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  1. Introduction: the plurality of modeling.Huneman Philippe & Lemoine Maël - 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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  • Romanian Studies in Philosophy of Science.Ilie Parvu, Gabriel Sandu & Iulian D. Toader (eds.) - 2015 - Boston Studies in the Philosophy and History of Science, vol. 313: Springer.
    This book presents a collection of studies by Romanian philosophers, addressing foundational issues currently debated in contemporary philosophy of science. It offers a historical survey of the tradition of scientific philosophy in Romania. It examines some problems in the foundations of logic, mathematics, linguistics, the natural and social sciences. Among the more specific topics, it discusses scientific explanation, models, and mechanisms, as well as memory, artifacts, and rules of research. The book is useful to those interested in the philosophy of (...)
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  • Interdisciplinarity in the Making: Models and Methods in Frontier Science.Nancy J. Nersessian - 2022 - Cambridge, MA: MIT.
    A cognitive ethnography of how bioengineering scientists create innovative modeling methods. In this first full-scale, long-term cognitive ethnography by a philosopher of science, Nancy J. Nersessian offers an account of how scientists at the interdisciplinary frontiers of bioengineering create novel problem-solving methods. Bioengineering scientists model complex dynamical biological systems using concepts, methods, materials, and other resources drawn primarily from engineering. They aim to understand these systems sufficiently to control or intervene in them. What Nersessian examines here is how cutting-edge bioengineering (...)
  • Modeling as a Case for the Empirical Philosophy of Science.Ekaterina Svetlova - 2015 - In Hanne Andersen, Nancy J. Nersessian & Susann Wagenknecht (eds.), Empirical Philosophy of Science: Introducing Qualitative Methods into Philosophy of Science. Cham: Springer International Publishing. pp. 65-82.
    In recent years, the emergence of a new trend in contemporary philosophy has been observed in the increasing usage of empirical research methods to conduct philosophical inquiries. Although philosophers primarily use secondary data from other disciplines or apply quantitative methods (experiments, surveys, etc.), the rise of qualitative methods (e.g., in-depth interviews, participant observations and qualitative text analysis) can also be observed. In this paper, I focus on how qualitative research methods can be applied within philosophy of science, namely within the (...)
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  • Perspectival Instruments.Ana-Maria Creţu - 2022 - Philosophy of Science 89 (3):521-541.
    Despite its potential implications for the objectivity of scientific knowledge, the claim that “scientific instruments are perspectival” has received little critical attention. I show that this claim is best understood as highlighting the dependence of instruments on different perspectives. When closely analyzed, instead of constituting a novel epistemic challenge, this dependence can be exploited to mount novel strategies for resolving two old epistemic problems: conceptual relativism and theory-ladeness. The novel content of this article consists in articulating and developing these strategies (...)
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  • Giere’s instrumental Perspectivism.Kane Baker - 2020 - European Journal for Philosophy of Science 10 (3):1-19.
    When Ron Giere introduced perspectivism into philosophy of science, he provided a perspectivist analysis of both scientific instruments and scientific theorizing. Today, there is a burgeoning literature that extends Giere’s analysis of theorizing, with many philosophers examining the perspectivist approach to aspects of theorizing such as models, laws, explanations, and so on. However, relatively little attention has been paid to Giere’s analysis of instruments. In this article, I hope to fill this gap. I argue that the perspectivist analysis of instruments (...)
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  • The Cost of Prediction.Johannes Lenhard, Simon Stephan & Hans Hasse - manuscript
    This paper examines a looming reproducibility crisis in the core of the hard sciences. Namely, it concentrates on molecular modeling and simulation (MMS), a family of methods that predict properties of substances through computing interactions on a molecular level and that is widely popular in physics, chemistry, materials science, and engineering. The paper argues that in order to make quantitative predictions, sophisticated models are needed which have to be evaluated with complex simulation procedures that amalgamate theoretical, technological, and social factors (...)
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  • Models and representation.Roman Frigg & James Nguyen - 2017 - In Magnani Lorenzo & Bertolotti Tommaso Wayne (eds.), Springer Handbook of Model-Based Science. Springer. pp. 49-102.
