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Scientific Models

Assistant editor: Guilherme Sanches De Oliveira (University of Cincinnati, Technische Universität Berlin)
About this topic
Summary Modeling is an increasingly important method in many fields of science. Scientific models are taken to be only partially similar to the phenomena they are used to study. Several philosophical questions result. For one, philosophers investigate how it is that models represent phenomena despite their differences, and what is responsible for models' epistemic success. This dovetails with questions about the nature of the representation relation. Philosophers also investigate abstraction and idealization in modeling, and some accord a further role to fictions. Finally, models are also significant in a different sense for the semantic view of theories. 
Key works Hesse 1963; Van Fraassen Bas 1980; Wimsatt (1987); Poland 1988; Morgan & Morrison 1999; Bailer-Jones 2009; Weisberg 2013.
Introductions Frigg and Hartmann (2006)
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807 found
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  1. Normative Formal Epistemology as Modelling.Joe Roussos - forthcoming - The British Journal for the Philosophy of Science.
    I argue that normative formal epistemology (NFE) is best understood as modelling, in the sense that this is the reconstruction of its methodology on which NFE is doing best. I focus on Bayesianism and show that it has the characteristics of modelling. But modelling is a scientific enterprise, while NFE is normative. I thus develop an account of normative models on which they are idealised representations put to normative purposes. Normative assumptions, such as the transitivity of comparative credence, are characterised (...)
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  2. When is Lockdown Justified?Lucie White, Philippe van Basshuysen & Mathias Frisch - manuscript
    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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  3. Contrasting Cases: The Lotka-Volterra Model Times Three.Tarja Knuuttila & Andrea Loettgers - 2016 - Boston Studies in the Philosophy of Science 319:151-178.
    How do philosophers of science make use of historical case studies? Are their accounts of historical cases purpose-built and lacking in evidential strength as a result of putting forth and discussing philosophical positions? We will study these questions through the examination of three different philosophical case studies. All of them focus on modeling and on Vito Volterra, contrasting his work to that of other theoreticians. We argue that the worries concerning the evidential role of historical case studies in philosophy are (...)
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  4. 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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  5. 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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  6. Exploring Minds: Modes of Modelling and Simulation in Artificial Intelligence.Hajo Greif - 2021 - Perspectives on Science 29 (4):409-435.
    -/- The aim of this paper is to grasp the relevant distinctions between various ways in which models and simulations in Artificial Intelligence (AI) relate to cognitive phenomena. In order to get a systematic picture, a taxonomy is developed that is based on the coordinates of formal versus material analogies and theory-guided versus pre-theoretic models in science. These distinctions have parallels in the computational versus mimetic aspects and in analytic versus exploratory types of computer simulation. The proposed taxonomy cuts across (...)
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  7. The Problem of Model Selection and Scientific Realism.Stanislav Larski - unknown
    This thesis has two goals. Firstly, we consider the problem of model selection for the purposes of prediction. In modern science predictive mathematical models are ubiquitous and can be found in such diverse fields as weather forecasting, economics, ecology, mathematical psychology, sociology, etc. It is often the case that for a given domain of inquiry there are several plausible models, and the issue then is how to discriminate between them – this is the problem of model selection. We consider approaches (...)
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  8. Sociologie fondamentale. Etude d'épistémologie.Dominique Raynaud - 2021 - Paris: Editions Matériologiques.
    Ce livre est un livre d’épistémologie de la sociologie. L’objectif est d’appliquer des méthodes analytiques pour clarifier le vocabulaire, expliciter des relations non-apparentes entre concepts, dégager la portée d’une méthode, ou souligner les incohérences d’un programme de recherche. Les questions épineuses ne sont pas écartéees: Comment clarifier des notions confuses? Peut-on mathématiser les concepts sociologiques? Peut-on pratiquer la sociologie comme on pratique les sciences naturelles? Quelle est la place du déterminisme? Chaque question est examinée à la fois dans sa structure (...)
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  9. The Epistemic Duties of Philosophers: An Addendum.Philippe van Basshuysen & Lucie White - forthcoming - Kennedy Institute of Ethics Journal.
