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  1. added 2020-05-28
    Model Anarchism.Walter Veit - manuscript
    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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  2. added 2020-04-20
    Polycratic Hierarchies and Networks: What Simulation-Modeling at the LHC Can Teach Us About the Epistemology of Simulation.Florian J. Boge & Christian Zeitnitz - forthcoming - Synthese:1-35.
    Large scale experiments at CERN’s Large Hadron Collider (LHC) rely heavily on computer simulations (CSs), a fact that has recently caught philosophers’ attention. CSs obviously require appropriate modeling, and it is a common assumption among philosophers that the relevant models can be ordered into hierarchical structures. Focusing on LHC’s ATLAS experiment, we will establish three central results here: (a) With some distinct modifications, individual components of ATLAS’ overall simulation infrastructure can be ordered into hierarchical structures. Hence, to a good degree (...)
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  3. added 2020-03-27
    Perspectives, Questions, and Epistemic Value.Kareem Khalifa & Jared A. Millson - 2020 - In Michela Massimi & Ana-Maria Cretu (eds.), Knowledge From a Human Point of View. Cham: Springer Verlag. pp. 87-106.
    Many epistemologists endorse true-belief monism, the thesis that only true beliefs are of fundamental epistemic value. However, this view faces formidable counterexamples. In response to these challenges, we alter the letter, but not the spirit, of true-belief monism. We dub the resulting view “inquisitive truth monism”, which holds that only true answers to relevant questions are of fundamental epistemic value. Which questions are relevant is a function of an inquirer’s perspective, which is characterized by his/her interests, social role, and background (...)
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  4. added 2020-03-06
    Investigating Interdisciplinary Practice: Methodological Challenges.Miles MacLeod, Martina Merz, Uskali Mäki & Michiru Nagatsu - 2019 - Perspectives on Science 27 (4):545-552.
    Interdisciplinarity is one of the most prominent ideas driving science and research policy today.1 It is applied widely as a conception of what particularly creative and socially relevant research processes should consist of, whether in the natural sciences, the social sciences, the humanities, or elsewhere. Its advocates, many of whom are located in current science and research administration themselves, are using ideas of interdisciplinarity to reshape university organization and research funding. For the last 40 years, researchers studying interdisciplinarity have built (...)
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  5. added 2020-01-13
    Idealisation in Natural Language Semantics: Truth-Conditions for Radical Contextualists.Gabe Dupre - forthcoming - Inquiry: An Interdisciplinary Journal of Philosophy.
    In this paper, I shall provide a novel response to the argument from context-sensitivity against truth-conditional semantics. It is often argued that the contextual influences on truth-conditions outstrip the resources of standard truth-conditional accounts, and so truth-conditional semantics rests on a mistake. The argument assumes that truth-conditional semantics is legitimate if and only if natural language sentences have truth-conditions. I shall argue that this assumption is mistaken. Truth-conditional analyses should be viewed as idealised approximations of the complexities of natural language (...)
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  6. added 2020-01-13
    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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  7. added 2019-09-09
    Deep Learning: A Philosophical Introduction.Cameron Buckner - 2019 - Philosophy Compass 14 (10).
  8. added 2019-09-09
    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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  9. added 2019-07-08
    Synthetic Versus Analytic Approaches to Protein and DNA Structure Determination.Agnes Bolinska - 2018 - Biology and Philosophy 33 (3-4):26.
    The structures of protein and DNA were discovered primarily by means of synthesizing component-level information about bond types, lengths, and angles, rather than analyzing X-ray diffraction photographs of these molecules. In this paper, I consider the synthetic and analytic approaches to exemplify alternative heuristics for approaching mid-twentieth-century macromolecular structure determination. I argue that the former was, all else being equal, likeliest to generate the correct structure in the shortest period of time. I begin by characterizing problem solving in these cases (...)
