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  1. Mixed-grain Property Collaboration: Reconstructing Multiple Realization after the Elimination of Levels.Robert D. Rupert - manuscript
  2. 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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  3. 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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  4. Scientific Models and Thought Experiments: Same Same but Different.Rawad El Skaf & Michael T. Stuart - forthcoming - In Handbook of Philosophy of Scientific Modeling. London: Routledge.
    The philosophical literatures on models and thought experiments have been developing exponentially, and independently, for decades. This independence is surprising, given how similar models and thought experiments are. They each have “lives of their own,” they sit between theory and experience, they are important for both pedagogy and cutting-edge science, they galvanize conceptual changes and paradigm shifts, and they involve entertaining imaginary scenarios and working out what happens. Recently, philosophers have begun to highlight these similarities. This entry aims at taking (...)
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  5. Antisocial Modelling.Georgi Gardiner - forthcoming - In Alfano Mark, Jeroen De Ridder & Colin Klein (eds.), Social Virtue Epistemology.
    This essay replies to Michael Morreau and Erik J. Olsson’s ‘Learning from Ranters: The Effect of Information Resistance on the Epistemic Quality of Social Network Deliberation’. Morreau and Olsson use simulations to suggest that false ranters—agents who do not update their beliefs and only ever assert false claims—do not diminish the epistemic value of deliberation for other agents and can even be epistemically valuable. They argue conclude that “Our study suggests that including [false] ranters has little or no negative effect (...)
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  6. 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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  7. Values in Psychometrics.Lisa D. Wijsen, Denny Borsboom & Anna Alexandrova - forthcoming - Perspectives on Psychological Science.
    When it originated in the late 19th century, psychometrics was a field with both a scientific and a social mission: psychometrics provided new methods for research into individual differences, and at the same time, these psychometric instruments were considered a means to create a new social order. In contrast, contemporary psychometrics - due to its highly technical nature and its limited involvement in substantive psychological research - has created the impression of being a value-free discipline. In this article, we develop (...)
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  8. A Complementary Account of Scientific Modelling: Modelling Mechanisms in Cancer Immunology.Martin Zach - forthcoming - British Journal for the Philosophy of Science.
    According to a widely held view, scientific modelling consists in entertaining a set of model descriptions that specify a model. Rather than studying the phenomenon of interest directly, scientists investigate the phenomenon indirectly via a model in the hope of learning about some of the phenomenon’s features. I call this view the description-driven modelling (DDM) account. I argue that although an accurate description of much of scientific research, the DDM account is found wanting as regards the mechanistic modelling found in (...)
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  9. Leveraging Distortions: Explanation, Idealization, and Universality in Science.Holly Andersen - 2023 - Philosophical Review 132 (3):499-503.
    A critical review of Collin Rice's book, Leveraging Distortions: Explanation, Idealization, and Universality in Science.
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  10. Trueing.Holly Andersen - 2023 - In The Pragmatist Challenge: Pragmatist Metaphysics for Philosophy of Science. Oxford University Press.
    Even in areas of philosophy of science that don’t involve formal treatments of truth, one’s background view of truth still centrally shapes views on other issues. I offer an informal way to think about truth as trueing, like trueing a bicycle wheel. This holist approach to truth provides a way to discuss knowledge products like models in terms of how well-trued they are to their target. Trueing emphasizes: the process by which models are brought into true; how the idealizations in (...)
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  11. Epistemic expression in the determination of biomolecular structure.Agnes Bolinska - 2023 - Studies in History and Philosophy of Science Part A 100 (C):107-115.
    Scientific research is constrained by limited resources, so it is imperative that it be conducted efficiently. This paper introduces the notion of epistemic expression, a kind of representation that expedites the solution of research problems. Epistemic expressions are representations that (i) contain information in a way that enables more reliable information to place the most stringent constraints on possible solutions and (ii) make new information readily extractible by biasing the search through that space. I illustrate these conditions using historical and (...)
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  12. Are Models Our Tools Not Our Masters?Caspar Jacobs - 2023 - Synthese 202 (4):1-21.
