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  1. Inferential power, formalisms, and scientific models.Vincent Ardourel, Anouk Barberousse & Cyrille Imbert - unknown
    Scientific models need to be investigated if they are to provide valuable information about the systems they represent. Surprisingly, the epistemological question of what enables this investigation has hardly been investigated. Even authors who consider the inferential role of models as central, like Hughes or Bueno and Colyvan, content themselves with claiming that models contain mathematical resources that provide inferential power. We claim that these notions require further analysis and argue that mathematical formalisms contribute to this inferential role. We characterize (...)
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  • Models as speech acts: the telling case of financial models.Nicolas Brisset - 2018 - Journal of Economic Methodology 25 (1):21-41.
    This paper intends to bring Austinian themes into methodological discussion about models. Using Austinian conceptual vocabulary, I argue that models perform actions in and outside of the academic field. This multiplicity of fields induces a variety of felicity conditions and types of performed actions. If for example, an inference from a model is judged according to some epistemological criteria in the scientific field, the representation of the world which the model carries will not be judged by the same criteria outside (...)
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  • Models in Economics Are Not (Always) Nomological Machines.Cyril Hédoin - 2013 - Philosophy of the Social Sciences 44 (4):424-459.
    This paper evaluates Nancy Cartwright’s critique of economic models. Cartwright argues that economics fails to build relevant “nomological machines” able to isolate capacities. In this paper, I contend that many economic models are not used as nomological machines. I give some evidence for this claim and build on an inferential and pragmatic approach to economic modeling. Modeling in economics responds to peculiar inferential norms where a “good” model is essentially a model that enhances our knowledge about possible worlds. As a (...)
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  • Why We Cannot Learn from Minimal Models.Roberto Fumagalli - 2016 - Erkenntnis 81 (3):433-455.
    Philosophers of science have developed several accounts of how consideration of scientific models can prompt learning about real-world targets. In recent years, various authors advocated the thesis that consideration of so-called minimal models can prompt learning about such targets. In this paper, I draw on the philosophical literature on scientific modelling and on widely cited illustrations from economics and biology to argue that this thesis fails to withstand scrutiny. More specifically, I criticize leading proponents of such thesis for failing to (...)
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  • Models and Truth: The functional decomposition approach.Uskali Mäki - 2009 - In M. Suàrez, M. Dorato & M. Rèdei (eds.), EPSA Epistemology and Methodology of Science: Launch of the European Philosophy of Science Association. Springer.
    Science is often said to aim at truth. And much of science is heavily dependent on the construction and use of theoretical models. But the notion of model has an uneasy relationship with that of truth. -/- Not so long ago, many philosophers held the view that theoretical models are different from theories in that they are not accompanied by any ontological commitments or presumptions of truth, whereas theories are (e.g. Achinstein 1964). More recently, some have thought that models are (...)
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  • The ample modelling mind.Mauricio Suárez - 2012 - Studies in History and Philosophy of Science Part A 43 (1):213-217.
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  • Constituting Objectivity: Transcendental Perspectives on Modern Physics.Jacob V. Pearce - 2010 - International Studies in the Philosophy of Science 24 (4):440-443.
    (2010). Constituting Objectivity: Transcendental Perspectives on Modern Physics. International Studies in the Philosophy of Science: Vol. 24, No. 4, pp. 440-443.
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  • Representing Reality: The Ontology of Scientific Models and Their Representational Function.Gabriele Contessa - 2007 - Dissertation, University of London
    Today most philosophers of science believe that models play a central role in science and that one of the main functions of scientific models is to represent systems in the world. Despite much talk of models and representation, however, it is not yet clear what representation in this context amounts to nor what conditions a certain model needs to meet in order to be a representation of a certain system. In this thesis, I address these two questions. First, I will (...)
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  • Mathematical Idealization.Chris Pincock - 2007 - Philosophy of Science 74 (5):957-967.
    Mathematical idealizations are scientific representations that result from assumptions that are believed to be false, and where mathematics plays a crucial role. I propose a two stage account of how to rank mathematical idealizations that is largely inspired by the semantic view of scientific theories. The paper concludes by considering how this approach to idealization allows for a limited form of scientific realism. ‡I would like to thank Robert Batterman, Gabriele Contessa, Eric Hiddleston, Nicholaos Jones, and Susan Vineberg for helpful (...)
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  • El problema de la representación: ¿razonamientos subrogantes válidos o sólidos?Hernán Lucas Accorinti - 2022 - Critica 54 (160):57-81.
