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Computer simulations and the trading zone

In Peter Louis Galison & David J. Stump (eds.), The Disunity of science: boundaries, contexts, and power. Stanford, Calif.: Stanford University Press. pp. 118--157 (1996)

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  1. Computer Simulations in Science and Engineering. Concept, Practices, Perspectives.Juan Manuel Durán - 2018 - Springer.
    This book addresses key conceptual issues relating to the modern scientific and engineering use of computer simulations. It analyses a broad set of questions, from the nature of computer simulations to their epistemological power, including the many scientific, social and ethics implications of using computer simulations. The book is written in an easily accessible narrative, one that weaves together philosophical questions and scientific technicalities. It will thus appeal equally to all academic scientists, engineers, and researchers in industry interested in questions (...)
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  • Simulated experiments: Methodology for a virtual world.Winsberg Eric - 2003 - Philosophy of Science 70 (1):105-125.
    This paper examines the relationship between simulation and experiment. Many discussions of simulation, and indeed the term "numerical experiments," invoke a strong metaphor of experimentation. On the other hand, many simulations begin as attempts to apply scientific theories. This has lead many to characterize simulation as lying between theory and experiment. The aim of the paper is to try to reconcile these two points of viewto understand what methodological and epistemological features simulation has in common with experimentation, while at the (...)
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  • (1 other version)Scientific Pluralism.Stephen H. Kellert, Helen E. Longino & C. Kenneth Waters (eds.) - 1956 - Univ of Minnesota Press.
    Scientific pluralism is an issue at the forefront of philosophy of science. This landmark work addresses the question, Can pluralism be advanced as a general, philosophical interpretation of science?
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  • The philosophy of simulation: hot new issues or same old stew?Roman Frigg & Julian Reiss - 2008 - Synthese 169 (3):593-613.
    Computer simulations are an exciting tool that plays important roles in many scientific disciplines. This has attracted the attention of a number of philosophers of science. The main tenor in this literature is that computer simulations not only constitute interesting and powerful new science , but that they also raise a host of new philosophical issues. The protagonists in this debate claim no less than that simulations call into question our philosophical understanding of scientific ontology, the epistemology and semantics of (...)
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  • Epistemic dependence in interdisciplinary groups.Hanne Andersen & Susann Wagenknecht - 2013 - Synthese 190 (11):1881-1898.
    In interdisciplinary research scientists have to share and integrate knowledge between people and across disciplinary boundaries. An important issue for philosophy of science is to understand how scientists who work in these kinds of environments exchange knowledge and develop new concepts and theories across diverging fields. There is a substantial literature within social epistemology that discusses the social aspects of scientific knowledge, but so far few attempts have been made to apply these resources to the analysis of interdisciplinary science. Further, (...)
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  • How can computer simulations produce new knowledge?Claus Beisbart - 2012 - European Journal for Philosophy of Science 2 (3):395-434.
    It is often claimed that scientists can obtain new knowledge about nature by running computer simulations. How is this possible? I answer this question by arguing that computer simulations are arguments. This view parallels Norton’s argument view about thought experiments. I show that computer simulations can be reconstructed as arguments that fully capture the epistemic power of the simulations. Assuming the extended mind hypothesis, I furthermore argue that running the computer simulation is to execute the reconstructing argument. I discuss some (...)
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  • Explaining ambiguity in scientific language.Beckett Sterner - 2022 - Synthese 200 (5):1-27.
    The idea that ambiguity can be productive in data science remains controversial. Efforts to make scientific publications and data intelligible to computers generally assume that accommodating multiple meanings for words, known as polysemy, undermines reasoning and communication. This assumption has nonetheless been contested by historians, philosophers, and social scientists, who have applied qualitative research methods to demonstrate the generative and strategic value of polysemy. Recent quantitative results from linguistics have also shown how polysemy can actually improve the efficiency of human (...)
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  • Rethinking unity as a "working hypothesis" for philosophy: How archaeologists exploit the disunities of science.Alison Wylie - 1999 - Perspectives on Science 7 (3):293-317.
    As a working hypothesis for philosophy of science, the unity of science thesis has been decisively challenged in all its standard formulations; it cannot be assumed that the sciences presuppose an orderly world, that they are united by the goal of systematically describing and explaining this order, or that they rely on distinctively scientific methodologies which, properly applied, produce domain-specific results that converge on a single coherent and comprehensive system of knowledge. I first delineate the scope of arguments against global (...)
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  • Technology and Epistemic Possibility.Isaac Record - 2013 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie (2):1-18.