    Scientific discourse is rife with passages that appear to be ordinary descriptions of systems of interest in a particular discipline. Equally, the pages of textbooks and journals are filled with discussions of the properties and the behavior of those systems. Students of mechanics investigate at length the dynamical properties of a system consisting of two or three spinning spheres with homogenous mass distributions gravitationally interacting only with each other. Population biologists study the evolution of one species procreating at a constant (...)
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  • Is Captain Kirk a natural blonde? Do X-ray crystallographers dream of electron clouds? Comparing model-based inferences in science with fiction.Ann-Sophie Barwich - 2017 - In Otávio Bueno, Steven French, George Darby & Dean Rickles (eds.), Thinking About Science, Reflecting on Art: Bringing Aesthetics and Philosophy of Science Together. New York: Routledge.
    Scientific models share one central characteristic with fiction: their relation to the physical world is ambiguous. It is often unclear whether an element in a model represents something in the world or presents an artifact of model building. Fiction, too, can resemble our world to varying degrees. However, we assign a different epistemic function to scientific representations. As artifacts of human activity, how are scientific representations allowing us to make inferences about real phenomena? In reply to this concern, philosophers of (...)
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  • Modeling and Inferring in Science.Emiliano Ippoliti, Thomas Nickles & Fabio Sterpetti - 2016 - In Emiliano Ippoliti, Fabio Sterpetti & Thomas Nickles (eds.), Models and Inferences in Science. Cham: Springer. pp. 1-9.
    Science continually contributes new models and rethinks old ones. The way inferences are made is constantly being re-evaluated. The practice and achievements of science are both shaped by this process, so it is important to understand how models and inferences are made. But, despite the relevance of models and inference in scientific practice, these concepts still remain contro-versial in many respects. The attempt to understand the ways models and infer-ences are made basically opens two roads. The first one is to (...)
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  • Modeling in Philosophy of Science.Stephan Hartmann - 2008 - In W. K. Essler & M. Frauchiger (eds.), Representation, Evidence, and Justification: Themes From Suppes. Frankfort, Germany: Ontos Verlag. pp. 1-95.
    Models are a principle instrument of modern science. They are built, applied, tested, compared, revised and interpreted in an expansive scientific literature. Throughout this paper, I will argue that models are also a valuable tool for the philosopher of science. In particular, I will discuss how the methodology of Bayesian Networks can elucidate two central problems in the philosophy of science. The first thesis I will explore is the variety-of-evidence thesis, which argues that the more varied the supporting evidence, the (...)
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  • Semantics and Truth.Jan Woleński - 2019 - Cham, Switzerland: Springer Verlag.
    The book provides a historical and systematic exposition of the semantic theory of truth formulated by Alfred Tarski in the 1930s. This theory became famous very soon and inspired logicians and philosophers. It has two different, but interconnected aspects: formal-logical and philosophical. The book deals with both, but it is intended mostly as a philosophical monograph. It explains Tarski’s motivation and presents discussions about his ideas as well as points out various applications of the semantic theory of truth to philosophical (...)
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  • The New Mechanical Philosophy.Stuart Glennan - 2017 - Oxford: Oxford University Press.
    This volume argues for a new image of science that understands both natural and social phenomena to be the product of mechanisms, casting the work of science as an effort to understand those mechanisms. Glennan offers an account of the nature of mechanisms and of the models used to represent them in physical, life, and social sciences.
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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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  • Understanding the Developing Role of Global Health Partnerships on Access to Medication: An STS Perspective.Michael Zisuh Ngoasong - 2010 - Bulletin of Science, Technology and Society 30 (1):33-42.
    A conceptual framework for studying the role of global health partnerships (GHPs) in determining policy practices on access to medication is presented. Although GHPs are of a practical nature, they are implicitly theory informed. The narratives used by GHP partners in relating to access to medication have theoretical origins. Building on the theoretical literature on models and the notion of embodied knowledge found in science and technology studies, GHPs are conceptualized as models that mediate between theory and practice. The proposed (...)
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  • Dissolving Decision Making? Models and Their Roles in Decision-Making Processes and Policy at Large.Ragna Zeiss & Stans van Egmond - 2014 - Science in Context 27 (4):631-657.
    ArgumentThis article studies the roles three science-based models play in Dutch policy and decision making processes. Key is the interaction between model construction and environment. Their political and scientific environments form contexts that shape the roles of models in policy decision making. Attention is paid to three aspects of the wider context of the models: a) the history of the construction process; b) the political and scientific environments; and c) the use in policy processes over longer periods of time. Models (...)