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  10. added 2019-03-31
    The Epistemic Virtue of Robustness in Climate Modeling (MA Dissertation).Parjanya Joshi - 2019 - Dissertation, Tata Institute of Social Sciences
    The aim of this dissertation is to comprehensively study various robustness arguments proposed in the literature from Levins to Lloyd as well as the opposition offered to them and pose enquiry into the degree of epistemic virtue that they provide to the model prediction results with respect to climate science and modeling. Another critical issue that this dissertation strives to examine is that of the actual epistemic notion that is operational when scientists and philosophers appeal to robustness. In attempting to (...)
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  11. added 2019-03-21
    Understanding Does Not Depend on (Causal) Explanation.Philippe Verreault-Julien - 2019 - European Journal for Philosophy of Science 9 (2):18.
    One can find in the literature two sets of views concerning the relationship between understanding and explanation: that one understands only if 1) one has knowledge of causes and 2) that knowledge is provided by an explanation. Taken together, these tenets characterize what I call the narrow knowledge account of understanding. While the first tenet has recently come under severe attack, the second has been more resistant to change. I argue that we have good reasons to reject it on the (...)
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  12. added 2019-03-12
    Similarity, Adequacy, and Purpose: Understanding the Success of Scientific Models.Melissa Jacquart - 2016 - Dissertation, University of Western Ontario
    A central component to scientific practice is the construction and use of scientific models. Scientists believe that the success of a model justifies making claims that go beyond the model itself. However, philosophical analysis of models suggests that drawing inferences about the world from successful models is more complex. In this dissertation I develop a framework that can help disentangle the related strands of evaluation of model success, model extendibility, and the ability to draw ampliative inferences about the world from (...)
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  13. added 2019-01-28
    Learning About Reality Through Models and Computer Simulations.Melissa Jacquart - 2018 - Science & Education 27 (7-8):805-810.
    Margaret Morrison, (2015) Reconstructing Reality: Models, Mathematics, and Simulations. Oxford University Press, New York. -/- Scientific models, mathematical equations, and computer simulations are indispensable to scientific practice. Through the use of models, scientists are able to effectively learn about how the world works, and to discover new information. However, there is a challenge in understanding how scientists can generate knowledge from their use, stemming from the fact that models and computer simulations are necessarily incomplete representations, and partial descriptions, of their (...)
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  14. added 2018-11-12
    Idealizations and Understanding: Much Ado About Nothing?Emily Sullivan & Kareem Khalifa - 2019 - Australasian Journal of Philosophy 97 (4):673-689.
    Because idealizations frequently advance scientific understanding, many claim that falsehoods play an epistemic role. In this paper, we argue that these positions greatly overstate idealiza...
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  15. added 2018-10-28
    Stochastic Stability and Disagreements Between Dynamics.Aydin Mohseni - 2019 - Philosophy of Science 86 (3):497-521.
    The replicator dynamics and Moran process are the main deterministic and stochastic models of evolutionary game theory. The models are connected by a mean-field relationship—the former describes the expected behavior of the latter. However, there are conditions under which their predictions diverge. I demonstrate that the divergence between their predictions is a function of standard techniques used in their analysis and of differences in the idealizations involved in each. My analysis reveals problems for stochastic stability analysis in a broad class (...)
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  16. added 2018-10-25
    The Exploratory Role of Idealizations and Limiting Cases in Models.Elay Shech & Axel Gelfert - forthcoming - Studia Metodologiczne.
    In this article we argue that idealizations and limiting cases in models play an exploratory role in science. Four senses of exploration are presented: exploration of the structure and representational capacities of theory; proof-of-principle demonstrations; potential explanations; and exploring the suitability of target systems. We illustrate our claims through three case studies, including the Aharonov-Bohm effect, the emergence of anyons and fractional quantum statistics, and the Hubbard model of the Mott phase transitions. We end by reflecting on how our case (...)
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  17. added 2018-09-04
    What Does a Computer Simulation Prove? The Case of Plant Modeling at CIRAD.Franck Varenne - 2001 - In N. Giambiasi & C. Frydman (eds.), Simulation in industry - ESS 2001, Proc. of the 13th European Simulation Symposium. Society for Computer Simulation (SCS).
    The credibility of digital computer simulations has always been a problem. Today, through the debate on verification and validation, it has become a key issue. I will review the existing theses on that question. I will show that, due to the role of epistemological beliefs in science, no general agreement can be found on this matter. Hence, the complexity of the construction of sciences must be acknowledged. I illustrate these claims with a recent historical example. Finally I temperate this diversity (...)
