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  1. Scientific Models.Stephen M. Downes - 2011 - Philosophy Compass 6 (11):757-764.
    This contribution provides an assessment of the epistemological role of scientific models. The prevalent view that all scientific models are representations of the world is rejected. This view points to a unified way of resolving epistemic issues for scientific models. The emerging consensus in philosophy of science that models have many different epistemic roles in science is presented and defended.
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  • Scientific Theories of Computational Systems in Model Checking.Nicola Angius & Guglielmo Tamburrini - 2011 - Minds and Machines 21 (2):323-336.
    Model checking, a prominent formal method used to predict and explain the behaviour of software and hardware systems, is examined on the basis of reflective work in the philosophy of science concerning the ontology of scientific theories and model-based reasoning. The empirical theories of computational systems that model checking techniques enable one to build are identified, in the light of the semantic conception of scientific theories, with families of models that are interconnected by simulation relations. And the mappings between these (...)
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  • (1 other version)'New age' philosophies of science: constructivism, feminism and postmodernism.N. Koertge - 2000 - British Journal for the Philosophy of Science 51 (4):667-683.
    This paper surveys three controversial new directions in research about the nature of science and briefly summarizes both the intellectual and sociological impact of this work. A bibliographic introduction to the major literature is provided and some fruitful directions for future research are proposed. Philosophers of science are also exhorted to perform 'community service' by correcting misunderstandings of the methods of science fostered by these new approaches.
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  • Preface.Lorenzo Magnani & Nancy J. Nersessian - 2001 - Mind and Society 2 (2):29-32.
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  • Symposium on “Cognition and Rationality: Part I” The rationality of scientific discovery: abductive reasoning and epistemic mediators. [REVIEW]Lorenzo Magnani - 2006 - Mind and Society 5 (2):213-228.
    Philosophers have usually offered a number of ways of describing hypotheses generation, but all aim at demonstrating that the activity of generating hypotheses is paradoxical, illusory or obscure, and then not analysable. Those descriptions are often so far from Peircian pragmatic prescription and so abstract to result completely unknowable and obscure. The “computational turn” gives us a new way to understand creative processes in a strictly pragmatic sense. In fact, by exploiting artificial intelligence and cognitive science tools, computational philosophy allows (...)
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  • Entropy - A Guide for the Perplexed.Roman Frigg & Charlotte Werndl - 2011 - In Claus Beisbart & Stephan Hartmann (eds.), Probabilities in Physics. Oxford, GB: Oxford University Press. pp. 115-142.
    Entropy is ubiquitous in physics, and it plays important roles in numerous other disciplines ranging from logic and statistics to biology and economics. However, a closer look reveals a complicated picture: entropy is defined differently in different contexts, and even within the same domain different notions of entropy are at work. Some of these are defined in terms of probabilities, others are not. The aim of this chapter is to arrive at an understanding of some of the most important notions (...)
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  • (1 other version)Scientific representation.Mauricio Suárez - 2010 - Philosophy Compass 5 (1):91-101.
    Scientific representation is a currently booming topic, both in analytical philosophy and in history and philosophy of science. The analytical inquiry attempts to come to terms with the relation between theory and world; while historians and philosophers of science aim to develop an account of the practice of model building in the sciences. This article provides a review of recent work within both traditions, and ultimately argues for a practice-based account of the means employed by scientists to effectively achieve representation (...)
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  • Morphodynamical abduction. Causation by attractors dynamics of explanatory hypotheses in science.Lorenzo Magnani & Matteo Piazza - 2005 - Foundations of Science 10 (1):107-132.
    Philosophers of science today by and large reject the cataclysmic and irrational interpretation of the scientific enterprise claimed by Kuhn. Many computational models have been implemented to rationally study the conceptual change in science. In this recent tradition a key role is played by the concept of abduction as a mechanism by which new explanatory hypotheses are introduced. Nevertheless some problems in describing the most interesting abductive issues rise from the classical computational approach. It describes a cognitive process (and so (...)
