Results for 'Models in science'

1000+ found
Order:
  1. 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. 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 (...)
    Download  
     
    Export citation  
     
    Bookmark  
  2. Novel Approaches to Models: Mauricio Suárez : Fictions in Science: Philosophical Essays on Modeling and Idealization, Routledge, New York, 2009, Vii + 282 Pp, US$118 HB. [REVIEW]Adam Toon - 2010 - Metascience 19 (2):285-288.
    This paper is a review of Suarez, M. (ed.) Fictions in Science (Routledge).
    Download  
     
    Export citation  
     
    Bookmark  
  3. Models and Analogies in Science.Mary Hesse - 1965 - British Journal for the Philosophy of Science 16 (62):161-163.
    Download  
     
    Export citation  
     
    Bookmark   129 citations  
  4.  88
    Reality in Science.Emma Ruttkamp - 1999 - South African Journal of Philosophy 18 (2):149-191.
    One way in which to address the intriguing relations between science and reality is to work via the models (mathematical structures) of formal scientific theories which are interpretations under which these theories turn out to be true. The so-called 'statement approach' to scientific theories -- characteristic for instance of Nagel, Carnap, and Hempel --depicts theories in terms of 'symbolic languages' and some set of 'correspondence rules' or 'definition principles'. The defenders of the oppositionist non-statement approach advocate an analysis (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  5. Bayesian Models and Simulations in Cognitive Science.Giuseppe Boccignone & Roberto Cordeschi - 2007 - Workshop Models and Simulations 2, Tillburg, NL.
    Bayesian models can be related to cognitive processes in a variety of ways that can be usefully understood in terms of Marr's distinction among three levels of explanation: computational, algorithmic and implementation. In this note, we discuss how an integrated probabilistic account of the different levels of explanation in cognitive science is resulting, at least for the current research practice, in a sort of unpredicted epistemological shift with respect to Marr's original proposal.
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  6. Models in the Geosciences.Alisa Bokulich & Naomi Oreskes - 2017 - In Lorenzo Magnani & Tommaso Wayne Bertolotti (eds.), Springer Handbook of Model-Based Science. Springer. pp. 891-911.
    The geosciences include a wide spectrum of disciplines ranging from paleontology to climate science, and involve studies of a vast range of spatial and temporal scales, from the deep-time history of microbial life to the future of a system no less immense and complex than the entire Earth. Modeling is thus a central and indispensable tool across the geosciences. Here, we review both the history and current state of model-based inquiry in the geosciences. Research in these fields makes use (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  7.  75
    Prediction and Topological Models in Neuroscience.Bryce Gessell, Matthew Stanley, Benjamin Geib & Felipe De Brigard - forthcoming - In Fabrizio Calzavarini & Marco Viola (eds.), Neural Mechanisms: New challenges in the philosophy of neuroscience. Springer.
    In the last two decades, philosophy of neuroscience has predominantly focused on explanation. Indeed, it has been argued that mechanistic models are the standards of explanatory success in neuroscience over, among other things, topological models. However, explanatory power is only one virtue of a scientific model. Another is its predictive power. Unfortunately, the notion of prediction has received comparatively little attention in the philosophy of neuroscience, in part because predictions seem disconnected from interventions. In contrast, we argue that (...)
    Download  
     
    Export citation  
     
    Bookmark  
  8. 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 (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  9. Science and Fiction: Analysing the Concept of Fiction in Science and its Limits.Ann-Sophie Barwich - 2013 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 44 (2):357-373.
    A recent and growing discussion in philosophy addresses the construction of models and their use in scientific reasoning by comparison with fiction. This comparison helps to explore the problem of mediated observation and, hence, the lack of an unambiguous reference of representations. Examining the usefulness of the concept of fiction for a comparison with non-denoting elements in science, the aim of this paper is to present reasonable grounds for drawing a distinction between these two kinds of representation. In (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  10. 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 - 2018 - In Otávio Bueno, George Darby, Steven French & Dean Rickles (eds.), Thinking About Science, Reflecting on Art: Bringing Aesthetics and Philosophy of Science Together. London, UK:
    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 (...)
    Download  
     