    En el presente trabajo intentaré poner de manifiesto las debilidades de los argumentos dados por Contessa para sustentar, como fuente del representar, a los razonamientos subrogantes válidos por sobre los sólidos. En primer lugar, analizo ciertas ventajas epistémicas del criterio sustentado sobre los RS sólidos, evidenciando, consecuentemente, los límites del criterio estipulado por Contessa. En segundo lugar, muestro que los argumentos utilizados por Contessa para descartar el criterio instituido en los RS sólidos son deficientes, ya que, en el mejor de (...)
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  • Special issue: Inferentialism in philosophy of science and in epistemology—introduction.Javier González de Prado Salas, Mauricio Suárez & Jesús Zamora-Bonilla - 2018 - Synthese 198 (Suppl 4):905-907.
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  • No Learning from Minimal Models.Roberto Fumagalli - 2015 - Philosophy of Science 82 (5):798-809.
    This article examines the issue of whether consideration of so-called minimal models can prompt learning about real-world targets. Using a widely cited example as a test case, it argues against the increasingly popular view that consideration of minimal models can prompt learning about such targets. The article criticizes influential defenses of this view for failing to explicate by virtue of what properties or features minimal models supposedly prompt learning. It then argues that consideration of minimal models cannot prompt learning about (...)
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  • Are There No Things That are Scientific Theories?Steven French & Peter Vickers - 2011 - British Journal for the Philosophy of Science 62 (4):771-804.
    The ontological status of theories themselves has recently re-emerged as a live topic in the philosophy of science. We consider whether a recent approach within the philosophy of art can shed some light on this issue. For many years philosophers of aesthetics have debated a paradox in the (meta)ontology of musical works (e.g. Levinson [1980]). Taken individually, there are good reasons to accept each of the following three propositions: (i) musical works are created; (ii) musical works are abstract objects; (iii) (...)
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  • An Inferential Account on Theoretical Concepts in Physics.Javier Anta - 2021 - Critica 52 (156).
    In this paper we develop an inferential account on the meaning and reference of theoretical concepts in physics, mainly based on the pragmatic notion of ‘inferential validity’. Firstly, we distinguish between empirical meaningfulness and theoretical significance as two different modes of meaning, wherein the former depends on consistently encoding experimental values, as proposed by Chang, and the latter on being semantically coherent with other concepts. Secondly, we argue that each of these contributions to the validity of inferences imports a causal (...)
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  • Do fictions explain?James Nguyen - 2020 - Synthese 199 (1-2):3219-3244.
    I argue that fictional models, construed as models that misrepresent certain ontological aspects of their target systems, can nevertheless explain why the latter exhibit certain behaviour. They can do this by accurately representing whatever it is that that behaviour counterfactually depends on. However, we should be sufficiently sensitive to different explanatory questions, i.e., ‘why does certain behaviour occur?’ versus ‘why does the counterfactual dependency invoked to answer that question actually hold?’. With this distinction in mind, I argue that whilst fictional (...)
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  • How to infer explanations from computer simulations.Florian J. Boge - 2020 - Studies in History and Philosophy of Science Part A 82:25-33.
    Computer simulations are involved in numerous branches of modern science, and science would not be the same without them. Yet the question of how they can explain real-world processes remains an issue of considerable debate. In this context, a range of authors have highlighted the inferences back to the world that computer simulations allow us to draw. I will first characterize the precise relation between computer and target of a simulation that allows us to draw such inferences. I then argue (...)
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  • Can Theories of Mental Representation Adequately Explain Mental Imagery?Jelena Issajeva - 2020 - Foundations of Science 25 (2):341-355.
    Traditionally it is taken for granted that mental imagery (MI) is a mental representation (MR) of some kind or format. This yields that theory of MR can give an adequate and exhaustive explanation of MI. Such co-relation between the two is usually seen as unproblematic. But is it really so? This article aims at challenging the theoretical claim that the dominant ‘two-world’ account of MR can adequately explain MI. Contrary to the standard theory of MR, there are reasons to believe (...)
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  • Incompatible models in chemistry: the case of electronegativity.Hernán Lucas Accorinti - 2019 - Foundations of Chemistry 21 (1):71-81.
    During the second half of the nineteenth century, electronegativity has been one of the most relevant chemical concepts to explain the relationships between chemical substances and their possible reactions. Specifically, EN is a property of the substances that allows them to attract external electrons in bonding situations. The problem arises because EN cannot be measured directly. Indeed, the only way to measure it is through different properties that do can be directly measured, for instance enthalpy, ionization energies or electron affinities. (...)