    We were slightly concerned, upon having read Eric Winsberg, Jason Brennan and Chris Surprenant’s reply to our paper “Were Lockdowns Justified? A Return to the Facts and Evidence”, that they may have fundamentally misunderstood the nature of our argument, so we issue the following clarification, along with a comment on our motivations for writing such a piece, for the interested reader.
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  10. Taming the Tyranny of Scales: Models and Scale in the Geosciences.Alisa Bokulich - forthcoming - Synthese.
    While the predominant focus of the philosophical literature on scientific modeling has been on single-scale models, most systems in nature exhibit complex multiscale behavior, requiring new modeling methods. This challenge of modeling phenomena across a vast range of spatial and temporal scales has been called the tyranny of scales problem. Drawing on research in the geosciences, I synthesize and analyze a number of strategies for taming this tyranny in the context of conceptual, physical, and mathematical modeling. This includes several strategies (...)
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  11. Two Dimensions of Opacity and the Deep Learning Predicament.Florian J. Boge - forthcoming - Minds and Machines:1-33.
    Deep neural networks have become increasingly successful in applications from biology to cosmology to social science. Trained DNNs, moreover, correspond to models that ideally allow the prediction of new phenomena. Building in part on the literature on ‘eXplainable AI’, I here argue that these models are instrumental in a sense that makes them non-explanatory, and that their automated generation is opaque in a unique way. This combination implies the possibility of an unprecedented gap between discovery and explanation: When unsupervised models (...)
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  12. Epistemic and Objective Possibility in Science.Ylwa Sjölin Wirling & Till Grüne-Yanoff - forthcoming - British Journal for the Philosophy of Science.
    Scientists regularly make possibility claims. While philosophers of science are well aware of the distinction between epistemic and objective notions of possibility, we believe that they often fail to apply this distinction in their analyses of scientific practices that employ modal concepts. We argue that heeding this distinction will help further progress in current debates in the philosophy of science, as it shows that the debaters talk about different things, rather than disagree on the same issue. We first discuss how (...)
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  13. Three Ways in Which Pandemic Models May Perform a Pandemic.Philippe van Basshuysen, Lucie White, Donal Khosrowi & Mathias Frisch - 2021 - Erasmus Journal for Philosophy and Economics 14 (1):110-127.
    Models not only represent but may also influence their targets in important ways. While models’ abilities to influence outcomes has been studied in the context of economic models, often under the label ‘performativity’, we argue that this phenomenon also pertains to epidemiological models, such as those used for forecasting the trajectory of the Covid-19 pandemic. After identifying three ways in which a model by the Covid-19 Response Team at Imperial College London may have influenced scientific advice, policy, and individual responses, (...)
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  14. Model Organisms for Studying Decision-Making: A Phylogenetically Expanded Perspective.Linus Ta-Lun Huang, Leonardo Bich & William Bechtel - forthcoming - Philosophy of Science.
    This paper 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, etc. First, decision mechanisms are distributed and heterarchically-structured. Second, they depend heavily on chemical information processing, such as those involving neuromodulators. We end by discussing the implications for (...)
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  15. Extending Similarity-Based Epistemology of Modality with Models.Ylwa Sjölin Wirling - forthcoming - Ergo: An Open Access Journal of Philosophy.
    Empiricist modal epistemologies can be attractive, but are often limited in the range of modal knowledge they manage to secure. In this paper, I argue that one such account – similarity-based modal empiricism – can be extended to also cover justification of many scientifically interesting possibility claims. Drawing on recent work on modelling in the philosophy of science, I suggest that scientific modelling is usefully seen as the creation and investigation of relevantly similar epistemic counterparts of real target systems. On (...)
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  16. Is Crediblity a Guide to Possibility? A Challenge for Toy Models in Science.Ylwa Sjölin Wirling - forthcoming - Analysis.