    Export citation  
     
    Bookmark  
  11. Implications of Action-Oriented Paradigm Shifts in Cognitive Science.Peter F. Dominey, Tony J. Prescott, Jeannette Bohg, Andreas K. Engel, Shaun Gallagher, Tobias Heed, Matej Hoffmann, Gunther Knoblich, Wolfgang Prinz & Andrew Schwartz - 2016 - In Andreas K. Engel, Karl J. Friston & Danica Kragic (eds.), The Pragmatic Turn: Toward Action-Oriented Views in Cognitive Science. MIT Press. pp. 333-356.
    An action-oriented perspective changes the role of an individual from a passive observer to an actively engaged agent interacting in a closed loop with the world as well as with others. Cognition exists to serve action within a landscape that contains both. This chapter surveys this landscape and addresses the status of the pragmatic turn. Its potential influence on science and the study of cognition are considered (including perception, social cognition, social interaction, sensorimotor entrainment, and language acquisition) and its (...)
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  12. The Importance of Models in Theorizing: A Deflationary Semantic View.Stephen M. Downes - 1992 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1992:142 - 153.
    I critically examine the semantic view of theories to reveal the following results. First, models in science are not the same as models in mathematics, as holders of the semantic view claim. Second, when several examples of the semantic approach are examined in detail no common thread is found between them, except their close attention to the details of model building in each particular science. These results lead me to propose a deflationary semantic view, which is (...)
    Download  
     
    Export citation  
     
    Bookmark   45 citations  
  13.  38
    A Model-Theoretic Interpretation of Science.Emma Ruttkamp - 1997 - South African Journal of Philosophy 16 (1):31-36.
    I am arguing that it is only by concentrating on the role of models in theory construction, interpretation and change, that one can study the progress of science sensibly. I define the level at which these models operate as a level above the purely empirical (consisting of various systems in reality) but also indeed below that of the fundamental formal theories (expressed linguistically). The essentially multi-interpretability of the theory at the general, abstract linguistic level, implies that it (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  14.  49
    The Beginning of the World in Science and Religion. A Possibility of Synthesis?Gregory Bugajak - 1999 - In Niels Henrik Gregersen, Ulf Görman & Ch Wassermann (eds.), Studies in Science and Theology, vol. 5(1997): The Interplay Between Scientific and Theological Worldviews, part I, Labor et Fides, Genève 1999. pp. 33–42.
    The beginning of the world seems to be a subject of investigations of contemporary sciences on the one hand, and a part of the religious truth on the other. Technical and scientific progress is conducive to constructing new models of the world and inspires modification or rejection of existing ones. The aim of the first part of this paper is to show some problems, among others methodological, theoretical and interpretational, that arise on account of current scientific theories. Certain basic (...)
    Download  
     
    Export citation  
     
    Bookmark  
  15. A Failed Encounter in Mathematics and Chemistry: The Folded Models of van ‘T Hoff and Sachse.Michael Friedman - 2016 - Teorie Vědy / Theory of Science 38 (3):359-386.
    Three-dimensional material models of molecules were used throughout the 19th century, either functioning as a mere representation or opening new epistemic horizons. In this paper, two case studies are examined: the 1875 models of van ‘t Hoff and the 1890 models of Sachse. What is unique in these two case studies is that both models were not only folded, but were also conceptualized mathematically. When viewed in light of the chemical research of that period not only (...)
    Download  
     
    Export citation  
     
    Bookmark  
  16. Unification Strategies in Cognitive Science.Marcin Miłkowski - 2016 - Studies in Logic, Grammar and Rhetoric 48 (1):13–33.
    Cognitive science is an interdisciplinary conglomerate of various research fields and disciplines, which increases the risk of fragmentation of cognitive theories. However, while most previous work has focused on theoretical integration, some kinds of integration may turn out to be monstrous, or result in superficially lumped and unrelated bodies of knowledge. In this paper, I distinguish theoretical integration from theoretical unification, and propose some analyses of theoretical unification dimensions. Moreover, two research strategies that are supposed to lead to unification (...)
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  17. Layers of Models in Computer Simulations.Thomas Boyer-Kassem - 2014 - International Studies in the Philosophy of Science 28 (4):417-436.
    I discuss here the definition of computer simulations, and more specifically the views of Humphreys, who considers that an object is simulated when a computer provides a solution to a computational model, which in turn represents the object of interest. I argue that Humphreys's concepts are not able to analyse fully successfully a case of contemporary simulation in physics, which is more complex than the examples considered so far in the philosophical literature. I therefore modify Humphreys's definition of simulation. I (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  18. The Role of Epistemological Models in Veronese's and Bettazzi's Theory of Magnitudes.Paola Cantù - 2010 - In M. D'Agostino, G. Giorello, F. Laudisa, T. Pievani & C. Sinigaglia (eds.), New Essays in Logic and Philosophy of Science. College Publications.
    The philosophy of mathematics has been accused of paying insufficient attention to mathematical practice: one way to cope with the problem, the one we will follow in this paper on extensive magnitudes, is to combine the `history of ideas' and the `philosophy of models' in a logical and epistemological perspective. The history of ideas allows the reconstruction of the theory of extensive magnitudes as a theory of ordered algebraic structures; the philosophy of models allows an investigation into the (...)
    Download  
    Translate
     