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  • The strategy of model-based science.Peter Godfrey-Smith - 2006 - Biology and Philosophy 21 (5):725-740.
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  • A.I., Scientific discovery and realism.Mario Alai - 2004 - Minds and Machines 14 (1):21-42.
    Epistemologists have debated at length whether scientific discovery is a rational and logical process. If it is, according to the Artificial Intelligence hypothesis, it should be possible to write computer programs able to discover laws or theories; and if such programs were written, this would definitely prove the existence of a logic of discovery. Attempts in this direction, however, have been unsuccessful: the programs written by Simon's group, indeed, infer famous laws of physics and chemistry; but having found no new (...)
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  • Conceptual Modelling, Combinatorial Heuristics and Ars Inveniendi: An Epistemological History (Ch 1 & 2).Tom Ritchey - manuscript
    (1) An introduction to the principles of conceptual modelling, combinatorial heuristics and epistemological history; (2) the examination of a number of perennial epistemological-methodological schemata: conceptual spaces and blending theory; ars inveniendi and ars demonstrandi; the two modes of analysis and synthesis and their relationship to ars inveniendi; taxonomies and typologies as two fundamental epistemic structures; extended cognition, cognitio symbolica and model-based reasoning; (3) Plato’s notions of conceptual spaces, conceptual blending and hypothetical-analogical models (paradeigmata); (4) Ramon Llull’s concept analysis and combinatoric (...)
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  • A pragmatic approach to scientific change: transfer, alignment, influence.Stefano Canali - 2022 - European Journal for Philosophy of Science 12 (3):1-25.
    I propose an approach that expands philosophical views of scientific change, on the basis of an analysis of contemporary biomedical research and recent developments in the philosophy of scientific change. Focusing on the establishment of the exposome in epidemiology as a case study and the role of data as a context for contrasting views on change, I discuss change at conceptual, methodological, material, and social levels of biomedical epistemology. Available models of change provide key resources to discuss this type of (...)
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  • Representing n-ary relations in the Semantic Web.Marco Giunti, Giuseppe Sergioli, Giuliano Vivanet & Simone Pinna - 2021 - Logic Journal of the IGPL 29 (4):697-717.
    Knowledge representation is a central issue for Artificial Intelligence and the Semantic Web. In particular, the problem of representing n-ary relations in RDF-based languages such as RDFS or OWL by no means is an obvious one. With respect to previous attempts, we show why the solutions proposed by the well known W3C Working Group Note on n-ary relations are not satisfactory on several scores. We then present our abstract model for representing n-ary relations as directed labeled graphs, and we show (...)
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  • On the Mutual Dependence Between Formal Methods and Empirical Testing in Program Verification.Nicola Angius - 2020 - Philosophy and Technology 33 (2):349-355.
    This paper provides a review of Raymond Turner’s book Computational Artefacts. Towards a Philosophy of Computer Science. Focus is made on the definition of program correctness as the twofold problem of evaluating whether both the symbolic program and the physical implementation satisfy a set of specifications. The review stresses how these are not two separate problems. First, it is highlighted how formal proofs of correctness need to rely on the analysis of physical computational processes. Secondly, it is underlined how software (...)
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  • Qualitative Models in Computational Simulative Sciences: Representation, Confirmation, Experimentation.Nicola Angius - 2019 - Minds and Machines 29 (3):397-416.
    The Epistemology Of Computer Simulation has developed as an epistemological and methodological analysis of simulative sciences using quantitative computational models to represent and predict empirical phenomena of interest. In this paper, Executable Cell Biology and Agent-Based Modelling are examined to show how one may take advantage of qualitative computational models to evaluate reachability properties of reactive systems. In contrast to the thesis, advanced by EOCS, that computational models are not adequate representations of the simulated empirical systems, it is shown how (...)
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  • The Strategies of Modeling in Biology Education.Julia Svoboda & Cynthia Passmore - 2013 - Science & Education 22 (1):119-142.
