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  1. What’s Right with a Syntactic Approach to Theories and Models?Sebastian Lutz - 2010 - Erkenntnis (S8):1-18.
    Syntactic approaches in the philosophy of science, which are based on formalizations in predicate logic, are often considered in principle inferior to semantic approaches, which are based on formalizations with the help of structures. To compare the two kinds of approach, I identify some ambiguities in common semantic accounts and explicate the concept of a structure in a way that avoids hidden references to a specific vocabulary. From there, I argue that contrary to common opinion (i) unintended models do not (...)
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  2. (1 other version)Economic Models as Argumentative Devices.N. Emrah Aydinonat - manuscript
    This article critically evaluates Itzhak Gilboa, Andrew Postlewaite, Larry Samuelson, and David Schmeidler’s account of economic models. First, it gives a selective overview of their argument, highlighting its emphasis on similarity and their oversight of the role of idealizations in economics. Second, it proposes a sketch of an account of models as arguments and argumentative devices. This account not only sheds light on Gilboa et al.’s approach, including its shortcomings, but also identifies key challenges in model-based inference, suggesting a fresh (...)
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  3. Complexity and scientific idealization: A philosophical introduction to the study of complex systems.Charles Rathkopf - manuscript
    In the philosophy of science, increasing attention has been given to the methodological novelties associated with the study of complex systems. However, there is little agreement on exactly what complex systems are. Although many characterizations of complex systems are available, they tend to be either impressionistic or overly formal. Formal definitions rely primarily on ideas from the study of computational complexity, but the relation between these formal ideas and the messy world of empirical phenomena is unclear. Here, I give a (...)
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  4. Epistemic Framing of Quantum Mechanics: A Structural Argument.Andrey Shkursky - manuscript
    We argue that quantum mechanics is not an ontological description of microscopic reality but a frame-dependent epistemic structure. Building upon the Aperture Stack architecture, we interpret quantum formalism as a topology of observational constraint rather than a reflection of physical entities. Wavefunction collapse, uncertainty, and measurement are reframed as structural transformations within epistemic geometry. Interpretations of QM are thus slices of frame geometry, not metaphysical claims. We further explore a structural homology between quantum formalism and reflexive cognitive architectures, suggesting a (...)
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  5. Symbols versus Models.Chuang Liu - 2013
    In this paper I argue against a deflationist view that as representational vehicles symbols and models do their jobs in essentially the same way. I argue that symbols are conventional vehicles whose chief function is denotation while models are epistemic vehicles whose chief function is showing what their targets are like in the relevant aspects. It is further pointed out that models usually do not rely on similarity or some such relations to relate to their targets. For that referential relation (...)
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  6. The value of mathematics for scientific representation.Author unknown - manuscript
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  7. Scientific Models and Thought Experiments: Same Same but Different.Rawad El Skaf & Michael T. Stuart - forthcoming - In Rawad El Skaf & Michael T. Stuart, 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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  8. Modeling Action: Recasting the Causal Theory.Megan Fritts & Frank Cabrera - forthcoming - Analytic Philosophy.
    Contemporary action theory is generally concerned with giving theories of action ontology. In this paper, we make the novel proposal that the standard view in action theory—the Causal Theory of Action—should be recast as a “model”, akin to the models constructed and investigated by scientists. Such models often consist in fictional, hypothetical, or idealized structures, which are used to represent a target system indirectly via some resemblance relation. We argue that recasting the Causal Theory as a model can not only (...)
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  9. Gründe einsehen . Visuelle Repräsentationen im Prozess des wissenschaftlichen Verstehens.Nicola Mößner - forthcoming - In Marcel Lemmes, Stephan Packard & Klaus Sachs-Hombach, Bilder im Aufbruch Herausforderungen der Bildwissenschaft. Herbert von Halem Verlag.
    Was macht wissenschaftliches Verstehen aus? Und inwiefern können visuelle Repräsentationen, wie sie vielfach in der (Ergebnis-)Präsentation (Publikationen, Vorträgen etc.) in unterschiedlichen wissenschaftlichen Disziplinen Verwendung finden, zum Verstehen untersuchter Fragestellungen beitragen? Diesen Themen soll im folgenden Beitrag genauer nachgegangen werden. Den Ausgangspunkt bildet dabei Henk W. de Regts Studie (2017) zum wissenschaftlichen Verstehen. De Regt plädiert dafür, Kriterien des wissenschaftlichen Verstehens aus der aktuellen wissenschaftlichen Praxis zur Anwendung zu bringen – was auch bedeutet, ihre historische Variabilität ernst zu nehmen. Ein Punkt (...)
