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Models and fiction

Synthese 172 (2):251-268 (2010)

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  1. It’s Not a Game: Accurate Representation with Toy Models.James Nguyen - 2020 - British Journal for the Philosophy of Science 71 (3):1013-1041.
    Drawing on ‘interpretational’ accounts of scientific representation, I argue that the use of so-called ‘toy models’ provides no particular philosophical puzzle. More specifically; I argue that once one gives up the idea that models are accurate representations of their targets only if they are appropriately similar, then simple and highly idealized models can be accurate in the same way that more complex models can be. Their differences turn on trading precision for generality, but, if they are appropriately interpreted, toy models (...)
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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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  • Formal Semantics and Applied Mathematics: An Inferential Account.Ryan M. Nefdt - 2020 - Journal of Logic, Language and Information 29 (2):221-253.
    In this paper, I utilise the growing literature on scientific modelling to investigate the nature of formal semantics from the perspective of the philosophy of science. Specifically, I incorporate the inferential framework proposed by Bueno and Colyvan : 345–374, 2011) in the philosophy of applied mathematics to offer an account of how formal semantics explains and models its data. This view produces a picture of formal semantic models as involving an embedded process of inference and representation applying indirectly to linguistic (...)
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  • Infinity and the foundations of linguistics.Ryan M. Nefdt - 2019 - Synthese 196 (5):1671-1711.
    The concept of linguistic infinity has had a central role to play in foundational debates within theoretical linguistics since its more formal inception in the mid-twentieth century. The conceptualist tradition, marshalled in by Chomsky and others, holds that infinity is a core explanandum and a link to the formal sciences. Realism/Platonism takes this further to argue that linguistics is in fact a formal science with an abstract ontology. In this paper, I argue that a central misconstrual of formal apparatus of (...)
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  • Veritism refuted? Understanding, idealization, and the facts.Tamer Nawar - 2021 - Synthese 198 (5):4295-4313.
    Elgin offers an influential and far-reaching challenge to veritism. She takes scientific understanding to be non-factive and maintains that there are epistemically useful falsehoods that figure ineliminably in scientific understanding and whose falsehood is no epistemic defect. Veritism, she argues, cannot account for these facts. This paper argues that while Elgin rightly draws attention to several features of epistemic practices frequently neglected by veritists, veritists have numerous plausible ways of responding to her arguments. In particular, it is not clear that (...)
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  • A Simulacrum Account of Dispositional Properties.Marco J. Nathan - 2013 - Noûs 49 (2):253-274.
    This essay presents a model-theoretic account of dispositional properties, according to which dispositions are not ordinary properties of real entities; dispositions capture the behavior of abstract, idealized models. This account has several payoffs. First, it saves the simple conditional analysis of dispositions. Second, it preserves the general connection between dispositions and regularities, despite the fact that some dispositions are not grounded in actual regularities. Finally, it brings together the analysis and the explanation of dispositions under a unified framework.
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  • くりこみ群におけるミニマルモデルに基づく局所的創発.Kohei Morita - 2022 - Kagaku Tetsugaku 55 (1):1-23.
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  • Deflationary realism: Representation and idealisation in cognitive science.Dimitri Coelho Mollo - 2021 - Mind and Language 37 (5):1048-1066.
    Debate on the nature of representation in cognitive systems tends to oscillate between robustly realist views and various anti‐realist options. I defend an alternative view, deflationary realism, which sees cognitive representation as an offshoot of the extended application to cognitive systems of an explanatory model whose primary domain is public representation use. This extended application, justified by a common explanatory target, embodies idealisations, partial mismatches between model and reality. By seeing representation as part of an idealised model, deflationary realism avoids (...)
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  • Branching in the landscape of possibilities.Thomas Müller - 2012 - Synthese 188 (1):41-65.
    The metaphor of a branching tree of future possibilities has a number of important philosophical and logical uses. In this paper we trace this metaphor through some of its uses and argue that the metaphor works the same way in physics as in philosophy. We then give an overview of formal systems for branching possibilities, viz., branching time and (briefly) branching space-times. In a next step we describe a number of different notions of possibility, thereby sketching a landscape of possibilities. (...)
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  • Imagination and insight: a new acount of the content of thought experiments.Letitia Meynell - 2014 - Synthese 191 (17):4149-4168.
    This paper motivates, explains, and defends a new account of the content of thought experiments. I begin by briefly surveying and critiquing three influential accounts of thought experiments: James Robert Brown’s Platonist account, John Norton’s deflationist account that treats them as picturesque arguments, and a cluster of views that I group together as mental model accounts. I use this analysis to motivate a set of six desiderata for a new approach. I propose that we treat thought experiments primarily as aesthetic (...)