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  • Revisiting abstraction and idealization: how not to criticize mechanistic explanation in molecular biology.Martin Zach - 2022 - European Journal for Philosophy of Science 12 (1):1-20.
    Abstraction and idealization are the two notions that are most often discussed in the context of assumptions employed in the process of model building. These notions are also routinely used in philosophical debates such as that on the mechanistic account of explanation. Indeed, an objection to the mechanistic account has recently been formulated precisely on these grounds: mechanists cannot account for the common practice of idealizing difference-making factors in models in molecular biology. In this paper I revisit the debate and (...)
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  • Simulations, models, and theories: Complex physical systems and their representations.Eric Winsberg - 2001 - Proceedings of the Philosophy of Science Association 2001 (3):S442-.
    Using an example of a computer simulation of the convective structure of a red giant star, this paper argues that simulation is a rich inferential process, and not simply a "number crunching" technique. The scientific practice of simulation, moreover, poses some interesting and challenging epistemological and methodological issues for the philosophy of science. I will also argue that these challenges would be best addressed by a philosophy of science that places less emphasis on the representational capacity of theories (and ascribes (...)
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  • Models of Success Versus the Success of Models: Reliability without Truth.Eric Winsberg - 2006 - Synthese 152 (1):1-19.
    In computer simulations of physical systems, the construction of models is guided, but not determined, by theory. At the same time simulations models are often constructed precisely because data are sparse. They are meant to replace experiments and observations as sources of data about the world; hence they cannot be evaluated simply by being compared to the world. So what can be the source of credibility for simulation models? I argue that the credibility of a simulation model comes not only (...)
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  • Modeling Authenticity.Daniel A. Wilkenfeld - 2016 - Res Philosophica 93 (1):245-268.
    In this paper, we explore the link between understanding and transformative decisions. Paul (2014) suggests that one important aspect of making some decisions is that we make them not just on the basis of what data from other people tell us, but based on our own acquaintance with how the decision affects us. In this paper, we draw out a parallel between the sort of reasoning that Paul argues is required for authentic decision making and the sort of epistemic grasp (...)
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  • Functional explaining: a new approach to the philosophy of explanation.Daniel A. Wilkenfeld - 2014 - Synthese 191 (14):3367-3391.
    In this paper, I argue that explanations just ARE those sorts of things that, under the right circumstances and in the right sort of way, bring about understanding. This raises the question of why such a seemingly simple account of explanation, if correct, would not have been identified and agreed upon decades ago. The answer is that only recently has it been made possible to analyze explanation in terms of understanding without the risk of collapsing both to merely phenomenological states. (...)
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  • Explaining models: Theoretical and phenomenological models and their role for the first explanation of the hydrogen spectrum. [REVIEW]Torsten Wilholt - 2004 - Foundations of Chemistry 7 (2):149-169.
    Traditional nomological accounts of scientific explanation have assumed that a good scientific explanation consists in the derivation of the explanandum’s description from theory (plus antecedent conditions). But in more recent philosophy of science the adequacy of this approach has been challenged, because the relation between theory and phenomena in actual scientific practice turns out to be more intricate. This critique is here examined for an explanatory paradigm that was groundbreaking for 20th century physics and chemistry (and their interrelation): Bohr’s first (...)
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  • Gluing life together. Computer simulation in the life sciences: an introduction.Janina Wellmann - 2018 - History and Philosophy of the Life Sciences 40 (4):70.
    Over the course of the last three decades, computer simulations have become a major tool of doing science and engaging with the world, not least in an effort to predict and intervene in a future to come. Born in the context of the Second World War and the discipline of physics, simulations have long spread into most diverse fields of enquiry and technological application. This paper introduces a topical collection focussing on simulations in the life sciences. Echoing the current state (...)
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  • Forty years of 'the strategy': Levins on model building and idealization.Michael Weisberg - 2006 - Biology and Philosophy 21 (5):623-645.
    This paper is an interpretation and defense of Richard Levins’ “The Strategy of Model Building in Population Biology,” which has been extremely influential among biologists since its publication 40 years ago. In this article, Levins confronted some of the deepest philosophical issues surrounding modeling and theory construction. By way of interpretation, I discuss each of Levins’ major philosophical themes: the problem of complexity, the brute-force approach, the existence and consequence of tradeoffs, and robustness analysis. I argue that Levins’ article is (...)