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  • Rigorous results, cross-model justification, and the transfer of empirical warrant: the case of many-body models in physics.Axel Gelfert - 2009 - Synthese 169 (3):497-519.
    This paper argues that a successful philosophical analysis of models and simulations must accommodate an account of mathematically rigorous results. Such rigorous results may be thought of as genuinely model-specific contributions, which can neither be deduced from fundamental theory nor inferred from empirical data. Rigorous results provide new indirect ways of assessing the success of models and simulations and are crucial to understanding the connections between different models. This is most obvious in cases where rigorous results map different models on (...)
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  • Reconsidering the Carnap-Kuhn Connection.Jonathan Y. Tsou - 2015 - In William J. Devlin & Alisa Bokulich (eds.), Kuhn’s Structure of Scientific Revolutions - 50 Years On. Cham: Boston Studies in the Philosophy and History of Science, vol. 311. Springer.
    Recently, some philosophers of science (e.g., Gürol Irzik, Michael Friedman) have challenged the ‘received view’ on the relationship between Rudolf Carnap and Thomas Kuhn, suggesting that there is a close affinity (rather than opposition) between their philosophical views. In support of this argument, these authors cite Carnap and Kuhn’s similar views on incommensurability, theory-choice, and scientific revolutions. Against this revisionist view, I argue that the philosophical relationship between Carnap and Kuhn should be regarded as opposed rather than complementary. In particular, (...)
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  • Scientific fictions as rules of inference.Mauricio Suárez - 2008 - In Mauricio Suárez (ed.), Fictions in Science: Philosophical Essays on Modeling and Idealization. New York: Routledge. pp. 158--178.
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  • Abstraction and Idealization in the Formal Verification of Software Systems.Nicola Angius - 2013 - Minds and Machines 23 (2):211-226.
    Questions concerning the epistemological status of computer science are, in this paper, answered from the point of view of the formal verification framework. State space reduction techniques adopted to simplify computational models in model checking are analysed in terms of Aristotelian abstractions and Galilean idealizations characterizing the inquiry of empirical systems. Methodological considerations drawn here are employed to argue in favour of the scientific understanding of computer science as a discipline. Specifically, reduced models gained by Dataion are acknowledged as Aristotelian (...)
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  • Metaphysics as modeling: the handmaiden’s tale.L. A. Paul - 2012 - Philosophical Studies 160 (1):1-29.
    Critics of contemporary metaphysics argue that it attempts to do the hard work of science from the ease of the armchair. Physics, not metaphysics, tells us about the fundamental facts of the world, and empirical psychology is best placed to reveal the content of our concepts about the world. Exploring and understanding the world through metaphysical reflection is obsolete. In this paper, I will show why this critique of metaphysics fails, arguing that metaphysical methods used to make claims about the (...)
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  • Models as make-believe.Adam Toon - 2008 - In Roman Frigg & Matthew Hunter (eds.), Beyond Mimesis and Convention: Representation in Art and Science. Boston Studies in Philosophy of Science.
    In this paper I propose an account of representation for scientific models based on Kendall Walton’s ‘make-believe’ theory of representation in art. I first set out the problem of scientific representation and respond to a recent argument due to Craig Callender and Jonathan Cohen, which aims to show that the problem may be easily dismissed. I then introduce my account of models as props in games of make-believe and show how it offers a solution to the problem. Finally, I demonstrate (...)
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  • Simulating many-body models in physics: Rigorous results, 'benchmarks', and cross-model justification.Axel Gelfert - unknown
    This paper argues that, for a prospective philosophical analysis of models and simulations to be successful, it must accommodate an account of mathematically rigorous results. Such rigorous results are best thought of as genuinely model-specific contributions, which can neither be deduced from fundamental theory nor inferred from empirical data. Rigorous results often provide new indirect ways of assessing the success of computer simulations of individual models. This is most obvious in cases where rigorous results map different models on to one (...)