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  • Thumper the Infinitesimal Rabbit: A Fictionalist Perspective on Some “Unimaginable” Model Systems in Biology.Brian McLoone - 2019 - Philosophy of Science 86 (4):662-671.
    Fictionalists believe that scientific models are about model systems that are imaginary. Michael Weisberg has claimed that fictionalism is indefensible because many scientific models are about model systems that are unimaginable. According to a certain account of imagination, what Weisberg says is plausible. According to another, more defensible account of imagination, it is not. I discuss these issues within the context of an allegedly unimaginable model system in ecology, but the conclusions I draw are more general. I then describe how (...)
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  • Simplified models: a different perspective on models as mediators.C. D. McCoy & Michela Massimi - 2018 - European Journal for Philosophy of Science 8 (1):99-123.
    We introduce a novel point of view on the “models as mediators” framework in order to emphasize certain important epistemological questions about models in science which have so far been little investigated. To illustrate how this perspective can help answer these kinds of questions, we explore the use of simplified models in high energy physics research beyond the Standard Model. We show in detail how the construction of simplified models is grounded in the need to mitigate pressing epistemic problems concerning (...)
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  • 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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  • Two Kinds of Exploratory Models.Michela Massimi - 2019 - Philosophy of Science 86 (5):869-881.
    I analyze the exploratory function of two main modeling practices: targetless fictional models and hypothetical perspectival models. In both cases, I argue, modelers invite us to imagine or conceive something about the target system, which is known to be either nonexistent or just hypothetical. I clarify the kind of imagining or conceiving involved in each modeling practice, and I show how each—in its own right—delivers important modal knowledge. I illustrate these two kinds of exploratory models with Maxwell’s ether model and (...)
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  • Symbolic versus Modelistic Elements in Scientific Modeling.Chuang Liu - 2015 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 30 (2):287.
    In this paper, we argue that symbols are conventional vehicles whose chief function is denotation, while models are epistemic vehicles, and their chief function is to show what their targets are like in the relevant aspects. And we explain why this is incompatible with the deflationary view on scientific modeling. Although the same object may serve both functions, the two vehicles are conceptually distinct and most models employ both elements. With the clarification of this point we offer an alternative account (...)
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  • Re-inflating the Conception of Scientific Representation.Chuang Liu - 2015 - International Studies in the Philosophy of Science 29 (1):41-59.
    This article argues for an anti-deflationist view of scientific representation. Our discussion begins with an analysis of the recent Callender–Cohen deflationary view on scientific representation. We then argue that there are at least two radically different ways in which a thing can be represented: one is purely symbolic, and therefore conventional, and the other is epistemic. The failure to recognize that scientific models are epistemic vehicles rather than symbolic ones has led to the mistaken view that whatever distinguishes scientific models (...)
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  • Against the New Fictionalism: A Hybrid View of Scientific Models.Chuang Liu - 2016 - International Studies in the Philosophy of Science 30 (1):39-54.
    This article develops an approach to modelling and models in science—the hybrid view—that is against model fictionalism of a recent stripe. It further argues that there is a version of fictionalism about models to which my approach is neutral and which makes sense only if one adopts a special sort of antirealism. Otherwise, my approach strongly suggests that one stay away from fictionalism and embrace realism directly.
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  • Modeling without models.Arnon Levy - 2015 - Philosophical Studies 172 (3):781-798.
    Modeling is an important scientific practice, yet it raises significant philosophical puzzles. Models are typically idealized, and they are often explored via imaginative engagement and at a certain “distance” from empirical reality. These features raise questions such as what models are and how they relate to the world. Recent years have seen a growing discussion of these issues, including a number of views that treat modeling in terms of indirect representation and analysis. Indirect views treat the model as a bona (...)
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  • Models, Fictions, and Realism: Two Packages.Arnon Levy - 2012 - Philosophy of Science 79 (5):738-748.
    Some philosophers of science – the present author included – appeal to fiction as an interpretation of the practice of modeling. This raises the specter of an incompatibility with realism, since fiction-making is essentially non-truth-regulated. I argue that the prima facie conflict can be resolved in two ways, each involving a distinct notion of fiction and a corresponding formulation of realism. The main goal of the paper is to describe these two packages. Toward the end I comment on how to (...)
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  • Models and Fictions: Not So Similar after All?Arnon Levy - 2020 - Philosophy of Science 87 (5):819-828.
