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  1. 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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  2. Maps and Models.Rasmus Grønfeldt Winther - forthcoming - In Routledge Handbook of Philosophy of Scientific Modeling. London, UK:
    Maps and mapping raise questions about models and modeling and in science. This chapter archives map discourse in the founding generation of philosophers of science (e.g., Rudolf Carnap, Nelson Goodman, Thomas Kuhn, and Stephen Toulmin) and in the subsequent generation (e.g., Philip Kitcher, Helen Longino, and Bas van Fraassen). In focusing on these two original framing generations of philosophy of science, I intend to remove us from the heat of contemporary discussions of abstraction, representation, and practice of science and thereby (...)
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  3. Unrealistic Models in Mathematics.William D'Alessandro - 2022 - Philosophers’ Imprint.
    Models are indispensable tools of scientific inquiry, and one of their main uses is to improve our understanding of the phenomena they represent. How do models accomplish this? And what does this tell us about the nature of understanding? While much recent work has aimed at answering these questions, philosophers' focus has been squarely on models in empirical science. I aim to show that pure mathematics also deserves a seat at the table. I begin by presenting two cases: Cramér’s random (...)
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  4. Introduction to the edited volume “Scientific Understanding and Representation: Modeling in the Physical Sciences”.Kareem Khalifa, Insa Lawler & Elay Shech - 2022 - In Insa Lawler, Kareem Khalifa & Elay Shech (eds.), Scientific Understanding and Representation: Modeling in the Physical Sciences. Routledge.
    This chapter gives an overview of the various themes and issues discussed in the volume. It includes summaries of all chapters and places the contributions, some of which are part of a critical conversation format, in the context of the larger literature and debates.
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  5. Teleosemantics and the free energy principle.Stephen Francis Mann & Ross Pain - 2022 - Biology and Philosophy 37 (4):1-25.
    The free energy principle is notoriously difficult to understand. In this paper, we relate the principle to a framework that philosophers of biology are familiar with: Ruth Millikan’s teleosemantics. We argue that: systems that minimise free energy are systems with a proper function; and Karl Friston’s notion of implicit modelling can be understood in terms of Millikan’s notion of mapping relations. Our analysis reveals some surprising formal similarities between the two frameworks, and suggests interesting lines of future research. We hope (...)
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  6. Inductive Risk, Understanding, and Opaque Machine Learning Models.Emily Sullivan - 2022 - Philosophy of Science 89 (5):1065-1074.
    Under what conditions does machine learning (ML) model opacity inhibit the possibility of explaining and understanding phenomena? In this article, I argue that nonepistemic values give shape to the ML opacity problem even if we keep researcher interests fixed. Treating ML models as an instance of doing model-based science to explain and understand phenomena reveals that there is (i) an external opacity problem, where the presence of inductive risk imposes higher standards on externally validating models, and (ii) an internal opacity (...)
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  7. Understanding from Machine Learning Models.Emily Sullivan - 2022 - British Journal for the Philosophy of Science 73 (1):109-133.
    Simple idealized models seem to provide more understanding than opaque, complex, and hyper-realistic models. However, an increasing number of scientists are going in the opposite direction by utilizing opaque machine learning models to make predictions and draw inferences, suggesting that scientists are opting for models that have less potential for understanding. Are scientists trading understanding for some other epistemic or pragmatic good when they choose a machine learning model? Or are the assumptions behind why minimal models provide understanding misguided? In (...)
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  8. Aristotle and Linearity in Substance, Measure, and Motion.Paul Taborsky - 2022 - Axiomathes 32 (6):1375-1399.
    The model of a closed linear measure space, which can be used to model Aristotle’s treatment of motion (kinesis), can be analogically extended to the qualitative ‘spaces’ implied by his theory of contraries in Physics I and in Metaphysics Iota, and to the dimensionless ‘space’ of the unity of matter and form discussed in book Eta of the Metaphysics. By examining Aristotle’s remarks on contraries, the subject of change, continuity, and the unity of matter and form, Aristotle’s thoughts on motion, (...)
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  9. g as bridge model.Devin Sanchez Curry - 2021 - Philosophy of Science 88 (5):1067-1078.