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  18. added 2018-08-29
    Modéliser le social. Méthodes fondatrices et évolutions récentes.Franck Varenne - 2011 - Paris, France: Dunod.
    Cet ouvrage très pédagogique informe les étudiants sur les méthodes quantitatives les plus classiques comme les plus récentes en sciences sociales, et notamment sur les différentes pratiques de modélisation et de simulation informatique des systèmes sociaux (sciences sociales computationnelles ou modèles informatiques).
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  19. added 2018-08-28
    Heuristics, Descriptions, and the Scope of Mechanistic Explanation.Carlos Zednik - 2015 - In P. Braillard & C. Malaterre (eds.), Explanation in Biology. An Enquiry into the Diversity of Explanatory Patterns in the Life Sciences. Dordrecht: Springer. pp. 295-318.
    The philosophical conception of mechanistic explanation is grounded on a limited number of canonical examples. These examples provide an overly narrow view of contemporary scientific practice, because they do not reflect the extent to which the heuristic strategies and descriptive practices that contribute to mechanistic explanation have evolved beyond the well-known methods of decomposition, localization, and pictorial representation. Recent examples from evolutionary robotics and network approaches to biology and neuroscience demonstrate the increasingly important role played by computer simulations and mathematical (...)
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  20. added 2018-06-12
    Prisoner's Dilemma Doesn't Explain Much.Robert Northcott & Anna Alexandrova - 2015 - In Martin Peterson (ed.), The Prisoner’s Dilemma. Classic philosophical arguments. Cambridge: Cambridge University Press. pp. 64-84.
    We make the case that the Prisoner’s Dilemma, notwithstanding its fame and the quantity of intellectual resources devoted to it, has largely failed to explain any phenomena of social scientific or biological interest. In the heart of the paper we examine in detail a famous purported example of Prisoner’s Dilemma empirical success, namely Axelrod’s analysis of WWI trench warfare, and argue that this success is greatly overstated. Further, we explain why this negative verdict is likely true generally and not just (...)
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  21. added 2018-04-27
    Simplified Models: A Different Perspective on Models as Mediators.C. D. McCoy & Michela Massimi - 2018 - European Journal for Philosophy of Science 8 (1):99-123.
    We introduce a novel point of view on the “models as mediators” framework in order to emphasize certain important epistemological questions about models in science which have so far been little investigated. To illustrate how this perspective can help answer these kinds of questions, we explore the use of simplified models in high energy physics research beyond the Standard Model. We show in detail how the construction of simplified models is grounded in the need to mitigate pressing epistemic problems concerning (...)
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  22. added 2018-03-29
    Research Habits in Financial Modelling: The Case of Non-Normativity of Market Returns in the 1970s and the 1980s.Boudewijn De Bruin & Christian Walter - 2017 - In Emiliano Ippoliti & Ping Chen (eds.), Methods and Finance: A Unifying View on Finance, Mathematics, and Philosophy. Cham: Springer. pp. 73-93.
    In this chapter, one considers finance at its very foundations, namely, at the place where assumptions are being made about the ways to measure the two key ingredients of finance: risk and return. It is well known that returns for a large class of assets display a number of stylized facts that cannot be squared with the traditional views of 1960s financial economics (normality and continuity assumptions, i.e. Brownian representation of market dynamics). Despite the empirical counterevidence, normality and continuity assumptions (...)
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  23. added 2018-02-17
    Modeling Social and Evolutionary Games.Angela Potochnik - 2012 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 43 (1):202-208.
    When game theory was introduced to biology, the components of classic game theory models were replaced with elements more befitting evolutionary phenomena. The actions of intelligent agents are replaced by phenotypic traits; utility is replaced by fitness; rational deliberation is replaced by natural selection. In this paper, I argue that this classic conception of comprehensive reapplication is misleading, for it overemphasizes the discontinuity between human behavior and evolved traits. Explicitly considering the representational roles of evolutionary game theory brings to attention (...)