    It is often claimed that one can avoid the kind of underdetermination that is a typical consequence of symmetries in physics by stipulating that symmetry-related models represent the same state of affairs (Leibniz Equivalence). But recent commentators (Dasgupta 2011; Pooley 2021; Pooley and Read 2021; Teitel 2021a) have responded that claims about the representational capacities of models are irrelevant to the issue of underdetermination, which concerns possible worlds themselves. In this paper I distinguish two versions of this objection: (1) that (...)
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  13. Usability of climate information: Toward a new scientific framework.Julie Jebeile & Joe Roussos - 2023 - WIREs Climate Change.
    Climate science is expected to provide usable information to policy-makers, to support the resolution of climate change. The complex, multiply connected nature of climate change as a social problem is reviewed and contrasted with current modular and discipline-bounded approaches in climate science. We argue that climate science retains much of its initial “physics-first” orientation, and that it adheres to a problematic notion of objectivity as freedom from value judgments. Together, these undermine its ability to provide usable information. We develop the (...)
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  14. Diagnosing errors in climate model intercomparisons.Ryan O’Loughlin - 2023 - European Journal for Philosophy of Science 13 (2):1-29.
    I examine error diagnosis (model-model disagreement) in climate model intercomparisons including its difficulties, fruitful examples, and prospects for streamlining error diagnosis. I suggest that features of climate model intercomparisons pose a more significant challenge for error diagnosis than do features of individual model construction and complexity. Such features of intercomparisons include, e.g., the number of models involved, how models from different institutions interrelate, and what scientists know about each model. By considering numerous examples in the climate modeling literature, I distill (...)
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  15. Introduction to the Synthese Topical Collection 'Modal Modeling in Science: Modal Epistemology meets Philosophy of Science’.Ylwa Sjölin Wirling & Till Grüne-Yanoff - 2023 - Synthese 201 (6):1-13.
  16. Interdisciplinary model transfer and realism about physical analogy.Peter Tan - 2023 - Synthese 201 (2):1-27.
    Model transfer is the scientific practice of taking a model which was initially applied in one particular kind of target system in some particular scientific domain and applying it to represent a novel target system in a novel scientific domain. This paper motivates a realist interpretation of empirically successful model transfers and the implications of such an interpretation for the metaphysics of science. The paper uses two examples of empirically successful model transfer, the first of which is a strikingly successful (...)
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  17. Joint representation: Modeling a phenomenon with multiple biological systems.Yoshinari Yoshida - 2023 - Studies in History and Philosophy of Science Part A 99:67-76.
    Biologists often study particular biological systems as models of a phenomenon of interest even if they already know that the phenomenon is produced by diverse mechanisms and hence none of those systems alone can sufficiently represent it. To understand this modeling practice, the present paper provides an account of how multiple model systems can be used to study a phenomenon that is produced by diverse mechanisms. Even if generalizability of results from a single model system is significantly limited, generalizations concerning (...)
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  18. A concrete example of representational licensing: The Mississippi River Basin Model.Brandon Boesch - 2022 - Studies in History and Philosophy of Science Part A 92 (C):36-44.
    Previously, I (Boesch 2017) described a notion called “representational licensing”—the set of activities of scientific practice by which scientists establish the intended representational use of a vehicle. In this essay, I expand and develop this concept of representational licensing. I begin by showing how the concept is of value for both pragmatic and substantive approaches to scientific representation. Then, through the examination of a case study of the Mississippi River Basin Model, I point out and explain some of the activities (...)
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  19. A Monist Proposal: Against Integrative Pluralism About Protein Structure.Agnes Bolinska - 2022 - Erkenntnis 1.
    Mitchell & Gronenborn propose that we account for the presence of multiple models of protein structure, each produced in different contexts, through the framework of integrative pluralism. I argue that two interpretations of this framework are available, neither of which captures the relationship between a model and the protein structure it represents or between multiple models of protein structure. Further, it inclines us toward concluding prematurely that models of protein structure are right in their contexts and makes extrapolation of findings (...)
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  20. 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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  21. Reichenbach’s empirical axiomatization of relativity.Joshua Eisenthal & Lydia Patton - 2022 - Synthese 200 (6):1-24.