    Several philosophers of science claim that scientific toy models afford knowledge of possibility, but answers to the question of why toy models can be expected to competently play this role are scarce. The main line of reply is that toy models support possibility claims insofar as they are credible. I raise a challenge for this credibility-thesis, drawing on a familiar problem for imagination-based modal epistemologies, and argue that it remains unanswered in the current literature. The credibility-thesis has a long way (...)
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  17. 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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  18. What Theoretical Equivalence Could Not Be.Trevor Teitel - 2021 - Philosophical Studies (12):1-31.
    Formal criteria of theoretical equivalence are mathematical mappings between specific sorts of mathematical objects, notably including those objects used in mathematical physics. Proponents of formal criteria claim that results involving these criteria have implications that extend beyond pure mathematics. For instance, they claim that formal criteria bear on the project of using our best mathematical physics as a guide to what the world is like, and also have deflationary implications for various debates in the metaphysics of physics. In this paper, (...)
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  19. Resenha do livro Imagens de natureza, imagens de ciência (2ª edição revista e ampliada. Rio de Janeiro: Eduerj, 2016), de Paulo C. Abrantes. [REVIEW]Bruno Camilo de Oliveira - 2020 - Revista Helius 3:1250-1263.
    The second edition of the work of the Brazilian physicist Paulo C. Abrantes (2016), entitled Images of nature, images of science, is a good alternative for students of history and philosophy of science. The reason is Abrantes' thesis in this work: to defend that the development of scientific knowledge is dependent on the influence of different images of "nature" and "science" existing during the history of Western scientific-philosophical thought; and an advocate for the historian of science Studying as reasons that (...)
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  20. The Dynamical Renaissance in Neuroscience.Luis H. Favela - 2020 - Synthese 1 (1):1-25.
    Although there is a substantial philosophical literature on dynamical systems theory in the cognitive sciences, the same is not the case for neuroscience. This paper attempts to motivate increased discussion via a set of overlapping issues. The first aim is primarily historical and is to demonstrate that dynamical systems theory is currently experiencing a renaissance in neuroscience. Although dynamical concepts and methods are becoming increasingly popular in contemporary neuroscience, the general approach should not be viewed as something entirely new to (...)
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  21. Disambiguation of Social Polarization Concepts and Measures.Aaron Bramson, Patrick Grim, Daniel J. Singer, Steven Fisher, William Berger, Graham Sack & Carissa Flocken - 2016 - Journal of Mathematical Sociology 40:80-111.
    ABSTRACT This article distinguishes nine senses of polarization and provides formal measures for each one to refine the methodology used to describe polarization in distributions of attitudes. Each distinct concept is explained through a definition, formal measures, examples, and references. We then apply these measures to GSS data regarding political views, opinions on abortion, and religiosity—topics described as revealing social polarization. Previous breakdowns of polarization include domain-specific assumptions and focus on a subset of the distribution’s features. This has conflated multiple, (...)
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  22. Philosophical Analysis in Modeling Polarization: Notes From a Work in Progress.Patrick Grim, Aaron Bramson, Daniel J. Singer, Stephen Fisher, Carissa Flocken & William Berger - 2013 - In Paul Youngman & Mirsad Hadzikadik (eds.), Complexity and the Human Experience: Modeling Complexity in the Humanities and Social Sciences. Pan Sanford.
  23. Estrategias tropológicas en ciencia.Israel Salas Llanas - 2019 - Dissertation, Universidad Autónoma de Madrid
    Para el constructivismo, la ciencia y la cognición comparten intereses similares. Ambos dominios pueden describirse como dos sistemas entrelazados que se activan mutuamente y se modulan entre sí a través de un lazo interno de retroalimentación, lazo que opera mediante la dinámica interna representativa en el caso de la cognición y mediante la dinámica del desarrollo teórico en el caso de la ciencia. Cada uno de estos dominios —ciencia y cognición— busca generar un marco de interacción adecuado que garantice, por (...)
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  24. A Critical Look on Critical Realism.Agustina Borella - 2012 - Perspectives on Epistemology of Economics:183-207.