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  10. 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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  11. Coordination Instead of Consensus Classification: Insights from Systematics for Bio-Ontologies.Beckett Sterner, Joeri Witteveen & Nico Franz - forthcoming - History and Philosophy of the Life Sciences.
    Big data is opening new angles on old questions about scientific progress. Is scientific knowledge cumulative? If yes, how does it make progress? In the life sciences, what we call the Consensus Principle has dominated the design of data discovery and integration tools: the design of a formal classificatory system for expressing a body of data should be grounded in consensus. Based on current approaches in biomedicine and systematic biology, we formulate and compare three types of the Consensus Principle: realist, (...)
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  12. Shape space as a conceptual space.Antonio Vassallo - forthcoming - Synthese.
    The notion of shape space was introduced in the second half of the 20th Century as a useful analytical tool for tackling problems related to the intrinsic spatial configuration of material systems. In recent years, the geometrical properties of shape spaces have been investigated and exploited to construct a totally relational description of physics (classical, relativistic, and quantum). The main aim of this relational framework—originally championed by Julian Barbour and Bruno Bertotti—is to cast the dynamical description of material systems in (...)
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  13. Modes, Media, and Formats of Scientific Representation.M. Vorms & T. Knuuttila - forthcoming - Erkenntnis: An International Journal of Analytic Philosophy.
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  14. Maps and Models.Rasmus Grønfeldt Winther - forthcoming - In Routledge Handbook of Philosophy of Scientific Modeling. London, UK:
    Maps and mapping raise questions about models and modeling and in science. This chapter archives map discourse in the founding generation of philosophers of science (e.g., Rudolf Carnap, Nelson Goodman, Thomas Kuhn, and Stephen Toulmin) and in the subsequent generation (e.g., Philip Kitcher, Helen Longino, and Bas van Fraassen). In focusing on these two original framing generations of philosophy of science, I intend to remove us from the heat of contemporary discussions of abstraction, representation, and practice of science and thereby (...)
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  15. Scientific Theory and Possibility.Sam Baron, Baptiste Le Bihan & James Read - 2025 - Erkenntnis 1:1-17.
    It is plausible that the models of scientific theories correspond to possibilities. But how do we know which models of which scientific theories so correspond? This paper provides a novel proposal for guiding belief about possibilities via scientific theories. The proposal draws on the notion of an effective theory: a theory that applies very well to a particular, restricted domain. We argue that it is the models of effective theories that we should believe correspond, at least in part, to possibilities. (...)
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  16. Categorical Abstractions for Representing Temporal Organizations of Type Mechanisms.Jinyeong Gim - 2025 - Korean Journal of Logic 28 (1):81-111.
    Craver's diagram, comprising symbols such as X (entity), S (mechanism), Φ (activity), and Ψ (phenomenon), is widely used to represent biological mechanisms in the New Mechanism. However, this paper demonstrates that Craver’s framework lacks the formal capacity to adequately capture the organizational structures and functional dynamics essential for mechanistic explanations, particularly the temporal interplay among entities and activities or the relational nature of enzymatic state transitions. To address these limitations, this paper proposes a supplementary framework based on category theory, enabling (...)
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  17. How theoretical terms effectively refer.Sébastien Rivat - 2025 - Synthese 205 (4):1-22.
    Scientific realists with traditional semantic inclinations are often pressed to explain away the distinguished series of referential failures that seem to plague our best past science. As recent debates make it particularly vivid, a central challenge is to find a reliable and principled way to assess referential success at the time a theory is still a live concern. In this paper, I argue that this is best done in the case of physics by examining whether the putative referent of a (...)
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  18. Two senses of representation in science.Quentin Ruyant - 2025 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 39 (3):353-371.
    Accounts of scientific representation typically assume that there is a single sense of “represent”, and they attempt to develop a theory that can account for all its features. The aim of this article is to draw the consequences of a distinction between two senses of “represent” that has been proposed recently. Taking inspiration from the distinction between speaker-meaning and expression-meaning in philosophy of language, a first sense is analysed in terms of the mental states of the user of a vehicle (...)
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  19. Through the Prism of Modal Epistemology: Perspective on Modal Modeling.Ylwa Sjölin Wirling & Till Grüne-Yanoff - 2025 - In Tarja Knuuttila, Till Grüne-Yanoff, Rami Koskinen & Ylwa Wirling, Modeling the Possible. Perspectives from Philosophy of Science. London: Routledge. pp. 27-47.