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  • The distribution of representation.Lisa M. Osbeck & Nancy J. Nersessian - 2006 - Journal for the Theory of Social Behaviour 36 (2):141–160.
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  • Preface.Lorenzo Magnani & Nancy J. Nersessian - 2005 - Foundations of Science 10 (1):1-4.
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  • Lessons from the Large Hadron Collider for model-based experimentation: the concept of a model of data acquisition and the scope of the hierarchy of models.Koray Karaca - 2018 - Synthese 195 (12):1-22.
    According to the hierarchy of models account of scientific experimentation developed by Patrick Suppes and elaborated by Deborah Mayo, theoretical considerations about the phenomena of interest are involved in an experiment through theoretical models that in turn relate to experimental data through data models, via the linkage of experimental models. In this paper, I dispute the HoM account in the context of present-day high-energy physics experiments. I argue that even though the HoM account aims to characterize experimentation as a model-based (...)
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  • Essay review: Models and exploratory models.Fiora Salis - 2017 - Studies in History and Philosophy of Science Part A 63:58-61.
    Review essay of How to do science with models. A philosophical primer. Springer briefs in philosophy, Axel Gelfert., 129, Price € 49,99 softcover, ISBN: 978-3-319-27954-1.
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  • Understanding Scientific Inquiries of Galileo’s Formulation for the Law of Free Falling Motion.Jun-Young Oh - 2016 - Foundations of Science 21 (4):567-578.
    The purpose of this study is to gain a better understanding of the role of abstraction and idealization in Galileo’s scientific inquiries into the law of free falling motion, and their importance in the history of science. Because there is no consensus on the use of the terms “abstraction” and “idealization” in the literature, it is necessary to distinguish between them at the outset. This paper will argue for the importance of abstraction and idealization in physics and the theories and (...)
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  • Naturalizing Peirce's Semiotics: Ecological Psychology's Solution to the Problem of Creative Abduction.Alex Kirlik & Peter Storkerson - 2010 - In W. Carnielli L. Magnani (ed.), Model-Based Reasoning in Science and Technology. pp. 31--50.
    "It is difficult not to notice a curious unrest in the philosophic atmosphere of the time, a loosening of old landmarks, a softening of oppositions, a mutual borrowing from one another on the part of systems anciently closed, and an interest in new suggestions, however vague, as if the one thing sure were the inadequacy of extant school-solutions. The dissatisfactions with these seems due for the most part to a feeling that they are too abstract and academic. Life is confused (...)
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  • Is it justifiable to abandon all search for a logic of discovery?Mehul Shah - 2007 - International Studies in the Philosophy of Science 21 (3):253 – 269.
    In his influential paper, 'Why Was the Logic of Discovery Abandoned?', Laudan contends that there has been no philosophical rationale for a logic of discovery since the emergence of consequentialism in the 19th century. It is the purpose of this paper to show that consequentialism does not involve the rejection of all types of logic of discovery. Laudan goes too far in his interpretation of the historical shift from generativism to consequentialism, and his claim that the context of pursuit belongs (...)
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  • Teleosemantics, Externalism, and the Content of Theoretical Concepts.Daniel C. Burnston - unknown
    In several works, Ruth Millikan has developed a ‘teleosemantic’ theory of concepts. Millikan’s theory has three explicit desiderata for concepts: wide scope, non-descriptionist content, and naturalism. I contend that Millikan’s theory cannot fulfill all of these desiderata simultaneously. Theoretical concepts, such as those of chemistry and physics, fall under Millikan’s intended scope, but I will argue that her theory cannot account for these concepts in a way that is compatible with both non-descriptionism and naturalism. In these cases, Millikan’s view is (...)
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  • Connecting internal and external representations: Spatial transformations of scientific visualizations. [REVIEW]J. Gregory Trafton, Susan B. Trickett & Farilee E. Mintz - 2005 - Foundations of Science 10 (1):89-106.