    Psychometric g—a statistical factor capturing intercorrelations between scores on different IQ tests—is of theoretical interest despite being a low-fidelity model of both folk psychological intelligence and its cognitive/neural underpinnings. Psychometric g idealizes away from those aspects of cognitive/neural mechanisms that are not explanatory of the relevant variety of folk psychological intelligence, and it idealizes away from those varieties of folk psychological intelligence that are not generated by the relevant cognitive/neural substrate. In this manner, g constitutes a high-fidelity bridge model of (...)
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  10. A New Role for Mathematics in Empirical Sciences.Atoosa Kasirzadeh - 2021 - Philosophy of Science 88 (4):686-706.
    Mathematics is often taken to play one of two roles in the empirical sciences: either it represents empirical phenomena or it explains these phenomena by imposing constraints on them. This article identifies a third and distinct role that has not been fully appreciated in the literature on applicability of mathematics and may be pervasive in scientific practice. I call this the “bridging” role of mathematics, according to which mathematics acts as a connecting scheme in our explanatory reasoning about why and (...)
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  11. Lange on Minimal Model Explanations: A Defense of Batterman and Rice.Travis McKenna - 2021 - Philosophy of Science 88 (4):731-741.
    Marc Lange has recently raised three objections to the account of minimal model explanations offered by Robert Batterman and Collin Rice. In this article, I suggest that these objections are misguided. I suggest that the objections raised by Lange stem from a misunderstanding of the what it is that minimal model explanations seek to explain. This misunderstanding, I argue, consists in Lange’s seeing minimal model explanations as relating special types of models to particular target systems rather than seeing minimal model (...)
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  12. Série Investigações Filosóficas: Textos Selecionados de Filosofia da Ciência II [Philosophical Investigation Series: Selected Texts on Philosophy of Science II].Luana Poliseli (ed.) - 2021 - Pelotas: Editora da Universidade Federal de Pelotas.
    A Série Investigação Filosófica, uma iniciativa do Núcleo de Ensino e Pesquisa em Filosofia do Departamento de Filosofia da UFPel e do Grupo de Pesquisa Investigação Filosófica do Departamento de Filosofia da UNIFAP, sob o selo editorial do NEPFil online e da Editora da Universidade Federal de Pelotas, com auxílio financeiro da John Templeton Foundation, tem por objetivo precípuo a publicação da tradução para a língua portuguesa de textos selecionados a partir de diversas plataformas internacionalmente reconhecidas, tal como a Stanford (...)
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  13. The Quest for System-Theoretical Medicine in the COVID-19 Era.Felix Tretter, Olaf Wolkenhauer, Michael Meyer-Hermann, Johannes W. Dietrich, Sara Green, James Marcum & Wolfram Weckwerth - 2021 - Frontiers in Medicine 8:640974.
    Precision medicine and molecular systems medicine (MSM) are highly utilized and successful approaches to improve understanding, diagnosis, and treatment of many diseases from bench-to-bedside. Especially in the COVID-19 pandemic, molecular techniques and biotechnological innovation have proven to be of utmost importance for rapid developments in disease diagnostics and treatment, including DNA and RNA sequencing technology, treatment with drugs and natural products and vaccine development. The COVID-19 crisis, however, has also demonstrated the need for systemic thinking and transdisciplinarity and the limits (...)
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  14. The Historical Distinctiveness of Central Europe: A Study in the Philosophy of History.Krzysztof Brzechczyn - 2020 - Bern: Peter Lang.
    The aim of this book is to explain economic dualism in the history of modern Europe. The emergence of the manorial-serf economy in the Bohemia, Poland, and Hungary in the 16th and the 17th centuries was the result of a cumulative impact of various circumstantial factors. The weakness of cities in Central Europe disturbed the social balance – so characteristic for Western-European societies – between burghers and the nobility. The political dominance of the nobility hampered the development of cities and (...)
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  15. Extrapolating from Laboratory Behavioral Research on Nonhuman Primates Is Unjustified.Parker Crutchfield - 2020 - Journal of Applied Philosophy 37 (4):628-645.
    Conducting research on animals is supposed to be valuable because it provides information on how human mechanisms work. But for the use of animal models to be ethically justified, it must be epistemically justified. The inference from an observation about an animal model to a conclusion about humans must be warranted for the use of animals to be moral. When researchers infer from animals to humans, it’s an extrapolation. Often non-human primates are used as animal models in laboratory behavioral research. (...)
