENTARI.
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  34. Quelques Aspects de L’Œuvre de Jean-Marie Legay.Franck Varenne - 2012 - Natures Sciences Sociétés 20 (4):461-463.
    Cet article revient sur la pratique scientifique et les thèses épistémologiques de Jean-Marie Legay concernant les modèles, les simulations et les systèmes complexes. Il montre qu'il y a une cohérence entre sa thèse anti-représentationnaliste concernant les modèles et les simulations et sa caractérisation même des systèmes complexes : une simulation informatique, seule, n'est pas une expérience au sens fort car, en l'isolant, on perd la dimension complexe de toute entreprise d'expérimentation scientifique dès lors qu'il y manque le modélisateur, le terrain (...)
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  35. Bernard Walliser's Comment Raisonnent les Économistes: Les Fonctions des Modèles. Paris: Odile Jacob, 2011, 278 Pp. [REVIEW]Philippe Verreault-Julien - 2012 - Erasmus Journal for Philosophy and Economics 5 (2):144.
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  36. An Agent-Based Conception of Models and Scientific Representation.Ronald N. Giere - 2010 - Synthese 172 (2):269–281.
    I argue for an intentional conception of representation in science that requires bringing scientific agents and their intentions into the picture. So the formula is: Agents (1) intend; (2) to use model, M; (3) to represent a part of the world, W; (4) for some purpose, P. This conception legitimates using similarity as the basic relationship between models and the world. Moreover, since just about anything can be used to represent anything else, there can be no unified ontology of models. (...)
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  37. Avoiding Policy Failure.Steven E. Wallis - 2010 - Emergent Publications.
    Why do policies fail? How can we objectively choose the best policy from two (or more) competing alternatives? How can we create better policies? To answer these critical questions this book presents an innovative yet workable approach. Avoiding Policy Failure uses emerging metapolicy methodologies in case studies that compare successful policies with ones that have failed. Those studies investigate the systemic nature of each policy text to gain new insights into why policies fail. -/- In addition to providing intriguing directions (...)
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  38. Logical Empiricism and Logical Positivism.Krzysztof Brzechczyn - 2009 - In Aviezer Tucker (ed.), A Companion to the Philosophy of History and Historiography. Wiley-Blackwell.
  39. Models, Pictures, and Unified Accounts of Representation: Lessons From Aesthetics for Philosophy of Science.Stephen M. Downes - 2009 - Perspectives on Science 17 (4):417-428.
    Several prominent philosophers of science, most notably Ron Giere, propose that scientific theories are collections of models and that models represent the objects of scientific study. Some, including Giere, argue that models represent in the same way that pictures represent. Aestheticians have brought the picturing relation under intense scrutiny and presented important arguments against the tenability of particular accounts of picturing. Many of these arguments from aesthetics can be used against accounts of representation in philosophy of science. I rely on (...)
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  40. Grados de materialidad y simulaciones computacionales.Juan M. Durán - 2009 - In Diego Letzen & Penélope Lodeyro (eds.), Epistemología e historia de la ciencia: Selección de trabajos de las XIX jornadas. pp. 171-177.
  41. On the Epistemological Foundations of the Law of the Lever.Maarten Van Dyck - 2009 - Studies in History and Philosophy of Science Part A 40 (3):315-318.
    In this paper I challenge Paolo Palmieri’s reading of the Mach-Vailati debate on Archimedes’s proof of the law of the lever. I argue that the actual import of the debate concerns the possible epistemic (as opposed to merely pragmatic) role of mathematical arguments in empirical physics, and that construed in this light Vailati carries the upper hand. This claim is defended by showing that Archimedes’s proof of the law of the lever is not a way of appealing to a non-empirical (...)
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  42. Alain Badiou : un philosophe face au concept de modèle.Franck Varenne - 2008 - Natures Sciences Sociétés 16 (3):252-257.
    In 1969, the influent French philosopher Alain Badiou published a book called "The concept of Model: An Introduction to the Materialist Epistemology of Mathematics". A recent reprint gives the opportunity to trace back and analyze its main arguments. This paper essentially aims to present and explain Badiou's arguments against the representationalist vision of models in empirical sciences and for a materialist interpretation of formal systems coupled with semantic models in mathematics. Now that the practices of scientific modeling and simulation have (...)