    Several philosophers of science have drawn attention to a number of modeling practices where scientific models primarily contribute modal information. Examples now abound, and, recently, there have also been some preliminary attempts to address questions of under what conditions, and by virtue of what, models can perform this modal epistemic function. This paper sets out to constructively review those attempts through a prism of the more general literature on the epistemology of modality. One aim of this exercise is to expose (...)
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  20. Mauricio Suárez, Inference and Representation: A Study in Modeling Science Chicago: University of Chicago Press, 2024. Pp. 328. ISBN 978-0-226-83004-9. $35.00 (paper). [REVIEW]Matthew Brewer & Matilde Carrera - 2024 - British Journal for the History of Science.
  21. Making Sense of Models and Modelling in Science Education: Atomic Models and Contributions from Mario Bunge’s Epistemology.Juliana Machado - 2024 - Mεtascience: Scientific General Discourse 3:103-126.
    Conceptions about the nature of scientific models held by science students frequently involve distorted views, with a tendency to consider them as mere copies of reality. Besides encompassing an untenable view about the nature of science itself, this misconstruction can effectively be a pedagogical impediment to learning. Objectives: We evaluate whether Mario Bunge’s epistemology might contribute to tackling issues related to the nature of models in science education contexts. De-sign: After identifying Bunge’s main model categories, we employ them to examine (...)
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  22. Does the no miracles argument apply to AI?Darrell P. Rowbottom, William Peden & André Curtis-Trudel - 2024 - Synthese 203 (173):1-20.
    According to the standard no miracles argument, science’s predictive success is best explained by the approximate truth of its theories. In contemporary science, however, machine learning systems, such as AlphaFold2, are also remarkably predictively successful. Thus, we might ask what best explains such successes. Might these AIs accurately represent critical aspects of their targets in the world? And if so, does a variant of the no miracles argument apply to these AIs? We argue for an affirmative answer to these questions. (...)
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  23. Epistemic and Objective Possibility in Science.Ylwa Sjölin Wirling & Till Grüne-Yanoff - 2024 - British Journal for the Philosophy of Science 75 (4):821-841.
    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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  24. Moving Targets and Models of Nothing: A New Sense of Abstraction for Philosophy of Science.Michael T. Stuart & Anatolii Kozlov - 2024 - In Chiara Ambrosio & Julia Sánchez-Dorado, Abstraction in science and art: philosophical perspectives. New York, NY: Routledge.
    As Nelson Goodman highlighted, there are two main senses of “abstract” that can be found in discussions about abstract art. On the one hand, a representation is abstract if it leaves out certain features of its target. On the other hand, something can be abstract to the extent that it does not represent a concrete subject. The first sense of “abstract” is well-known in philosophy of science. For example, philosophers discuss mathematical models of physical, biological, and economic systems as being (...)
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  25. Informational Equivalence but Computational Differences? Herbert Simon on Representations in Scientific Practice.David Waszek - 2024 - Minds and Machines 34 (1):93-116.
    To explain why, in scientific problem solving, a diagram can be “worth ten thousand words,” Jill Larkin and Herbert Simon (1987) relied on a computer model: two representations can be “informationally” equivalent but differ “computationally,” just as the same data can be encoded in a computer in multiple ways, more or less suited to different kinds of processing. The roots of this proposal lay in cognitive psychology, more precisely in the “imagery debate” of the 1970s on whether there are image-like (...)
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  26. Signs as a Theme in the Philosophy of Mathematical Practice.David Waszek - 2024 - In Bharath Sriraman, Handbook of the History and Philosophy of Mathematical Practice. Cham: Springer.
    Why study notations, diagrams, or more broadly the variety of nonverbal “representations” or “signs” that are used in mathematical practice? This chapter maps out recent work on the topic by distinguishing three main philosophical motivations for doing so. First, some work (like that on diagrammatic reasoning) studies signs to recover norms of informal or historical mathematical practices that would get lost if the particular signs that these practices rely on were translated away; work in this vein has the potential to (...)
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  27. Scientific Representation. [REVIEW]Cory Wright - 2024 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 55 (2):485-490.
  28. 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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  29. A representação científica a partir das “Analogias da experiência” de Kant.Bruno Camilo Camilo - 2023 - Kant E-Prints 17 (3):132-141.
    The objective of this article is to approach the way in which Kant considers the “analogies of experience” necessary connections for the scientific representation of the physical world to occur. The method consists of carrying out a conceptual analysis of selected excerpts from theCritique of pure reasonthat may serve to support the interpretation that the analogies of experience are, for Kant, rules that determine the necessary links between perceptions and the ability to understand phenomena. from them. In this way, we (...)