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  16. Viewing-as explanations and ontic dependence.William D’Alessandro - 2020 - Philosophical Studies 177 (3):769-792.
    According to a widespread view in metaphysics and philosophy of science, all explanations involve relations of ontic dependence between the items appearing in the explanandum and the items appearing in the explanans. I argue that a family of mathematical cases, which I call “viewing-as explanations”, are incompatible with the Dependence Thesis. These cases, I claim, feature genuine explanations that aren’t supported by ontic dependence relations. Hence the thesis isn’t true in general. The first part of the paper defends this claim (...)
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  17. Explanations and candidate explanations in physics.Martin King - 2020 - European Journal for Philosophy of Science 10 (1):1-17.
    There has been a growing trend to include non-causal models in accounts of scientific explanation. A worry addressed in this paper is that without a higher threshold for explanation there are no tools for distinguishing between models that provide genuine explanations and those that provide merely potential explanations. To remedy this, a condition is introduced that extends a veridicality requirement to models that are empirically underdetermined, highly-idealised, or otherwise non-causal. This condition is applied to models of electroweak symmetry breaking beyond (...)
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  18. The Exploratory Status of Postconnectionist Models.Miljana Milojevic & Vanja Subotić - 2020 - Theoria: Beograd 2 (63):135-164.
    This paper aims to offer a new view of the role of connectionist models in the study of human cognition through the conceptualization of the history of connectionism – from the simplest perceptrons to convolutional neural nets based on deep learning techniques, as well as through the interpretation of criticism coming from symbolic cognitive science. Namely, the connectionist approach in cognitive science was the target of sharp criticism from the symbolists, which on several occasions caused its marginalization and almost complete (...)
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  19. Mechanist idealisation in systems biology.Dingmar van Eck & Cory Wright - 2020 - Synthese 199 (1-2):1555-1575.
    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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  20. Préface à "La diffusion de la Covid-19 - Que peuvent les modèles ?".Franck Varenne - 2020 - In Juliette Rouchier & Victorien Barbet (eds.), La diffusion de la Covid-19. Paris: pp. 3-10.
    Voilà un livre comme on pouvait l’espérer. Centré sur la Covid-19 et sur sa diffusion, il s’installe au cœur de questions brûlantes, encore urgentes pour tout un chacun, mais il garde aussi la tête froide, prend du recul, informe, enseigne et questionne, qui plus est de façon pédagogique. Davantage : au-delà du bilan critique, il propose des perspectives inédites, voire quelques suggestions solides. Il nous donne à réfléchir sur des chemins moins balisés. À le lire, on comprendra, par l’exemple, pourquoi (...)
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  21. Near-Decomposability and the Timescale Relativity of Causal Representations.Naftali Weinberger - 2020 - Philosophy of Science 87 (5):841-856.
    A common strategy for simplifying complex systems involves partitioning them into subsystems whose behaviors are roughly independent of one another at shorter timescales. Dynamic causal models clarify how doing so reveals a system’s nonequilibrium causal relationships. Here I use these models to elucidate the idealizations and abstractions involved in representing a system at a timescale. The models reveal that key features of causal representations—such as which variables are exogenous—may vary with the timescale at which a system is considered. This has (...)
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  22. Mathematical Representation and Explanation: structuralism, the similarity account, and the hotchpotch picture.Ziren Yang - 2020 - Dissertation, University of Leeds
    This thesis starts with three challenges to the structuralist accounts of applied mathematics. Structuralism views applied mathematics as a matter of building mapping functions between mathematical and target-ended structures. The first challenge concerns how it is possible for a non-mathematical target to be represented mathematically when the mapping functions per se are mathematical objects. The second challenge arises out of inconsistent early calculus, which suggests that mathematical representation does not require rigorous mathematical structures. The third challenge comes from renormalisation group (...)
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  23. Explicating objectual understanding: taking degrees seriously.Christoph Baumberger - 2019 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 1:1-22.