    Tony Lawson, founder of The Social Ontology Group and The Realist Workshop of Cambridge, has proposed critical realism to reorient economics. The transformation of the social world that Lawson tries, emerges from the adherence to critical realism, this is, from taking the transcendental realism of Roy Bhaskar to the social realm. With the purpose of deepening the criticisms to this movement, we will specify what is critical realism, and which are the philosophical assumptions of the mainstream according to this author. (...)
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  25. Modelar o no modelar: esa no es la cuestión. ¿Hay algo intermedio?Agustina Borella - 2017 - Revista Perspectivas de Las Ciencias Económicas y Jurídicas 7 (2):89-100.
    The present paper tries to show that in the discussion on whether it is better to model or not to capture truth in the social world, that is not what is mainly being discussed. We put forward that the main question in this discussion is, essentially, ontological, not methodological. As a representative of the “to model position” we will refer to Uskali Mäki’s Possible Realism, and as one ofthe “notto model position” we will consider Tony Lawson’s Critical Realism. What will (...)
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  26. Pinceladas de Realismo Finlandés. [REVIEW]Agustina Borella - 2013 - Filosofia de la Economia 1 (1):131-137.
    La presente obra ofrece un análisis crítico de la filosofía de la economía de Uskali Mäki; en particular de la consideración realista científica de la economía. Se intenta a lo largo del texto responder, de algún modo, a las preguntas que plantea Lehtinen en la introducción: “¿Están los economistas aspirando en absoluto a la verdad, o están solamente jugando un juego intelectual en que tales supuestos son aceptables por alguna razón misteriosa? ¿Están estudiando la economía en serio? ¿Están simplemente desinteresados (...)
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  27. Trazos- Ensayos de Filosofía para el Mundo Social.Agustina Borella (ed.) - 2020 - Buenos Aires, CABA, Argentina: Grupo Unión.
    Entender algo sobre un mundo que se nos presenta de modo desordenado e incompleto constituye buena parte de la tarea de la filosofía y de la ciencia. La racionalidad, los modelos, y el mundo social introducen preocupaciones propias de la filosofía de la ciencia en general y de la epistemología de la economía en particular. Los aportes de Popper, Lawson, Mäki, Hayek y Cartwright se expresan en estos trazos como intentos abiertos para alcanzar a comprender nuestro mundo.
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  28. Fundamento Ontológico del Modelo en Hayek.Agustina Borella - 2019 - Procesos de Mercado. Revista Europea de Economía Política 2 (XVI):103-124.
    In the debate on realism of models in economics, the Austrian School and Hayekin particular, seem to have, in a certain way, remained outside. Assuming neoclassical models asunrealistic, the theory of the market as a process looks like a more realistic proposal. However, oneof the fundamental issue s in Hayek’s dissent is not so much the unrealism of the assumptions, but that the market equilibrium theory was not correctly raised, especially with regards to the perfectknowledge assumption. Despite this, in this (...)
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  29. 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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  30. Models, Information and Meaning.Marc Artiga - 2020 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 82:101284.
    There has recently been an explosion of formal models of signalling, which have been developed to learn about different aspects of meaning. This paper discusses whether that success can also be used to provide an original naturalistic theory of meaning in terms of information or some related notion. In particular, it argues that, although these models can teach us a lot about different aspects of content, at the moment they fail to support the idea that meaning just is some kind (...)
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  31. How Disunity Matters to the History of Cybernetics in the Human Sciences in the United States, 1940–80.Ronald Kline - 2020 - History of the Human Sciences 33 (1):12-35.
    Rather than assume a unitary cybernetics, I ask how its disunity mattered to the history of the human sciences in the United States from about 1940 to 1980. I compare the work of four prominent social scientists – Herbert Simon, George Miller, Karl Deutsch, and Talcott Parsons – who created cybernetic models in psychology, economics, political science, and sociology with the work of anthropologist Gregory Bateson, and relate their interpretations of cybernetics to those of such well-known cyberneticians as Norbert Wiener, (...)
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  32. The Use and Limitations of Null-Model-Based Hypothesis Testing.Mingjun Zhang - 2020 - Biology and Philosophy 35 (2):1-22.