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  • Experimental Modeling in Biology: In Vivo Representation and Stand-ins As Modeling Strategies.Marcel Weber - 2014 - Philosophy of Science 81 (5):756-769.
    Experimental modeling in biology involves the use of living organisms (not necessarily so-called "model organisms") in order to model or simulate biological processes. I argue here that experimental modeling is a bona fide form of scientific modeling that plays an epistemic role that is distinct from that of ordinary biological experiments. What distinguishes them from ordinary experiments is that they use what I call "in vivo representations" where one kind of causal process is used to stand in for a physically (...)
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  • The ontology of theoretical modelling: models as make-believe.Adam Toon - 2010 - Synthese 172 (2):301-315.
    The descriptions and theoretical laws scientists write down when they model a system are often false of any real system. And yet we commonly talk as if there were objects that satisfy the scientists’ assumptions and as if we may learn about their properties. Many attempt to make sense of this by taking the scientists’ descriptions and theoretical laws to define abstract or fictional entities. In this paper, I propose an alternative account of theoretical modelling that draws upon Kendall Walton’s (...)
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  • Abduction in economics: a conceptual framework and its model.Fernando Tohmé & Ricardo Crespo - 2013 - Synthese 190 (18):4215-4237.
    We discuss in this paper the scope of abduction in Economics. The literature on this type of inference shows that it can be interpreted in different ways, according to the role and nature of its outcome. We present a formal model that allows to capture these various meanings in different economic contexts.
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  • Missing systems and the face value practice.Martin Thomson-Jones - 2010 - Synthese 172 (2):283-299.
    Call a bit of scientific discourse a description of a missing system when (i) it has the surface appearance of an accurate description of an actual, concrete system (or kind of system) from the domain of inquiry, but (ii) there are no actual, concrete systems in the world around us fitting the description it contains, and (iii) that fact is recognised from the outset by competent practitioners of the scientific discipline in question. Scientific textbooks, classroom lectures, and journal articles abound (...)
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  • ‘A mechanistic interpretation, if possible’: How does predictive modelling causality affect the regulation of chemicals?François Thoreau - 2016 - Big Data and Society 3 (2).
    The regulation of chemicals is undergoing drastic changes with the use of computational models to predict environmental toxicity. This particular issue has not attracted much attention, despite its major impacts on the regulation of chemicals. This raises the problem of causality at the crossroads between data and regulatory sciences, particularly in the case models known as quantitative structure–activity relationship models. This paper shows that models establish correlations and not scientific facts, and it engages anew the way regulators deal with uncertainties. (...)
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  • Conceptual Constructive Models and Abstraction-as-Aggregation.Sim-Hui Tee - 2021 - Philosophia 49 (2):819-837.
    Conceptual constructive models are a type of scientific model that can be used to construct or reshape the target phenomenon conceptually. Though it has received scant attention from the philosophers, it raises an intriguing issue of how a conceptual constructive model can construct the target phenomenon in a conceptual way. Proponents of the conception of conceptual constructive models are not being explicit about the application of the constructive force of a model in the target construction. It is far from clear (...)
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  • Old and New Problems in Philosophy of Measurement.Eran Tal - 2013 - Philosophy Compass 8 (12):1159-1173.
    The philosophy of measurement studies the conceptual, ontological, epistemic, and technological conditions that make measurement possible and reliable. A new wave of philosophical scholarship has emerged in the last decade that emphasizes the material and historical dimensions of measurement and the relationships between measurement and theoretical modeling. This essay surveys these developments and contrasts them with earlier work on the semantics of quantity terms and the representational character of measurement. The conclusions highlight four characteristics of the emerging research program in (...)
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  • How Computational Models Predict the Behavior of Complex Systems.John Symons & Fabio Boschetti - 2013 - Foundations of Science 18 (4):809-821.
    In this paper, we argue for the centrality of prediction in the use of computational models in science. We focus on the consequences of the irreversibility of computational models and on the conditional or ceteris paribus, nature of the kinds of their predictions. By irreversibility, we mean the fact that computational models can generally arrive at the same state via many possible sequences of previous states. Thus, while in the natural world, it is generally assumed that physical states have a (...)