    My aim in this paper is to give a philosophical analysis of the relationship between contingently available technology and the knowledge that it makes possible. My concern is with what specific subjects can know in practice, given their particular conditions, especially available technology, rather than what can be known “in principle” by a hypothetical entity like Laplace’s Demon. The argument has two parts. In the first, I’ll construct a novel account of epistemic possibility that incorporates two pragmatic conditions: responsibility and (...)
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  • Science and Philosophy: A Love–Hate Relationship.Sebastian De Haro - 2020 - Foundations of Science 25 (2):297-314.
    In this paper I review the problematic relationship between science and philosophy; in particular, I will address the question of whether science needs philosophy, and I will offer some positive perspectives that should be helpful in developing a synergetic relationship between the two. I will review three lines of reasoning often employed in arguing that philosophy is useless for science: philosophy’s death diagnosis ; the historic-agnostic argument/challenge “show me examples where philosophy has been useful for science, for I don’t know (...)
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  • The philosophy of simulation: hot new issues or same old stew?Roman Frigg & Julian Reiss - 2011 - Synthese 180 (1):77-77.
    Computer simulations are an exciting tool that plays important roles in many scientific disciplines. This has attracted the attention of a number of philosophers of science. The main tenor in this literature is that computer simulations not only constitute interesting and powerful new science, but that they also raise a host of new philosophical issues. The protagonists in this debate claim no less than that simulations call into question our philosophical understanding of scientific ontology, the epistemology and semantics of models (...)
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  • Why computer simulations are not inferences, and in what sense they are experiments.Florian J. Boge - 2018 - European Journal for Philosophy of Science 9 (1):1-30.
    The question of where, between theory and experiment, computer simulations (CSs) locate on the methodological map is one of the central questions in the epistemology of simulation (cf. Saam Journal for General Philosophy of Science, 48, 293–309, 2017). The two extremes on the map have them either be a kind of experiment in their own right (e.g. Barberousse et al. Synthese, 169, 557–574, 2009; Morgan 2002, 2003, Journal of Economic Methodology, 12(2), 317–329, 2005; Morrison Philosophical Studies, 143, 33–57, 2009; Morrison (...)
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  • Woodger, positivism, and the evolutionary synthesis.Joe Cain - 2000 - Biology and Philosophy 15 (4):535-551.
    In Unifying Biology, Smocovitis offers a series of claimsregarding the relationship between key actors in the synthesisperiod of evolutionary studies and positivism, especially claimsentailing Joseph Henry Woodger and the Unity of Science Movement.This commentary examines Woodger''s possible relevance to key synthesis actors and challenges Smocovitis'' arguments for theexplanatory relevance of logical positivism, and positivism moregenerally, to synthesis history. Under scrutiny, these arguments areshort on evidence and subject to substantial conceptual confusion.Though plausible, Smocovitis'' minimal interpretation – that somegeneralised form of Comtean (...)
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  • Experimenting on Theories.Deborah Dowling - 1999 - Science in Context 12 (2):261-273.
    The ArgumentThis paper sets out a framework for understanding how the scientific community constructs computer simulation as an epistemically and pragmatically useful methodology. The framework is based on comparisons between simulation and the loosely-defined categories of “theoretical work” and “experimental work.” Within that framework, the epistemological adequacy of simulation arises from its role as a mathematical manipulation of a complex, abstract theoretical model. To establish that adequacy demands a detailed “theoretical” grasp of the internal structure of the computer program. Simultaneously, (...)
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  • What is a Simulation Model?Juan M. Durán - 2020 - Minds and Machines 30 (3):301-323.
    Many philosophical accounts of scientific models fail to distinguish between a simulation model and other forms of models. This failure is unfortunate because there are important differences pertaining to their methodology and epistemology that favor their philosophical understanding. The core claim presented here is that simulation models are rich and complex units of analysis in their own right, that they depart from known forms of scientific models in significant ways, and that a proper understanding of the type of model simulations (...)
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  • Computing the perfect model: Why do economists Shun simulation?Aki Lehtinen & Jaakko Kuorikoski - 2007 - Philosophy of Science 74 (3):304-329.
    Like other mathematically intensive sciences, economics is becoming increasingly computerized. Despite the extent of the computation, however, there is very little true simulation. Simple computation is a form of theory articulation, whereas true simulation is analogous to an experimental procedure. Successful computation is faithful to an underlying mathematical model, whereas successful simulation directly mimics a process or a system. The computer is seen as a legitimate tool in economics only when traditional analytical solutions cannot be derived, i.e., only as a (...)
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  • Why did Feyerabend Defend Astrology? Integrity, Virtue, and the Authority of Science.Ian James Kidd - 2016 - Social Epistemology 30 (4):464-482.