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  30. A quick overview of scientific representation and modelling. [REVIEW]Dimitri Coelho Mollo - 2023 - Metascience 32:321-324.
  31. Categorical Abstractions of Molecular Structures of Biological Objects: A Case Study of Nucleic Acids.Jinyeong Gim - 2023 - Global Philosophy 33 (5):No.43.
    The type-level abstraction is a formal way to represent molecular structures in biological practice. Graphical representations of molecular structures of biological objects are also used to identify functional processes of things. This paper will reveal that category theory is a formal mathematical language not only to visualize molecular structures of biological objects as type-level abstraction formally but also to understand how to infer biological functions from the molecular structures of biological objects. Category theory is a toolkit to understand biological knowledge (...)
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  32. Operationalising Representation in Natural Language Processing.Jacqueline Harding - 2023 - British Journal for the Philosophy of Science.
    Despite its centrality in the philosophy of cognitive science, there has been little prior philosophical work engaging with the notion of representation in contemporary NLP practice. This paper attempts to fill that lacuna: drawing on ideas from cognitive science, I introduce a framework for evaluating the representational claims made about components of neural NLP models, proposing three criteria with which to evaluate whether a component of a model represents a property and operationalising these criteria using probing classifiers, a popular analysis (...)
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  33. 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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  34. Consistent histories through pragmatist lenses.Quentin Ruyant - 2023 - Studies in History and Philosophy of Science Part A 98 (C):40-48.
    This article adopts a bottom-up approach to theory interpretation, following the slogan “meaning is use”, and applies it to quantum mechanics. I argue that it fits very well with the Consistent Histories formulation of quantum mechanics, interpreted in a particular way that is not the interpretation favoured by original proponents of the formulation. I examine the difficulties and advantages of this interpretation.
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  35. Valeurs Dans la Representation Scientifique.Quentin Ruyant - 2023 - Lato Sensu: Revue de la Société de Philosophie des Sciences 10 (1):24-38.
    Le but de cet article est d'examiner le rôle joué par les valeurs dans les activités de représentation en science, notamment la construction ou utilisation de modèles, en distinguant représentation concrète et abstraite. Un modèle hiérarchique est proposé. La conclusion est que l'influence des valeurs sociales dans la représentation scientifique dépend du niveau d'abstraction considéré, et qu'elle n'est problématique que quand des valeurs locales sont considérées pour évaluer des représentations plus générales.
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  36. 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.
  37. Fiction and Scientific Knowledge.Adam Toon - 2023 - In Alison James, Akihiro Kubo & Françoise Lavocat, The Routledge Handbook of Fiction and Belief. Routledge. pp. 115-125.
    What has fiction to do with science? At first glance, the two activities seem to have entirely different aims and products. Science aims at truth, while fiction can deviate wildly from it. Science produces theories, which we are asked to believe. Fiction produces stories, which we are asked to imagine. Given these differences, associating science and fiction might seem like a serious mistake, or even a threat to science. And yet many authors have tried to understand science by looking to (...)
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  38. 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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  39. Against ‘Interpretation’: Quantum Mechanics Beyond Syntax and Semantics.Raoni Wohnrath Arroyo & Gilson Olegario da Silva - 2022 - Axiomathes 32 (6):1243-1279.
    The question “what is an interpretation?” is often intertwined with the perhaps even harder question “what is a scientific theory?”. Given this proximity, we try to clarify the first question to acquire some ground for the latter. The quarrel between the syntactic and semantic conceptions of scientific theories occupied a large part of the scenario of the philosophy of science in the 20th century. For many authors, one of the two currents needed to be victorious. We endorse that such debate, (...)
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  40. 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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  41. Representaciones como sistemas (2nd edition).Esteban Céspedes & Cecilia Valdivia - 2022 - Artefactos 11 (1).
    One of the problems that are often indicated as a criticism of different forms of representationalism is the difficulty to find definitions that are neither semantic nor realist in a simple sense. The present work tackles this class of critiques from a contextualist point of view, assuming those semantic aspects that are necessary for a concept of representation, but showing that semantic relations of representation should neither be static, nor referential in a classical and strictly realist sense. Two distinctions are (...)
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  42. Introduction.Kareem Kareem Khalifa, Insa Lawler & Elay Shech - 2022 - In Insa Lawler, Kareem Khalifa & Elay Shech, Scientific Understanding and Representation: Modeling in the Physical Sciences. New York, NY: Routledge.