    The paper argues that an account of understanding should take the form of a Carnapian explication and acknowledge that understanding comes in degrees. An explication of objectual understanding is defended, which helps to make sense of the cognitive achievements and goals of science. The explication combines a necessary condition with three evaluative dimensions: An epistemic agent understands a subject matter by means of a theory only if the agent commits herself sufficiently to the theory of the subject matter, and to (...)
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  24. 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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  25. Two Tales of Epistemic Models.Yang Liu - 2019 - Thought: A Journal of Philosophy 8 (4):291-302.
    This short paper has two parts. First,we prove a generalisation of Aumann’s surprising impossibility result in the context of rational decision making. We then move, in the second part, to discuss the interpretational meaning of some formal setups of epistemic models, and we do so by means of presenting an interesting puzzle in epistemic logic. The aim is to highlight certain problematic aspects of these epistemic systems concerning first/third-person asymmetry which underlies both parts of the story. This asymmetry, we argue, (...)
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  26. Analytic Narratives: What they are and how they contribute to historical explanation.Philippe Mongin - 2019 - In Claude Diebolt & Michael Haupert (eds.), Handbook of Cliometrics. Berlin: Springer.
    The expression "analytic narratives" is used to refer to a range of quite recent studies that lie on the boundaries between history, political science, and economics. These studies purport to explain specific historical events by combining the usual narrative approach of historians with the analytic tools that economists and political scientists draw from formal rational choice theories. Game theory, especially of the extensive form version, is currently prominent among these tools, but there is nothing inevitable about such a technical choice. (...)
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  27. Integrative pluralism for biological function.Beckett Sterner & Samuel Cusimano - 2019 - Biology and Philosophy 34 (6):1-21.
    We introduce a new type of pluralism about biological function that, in contrast to existing, demonstrates a practical integration among the term’s different meanings. In particular, we show how to generalize Sandra Mitchell’s notion of integrative pluralism to circumstances where multiple epistemic tools of the same type are jointly necessary to solve scientific problems. We argue that the multiple definitions of biological function operate jointly in this way based on how biologists explain the evolution of protein function. To clarify how (...)
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  28. The Diversity of Models as a Means to Better Explanations in Economics.Emrah Aydinonat - 2018 - Journal of Economic Methodology 25 (3):237-251.
    In Economics Rules, Dani Rodrik (2015) argues that what makes economics powerful despite the limitations of each and every model is its diversity of models. Rodrik suggests that the diversity of models in economics improves its explanatory capacities, but he does not fully explain how. I offer a clearer picture of how models relate to explanations of particular economic facts or events, and suggest that the diversity of models is a means to better economic explanations.
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  29. When ecology and philosophy meet: constructing explanation and assessing understanding in scientific practice.Luana Poliseli - 2018 - Dissertation, Federal University of Bahia
    Philosophy of Science in Practice (PoSiP) has the “practice of science” as its object of research. Notwithstanding, it does not possess yet any general or specific methodology in order to achieve its goal. Instead of sticking to one protocol, PoSiP takes advantage of a set of approaches from different fields. This thesis takes as a starting point a collaborative and interdisciplinary research between two Ph.D. students from distinct areas: ecology and philosophy. This collaboration showed how a scientist could benefit from (...)
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  30. Rational analysis, intractability, and the prospects of ‘as if’-explanations.Iris van Rooij, Cory D. Wright, Johan Kwisthout & Todd Wareham - 2018 - Synthese 195 (2):491-510.
    Despite their success in describing and predicting cognitive behavior, the plausibility of so-called ‘rational explanations’ is often contested on the grounds of computational intractability. Several cognitive scientists have argued that such intractability is an orthogonal pseudoproblem, however, since rational explanations account for the ‘why’ of cognition but are agnostic about the ‘how’. Their central premise is that humans do not actually perform the rational calculations posited by their models, but only act as if they do. Whether or not the problem (...)
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  31. 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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  32. Modeling and Inferring in Science.Emiliano Ippoliti, Thomas Nickles & Fabio Sterpetti - 2016 - In Emiliano Ippoliti, Fabio Sterpetti & Thomas Nickles (eds.), Models and Inferences in Science. Springer. pp. 1-9.
    Science continually contributes new models and rethinks old ones. The way inferences are made is constantly being re-evaluated. The practice and achievements of science are both shaped by this process, so it is important to understand how models and inferences are made. But, despite the relevance of models and inference in scientific practice, these concepts still remain contro-versial in many respects. The attempt to understand the ways models and infer-ences are made basically opens two roads. The first one is to (...)