    A well known conception of axiomatization has it that an axiomatized theory must be interpreted, or otherwise coordinated with reality, in order to acquire empirical content. An early version of this account is often ascribed to key figures in the logical empiricist movement, and to central figures in the early “formalist” tradition in mathematics as well. In this context, Reichenbach’s “coordinative definitions” are regarded as investing abstract propositions with empirical significance. We argue that over-emphasis on the abstract elements of this (...)
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  22. On the Relationship Between Modelling Practices and Interpretive Stances in Quantum Mechanics.Quentin Ruyant - 2022 - Foundations of Science 27 (2):387-405.
    The purpose of this article is to establish a connection between modelling practices and interpretive approaches in quantum mechanics, taking as a starting point the literature on scientific representation. Different types of modalities play different roles in scientific representation. I postulate that the way theoretical structures are interpreted in this respect affects the way models are constructed. In quantum mechanics, this would be the case in particular of initial conditions and observables. I examine two formulations of quantum mechanics, the standard (...)
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  23. Computational modeling in philosophy: introduction to a topical collection.Simon Scheller, Christoph Merdes & Stephan Hartmann - 2022 - Synthese 200 (2):1-10.
    Computational modeling should play a central role in philosophy. In this introduction to our topical collection, we propose a small topology of computational modeling in philosophy in general, and show how the various contributions to our topical collection fit into this overall picture. On this basis, we describe some of the ways in which computational models from other disciplines have found their way into philosophy, and how the principles one found here still underlie current trends in the field. Moreover, we (...)
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  24. Two epistemological challenges regarding hypothetical modeling.Peter Tan - 2022 - Synthese 200 (6).
    Sometimes, scientific models are either intended to or plausibly interpreted as representing nonactual but possible targets. Call this “hypothetical modeling”. This paper raises two epistemological challenges concerning hypothetical modeling. To begin with, I observe that given common philosophical assumptions about the scope of objective possibility, hypothetical models are fallible with respect to what is objectively possible. There is thus a need to distinguish between accurate and inaccurate hypothetical modeling. The first epistemological challenge is that no account of the epistemology of (...)
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  25. Evaluating the Validity of Animal Models of Mental Disorder: From Modeling Syndromes to Modeling Endophenotypes.Hein van den Berg - 2022 - History and Philosophy of the Life Sciences 44 (4):1-26.
    This paper provides a historical analysis of a shift in the way animal models of mental disorders were conceptualized: the shift from the mid-twentieth-century view, adopted by some, that animal models model syndromes classified in manuals such as the Diagnostic and Statistical Manual of Mental Disorders (DSM), to the later widespread view that animal models model component parts of psychiatric syndromes. I argue that in the middle of the twentieth century the attempt to maximize the face validity of animal models (...)
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  26. Comparer les modèles à l’aide du vecteur caractéristique : fonction, nature, principe et usage des modèles.Franck Varenne - 2022 - Natures Sciences Sociétés 30 (1):93-102.
    In the context of pluralization, sophistication, and combination of formal models, it is becoming difficult to propose uniform – or even comparable – model comparison practices. This paper outlines a broad and classificatory comparative epistemology of models. The aim of this epistemology is to propose applicable, and if necessary rectifiable, conceptual tools that can be useful to modellers as well as to historians and epistemologists. The notion of model characteristic vector – incorporating concepts of function, nature, principle and use of (...)
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  27. When is Lockdown Justified?Lucie White, Philippe van Basshuysen & Mathias Frisch - 2022 - Philosophy of Medicine 3 (1):1-22.
    How could the initial, drastic decisions to implement “lockdowns” to control the spread of COVID-19 infections be justifiable, when they were made on the basis of such uncertain evidence? We defend the imposition of lockdowns in some countries by first, and focusing on the UK, looking at the evidence that undergirded the decision, second, arguing that this provided us with sufficient grounds to restrict liberty given the circumstances, and third, defending the use of poorly-empirically-constrained epidemiological models as tools that can (...)
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  28. Taming the tyranny of scales: models and scale in the geosciences.Alisa Bokulich - 2021 - Synthese 199 (5-6):14167-14199.