     
    Export citation  
     
    Bookmark  
  19.  44
    Granger and Science as Network of Models.Sergio Volodia Marcello Cremaschi - 1987 - Manuscrito 10 (2):111-136.
    The discovery of the role of models in science by Granger parallels the analogous discovery made by Mary Hesse and Marx Wartofsky. The role models are granted highlights the linguistic dimension of science, resulting in a 'softening' of Bachelard's rationalistic epistemology without lapsing into relativism. A 'linguistic' theory of metaphor, as contrasted with Bachelard's 'psychological' theory, is basic to Granger's account of models. A final paragraph discusses to what extent Granger's 'mature' theory of models (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  20. Lightning in a Bottle: Complexity, Chaos, and Computation in Climate Science.Jon Lawhead - 2014 - Dissertation, Columbia University
    Climatology is a paradigmatic complex systems science. Understanding the global climate involves tackling problems in physics, chemistry, economics, and many other disciplines. I argue that complex systems like the global climate are characterized by certain dynamical features that explain how those systems change over time. A complex system's dynamics are shaped by the interaction of many different components operating at many different temporal and spatial scales. Examining the multidisciplinary and holistic methods of climatology can help us better understand the (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  21. Interdisciplinarity and Insularity in the Diffusion of Knowledge: An Analysis of Disciplinary Boundaries Between Philosophy of Science and the Sciences.John McLevey, Alexander V. Graham, Reid McIlroy-Young, Pierson Browne & Kathryn Plaisance - 2018 - Scientometrics 1 (117):331-349.
    Two fundamentally different perspectives on knowledge diffusion dominate debates about academic disciplines. On the one hand, critics of disciplinary research and education have argued that disciplines are isolated silos, within which specialists pursue inward-looking and increasingly narrow research agendas. On the other hand, critics of the silo argument have demonstrated that researchers constantly import and export ideas across disciplinary boundaries. These perspectives have different implications for how knowledge diffuses, how intellectuals gain and lose status within their disciplines, and how intellectual (...)
    Download  
     
    Export citation  
     
    Bookmark  
  22. The Nature and Function of Content in Computational Models.Frances Egan - 2018 - In Mark Sprevak & Matteo Colombo (eds.), The Routledge Handbook of the Computational Mind. Routledge.
    Much of computational cognitive science construes human cognitive capacities as representational capacities, or as involving representation in some way. Computational theories of vision, for example, typically posit structures that represent edges in the distal scene. Neurons are often said to represent elements of their receptive fields. Despite the ubiquity of representational talk in computational theorizing there is surprisingly little consensus about how such claims are to be understood. The point of this chapter is to sketch an account of the (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  23. Semantic Approaches in the Philosophy of Science.Emma B. Ruttkamp - 1999 - South African Journal of Philosophy 18 (2):100-148.
    In this article I give an overview of some recent work in philosophy of science dedicated to analysing the scientific process in terms of (conceptual) mathematical models of theories and the various semantic relations between such models, scientific theories, and aspects of reality. In current philosophy of science, the most interesting questions centre around the ways in which writers distinguish between theories and the mathematical structures that interpret them and in which they are true, i.e. between (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  24. On the Role of Newtonian Analogies in Eighteenth-Century Life Science:Vitalism and Provisionally Inexplicable Explicative Devices.Charles T. Wolfe - 2014 - In Zvi Biener & Eric Schliesser (eds.), Newton and Empiricism. Oxford University Press. pp. 223-261.
    Newton’s impact on Enlightenment natural philosophy has been studied at great length, in its experimental, methodological and ideological ramifications. One aspect that has received fairly little attention is the role Newtonian “analogies” played in the formulation of new conceptual schemes in physiology, medicine, and life science as a whole. So-called ‘medical Newtonians’ like Pitcairne and Keill have been studied; but they were engaged in a more literal project of directly transposing, or seeking to transpose, Newtonian laws into quantitative (...) of the body. I am interested here in something different: neither the metaphysical reading of Newton, nor direct empirical transpositions, but rather, a more heuristic, empiricist construction of Newtonian analogies. Figures such as Haller, Barthez, and Blumenbach constructed analogies between the method of celestial mechanics and the method of physiology. In celestial mechanics, they held, an unknown entity such as gravity is posited and used to mathematically link sets of determinate physical phenomena (e.g., the phases of the moon and tides). This process allows one to remain agnostic about the ontological status of the unknown entity, as long as the two linked sets of phenomena are represented adequately. Haller et. al. held that the Newtonian physician and physiologist can similarly posit an unknown called ‘life’ and use it to link various other phenomena, from digestion to sensation and the functioning of the glands. These phenomena consequently appear as interconnected, goal-oriented processes which do not exist either in an inanimate mechanism or in a corpse. In keeping with the empiricist roots of the analogy, however, no ontological claims are made about the nature of this vital principle, and no attempts are made to directly causally connect such a principle and observable phenomena. The role of the “Newtonian analogy” thus brings together diverse schools of thought, and cuts across a surprising variety of programs, models and practices in natural philosophy. (shrink)
    Download  
     