    A number of philosophers draw a close analogy between scientific modeling and fiction, often appealing to Kendall Walton’s make-believe view. I assess the models-fictions analogy from a cognitive a...
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  • Information in Biology: A Fictionalist Account.Arnon Levy - 2010 - Noûs 45 (4):640-657.
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  • Anchoring fictional models: Adam Toon: Models as make-believe. Plagrave-Macmillan, 2012.Arnon Levy - 2013 - Biology and Philosophy 28 (4):693-701.
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  • Models, structures, and the explanatory role of mathematics in empirical science.Mary Leng - 2021 - Synthese 199 (3-4):10415-10440.
    Are there genuine mathematical explanations of physical phenomena, and if so, how can mathematical theories, which are typically thought to concern abstract mathematical objects, explain contingent empirical matters? The answer, I argue, is in seeing an important range of mathematical explanations as structural explanations, where structural explanations explain a phenomenon by showing it to have been an inevitable consequence of the structural features instantiated in the physical system under consideration. Such explanations are best cast as deductive arguments which, by virtue (...)
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  • A review on Katzner’s Models, mathematics and methodology in economic explanation, Cambridge University Press 2018.Aki Lehtinen - 2021 - Journal of Economic Methodology 29 (1):105-109.
    A review of Donald Katzner's book on economic modelling is provided. In addition to characterising the book, I give critical comments on the distinction between primary and secondary assumptions.
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  • Scientific understanding and felicitous legitimate falsehoods.Insa Lawler - 2021 - Synthese 198 (7):6859-6887.
    Science is replete with falsehoods that epistemically facilitate understanding by virtue of being the very falsehoods they are. In view of this puzzling fact, some have relaxed the truth requirement on understanding. I offer a factive view of understanding that fully accommodates the puzzling fact in four steps: (i) I argue that the question how these falsehoods are related to the phenomenon to be understood and the question how they figure into the content of understanding it are independent. (ii) I (...)
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  • Model Explanation Versus Model-Induced Explanation.Insa Lawler & Emily Sullivan - 2021 - Foundations of Science 26 (4):1049-1074.
    Scientists appeal to models when explaining phenomena. Such explanations are often dubbed model explanations or model-based explanations. But what are the precise conditions for ME? Are ME special explanations? In our paper, we first rebut two definitions of ME and specify a more promising one. Based on this analysis, we single out a related conception that is concerned with explanations that are induced from working with a model. We call them ‘model-induced explanations’. Second, we study three paradigmatic cases of alleged (...)
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  • Technische Fiktionen: Zur Ontologie und Ethik der Gestaltung.Michael Kuhn - 2023 - transcript Verlag.
    Unentwegt werden neue technische Produkte gestaltet. Doch was macht die technische Gestaltung aus? Wie lässt sich ihr Gegenstand - (noch) nicht existierende Artefakte - adäquat auf den Begriff bringen? Michael Kuhn begreift technische Ideen vor ihrer Realisierung als Fiktionen. Er bietet eine fiktionstheoretische Rekonstruktion der Gestaltungstätigkeit und entwickelt hieraus eine Ethik der Gestaltung. Der stark interdisziplinäre Zugang zwischen Technikphilosophie und Ingenieurwissenschaften liefert neue Erkenntnisse für beide Fachrichtungen und stellt wertvolle Grundlagen bereit.
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  • Models as icons: modeling models in the semiotic framework of Peirce’s theory of signs.Björn Kralemann & Claas Lattmann - 2013 - Synthese 190 (16):3397-3420.
    In this paper, we try to shed light on the ontological puzzle pertaining to models and to contribute to a better understanding of what models are. Our suggestion is that models should be regarded as a specific kind of signs according to the sign theory put forward by Charles S. Peirce, and, more precisely, as icons, i.e. as signs which are characterized by a similarity relation between sign (model) and object (original). We argue for this (1) by analyzing from a (...)
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  • Models as Relational Categories.Tommi Kokkonen - 2017 - Science & Education 26 (7-9):777-798.
    Model-based learning has an established position within science education. It has been found to enhance conceptual understanding and provide a way for engaging students in authentic scientific activity. Despite ample research, few studies have examined the cognitive processes regarding learning scientific concepts within MBL. On the other hand, recent research within cognitive science has examined the learning of so-called relational categories. Relational categories are categories whose membership is determined on the basis of the common relational structure. In this theoretical paper, (...)
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  • Synthetic fictions: turning imagined biological systems into concrete ones.Tarja Knuuttila & Rami Koskinen - 2020 - Synthese 198 (9):8233-8250.