    In this article I give a critical evaluation of the use and limitations of null-model-based hypothesis testing as a research strategy in the biological sciences. According to this strategy, the null model based on a randomization procedure provides an appropriate null hypothesis stating that the existence of a pattern is the result of random processes or can be expected by chance alone, and proponents of other hypotheses should first try to reject this null hypothesis in order to demonstrate their own (...)
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  33. From a Boson to the Standard Model Higgs: A Case Study in Confirmation and Model Dynamics.Cristin Chall, Martin King, Peter Mättig & Michael Stöltzner - 2019 - Synthese 198 (Suppl 16):3779-3811.
    Our paper studies the anatomy of the discovery of the Higgs boson at the Large Hadron Collider and its influence on the broader model landscape of particle physics. We investigate the phases of this discovery, which led to a crucial reconfiguration of the model landscape of elementary particle physics and eventually to a confirmation of the standard model. A keyword search of preprints covering the electroweak symmetry breaking sector of particle physics, along with an examination of physicists own understanding of (...)
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  34. Actual Causation and the Art of Modeling.Joseph Halpern & Christopher Hitchcock - 2010 - In Causality, Probability, and Heuristics: A Tribute to Judea Pearl. London: College Publications. pp. 383-406.
  35. Scientific Modelling in Generative Grammar and the Dynamic Turn in Syntax.Ryan Nefdt - 2016 - Linguistics and Philosophy 39 (5):357-394.
    In this paper, I address the issue of scientific modelling in contemporary linguistics, focusing on the generative tradition. In so doing, I identify two common varieties of linguistic idealisation, which I call determination and isolation respectively. I argue that these distinct types of idealisation can both be described within the remit of Weisberg’s :639–659, 2007) minimalist idealisation strategy in the sciences. Following a line set by Blutner :27–35, 2011), I propose this minimalist idealisation analysis for a broad construal of the (...)
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  36. Explanation and Understanding Through Scientific Models.Richard David-Rus - unknown
  37. Mathematical Models, Rational Choice, and the Search for Cold War Culture.Paul Erickson - 2010 - Isis 101:386-392.
  38. So Simple a Thing as a Star: The Eddington–Jeans Debate Over Astrophysical Phenomenology.Matthew Stanley - 2007 - British Journal for the History of Science 40 (1):53-82.
    Theoretical astrophysics emerged as a significant research programme with the construction of a series of stellar models by A. S. Eddington. This paper examines the controversies surrounding those models as a way of understanding the development and justification of new theoretical technologies. In particular, it examines the challenges raised against Eddington by James Jeans, and explores how the two astronomers championed different visions of what it meant to do science. Jeans argued for a scientific method based on certainty and completeness, (...)
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  39. Model Change and Reliability in Scientific Inference.Erich Kummerfeld & David Danks - 2014 - Synthese 191 (12):2673-2693.
    One persistent challenge in scientific practice is that the structure of the world can be unstable: changes in the broader context can alter which model of a phenomenon is preferred, all without any overt signal. Scientific discovery becomes much harder when we have a moving target, and the resulting incorrect understandings of relationships in the world can have significant real-world and practical consequences. In this paper, we argue that it is common (in certain sciences) to have changes of context that (...)
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  40. Galton's Contribution to the Theory of Evolution with Special Reference to His Use of Models and Metaphors.J. S. Wilkie - 1955 - Annals of Science 11 (3):194-205.
  41. Environmental Risk Analysis: Robustness Is Essential for Precaution.Jan Sprenger - 2012 - Philosophy of Science 79 (5):881-892.
    Precaution is a relevant and much-invoked value in environmental risk analysis, as witnessed by the ongoing vivid discussion about the precautionary principle (PP). This article argues (i) against purely decision-theoretic explications of PP; (ii) that the construction, evaluation, and use of scientific models falls under the scope of PP; and (iii) that epistemic and decision-theoretic robustness are essential for precautionary policy making. These claims are elaborated and defended by means of case studies from climate science and conservation biology.