    This chapter gives an overview of the various themes and issues discussed in the volume. It includes summaries of all chapters and places the contributions, some of which are part of a critical conversation format, in the context of the larger literature and debates.
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  43. Introduction to the edited volume “Scientific Understanding and Representation: Modeling in the Physical Sciences”.Kareem Khalifa, Insa Lawler & Elay Shech - 2022 - In Insa Lawler, Kareem Khalifa & Elay Shech, Scientific Understanding and Representation: Modeling in the Physical Sciences. New York, NY: Routledge.
    This chapter gives an overview of the various themes and issues discussed in the volume. It includes summaries of all chapters and places the contributions, some of which are part of a critical conversation format, in the context of the larger literature and debates.
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  44. Scientific Representation: An Inferentialist-Expressivist Manifesto.Kareem Khalifa, Jared Millson & Mark Risjord - 2022 - Philosophical Topics 50 (1):263-291.
    This essay presents a fully inferentialist-expressivist account of scientific representation. In general, inferentialist approaches to scientific representation argue that the capacity of a model to represent a target system depends on inferences from models to target systems. Inferentialism is attractive because it makes the epistemic function of models central to their representational capacity. Prior inferentialist approaches to scientific representation, however, have depended on some representational element, such as denotation or representational force. Brandom’s Making It Explicit provides a model of how (...)
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  45. Real quantitativeness: what formal investigations can(not) show. [REVIEW]Derek Lam - 2022 - Metascience 31 (1):125-128.
    Review: J. E. Wolff. The metaphysics of quantity. New York: Oxford University Press, 2020. 240 pp, $72.00 HB.
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  46. Empirical techniques and the accuracy of scientific representations.Dana Matthiessen - 2022 - Studies in History and Philosophy of Science Part A 94 (C):143-157.
    This paper proposes an account of accurate scientific representation in terms of techniques that produce data from a target phenomenon. I consider an approach to accurate representation that abstracts from such epistemic factors, justified by a thesis I call Ontic Priority. This holds that criteria for representational accuracy depend on a pre-established account of the nature of the relation between a model and its target phenomenon. I challenge Ontic Priority, drawing on the observation that many working scientists do not have (...)
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  47. An Inferential Response to the "Loss of Reality Objection" to Structural Empiricism.Franco Menares Paredes - 2022 - Principia: An International Journal of Epistemology 26 (3):539–558.
    This paper aims to meet an objection that has been raised against structural empiricism known as the “loss of reality objection.” I argue that an inferential approach to scientific representation allows the structural empiricist to account for the representation of phenomena by data models and ensures that such a representation is not arbitrary. By the notions of immersion, derivation, and interpretation, I show how data models are able to represent phenomena in a non-arbitrary manner. I conclude this paper with a (...)
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  48. Cognitive Artifacts and Their Virtues in Scientific Practice.Marcin Miłkowski - 2022 - Studies in Logic, Grammar and Rhetoric 67 (1):219-246.
    One of the critical issues in the philosophy of science is to understand scientific knowledge. This paper proposes a novel approach to the study of reflection on science, called “cognitive metascience”. In particular, it offers a new understanding of scientific knowledge as constituted by various kinds of scientific representations, framed as cognitive artifacts. It introduces a novel functional taxonomy of cognitive artifacts prevalent in scientific practice, covering a huge diversity of their formats, vehicles, and functions. As a consequence, toolboxes, conceptual (...)
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  49. Scientific representation.James Nguyen - 2022 - New York, NY: Cambridge University Press. Edited by Roman Frigg.
    This Element presents a philosophical exploration of the notion of scientific representation. It does so by focussing on an important class of scientific representations, namely scientific models. Models are important in the scientific process because scientists can study a model to discover features of reality. But what does it mean for something to represent something else? This is the question discussed in this Element. The authors begin by disentangling different aspects of the problem of representation and then discuss the dominant (...)
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  50. An alternative View for Scientific Models Based on Metaphors: a case analysis from Darwin's use of metaphors.Deivide Garcia da Silva Oliveira - 2022 - Principia: An International Journal of Epistemology 26 (2):347-373.
    This paper aims to offer an alternative view for understanding scientific models based on metaphors. To accomplish this, we employ a special case of Darwin’s use of metaphors, such as the notion of powerful Being, in order to represent natural selection. Our proposal contributes to issues in the literature of scientific model, such as imprecisions in the understanding of scientific models, especially in models based on metaphors. Thus, our alternative view of models based on metaphors, and inspired by Darwin’s use (...)
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