    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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  29. Data models, representation and adequacy-for-purpose.Alisa Bokulich & Wendy Parker - 2021 - European Journal for Philosophy of Science 11 (1):1-26.
    We critically engage two traditional views of scientific data and outline a novel philosophical view that we call the pragmatic-representational view of data. On the PR view, data are representations that are the product of a process of inquiry, and they should be evaluated in terms of their adequacy or fitness for particular purposes. Some important implications of the PR view for data assessment, related to misrepresentation, context-sensitivity, and complementary use, are highlighted. The PR view provides insight into the common (...)
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  30. Modeling the Past: Using History of Science to predict alternative scenarios on science-based legislation.José Ferraz-Caetano - 2021 - Hypothesis Historia Periodical 1 (1):60-70.
    In an ever-changing world, when we search for answers on our present challenges, it can be tricky to extrapolate past realities when concerning science-based issues. Climate change, public health or artificial intelligence embody issues on how scientific evidence is often challenged, as false beliefs could drive the design of public policies and legislation. Therefore , how can we foresee if science can tip the scales of political legislation? In this article, we outline how models of historical cases can be used (...)
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  31. Model Organisms for Studying Decision-Making: A Phylogenetically Expanded Perspective.Linus Ta-Lun Huang, Leonardo Bich & William Bechtel - 2021 - Philosophy of Science 88 (5):1055-1066.
    This article explores the use of model organisms in studying the cognitive phenomenon of decision-making. Drawing on the framework of biological control to develop a skeletal conception of decision-making, we show that two core features of decision-making mechanisms can be identified by studying model organisms, such as E. coli, jellyfish, C. elegans, lamprey, and so on. First, decision mechanisms are distributed and heterarchically structured. Second, they depend heavily on chemical information processing, such as that involving neuromodulators. We end by discussing (...)
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  32. Epistemic artifacts and the modal dimension of modeling.Tarja Knuuttila - 2021 - European Journal for Philosophy of Science 11 (3):1-18.
    The epistemic value of models has traditionally been approached from a representational perspective. This paper argues that the artifactual approach evades the problem of accounting for representation and better accommodates the modal dimension of modeling. From an artifactual perspective, models are viewed as erotetic vehicles constrained by their construction and available representational tools. The modal dimension of modeling is approached through two case studies. The first portrays mathematical modeling in economics, while the other discusses the modeling practice of synthetic biology, (...)
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  33. Close encounters with scientific analogies of the third kind.Francesco Nappo - 2021 - European Journal for Philosophy of Science 11 (3):1-20.
    Arguments from non-causal analogy form a distinctive class of analogical arguments in science not recognized in authoritative classifications by, e.g., Hesse and Bartha. In this paper, I illustrate this novel class of scientific analogies by means of historical examples from physics, biology and economics, at the same time emphasizing their broader significance for contemporary debates in epistemology.
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  34. Robustness reasoning in climate model comparisons.Ryan O’Loughlin - 2021 - Studies in History and Philosophy of Science Part A 85 (C):34-43.
  35. Idealizations and Analogies: Explaining Critical Phenomena.Quentin Rodriguez - 2021 - Studies in History and Philosophy of Science Part A 89 (C):235-247.
    The “universality” of critical phenomena is much discussed in philosophy of scientific explanation, idealizations and philosophy of physics. Lange and Reutlinger recently opposed Batterman concerning the role of some deliberate distortions in unifying a large class of phenomena, regardless of microscopic constitution. They argue for an essential explanatory role for “commonalities” rather than that of idealizations. Building on Batterman's insight, this article aims to show that assessing the differences between the universality of critical phenomena and two paradigmatic cases of “commonality (...)
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  36. 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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  37. The epistemology of modal modeling.Ylwa Sjölin Wirling & Till Grüne-Yanoff - 2021 - Philosophy Compass 16 (10):e12775.
    Philosophers of science have recently taken care to highlight different modeling practices where scientific models primarily contribute modal information, in the form of for example possibility claims, how-possibly explanations, or counterfactual conditionals. While examples abound, comparatively little attention is being paid to the question of under what conditions, and in virtue of what, models can perform this epistemic function. In this paper, we firstly delineate modal modeling from other modeling practices, and secondly reviewattempts to spell out and explain the epistemic (...)