    Export citation  
     
    Bookmark   7 citations  
  25. Tools or Toys? On Specific Challenges for Modeling and the Epistemology of Models and Computer Simulations in the Social Sciences.Eckhart Arnold - manuscript
    Mathematical models are a well established tool in most natural sciences. Although models have been neglected by the philosophy of science for a long time, their epistemological status as a link between theory and reality is now fairly well understood. However, regarding the epistemological status of mathematical models in the social sciences, there still exists a considerable unclarity. In my paper I argue that this results from specific challenges that mathematical models and especially computer simulations (...)
    Download  
     
    Export citation  
     
    Bookmark  
  26. Achieving Cumulative Progress In Understanding Crime: Some Insights From the Philosophy of Science.Jacqueline Anne Sullivan - forthcoming - Psychology, Crime and Law.
    Crime is a serious social problem, but its causes are not exclusively social. There is growing consensus that explaining and preventing it requires interdisciplinary research efforts. Indeed, the landscape of contemporary criminology includes a variety of theoretical models that incorporate psychological, biological and sociological factors. These multi-disciplinary approaches, however, have yet to radically advance scientific understandings of crime and shed light on how to manage it. In this paper, using conceptual tools on offer in the philosophy of science (...)
    Download  
    Translate
     
     
    Export citation  
     
    Bookmark  
  27. The Self in the Age of Cognitive Science: Decoupling the Self From the Personal Level.Robert D. Rupert - 2018 - Philosophic Exchange 2018.
    Philosophers of mind commonly draw a distinction between the personal level – the distinctive realm of conscious experience and reasoned deliberation – and the subpersonal level, the domain of mindless mechanism and brute cause and effect. Moreover, they tend to view cognitive science through the lens of this distinction. Facts about the personal level are given a priori, by introspection, or by common sense; the job of cognitive science is merely to investigate the mechanistic basis of these facts. (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  28.  91
    AISC 17 Talk: The Explanatory Problems of Deep Learning in Artificial Intelligence and Computational Cognitive Science: Two Possible Research Agendas.Antonio Lieto - 2018 - In Proceedings of AISC 2017.
    Endowing artificial systems with explanatory capacities about the reasons guiding their decisions, represents a crucial challenge and research objective in the current fields of Artificial Intelligence (AI) and Computational Cognitive Science [Langley et al., 2017]. Current mainstream AI systems, in fact, despite the enormous progresses reached in specific tasks, mostly fail to provide a transparent account of the reasons determining their behavior (both in cases of a successful or unsuccessful output). This is due to the fact that the classical (...)
    Download  
     
    Export citation  
     
    Bookmark  
  29. Jung in Dialogue with Freud and Patañjali: Instinct, Affective Neuroscience, and the Reconciliation of Science and Religious Experience.Leanne Whitney - 2017 - Cosmos and History 13 (2):298-312.
    For both Jung and Patañjali our human desire to understand “God” is as real as any other instinct. Jung’s and Patañjali’s models further align in their emphasis on the teleological directedness of the psyche, and their aim at reconciling science and religious experience. As an atheist, Freud was in disagreement, but all three scholars align in their emphasis on the study of affect as an empirical means of entering into the psyche. For Patañjali, the nadir of affect lays (...)
    Download  
     