    This paper explores the relationship between epistemic integrity, virtue, and authority by offering a virtue epistemological reading of the defences of non-scientific beliefs, practices, and traditions in the writings of Paul Feyerabend. I argue that there was a robust epistemic rationale for those defences and that it can inform contemporary reflection on the epistemic authority of the sciences. Two common explanations of the purpose of those defences are rejected as lacking textual support. A third “pluralist” reading is judged more persuasive, (...)
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  • Introduction: Interdisciplinary model exchanges.Till Grüne-Yanoff & Uskali Mäki - 2014 - Studies in History and Philosophy of Science Part A 48:52-59.
    The five studies of this special section investigate the role of models and similar representational tools in interdisciplinarity. These studies were all written by philosophers of science, who focused on interdisciplinary episodes between disciplines and sub-disciplines ranging from physics, chemistry and biology to the computational sciences, sociology and economics. The reasons we present these divergent studies in a collective form are three. First, we want to establish model-exchange as a kind of interdisciplinary event. The five case studies, which are summarized (...)
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  • What is a Computer Simulation? A Review of a Passionate Debate.Nicole J. Saam - 2017 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 48 (2):293-309.
    Where should computer simulations be located on the ‘usual methodological map’ which distinguishes experiment from theory? Specifically, do simulations ultimately qualify as experiments or as thought experiments? Ever since Galison raised that question, a passionate debate has developed, pushing many issues to the forefront of discussions concerning the epistemology and methodology of computer simulation. This review article illuminates the positions in that debate, evaluates the discourse and gives an outlook on questions that have not yet been addressed.
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  • Unificatory Explanation.Marco J. Nathan - 2017 - British Journal for the Philosophy of Science 68 (1).
    Philosophers have traditionally addressed the issue of scientific unification in terms of theoretical reduction. Reductive models, however, cannot explain the occurrence of unification in areas of science where successful reductions are hard to find. The goal of this essay is to analyse a concrete example of integration in biology—the developmental synthesis—and to generalize it into a model of scientific unification, according to which two fields are in the process of being unified when they become explanatorily relevant to each other. I (...)
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  • Boon and Bane: On the Role of Adjustable Parameters in Simulation Models.Hans Hasse & Johannes Lenhard - 2017 - In Martin Carrier & Johannes Lenhard (eds.), Mathematics as a Tool: Tracing New Roles of Mathematics in the Sciences. Springer Verlag.
    We claim that adjustable parameters play a crucial role in building and applying simulation models. We analyze that role and illustrate our findings using examples from equations of state in thermodynamics. In building simulation models, two types of experiments, namely, simulation and classical experiments, interact in a feedback loop, in which model parameters are adjusted. A critical discussion of how adjustable parameters function shows that they are boon and bane of simulation. They help to enlarge the scope of simulation far (...)
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  • Philosophy of and as interdisciplinarity.Michael Hg Hoffmann, Jan C. Schmidt & Nancy J. Nersessian - 2013 - Synthese 190 (11):1857-1864.
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  • Philosophy of and as interdisciplinarity.Michael H. G. Hoffmann, Jan C. Schmidt & Nancy J. Nersessian - 2013 - Synthese 190 (11):1857-1864.
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  • Validation and variability: Dual challenges on the path from systems biology to systems medicine.Annamaria Carusi - 2014 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 48:28-37.
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  • Why It Is Time To Move Beyond Nagelian Reduction.Marie I. Kaiser - 2012 - In D. Dieks, S. Hartmann, T. Uebel & M. Weber (eds.), Probabilities, Laws and Structure. Springer. pp. 255-272.
    In this paper I argue that it is finally time to move beyond the Nagelian framework and to break new ground in thinking about epistemic reduction in biology. I will do so, not by simply repeating all the old objections that have been raised against Ernest Nagel’s classical model of theory reduction. Rather, I grant that a proponent of Nagel’s approach can handle several of these problems but that, nevertheless, Nagel’s general way of thinking about epistemic reduction in terms of (...)
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  • Complex Systems, Modelling and Simulation.Sam Schweber & Matthias Wächter - 2000 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 31 (4):583-609.
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  • Connections between simulations and observation in climate computer modeling. Scientist’s practices and “bottom-up epistemology” lessons.Hélène Guillemot - 2010 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 41 (3):242-252.
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  • Simulation Methods for an Abductive System in Science.Tom Addis, Jan Townsend Addis, Dave Billinge, David Gooding & Bart-Floris Visscher - 2008 - Foundations of Science 13 (1):37-52.