    The recent discussion of fictional models has focused on imagination, implicitly considering fictions as something nonconcrete. We present two cases from synthetic biology that can be viewed as concrete fictions. Both minimal cells and alternative genetic systems are modal in nature: they, as well as their abstract cousins, can be used to study unactualized possibilia. We approach these synthetic constructs through Vaihinger’s notion of a semi-fiction and Goodman’s notion of semifactuality. Our study highlights the relative existence of such concrete fictions. (...)
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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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  • Modelling as Indirect Representation? The Lotka–Volterra Model Revisited.Tarja Knuuttila & Andrea Loettgers - 2017 - British Journal for the Philosophy of Science 68 (4):1007-1036.
    ABSTRACT Is there something specific about modelling that distinguishes it from many other theoretical endeavours? We consider Michael Weisberg’s thesis that modelling is a form of indirect representation through a close examination of the historical roots of the Lotka–Volterra model. While Weisberg discusses only Volterra’s work, we also study Lotka’s very different design of the Lotka–Volterra model. We will argue that while there are elements of indirect representation in both Volterra’s and Lotka’s modelling approaches, they are largely due to two (...)
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  • Models, Fictions and Artifacts.Tarja Knuuttila - 2021 - In Wenceslao J. Gonzalez (ed.), Language and Scientific Research. Springer Verlag. 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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  • Epistemic artifacts and the modal dimension of modeling.Tarja Knuuttila - 2021 - European Journal for Philosophy of Science 11 (3):1-18.
    The epistemic value of models has traditionally been approached from a representational perspective. This paper argues that the artifactual approach evades the problem of accounting for representation and better accommodates the modal dimension of modeling. From an artifactual perspective, models are viewed as erotetic vehicles constrained by their construction and available representational tools. The modal dimension of modeling is approached through two case studies. The first portrays mathematical modeling in economics, while the other discusses the modeling practice of synthetic biology, (...)
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  • Imagination extended and embedded: artifactual versus fictional accounts of models.Tarja Knuuttila - 2017 - Synthese 198 (Suppl 21):5077-5097.
    This paper presents an artifactual approach to models that also addresses their fictional features. It discusses first the imaginary accounts of models and fiction that set model descriptions apart from imagined-objects, concentrating on the latter :251–268, 2010; Frigg and Nguyen in The Monist 99:225–242, 2016; Godfrey-Smith in Biol Philos 21:725–740, 2006; Philos Stud 143:101–116, 2009). While the imaginary approaches accommodate surrogative reasoning as an important characteristic of scientific modeling, they simultaneously raise difficult questions concerning how the imagined entities are related (...)
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  • Philosophical issues related to risks and values.Renato Rodrigues Kinouchi - 2018 - Filosofia Unisinos 19 (3).
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  • Necessary Laws and the Problem of Counterlegals.Samuel Kimpton-Nye - 2020 - Philosophy of Science 87 (3):518-535.
    Substantive counterlegal discourse poses a problem for those according to whom the laws of nature are metaphysically necessary. I discern two types of necessitarianism about laws: dispositional essentialism and modal necessitarianism. I argue that Toby Handfield’s response to the problem of counterlegals cannot help the modal necessitarian, according to whom all possible worlds are identical with respect to the laws. I thus propose a fictionalist treatment of counterlegals. Fictions are not limited by metaphysical possibility; hence, fictionalism affords the modal necessitarian (...)
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  • When Do Scientific Explanations Compete? Steps Toward a Heuristic Checklist.Todd Jones & Michael Pravica - 2017 - Metaphilosophy 48 (1-2):96-122.
    It's not uncommon for scientists to give different explanations of the same phenomenon, but we currently lack clear guidelines for deciding whether to treat such accounts as competitors. This article discusses how science studies can help create tools and guidelines for thinking about whether explanations compete. It also specifies how one family of discourse rules enables there to be differing accounts that appear to compete but don't. One hopes that being more aware of the linguistic mechanisms making compatible accounts appear (...)
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  • Don’t Blame the Idealizations.Nicholaos Jones - 2013 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 44 (1):85-100.
    Idealizing conditions are scapegoats for scientific hypotheses, too often blamed for falsehood better attributed to less obvious sources. But while the tendency to blame idealizations is common among both philosophers of science and scientists themselves, the blame is misplaced. Attention to the nature of idealizing conditions, the content of idealized hypotheses, and scientists’ attitudes toward those hypotheses shows that idealizing conditions are blameless when hypotheses misrepresent. These conditions help to determine the content of idealized hypotheses, and they do so in (...)