    Export citation  
     
    Bookmark  
  30. Counterpossibles in Science: The Case of Relative Computability.Matthias Jenny - 2018 - Noûs 52 (3):530-560.
    I develop a theory of counterfactuals about relative computability, i.e. counterfactuals such as 'If the validity problem were algorithmically decidable, then the halting problem would also be algorithmically decidable,' which is true, and 'If the validity problem were algorithmically decidable, then arithmetical truth would also be algorithmically decidable,' which is false. These counterfactuals are counterpossibles, i.e. they have metaphysically impossible antecedents. They thus pose a challenge to the orthodoxy about counterfactuals, which would treat them as uniformly true. What’s more, I (...)
    Download  
     
    Export citation  
     
    Bookmark   11 citations  
  31. The Tool Box of Science: Tools for the Building of Models with a Superconductivity Example.Nancy Cartwright, Towfic Shomar & Mauricio Suárez - 1995 - Poznan Studies in the Philosophy of the Sciences and the Humanities 44:137-149.
    We call for a new philosophical conception of models in physics. Some standard conceptions take models to be useful approximations to theorems, that are the chief means to test theories. Hence the heuristics of model building is dictated by the requirements and practice of theory-testing. In this paper we argue that a theory-driven view of models can not account for common procedures used by scientists to model phenomena. We illustrate this thesis with a case study: the construction (...)
    Download  
     
    Export citation  
     
    Bookmark   57 citations  
  32. Mentalism Versus Behaviourism in Economics: A Philosophy-of-Science Perspective.Franz Dietrich & Christian List - 2016 - Economics and Philosophy 32 (2):249-281.
    Behaviourism is the view that preferences, beliefs, and other mental states in social-scientific theories are nothing but constructs re-describing people's behaviour. Mentalism is the view that they capture real phenomena, on a par with the unobservables in science, such as electrons and electromagnetic fields. While behaviourism has gone out of fashion in psychology, it remains influential in economics, especially in ‘revealed preference’ theory. We defend mentalism in economics, construed as a positive science, and show that it fits best (...)
    Download  
     
    Export citation  
     
    Bookmark   21 citations  
  33.  41
    Underdetermination and Models in Biology.Petr Jedlička - 2017 - Teorie Vědy / Theory of Science 39 (2):167-186.
    Since the early 20th century underdetermination has been one of the most contentious problems in the philosophy of science. In this article I relate the underdetermination problem to models in biology and defend two main lines of argument: First, the use of models in this discipline lends strong support to the underdetermination thesis. Second, models and theories in biology are not determined strictly by the logic of representation of the studied phenomena, but also by other constraints (...)
    Download  
     
    Export citation  
     
    Bookmark  
  34. Dynamic Models in Imperative Logic (Imperatives in Action: Changing Minds and Norms).Berislav Žarnić - 2011 - In Anna Brozek, Jacek Jadacki & Berislav Žarnić (eds.), Theory of Imperatives from Different Points of View (2). Wydawnictwo Naukowe Semper.
    The theory of imperatives is philosophically relevant since in building it — some of the long standing problems need to be addressed, and presumably some new ones are waiting to be discovered. The relevance of the theory of imperatives for philosophical research is remarkable, but usually recognized only within the field of practical philosophy. Nevertheless, the emphasis can be put on problems of theoretical philosophy. Proper understanding of imperatives is likely to raise doubts about some of our deeply entrenched and (...)
    Download  
    Translate
     
     
    Export citation  
     
    Bookmark   2 citations  
  35. Illegitimate Values, Confirmation Bias, and Mandevillian Cognition in Science.Uwe Peters - forthcoming - British Journal for the Philosophy of Science:axy079.
    In the philosophy of science, it is a common proposal that values are illegitimate in science and should be counteracted whenever they drive inquiry to the confirmation of predetermined conclusions. Drawing on recent cognitive scientific research on human reasoning and confirmation bias, I argue that this view should be rejected. Advocates of it have overlooked that values that drive inquiry to the confirmation of predetermined conclusions can contribute to the reliability of scientific inquiry at the group level even (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  36.  78
    Belief Revision in Science: Informational Economy and Paraconsistency.Daniel Coimbra - 2017 - Contemplação 1 (15):19-38.
    In the present paper, our objective is to examine the application of belief revision models to scientific rationality. We begin by considering the standard model AGM, and along the way a number of problems surface that make it seem inadequate for this specific application. After considering three different heuristics of informational economy that seem fit for science, we consider some possible adaptations for it and argue informally that, overall, some paraconsistent models seem to better satisfy these principles, (...)
    Download  
     