    We argue that abduction does not work in isolation from other inference mechanisms and illustrate this through an inference scheme designed to evaluate multiple hypotheses. We use game theory to relate the abductive system to actions that produce new information. To enable evaluation of the implications of this approach we have implemented the procedures used to calculate the impact of new information in a computer model. Experiments with this model display a number of features of collective belief-revision leading to consensus-formation, (...)
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  • A Formal Framework for Computer Simulations: Surveying the Historical Record and Finding Their Philosophical Roots.Juan M. Durán - 2019 - Philosophy and Technology 34 (1):105-127.
    A chronicled approach to the notion of computer simulations shows that there are two predominant interpretations in the specialized literature. According to the first interpretation, computer simulations are techniques for finding the set of solutions to a mathematical model. I call this first interpretation the problem-solving technique viewpoint. In its second interpretation, computer simulations are considered to describe patterns of behavior of a target system. I call this second interpretation the description of patterns of behavior viewpoint of computer simulations. This (...)
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  • Computational Models of Emergent Properties.John Symons - 2008 - Minds and Machines 18 (4):475-491.
    Computational modeling plays an increasingly important explanatory role in cases where we investigate systems or problems that exceed our native epistemic capacities. One clear case where technological enhancement is indispensable involves the study of complex systems.1 However, even in contexts where the number of parameters and interactions that define a problem is small, simple systems sometimes exhibit non-linear features which computational models can illustrate and track. In recent decades, computational models have been proposed as a way to assist us in (...)
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  • Feminist perspectives on science.Alison Wylie, Elizabeth Potter & Wenda K. Bauchspies - 2010 - Stanford Encyclopedia of Philosophy.
    **No longer the current version available on SEP; see revised version by Sharon Crasnow** -/- Feminists have a number of distinct interests in, and perspectives on, science. The tools of science have been a crucial resource for understanding the nature, impact, and prospects for changing gender-based forms of oppression; in this spirit, feminists actively draw on, and contribute to, the research programs of a wide range of sciences. At the same time, feminists have identified the sciences as a source as (...)
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  • Chemical translators: Pauling, Wheland and their strategies for teaching the theory of resonance.Buhm Soon Park - 1999 - British Journal for the History of Science 32 (1):21-46.
    The entry of resonance into chemistry, or the reception of the theory of resonance in the chemical community, has drawn considerable attention from historians of science. In particular, they have noted Pauling's ¯amboyant yet effective style of exposition, which became a factor in the early popularity of the resonance theory in comparison to the molecular orbital theory, another way of applying quantum mechanics to chemical problems.$ To be sure, the non-mathematical presentation of the resonance theory by Pauling and his collaborator, (...)
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  • Capturing the representational and the experimental in the modelling of artificial societies.David Anzola - 2021 - European Journal for Philosophy of Science 11 (3):1-29.
    Even though the philosophy of simulation is intended as a comprehensive reflection about the practice of computer simulation in contemporary science, its output has been disproportionately shaped by research on equation-based simulation in the physical and climate sciences. Hence, the particularities of alternative practices of computer simulation in other scientific domains are not sufficiently accounted for in the current philosophy of simulation literature. This article centres on agent-based social simulation, a relatively established type of simulation in the social sciences, to (...)
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  • Explaining simulated phenomena. A defense of the epistemic power of computer simulations.Juan M. Durán - 2013 - Dissertation, University of Stuttgart
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  • Computersimulationen: Modellierungen 2. Ordnung.Günter Küppers & Johannes Lenhard - 2005 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 36 (2):305-329.
    Es soll ein Beitrag zur epistemischen Charakterisierung von Computersimulationen als jenseits von Experiment und Theorie geleistet werden. Es wird argumentiert, dass die in der Simulationstechnik eingesetzten Verfahren nicht numerische Lösungen liefern, sondern deren Dynamik mittels generativer Mechanismen imitieren. Die Computersimulationen in der Klimatologie werden als systematisches wie historisches Fallbeispiel behandelt. Erst "Simulationsexperimente" gestatten es, mittels Modellen eine Dynamik zu imitieren, ohne deren Grundgleichungen zu "lösen". /// Computer simulations will be characterized in epistemic respect as a method between experiment and theory. (...)
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  • Computer Simulation, Experiment, and Novelty.Julie Jebeile - 2017 - International Studies in the Philosophy of Science 31 (4):379-395.
    It is often said that computer simulations generate new knowledge about the empirical world in the same way experiments do. My aim is to make sense of such a claim. I first show that the similarities between computer simulations and experiments do not allow them to generate new knowledge but invite the simulationist to interact with simulations in an experimental manner. I contend that, nevertheless, computer simulations and experiments yield new knowledge under the same epistemic circumstances, independently of any features (...)