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  38. 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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  39. The Epistemic Duties of Philosophers: An Addendum.Philippe van Basshuysen & Lucie White - 2021 - Kennedy Institute of Ethics Journal 31 (4):447-451.
    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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  40. Multiple-Models Juxtaposition and Trade-Offs among Modeling Desiderata.Yoshinari Yoshida - 2021 - Philosophy of Science 88 (1):103-123.
    This article offers a characterization of what I call multiple-models juxtaposition, a strategy for managing trade-offs among modeling desiderata. MMJ displays models of distinct phenomena to...
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  41. Are Scientific Models of life Testable? A lesson from Simpson's Paradox.Prasanta S. Bandyopadhyay, Don Dcruz, Nolan Grunska & Mark Greenwood - 2020 - Sci 1 (3).
    We address the need for a model by considering two competing theories regarding the origin of life: (i) the Metabolism First theory, and (ii) the RNA World theory. We discuss two interrelated points, namely: (i) Models are valuable tools for understanding both the processes and intricacies of origin-of-life issues, and (ii) Insights from models also help us to evaluate the core objection to origin-of-life theories, called “the inefficiency objection”, which is commonly raised by proponents of both the Metabolism First theory (...)
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  42. Polycratic hierarchies and networks: what simulation-modeling at the LHC can teach us about the epistemology of simulation.Florian J. Boge & Christian Zeitnitz - 2020 - Synthese 199 (1-2):445-480.
    Large scale experiments at CERN’s Large Hadron Collider rely heavily on computer simulations, 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: with some distinct modifications, individual components of ATLAS’ overall simulation infrastructure can be ordered into hierarchical structures. Hence, to a good degree of approximation, hierarchical (...)
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  43. “ « And the rod starts to swing ». Morphogènes, instabilités et organismes imaginaires dans l’approche de Turing à la biologie » ”.Sara Franceschelli - 2020 - Intellectica 72:191-214.
  44. 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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  45. Perspectives, Questions, and Epistemic Value.Kareem Khalifa & Jared 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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  46. Unifying the essential concepts of biological networks: biological insights and philosophical foundations.Daniel Kostic, Claus Hilgetag & Marc Tittgemeyer - 2020 - Philosophical Transactions of the Royal Society B: Biological Sciences 375 (1796):1-8.
    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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  47. Thought Experiments and the Scientific Imagination.Alice Murphy - 2020 - Dissertation, University of Leeds
    Thought experiments (TEs) are important tools in science, used to both undermine and support theories, and communicate and explain complex phenomena. Their interest within philosophy of science has been dominated by a narrow question: How do TEs increase knowledge? My aim is to push beyond this to consider their broader value in scientific practice. I do this through an investigation into the scientific imagination. Part one explores questions regarding TEs as “experiments in the imagination” via a debate concerning the epistemic (...)
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  48. Learning from Non-Causal Models.Francesco Nappo - 2020 - Erkenntnis 87 (5):2419-2439.
    This paper defends the thesis of learning from non-causal models: viz. that the study of some model can prompt justified changes in one’s confidence in empirical hypotheses about a real-world target in the absence of any known or predicted similarity between model and target with regards to their causal features. Recognizing that we can learn from non-causal models matters not only to our understanding of past scientific achievements, but also to contemporary debates in the philosophy of science. At one end (...)
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  49. Designing as playing games of make-believe.Michael Poznic, Martin Stacey, Rafaela Hillerbrand & Claudia Eckert - 2020 - Design Science 6:e10.
    Designing complex products involves working with uncertainties as the product, the requirements and the environment in which it is used co-evolve, and designers and external stakeholders make decisions that affect the evolving design. Rather than being held back by uncertainty, designers work, cooperate and communicate with each other notwithstanding these uncertainties by making assumptions to carry out their own tasks. To explain this, the paper proposes an adaptation of Kendall Walton’s make-believe theory to conceptualise designing as playing games of make-believe (...)
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  50. 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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