    Export citation  
     
    Bookmark  
  37. Democratic Values: A Better Foundation for Public Trust in Science.S. Andrew Schroeder - 2018 - British Journal for the Philosophy of Science:axz023.
    There is a growing consensus among philosophers of science that core parts of the scientific process involve non-epistemic values. This undermines the traditional foundation for public trust in science. In this article I consider two proposals for justifying public trust in value-laden science. According to the first, scientists can promote trust by being transparent about their value choices. On the second, trust requires that the values of a scientist align with the values of an individual member of (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  38. Real Kinds in Real Time: On Responsible Social Modeling.Theodore Bach - 2019 - The Monist 102 (2):236-258.
    There is broad agreement among social researchers and social ontologists that the project of dividing humans into social kinds should be guided by at least two methodological commitments. First, a commitment to what best serves moral and political interests, and second, a commitment to describing accurately the causal structures of social reality. However, researchers have not sufficiently analyzed how these two commitments interact and constrain one another. In the absence of that analysis, several confusions have set in, threatening to undermine (...)
    Download  
     
    Export citation  
     
    Bookmark  
  39. From Tapestry to Loom: Broadening the Perspective on Values in Science.Heather Douglas - 2018 - Philosophy, Theory, and Practice in Biology 10 (8).
    After raising some minor philosophical points about Kevin Elliott’s A Tapestry of Values (2017), I argue that we should expand on the themes raised in the book and that philosophers of science need to pay as much attention to the loom of science (i.e., the institutional structures which guide the pursuit of science) as the tapestry of science. The loom of science includes such institutional aspects as patents, funding sources, and evaluation regimes that shape how (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  40.  95
    The Error Is in the Gap: Synthesizing Accounts for Societal Values in Science.Christopher ChoGlueck - 2018 - Philosophy of Science 85 (4):704-725.
    Kevin Elliott and others separate two common arguments for the legitimacy of societal values in scientific reasoning as the gap and the error arguments. This article poses two questions: How are these two arguments related, and what can we learn from their interrelation? I contend that we can better understand the error argument as nested within the gap because the error is a limited case of the gap with narrower features. Furthermore, this nestedness provides philosophers with conceptual tools for analyzing (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  41. Modeling Measurement: Error and Uncertainty.Alessandro Giordani & Luca Mari - 2014 - In Marcel Boumans, Giora Hon & Arthur Petersen (eds.), Error and Uncertainty in Scientific Practice. Pickering & Chatto. pp. 79-96.
    In the last few decades the role played by models and modeling activities has become a central topic in the scientific enterprise. In particular, it has been highlighted both that the development of models constitutes a crucial step for understanding the world and that the developed models operate as mediators between theories and the world. Such perspective is exploited here to cope with the issue as to whether error-based and uncertainty-based modeling of measurement are incompatible, and thus (...)
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  42. Should Causal Models Always Be Markovian? The Case of Multi-Causal Forks in Medicine.Donald Gillies & Aidan Sudbury - 2013 - European Journal for Philosophy of Science 3 (3):275-308.
    The development of causal modelling since the 1950s has been accompanied by a number of controversies, the most striking of which concerns the Markov condition. Reichenbach's conjunctive forks did satisfy the Markov condition, while Salmon's interactive forks did not. Subsequently some experts in the field have argued that adequate causal models should always satisfy the Markov condition, while others have claimed that non-Markovian causal models are needed in some cases. This paper argues for the second position by considering (...)
    Download  
     
    Export citation  
     
    Bookmark  
  43. Embodiment, Interaction, and Experience: Toward a Comprehensive Model in Addiction Science.Nicholas Zautra - 2015 - Philosophy of Science 82 (5):1023-1034.
    Current theories of addiction try to explain what addiction is, who experiences it, why it occurs, and how it develops and persists. In this article, I explain why none of these theories can be accepted as a comprehensive model. I argue that current models fail to account for differences in embodiment, interaction processes, and the experience of addiction. To redress these limiting factors, I design a proposal for an enactive account of addiction that follows the enactive model of autism (...)
    Download  
     