    Many scientific discoveries have depended on external diagrams or visualizations. Many scientists also report to use an internal mental representation or mental imagery to help them solve problems and reason. How do scientists connect these internal and external representations? We examined working scientists as they worked on external scientific visualizations. We coded the number and type of spatial transformations (mental operations that scientists used on internal or external representations or images) and found that there were a very large number of (...)
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  • Idealization within a Structuralist Perspective.Xavier de Donato Rodríguez - 2011 - Metatheoria – Revista de Filosofía E Historia de la Ciencia 1:65--90.
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  • Simulation Methods for an Abductive System in Science.Tom Addis, Jan Townsend Addis, Dave Billinge, David Gooding & Bart-Floris Visscher - 2008 - Foundations of Science 13 (1):37-52.
    We argue that abduction does not work in isolation from other inference mechanisms and illustrate this through an inference scheme designed to evaluate multiple hypotheses. We use game theory to relate the abductive system to actions that produce new information. To enable evaluation of the implications of this approach we have implemented the procedures used to calculate the impact of new information in a computer model. Experiments with this model display a number of features of collective belief-revision leading to consensus-formation, (...)
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  • The Problem of Justification of Empirical Hypotheses in Software Testing.Nicola Angius - 2014 - Philosophy and Technology 27 (3):423-439.
    This paper takes part in the methodological debate concerning the nature and the justification of hypotheses about computational systems in software engineering by providing an epistemological analysis of Software Testing, the practice of observing the programs’ executions to examine whether they fulfil software requirements. Property specifications articulating such requirements are shown to involve falsifiable hypotheses about software systems that are evaluated by means of tests which are likely to falsify those hypotheses. Software Reliability metrics, used to measure the growth of (...)
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  • Soccer Science and the Bayes Community: Exploring the Cognitive Implications of Modern Scientific Communication.Jeff Shrager, Dorrit Billman, Gregorio Convertino, J. P. Massar & Peter Pirolli - 2010 - Topics in Cognitive Science 2 (1):53-72.
    Science is a form of distributed analysis involving both individual work that produces new knowledge and collaborative work to exchange information with the larger community. There are many particular ways in which individual and community can interact in science, and it is difficult to assess how efficient these are, and what the best way might be to support them. This paper reports on a series of experiments in this area and a prototype implementation using a research platform called CACHE. CACHE (...)
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  • Model‐Based Reasoning in Distributed Cognitive Systems.Nancy J. Nersessian - 2006 - Philosophy of Science 73 (5):699-709.
    This paper examines the nature of model-based reasoning in the interplay between theory and experiment in the context of biomedical engineering research laboratories, where problem solving involves using physical models. These "model systems" are sites of experimentation where in vitro models are used to screen, control, and simulate specific aspects of in vivo phenomena. As with all models, simulation devices are idealized representations, but they are also systems themselves, possessing engineering constraints. Drawing on research in contemporary cognitive science that construes (...)
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  • Enculturation into Technoscience: Analysis of the Views of Novices and Experts on Modelling and Learning in Nanophysics.Suvi Tala - 2011 - Science & Education 20 (7-8):733-760.
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  • Scientific representation in practice: Models and creative similarity.Julia Sanchez-Dorado - 2019 - Dissertation,
    The thesis proposes an account of the means of scientific representation focused on similarity, or more specifically, on the notion of “creative similarity”. I first distinguish between two different questions regarding the problem of representation: the question about the constituents and the question about the means of representation (following Suárez 2003; van Fraassen 2008). I argue that, although similarity is not a good candidate for constituent of representation, it can satisfactorily answer the question about the means of representation if adequately (...)
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  • A ‘Semantic’ View of Scientific Models for Science Education.Agustín Adúriz-Bravo - 2013 - Science & Education 22 (7):1593-1611.
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  • (1 other version)Explanation and Understanding through Scientific Models.Richard David-Rus - 2009 - Dissertation, University Munich
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  • Imagination's grip on science.Tim Mey - 2006 - Metaphilosophy 37 (2):222-239.