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  43. Agent-Based Models and Simulations in Economics and Social Sciences: From Conceptual Exploration to Distinct Ways of Experimenting.Franck Varenne & Denis Phan - 2008 - In Nuno David, José Castro Caldas & Helder Coelho (eds.), Proceedings of the 3rd EPOS congress (Epistemological Perspectives On Simulations). Lisbon: pp. 51-69.
    Now that complex Agent-Based Models and computer simulations spread over economics and social sciences - as in most sciences of complex systems -, epistemological puzzles (re)emerge. We introduce new epistemological tools so as to show to what precise extent each author is right when he focuses on some empirical, instrumental or conceptual significance of his model or simulation. By distinguishing between models and simulations, between types of models, between types of computer simulations and between types of empiricity, section 2 gives (...)
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  44. Growing Weed, Producing Knowledge An Epistemic History of Arabidopsis Thaliana.Sabina Leonelli - 2007 - History and Philosophy of the Life Sciences 29 (2):193 - 223.
    Arabidopsis is currently the most popular and well-researched model organism in plant biology. This paper documents this plant's rise to scientific fame by focusing on two interrelated aspects of Arabidopsis research. One is the extent to which the material features of the plant have constrained research directions and enabled scientific achievements. The other is the crucial role played by the international community of Arabidopsis researchers in making it possible to grow, distribute and use plant specimen that embody these material features. (...)
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  45. Robust Simulations.Ryan Muldoon - 2007 - 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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  46. Bachelard avec la simulation informatique: nous faut-il reconduire sa critique de l'intuition ?Franck Varenne - 2006 - In Robert Damien & B. Hufschmitt (eds.), Bachelard: Confiance Raisonnée Et Défiance Rationnelle. Besançon: Presses Universitaires de Franche-Comté. pp. 111-143.
    Dans un nombre croissant de domaines scientifiques - sciences de la nature, sciences humaines aussi bien que sciences des artefacts -, la simulation ne joue plus le rôle de succédané temporaire d'une théorie encore en gésine parce que non encore élaborée ; c'est-à-dire qu'elle ne joue plus systématiquement le rôle d'un modèle provisoire ou d'un schéma servant à condenser les mesures. C'est qu'elle n'a pas la nature d'un signe graphique, linguistique ou mathématique. Elle joue au contraire de plus en plus (...)
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  47. There Is No Special Problem About Scientific Representation.Craig Callender & Jonathan Cohen - 2005 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 21 (1):67-85.
    We propose that scientific representation is a special case of a more general notion of representation, and that the relatively well worked-out and plausible theories of the latter are directly applicable to thc scientific special case. Construing scientific representation in this way makes the so-called “problem of scientific representation” look much less interesting than it has seerned to many, and suggests that some of the debates in the literature are concerned with non-issues.
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  48. Scientific Models.Stephan Hartmann & Roman Frigg - 2005 - In Sarkar Sahotra (ed.), The Philosophy of Science: An Encyclopedia, Vol. 2. Routledge.
    Models are of central importance in many scientific contexts. The roles the MIT bag model of the nucleon, the billiard ball model of a gas, the Bohr model of the atom, the Gaussian-chain model of a polymer, the Lorenz model of the atmosphere, the Lotka- Volterra model of predator-prey interaction, agent-based and evolutionary models of social interaction, or general equilibrium models of markets play in their respective domains are cases in point.
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  49. Comentarios a «Explicación Teórica y Compromisos Ontológicos: Un Modelo Estructuralista», de C. Ulises Moulines.Pablo Lorenzano - 2005 - Enrahonar: Quaderns de Filosofía 37:55-59.
    In this comment on the work by Ulises Moulines I shall not refer to the interesting analysis of the ontological commitments that depends the treatment of the so-called «data models», nor shall I debate the general metaphysical principles proposed in his approach, adopting an experimentalist, instrumentalist, anti-realistic, positivist or empirical stance. I shall focus on the last part of his article in which he elaborates on the links between Wesley Salmon's causalist approach and the structuralist analysis of explanation viewed as (...)
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  50. Review of Paul Humphreys, Extending Ourselves: Computational Science, Empiricism, and Scientific Method[REVIEW]Paul Thagard - 2005 - Notre Dame Philosophical Reviews 2005 (6).
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