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  • Models at Work—Models in Decision Making.Ekaterina Svetlova & Vanessa Dirksen - 2014 - Science in Context 27 (4):561-577.
    In this topical section, we highlight the next step of research on modeling aiming to contribute to the emerging literature that radically refrains from approaching modeling as a scientific endeavor. Modeling surpasses “doing science” because it is frequently incorporated into decision-making processes in politics and management, i.e., areas which are not solely epistemically oriented. We do not refer to the production of models in academia for abstract or imaginary applications in practical fields, but instead highlight the real entwinement of science (...)
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  • Modelling Beyond Application: Epistemic and Non-epistemic Values in Modern Science.Ekaterina Svetlova - 2014 - International Studies in the Philosophy of Science 28 (1):79-98.
    In recent years, philosophers of science have begun to realize that the clear separation of the creation of models in academia and the application of models outside science is not possible. When these philosophers address hybrid contexts in which science is entwined with policy, business, and other realms of society, these often practically oriented realms no longer represent ‘the surroundings’ of science but rather are considered an essential part of it. I argue—and demonstrate empirically—that the judgement of a theory or (...)
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  • De-idealization by commentary: the case of financial valuation models.Ekaterina Svetlova - 2013 - Synthese 190 (2):321-337.
    Is there a unique way to de-idealize models? If not, how might the possible ways of reducing the distortion between models and reality differ from each other? Based on an empirical case study conducted in financial markets, this paper discusses how a popular valuation model (the Discounted Cash Flow model) idealizes reality and how the market participants de-idealize it in concrete market situations. In contrast to Cartwright's view that economic models are generally over-constrained, this paper suggests that valuation models are (...)
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  • Theories: Tools versus models.Mauricio Suárez & Nancy Cartwright - 2008 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 39 (1):62-81.
    In “The Toolbox of Science” (1995) together with Towfic Shomar we advocated a form of instrumentalism about scientific theories. We separately developed this view further in a number of subsequent works. Steven French, James Ladyman, Otavio Bueno and Newton Da Costa (FLBD) have since written at least eight papers and a book criticising our work. Here we defend ourselves. First we explain what we mean in denying that models derive from theory – and why their failure to do so should (...)
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  • 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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  • Credible Worlds, Capacities and Mechanisms.Robert Sugden - 2009 - Erkenntnis 70 (1):3-27.
    This paper asks how, in science in general and in economics in particular, theoretical models aid the understanding of real-world phenomena. Using specific models in economics and biology as test cases, it considers three alternative answers: that models are tools for isolating the ‘capacities’ of causal factors in the real world; that modelling is ‘conceptual exploration’ which ultimately contributes to the development of genuinely explanatory theories; and that models are credible counterfactual worlds from which inductive inferences can be made. The (...)
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  • Understanding metaphorical understanding (literally).Michael T. Stuart & Daniel Wilkenfeld - 2022 - European Journal for Philosophy of Science 12 (3):1-20.
    Metaphors are found all throughout science: in published papers, working hypotheses, policy documents, lecture slides, grant proposals, and press releases. They serve different functions, but perhaps most striking is the way they enable understanding, of a theory, phenomenon, or idea. In this paper, we leverage recent advances on the nature of metaphor and the nature of understanding to explore how they accomplish this feat. We attempt to shift the focus away from the epistemic value of the content of metaphors, to (...)
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  • The variety of explanations in the Higgs sector.Michael Stöltzner - 2017 - Synthese 194 (2).
    This paper argues that there is no single universal conception of scientific explanation that is consistently employed throughout the whole domain of Higgs physics—ranging from the successful experimental search for a standard model Higgs particle and the hitherto unsuccessful searches for any particles beyond the standard model, to phenomenological model builders in the Higgs sector and theoretical physicists interested in how the core principles of quantum field theory apply to spontaneous symmetry breaking and the Higgs mechanism. Yet the coexistence of (...)
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  • Higgs Models and Other Stories about Mass Generation.Michael Stöltzner - 2014 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 45 (2):369-386.