    In part because “imagination” is a slippery notion, its exact role in the production of scientific knowledge remains unclear. There is, however, one often explicit and deliberate use of imagination by scientists that can be (and has been) studied intensively by epistemologists and historians of science: thought experiments. The main goal of this article is to document the varieties of thought experimentation, not so much in terms of the different sciences in which they occur but rather in terms of the (...)
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  • Perceiving the infinite and the infinitesimal world: Unveiling and optical diagrams in mathematics. [REVIEW]Lorenzo Magnani & Riccardo Dossena - 2005 - Foundations of Science 10 (1):7-23.
    Many important concepts of the calculus are difficult to grasp, and they may appear epistemologically unjustified. For example, how does a real function appear in “small” neighborhoods of its points? How does it appear at infinity? Diagrams allow us to overcome the difficulty in constructing representations of mathematical critical situations and objects. For example, they actually reveal the behavior of a real function not “close to” a point (as in the standard limit theory) but “in” the point. We are interested (...)
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  • Inductive knowledge under dominance.Marco C. Campi - 2023 - Synthese 201 (6):1-29.
    Inductive reasoning aims at constructing rules and models of general applicability from a restricted set of observations. Induction is a keystone in natural sciences, and it influences diverse application fields such as engineering, medicine and economics. More generally, induction plays a major role in the way humans learn and operate in their everyday life. The level of reliability that a model achieves depends on how informative the observations are relative to the flexibility of the process by which the model is (...)
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  • Teaching scientific creativity through philosophy of science.Rasmus Jaksland - 2021 - European Journal for Philosophy of Science 11 (4):1-17.
    There is a demand to nurture scientific creativity in science education. This paper proposes that the relevant conceptual infrastructure with which to teach scientific creativity is often already included in philosophy of science courses, even those that do not cover scientific creativity explicitly. More precisely, it is shown how paradigm theory can serve as a framework with which to introduce the differences between combinational, exploratory, and transformational creativity in science. Moreover, the types of components given in Kuhn’s disciplinary matrix are (...)
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  • Remodeling the past.Tim De Mey - 2005 - Foundations of Science 10 (1):47-66.
    In some of the papers in which she develops and defends the mental modelview of thought experiments in physics, Nersessian expresses the belief that her account has implications for thought experiments in other domains as well. In this paper, I argue, firstly, that counterfactual reasoning has a legitimate place in historical inquiry, and secondly, that the mental model view can account for such "alternative histories". I proceed as follows. Firstly, I review the main accounts of thought experiments in physics and (...)
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  • Analogue Models and Universal Machines. Paradigms of Epistemic Transparency in Artificial Intelligence.Hajo Greif - 2022 - Minds and Machines 32 (1):111-133.
    The problem of epistemic opacity in Artificial Intelligence is often characterised as a problem of intransparent algorithms that give rise to intransparent models. However, the degrees of transparency of an AI model should not be taken as an absolute measure of the properties of its algorithms but of the model’s degree of intelligibility to human users. Its epistemically relevant elements are to be specified on various levels above and beyond the computational one. In order to elucidate this claim, I first (...)
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  • Mathematical Representations in Science: A Cognitive–Historical Case History.Ryan D. Tweney - 2009 - Topics in Cognitive Science 1 (4):758-776.
    The important role of mathematical representations in scientific thinking has received little attention from cognitive scientists. This study argues that neglect of this issue is unwarranted, given existing cognitive theories and laws, together with promising results from the cognitive historical analysis of several important scientists. In particular, while the mathematical wizardry of James Clerk Maxwell differed dramatically from the experimental approaches favored by Michael Faraday, Maxwell himself recognized Faraday as “in reality a mathematician of a very high order,” and his (...)
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  • Estruturas conceituais e estratégias de investigação: modelos representacionais e instanciais, analogias e correspondência.Valter Alnis Bezerra - 2011 - Scientiae Studia 9 (3):585-609.
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  • (2 other versions)Preface.Lorenzo Magnani & Nancy J. Nersessian - 2002 - Mind and Society 3 (1):3-7.
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