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  • Introduction: the plurality of modeling.Philippe Huneman & Maël Lemonie - 2014 - History and Philosophy of the Life Sciences 36 (1):5-15.
    Philosophers of science have recently focused on the scientific activity of modeling phenomena, and explicated several of its properties, as well as the activities embedded into it. A first approach to modeling has been elaborated in terms of representing a target system: yet other epistemic functions, such as producing data or detecting phenomena, are at least as relevant. Additional useful distinctions have emerged, such as the one between phenomenological and mechanistic models. In biological sciences, besides mathematical models, models now come (...)
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  • Representational indispensability and ontological commitment.John Heron - 2020 - Thought: A Journal of Philosophy 9 (2):105-114.
    Recent debates about mathematical ontology are guided by the view that Platonism's prospects depend on mathematics' explanatory role in science. If mathematics plays an explanatory role, and in the right kind of way, this carries ontological commitment to mathematical objects. Conversely, the assumption goes, if mathematics merely plays a representational role then our world-oriented uses of mathematics fail to commit us to mathematical objects. I argue that it is a mistake to think that mathematical representation is necessarily ontologically innocent and (...)
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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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  • Sparks of New Metaphysics and the Limits of Explanatory Abstractions.Thomas Hauer - 2024 - Metaphysica 25 (1):15-39.
    Physical reality as an explanatory model is an abstraction of the mind. Every perceptual system is a user interface, like the dashboard of an aeroplane or the desktop of a computer. We do not see or otherwise perceive reality but only interface with reality. The user interface concept is a starting point for a critical dialogue with those epistemic theories that present themselves as veridical and take explanatory abstractions as ontological primitives. At the heart of any scientific model are assumptions (...)
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  • Mechanistic inquiry and scientific pursuit: The case of visual processing.Philipp Haueis & Lena Kästner - 2022 - Studies in History and Philosophy of Science Part A 93 (C):123-135.
    Why is it rational for scientists to pursue multiple models of a phenomenon at the same time? The literatures on mechanistic inquiry and scientific pursuit each develop answers to a version of this question which is rarely discussed by the other. The mechanistic literature suggests that scientists pursue different complementary models because each model provides detailed insights into different aspects of the phenomenon under investigation. The pursuit literature suggests that scientists pursue competing models because alternative models promise to solve outstanding (...)
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  • Lagrangian possibilities.Alexandre Guay & Quentin Ruyant - 2024 - Synthese 203 (4):1-22.
    Natural modalities are often analysed from an abstract point of view where they are associated with putative laws of nature. However, the way possibilities are represented in physics is more complex. Lagrangian mechanics, for instance, involves two different layers of modalities: kinematical and dynamical possibilities. This paper examines the status of these two layers, both in the classical and quantum case. The quantum case is particularly problematic: we identify four possible interpretive options. The upshot is that a close inspection of (...)
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  • 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.
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  • Models and fictions in science.Peter Godfrey-Smith - 2009 - Philosophical Studies 143 (1):101 - 116.
    Non-actual model systems discussed in scientific theories are compared to fictions in literature. This comparison may help with the understanding of similarity relations between models and real-world target systems. The ontological problems surrounding fictions in science may be particularly difficult, however. A comparison is also made to ontological problems that arise in the philosophy of mathematics.
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  • Manipulative imagination: how to move things around in mathematics.Valeria Giardino - 2018 - Theoria : An International Journal for Theory, History and Fundations of Science 33 (2):345-360.
    In the first part of the paper, previous work about embodied mathematics and the practice of topology will be presented. According to the proposed view, in order to become experts, topologists have to learn how to use manipulative imagination: representations are cognitive tools whose functioning depends from pre-existing cognitive abilities and from specific training. In the second part of the paper, the notion of imagination as “make-believe” is discussed to give an account of cognitive tools in mathematics as props; to (...)
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  • Imitation in automata and robots: A philosophical case study on Kempelen.Lukas Geiszler - 2023 - Studies in History and Philosophy of Science Part A 100 (C):22-31.
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  • Scientific Models and Games of Make-Believe: A Modal-Logical Perspective.Matthieu Gallais - 2016 - Kairos 17 (1):73-109.
    Some fictionalist approaches to the notion of scientific model are based on the concept of game of make-believe developed by Kendall Walton, without proposing a similar interpretation of it. The distinction between authorized and unauthorized games can be one of the sources of those divergences. In relation to the distinction made by Walton, the de dicto and de re modalities of the fiction-operator reflect different epistemological engagements concerning objects which satisfy properties. This paper aims at following up on the proposals (...)
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