    The paper studies the topography of the model landscape of the physics in the Higgs sector both within the Standard Model of Elementary Particle Physics and beyond in the months before the discovery of a SM Higgs boson. At first glance, this landscape appears fragmented into a large number of different models and research communities. But it also clusters around certain guiding ideas, among them supersymmetry or dynamical symmetry breaking, in which representative and narrative features of the models are combined. (...)
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  • The Practical Value of Biological Information for Research.Beckett Sterner - 2014 - Philosophy of Science 81 (2):175-194,.
    Many philosophers are skeptical about the scientific value of the concept of biological information. However, several have recently proposed a more positive view of ascribing information as an exercise in scientific modeling. I argue for an alternative role: guiding empirical data collection for the sake of theorizing about the evolution of semantics. I clarify and expand on Bergstrom and Rosvall’s suggestion of taking a “diagnostic” approach that defines biological information operationally as a procedure for collecting empirical cases. The more recent (...)
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  • Sustainability and the Infinite Future: A Case Study of a False Modeling Assumption in Environmental Economics.Daniel Steel - 2017 - Erkenntnis 82 (5):1065-1084.
    This essay examines the issue of false assumptions in models via a case study of a prominent economic model of sustainable development, wherein the assumption of an infinite future plays a central role. Two proposals are found to be helpful for this case, one based on the concept of derivational robustness and the other on understanding. Both suggest that the assumption of an infinite future, while arguably legitimate in some applications of the model, is problematic with respect to what I (...)
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  • Science without (parametric) models: the case of bootstrap resampling.Jan Sprenger - 2011 - Synthese 180 (1):65-76.
    Scientific and statistical inferences build heavily on explicit, parametric models, and often with good reasons. However, the limited scope of parametric models and the increasing complexity of the studied systems in modern science raise the risk of model misspecification. Therefore, I examine alternative, data-based inference techniques, such as bootstrap resampling. I argue that their neglect in the philosophical literature is unjustified: they suit some contexts of inquiry much better and use a more direct approach to scientific inference. Moreover, they make (...)
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  • From the Lucasian revolution to DSGE models: an account of recent developments in macroeconomic modelling.Francesco Sergi - 2017 - Erasmus Journal for Philosophy and Economics 10 (1):142-145.
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  • Searches for the origins of the epistemological concept of model in mathematics.Gert Schubring - 2017 - Archive for History of Exact Sciences 71 (3):245-278.
    When did the concept of model begin to be used in mathematics? This question appears at first somewhat surprising since “model” is such a standard term now in the discourse on mathematics and “modelling” such a standard activity that it seems to be well established since long. The paper shows that the term— in the intended epistemological meaning—emerged rather recently and tries to reveal in which mathematical contexts it became established. The paper discusses various layers of argumentations and reflections in (...)
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  • Model, theory, and evidence in the discovery of the DNA structure.Samuel Schindler - 2008 - British Journal for the Philosophy of Science 59 (4):619-658.
    In this paper, I discuss the discovery of the DNA structure by Francis Crick and James Watson, which has provoked a large historical literature but has yet not found entry into philosophical debates. I want to redress this imbalance. In contrast to the available historical literature, a strong emphasis will be placed upon analysing the roles played by theory, model, and evidence and the relationship between them. In particular, I am going to discuss not only Crick and Watson's well-known model (...)
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  • Learning from the existence of models: On psychic machines, tortoises, and computer simulations.Dirk Schlimm - 2009 - Synthese 169 (3):521 - 538.
    Using four examples of models and computer simulations from the history of psychology, I discuss some of the methodological aspects involved in their construction and use, and I illustrate how the existence of a model can demonstrate the viability of a hypothesis that had previously been deemed impossible on a priori grounds. This shows a new way in which scientists can learn from models that extends the analysis of Morgan (1999), who has identified the construction and manipulation of models as (...)
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  • The nature of model-based understanding in condensed matter physics.Sang Wook Yi - 2002 - Mind and Society 3 (1):81-91.
    The paper studies the nature of understanding in condensed matter physics (CMP), mediated by the successful employment of its models. I first consider two obvious candidates for the criteria of model-based understanding, Van Fraassen's sense of empirical adequacy and Hacking's instrumental utility , and conclude that both are unsatisfactory. Inspired by Hasok Chang's recent proposal to reformulate realism as the pursuit of ontological plausibility in our system of knowledge, we may require the model under consideration to be understood (or intelligible) (...)
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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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