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  33. On structural accounts of model-explanations.Martin King - 2016 - Synthese 193 (9):2761-2778.
    The focus in the literature on scientific explanation has shifted in recent years towards model-based approaches. In recent work, Alisa Bokulich has argued that idealization has a central role to play in explanation. Bokulich claims that certain highly-idealized, structural models can be explanatory, even though they are not considered explanatory by causal, mechanistic, or covering law accounts of explanation. This paper focuses on Bokulich’s account in order to make the more general claim that there are problems with maintaining that a (...)
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  34. How Models Fail. A Critical Look at the History of Computer Simulations of the Evolution of Cooperation.Eckhart Arnold - 2015 - In Catrin Misselhorn (ed.), Collective Agency and Cooperation in Natural and Artificial Systems. Explanation, Implementation and Simulation, Philosophical Studies Series. Springer. pp. 261-279.
    Simulation models of the Reiterated Prisoner's Dilemma have been popular for studying the evolution of cooperation since more than 30 years now. However, there have been practically no successful instances of empirical application of any of these models. At the same time this lack of empirical testing and confirmation has almost entirely been ignored by the modelers community. In this paper, I examine some of the typical narratives and standard arguments with which these models are justified by their authors despite (...)
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  35. Understanding Cognition.Gordon Steenbergen - 2015 - Dissertation, Duke University
    Cognitive neuroscience is an interdisciplinary enterprise aimed at explaining cognition and behavior. It appears to be succeeding. What accounts for this apparent explanatory success? According to one prominent philosophical thesis, cognitive neuroscience explains by discovering and describing mechanisms. This "mechanist thesis" is open to at least two interpretations: a strong metaphysical thesis that Carl Craver and David Kaplan defend, and a weaker methodological thesis that William Bechtel defends. I argue that the metaphysical thesis is false and that the methodological thesis (...)
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  36. 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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  37. Don’t Blame the Idealizations.Nicholaos Jones - 2013 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 44 (1):85-100.
    Idealizing conditions are scapegoats for scientific hypotheses, too often blamed for falsehood better attributed to less obvious sources. But while the tendency to blame idealizations is common among both philosophers of science and scientists themselves, the blame is misplaced. Attention to the nature of idealizing conditions, the content of idealized hypotheses, and scientists’ attitudes toward those hypotheses shows that idealizing conditions are blameless when hypotheses misrepresent. These conditions help to determine the content of idealized hypotheses, and they do so in (...)
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  38. 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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  39. Alife models as epistemic artefacts.Xabier Barandiaran & Alvaro Moreno - 2006 - In Luis Rocha, Larry Yaeger & Mark Bedau (eds.), Artificial Life X : Proceedings of the Tenth International Conference on the Simulation and Synthesis of Living Systems. MIT Press. pp. 513-519.
    Both the irreducible complexity of biological phenomena and the aim of a universalized biology (life-as-it-could-be) have lead to a deep methodological shift in the study of life; represented by the appearance of ALife, with its claim that computational modelling is the main tool for studying the general principles of biological phenomenology. However this methodological shift implies important questions concerning the aesthetic, engineering and specially the epistemological status of computational models in scientific research: halfway between the well established categories of theory (...)
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  40. 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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  41. Remarks on Scientific Metaphors.Sergio Volodia Marcello Cremaschi - 1988 - In Maria Luisa Dalla Chiara & Maria Clara Galavotti (eds.), Temi e prospettive della Logica e Filosofia della Scienza. Volume 2. Bologna, Italy: CLUEB. pp. 114-116.
    Recent contributions by Kuhn, Wartofsky, and Granger, converge in the direction of an extended view of models, one that acknowledges a metaphorical dimension in the language of science. Such a view is in some respects the opposite of the views of both Bachelard and the Logical Empiricists. A number of familiar puzzles of the philosophy of science, such as the problem of reference, the opposition of realism and instrumentalism, that between explanation and understanding, and the status of scientific objectivity, may (...)
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  42. Models and Scientific Explanations.Robert C. Richardson - 1986 - Philosophica 37:59-72.
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