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  24. added 2017-12-12
    Idealized and Perspectival Representations: Some Reasons for Making a Distinction.Alexander Rueger - 2014 - Synthese 191 (8):1831-1845.
    I argue that an adequate understanding of the practice of constructing models in physics requires a distinction between two strategies that are commonly both labeled ‘idealization’. The formal characteristic of both methods is to let a parameter in the equations for a target system go to zero. But the discussion of examples from various applications of perturbation theory shows that there is in general a difference with respect to the aims such limiting procedures are supposed to serve; and with different (...)
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  25. added 2017-12-12
    The Aerodynamics of Insects: The Role of Models and Matter in Scientific Experimentation.Michelle R. Silva - 2005 - Social Epistemology 19 (4):325 – 337.
    Historians and philosophers of science have examined the relationship between language and practice for a long time. Scholars have made important contributions to the field by attending to the social, cultural and economic contexts in which scientific paradigms are created and re-created. However, this article posits that while it is true that scientific practice and the artifacts they generate are both socially and discursively constructed and therefore, inextricable from the human contexts that produce them, these artifacts are not only texts (...)
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  26. added 2017-12-12
    Komparative Aussagemuster in Bezug Zu Komplementären Und Enkaptischen Modellen der Morphologie.A. Ritterbusch - 1981 - Acta Biotheoretica 30 (1):49-66.
    The unity of organisms can be viewed in terms of the concepts of enkapsis and complementarity. A model (or a type) represents those properties (of elements, structure, and system) which renders cases - the organisms under consideration — comparable. Comparability is established by operations (or metamorphoses) which relate a case to a model. Therefore, the model and the operations must be enumerated together, if a certain morphology is to be established and applied. Two models, which in some way are related, (...)
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  27. added 2017-12-06
    A Theory of Scientific Model Construction: The Conceptual Process of Abstraction and Concretisation. [REVIEW]Demetris P. Portides - 2005 - Foundations of Science 10 (1):67-88.
    The process of abstraction and concretisation is a label used for an explicative theory of scientific model-construction. In scientific theorising this process enters at various levels. We could identify two principal levels of abstraction that are useful to our understanding of theory-application. The first level is that of selecting a small number of variables and parameters abstracted from the universe of discourse and used to characterise the general laws of a theory. In classical mechanics, for example, we select position and (...)
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  28. added 2017-11-27
    The Use of Models.Bruce Edmonds - manuscript
    The use of MABS (Multi-Agent Based Simulations) is analysed as the modelling of distributed (usually social) systems using MAS as the model structure. It is argued that rarely is direct modelling of target systems attempted but rather an abstraction of the target systems is modelled and insights gained about the abstraction then applied back to the target systems. The MABS modelling process is divided into six steps: abstraction, design, inference, analysis, interpretation and application. Some types of MABS papers are characterised (...)
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  29. added 2017-11-27
    The Role Of Models In Computer Science.James H. Fetzer - 1999 - The Monist 82 (1):20-36.
    Taking Brian Cantwell Smith’s study, “Limits of Correctness in Computers,” as its point of departure, this article explores the role of models in computer science. Smith identifies two kinds of models that play an important role, where specifications are models of problems and programs are models of possible solutions. Both presuppose the existence of conceptualizations as ways of conceiving the world “in certain delimited ways.” But high-level programming languages also function as models of virtual (or abstract) machines, while low-level programming (...)
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  30. added 2017-11-27
    Bootstrapping Knowledge About Social Phenomena Using Simulation Models.Bruce Edmonds - unknown
    Formidable difficulties face anyone trying to model social phenomena using a formal system, such as a computer program. The differences between formal systems and complex, multi-facetted and meaning-laden social systems are so fundamental that many will criticise any attempt to bridge this gap. Despite this, there are those who are so bullish about the project of social simulation that they appear to believe that simple computer models, that are also useful and reliable indicators of how aspects of society works, are (...)
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  31. added 2017-11-01
    Partial Possible Models: An Approach to Interpret Students' Physical Representation.Fernando Flores Camacho & Leticia Gallegos Cazares - 1998 - Science Education 82 (1):15-29.