    Export citation  
     
    Bookmark  
  44. Values in Science: Assessing the Case for Mixed Claims.Uwe Peters - forthcoming - Inquiry: An Interdisciplinary Journal of Philosophy.
    Social and medical scientists frequently produce empirical generalizations that involve concepts partly defined by value judgments. These generalizations, which have been called ‘mixed claims’, raise interesting questions. Does the presence of them in science imply that science is value-laden? Is the value-ladenness of mixed claims special compared to other kinds of value-ladenness of science? Do we lose epistemically if we reformulate these claims as conditional statements? And if we want to allow mixed claims in science, do (...)
    Download  
     
    Export citation  
     
    Bookmark  
  45. Constitutive Elements in Science Beyond Physics: The Case of the Hardy–Weinberg Principle.Michele Luchetti - forthcoming - Synthese.
    In this paper, I present a new framework supporting the claim that some elements in science play a constitutive function, with the aim of overcoming some limitations of Friedman's (2001) account. More precisely, I focus on what I consider to be the gradualism implicit in Friedman's interpretation of the constitutive a priori, that is, the fact that it seems to allow for degrees of 'constitutivity'. I tease out such gradualism by showing that the constitutive character Friedman aims to track (...)
    Download  
     
    Export citation  
     
    Bookmark  
  46. Beyond Falsifiability: Normal Science in a Multiverse.Sean M. Carroll - forthcoming - In Richard Dawid, Radin Dardashti & Karim Thebault (eds.), Epistemology of Fundamental Physics: Why Trust a Theory? Cambridge, UK: Cambridge University Press.
    Cosmological models that invoke a multiverse - a collection of unobservable regions of space where conditions are very different from the region around us - are controversial, on the grounds that unobservable phenomena shouldn't play a crucial role in legitimate scientific theories. I argue that the way we evaluate multiverse models is precisely the same as the way we evaluate any other models, on the basis of abduction, Bayesian inference, and empirical success. There is no scientifically respectable (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  47.  75
    Inference Belief and Interpretation in Science.Avijit Lahiri - manuscript
    This monograph is an in-depth and engaging discourse on the deeply cognitive roots of human scientific quest. The process of making scientific inferences is continuous with the day-to-day inferential activity of individuals, and is predominantly inductive in nature. Inductive inference, which is fallible, exploratory, and open-ended, is of essential relevance in our incessant efforts at making sense of a complex and uncertain world around us, and covers a vast range of cognitive activities, among which scientific exploration constitutes the pinnacle. Inductive (...)
    Download  
     
    Export citation  
     
    Bookmark  
  48.  30
    Values and Credibility in Science Communication.Janet Michaud & John Turri - 2018 - Logos and Episteme 9 (2):199-214.
    Understanding science requires appreciating the values it presupposes and its social context. Both the values that scientists hold and their social context can affect scientific communication. Philosophers of science have recently begun studying scientific communication, especially as it relates to public policy. Some have proposed “guiding principles for communicating scientific findings” to promote trust and objectivity. This paper contributes to this line of research in a novel way using behavioural experimentation. We report results from three experiments testing judgments (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  49. Communism and the Incentive to Share in Science.Remco Heesen - 2017 - Philosophy of Science 84 (4):698-716.
    The communist norm requires that scientists widely share the results of their work. Where did this norm come from, and how does it persist? Michael Strevens provides a partial answer to these questions by showing that scientists should be willing to sign a social contract that mandates sharing. However, he also argues that it is not in an individual credit-maximizing scientist's interest to follow this norm. I argue against Strevens that individual scientists can rationally conform to the communist norm, even (...)
    Download  
     
    Export citation  
     
    Bookmark   14 citations  
  50.  26
    The Toys of Organic Chemistry: Material Manipulatives and Inductive Reasoning.Kate McKinney Maddalena - 2013 - Teorie Vědy / Theory of Science 35 (2):227-248.
    Chemical visualizations and models are special kinds of situated, inductive arguments. In this paper, I examine several historical case studies—an archive of images from museums, special collections, and popular magazines—as examples of emergent practices of physical modeling as theoretical play which became the basis for molecular biology and structural chemistry. Specifically, I trace a legacy of visualization tools that starts with Archibald Scott Cooper and Friedrich Kekulé in the late 1800s, crystallizes as material manipulatives in Kekulé’s student Jacobus Henricus (...)
    Download  
     
    Export citation  
     
    Bookmark  
1 — 50 / 1000