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  • Thin versus thick accounts of scientific representation.Michael Poznic - 2018 - Synthese 195 (8):3433-3451.
    This paper proposes a novel distinction between accounts of scientific representation: it distinguishes thin accounts from thick accounts. Thin accounts focus on the descriptive aspect of representation whereas thick accounts acknowledge the evaluative aspect of representation. Thin accounts focus on the question of what a representation as such is. Thick accounts start from the question of what an adequate representation is. In this paper, I give two arguments in favor of a thick account, the Argument of the Epistemic Aims of (...)
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  • Scientific Models in Philosophy of Science.Tarja Knuuttila - 2010 - International Studies in the Philosophy of Science 24 (4):437-440.
    Scientists have used models for hundreds of years as a means of describing phenomena and as a basis for further analogy. In Scientific Models in Philosophy of Science, Daniela Bailer-Jones assembles an original and comprehensive philosophical analysis of how models have been used and interpreted in both historical and contemporary contexts. Bailer-Jones delineates the many forms models can take (ranging from equations to animals; from physical objects to theoretical constructs), and how they are put to use. She examines early mechanical (...)
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  • Unfolding in the empirical sciences: experiments, thought experiments and computer simulations.Rawad El Skaf & Cyrille Imbert - 2013 - Synthese 190 (16):3451-3474.
    Experiments (E), computer simulations (CS) and thought experiments (TE) are usually seen as playing different roles in science and as having different epistemologies. Accordingly, they are usually analyzed separately. We argue in this paper that these activities can contribute to answering the same questions by playing the same epistemic role when they are used to unfold the content of a well-described scenario. We emphasize that in such cases, these three activities can be described by means of the same conceptual framework—even (...)
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  • Scientific Realism and the History of Chemistry.Robin Hendry - 2018 - Spontaneous Generations 9 (1):108-117.
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  • Scientific misrepresentation and guides to ontology: the need for representational code and contents.Elay Shech - 2015 - Synthese 192 (11):3463-3485.
    In this paper I show how certain requirements must be set on any tenable account of scientific representation, such as the requirement allowing for misrepresentation. I then continue to argue that two leading accounts of scientific representation— the inferential account and the interpretational account—are flawed for they do not satisfy such requirements. Through such criticism, and drawing on an analogy from non-scientific representation, I also sketch the outline of a superior account. In particular, I propose to take epistemic representations to (...)
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  • On the Ideal of Autonomous Science.Dan Hicks - 2011 - Philosophy of Science 78 (5):1235-1248.
    In this article I first use Alasdair MacIntyre’s conception of a practice to develop a version of the common, although increasingly controversial, ideal of value-free, value-neutral, or autonomous science. I then briefly show how this ideal has been used by some philosophers to criticize both governmental and commercial funding of science. I go on to argue that, far from being value neutral, certain elements of this ideal strongly resemble some controversial elements of libertarian political philosophy. I suggest that alternative ideals (...)
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  • Psa 2018.Philsci-Archive -Preprint Volume- - unknown
    These preprints were automatically compiled into a PDF from the collection of papers deposited in PhilSci-Archive in conjunction with the PSA 2018.
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  • Remarks on a Structural Account of Scientific Explanation.Laura Felline - 2009 - In M. Suarez, M. Dorato & M. Redei (eds.), EPSA Philosophical Issues in the Sciences: Launch of the European Philosophy of Science Association. Dordrecht, Netherland: Springer. pp. 43--53.
    The problems that exist in relating quantum mechanical phenomena to classical concepts like properties, causes, or entities like particles or waves are well-known and still open to question, so that there is not yet an agreement on what kind of metaphysics lies at the foundations of quantum mechanics. However, physicists constantly use the formal resources of quantum mechanics in order to explain quantum phenomena. The structural account of explanation, therefore, tries to account for this kind of mathematical explanation in physics, (...)
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  • Similarity and representation in chemical knowledge practices.Juan Bautista Bengoetxea, Oliver Todt & José Luis Luján - 2014 - Foundations of Chemistry 16 (3):215-233.
    This paper argues for the theoretical and practical validity of similarity as a useful epistemological tool in scientific knowledge generation, specifically in chemistry. Classical analyses of similarity in philosophy of science do not account for the concept’s practical significance in scientific activities. We recur to examples from chemistry to counter the claim of authors like Quine or Goodman to the effect that similarity must be excluded from scientific practices . In conclusion we argue that more recent conceptualizations of the notion (...)
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