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  42. D. Rothbart, Editor, Modeling: Gateway to the Unknown. A Work by Rom Harré, Elsevier, London (2004) ISBN 0-444-51464-3 (300pp., US$ 119 Hardbound). [REVIEW]M. Morrison - 2005 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 36 (3):583-585.
  43. On Hodgkin and Huxley's Theory of Excitable Membranes.Ulrich Müller & Stephan Pilatus - 1982 - Theoretical Medicine and Bioethics 3 (2):193-208.
    Using Sneed's metatheory an attempt is made to reconstruct Hodgkin and Huxley's theory of excitation of cell membranes. The structure of this theory is uncovered by defining set-theoretical predicates for the partial potential models, potential models, and models of the theory. The function of permeability is said to be the only theoretical function with respect to this theory. The main underlying assumptions of the theory are briefly outlined.
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  44. Rejoinder.David Freedman - 1995 - Foundations of Science 1 (1):69-83.
    My favorite opponent in this debate once made a remarkable concession, not that it interfered with business as usual:No sensible social scientist believes any particular specification, coefficient estimate, or standard error. Social science theories ... imply that specifications and parameters constant over situations do not exist ... One searches for qualitative theory ... not for quantitative specifications Achen (1987, p.149). . With Hooke's law and the like, we are estimating parameters in specifications that are constant across time—at least to a (...)
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  45. Natural Science as a Hermeneutic of Instrumentation.Patrick Heelan - 1983 - Philosophy of Science 50 (2):181-204.
    The author proposes the thesis that all perception, including observation in natural science, is hermeneutical as well as causal; that is, the perceiver (or observer) learns to 'read' instrumental or other perceptual stimuli as one learns to read a text. This hermeneutical aspect at the heart of natural science is located where it might be least expected, within acts of scientific observation. In relation to the history of science, the question is addressed to what extent the hermeneutical component within scientific (...)
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  46. Model Selection and the Multiplicity of Patterns in Empirical Data.James W. McAllister - 2007 - Philosophy of Science 74 (5):884-894.
    Several quantitative techniques for choosing among data models are available. Among these are techniques based on algorithmic information theory, minimum description length theory, and the Akaike information criterion. All these techniques are designed to identify a single model of a data set as being the closest to the truth. I argue, using examples, that many data sets in science show multiple patterns, providing evidence for multiple phenomena. For any such data set, there is more than one data model that must (...)
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The Nature of Models
  1. Exploring Minds: Modes of Modeling and Simulation in Artificial Intelligence.Hajo Greif - 2021 - Perspectives on Science 29 (4):409-435.
    The aim of this paper is to grasp the relevant distinctions between various ways in which models and simulations in Artificial Intelligence (AI) relate to cognitive phenomena. In order to get a systematic picture, a taxonomy is developed that is based on the coordinates of formal versus material analogies and theory-guided versus pre-theoretic models in science. These distinctions have parallels in the computational versus mimetic aspects and in analytic versus exploratory types of computer simulation. The proposed taxonomy cuts across the (...)
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  2. Cognitive Pluralism.Steven Horst - 2016 - MIT Press.
    This book introduces an account of cognitive architecture, Cognitive Pluralism, on which the basic units of understanding are models of particular content domains. Having many mental models is a good adaptive strategy for cognition, but models can be incompatible with one another, leading to paradoxes and inconsistencies of belief, and it may not be possible to integrate the understanding supplied by multiple models into a comprehensive and self-consistent "super model". The book applies the theory to explaining intuitive reasoning and cognitive (...)
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  3. Models, Fictions and Artifacts.Tarja Knuuttila - 2021 - In Wenceslao J. Gonzalez (ed.), Language and Scientific Research. Cham: Palgrave Macmillan. pp. 199-22.
    This paper discusses modeling from the artifactual perspective. The artifactual approach conceives models as erotetic devices. They are purpose-built systems of dependencies that are constrained in view of answering a pending scientific question, motivated by theoretical or empirical considerations. In treating models as artifacts, the artifactual approach is able to address the various languages of sciences that are overlooked by the traditional accounts that concentrate on the relationship of representation in an abstract and general manner. In contrast, the artifactual approach (...)
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  4. 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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