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  • Computer Simulations Then and Now: an Introduction and Historical Reassessment.Arianna Borrelli & Janina Wellmann - 2019 - NTM Zeitschrift für Geschichte der Wissenschaften, Technik und Medizin 27 (4):407-417.
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  • Understanding and misunderstanding computer simulation: The case of atmospheric and climate science—An introduction.Matthias Heymann - 2010 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 41 (3):193-200.
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  • Chains of Reference in Computer Simulations.Franck Varenne - 2013 - FMSH Working Papers 51:1-32.
    This paper proposes an extensionalist analysis of computer simulations (CSs). It puts the emphasis not on languages nor on models, but on symbols, on their extensions, and on their various ways of referring. It shows that chains of reference of symbols in CSs are multiple and of different kinds. As they are distinct and diverse, these chains enable different kinds of remoteness of reference and different kinds of validation for CSs. Although some methodological papers have already underlined the role of (...)
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  • A story of nimble knowledge production in an era of academic capitalism.Steve G. Hoffman - 2021 - Theory and Society 50 (4):541-575.
    A rise of academic capitalism over the past four decades has been well documented within many research-intensive universities. Largely missing, however, are in-depth studies of how particularly situated academic groups manage the uncertainties that come with intermittent and fickle commercial funding streams in their daily research practice and problem choice. To capture the strategies scientists adopt under these conditions, this article provides an ethnographically detailed (and true) story about how a single project in Artificial Intelligence grew over several years from (...)
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  • The hermeneutics of ecological simulation.Steven L. Peck - 2008 - Biology and Philosophy 23 (3):383-402.
    Computer simulation has become important in ecological modeling, but there have been few assessments on how complex simulation models differ from more traditional analytic models. In Part I of this paper, I review the challenges faced in complex ecological modeling and how models have been used to gain theoretical purchase for understanding natural systems. I compare the use of traditional analytic simulation models and point how that the two methods require different kinds of practical engagement. I examine a case study (...)
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  • Computer Image Processing: An Epistemological Aid in Scientific Investigation.Vincent Israel-Jost - 2016 - Perspectives on Science 24 (6):669-695.
    In many scientific fields, today’s practices of empirical enquiry rely heavily on the production of images that display the investigated phenomena. And while scientific images of phenomena have been important for a long time, what is striking now is that scientists have found ways to visualize such widely different types of phenomena. In the past twenty or thirty years, we have become accustomed to seeing images of galaxies, of cells, of the human brain but also of blood flow or of (...)
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  • Eric Winsberg y la epistemología de las simulaciones computacionales.Juan M. Durán - 2017 - Argumentos de Razón Técnica 20:xx-yy.
    En este trabajo presento un estudio sobre el estado del arte de la llamada ‘epistemología de las simulaciones computacionales’. En particular, me centro en los varios trabajos de Eric Winsberg quién es uno de los filósofos más fructíferos y sistemáticos en este tema. Además de analizar la obra de Winsberg, y basándome en sus trabajos y en el de otros filósofos, mostraré que hay buenas razones para pensar que la epistemología tradicional de la ciencia no es suficiente para el análisis (...)
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  • Sciences as Systems.David Alvargonzález - 2019 - Perspectives on Science 27 (6):839-860.
    This paper opens by distinguishing between the multiple concepts of system and the philosophical idea of system. It then goes on to discuss the differences between systems and other proximate ideas, such as whole, set, aggregate and structure. Subsequently, it proposes a definition of system, and then lays out three classifications of systems. When elaborating a general definition of system, the main challenge is finding a general criterion with which to characterize both technical systems built by men, and scientific systems (...)
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  • A Promethean Philosophy of External Technologies, Empiricism, & the Concept: Second-Order Cybernetics, Deep Learning, and Predictive Processing.Ekin Erkan - 2020 - Media Theory 4 (1):87-146.
    Beginning with a survey of the shortcoming of theories of organology/media-as-externalization of mind/body—a philosophical-anthropological tradition that stretches from Plato through Ernst Kapp and finds its contemporary proponent in Bernard Stiegler—I propose that the phenomenological treatment of media as an outpouching and extension of mind qua intentionality is not sufficient to counter the ̳black-box‘ mystification of today‘s deep learning‘s algorithms. Focusing on a close study of Simondon‘s On the Existence of Technical Objectsand Individuation, I argue that the process-philosophical work of Gilbert (...)
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  • A new disease of the intellect? Some reflections on the therapeutic value of Peter Winch’s philosophy for social and cultural studies of science.Michael Lynch - 2000 - History of the Human Sciences 13 (1):140-156.
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  • Brain in the Shell. Assessing the Stakes and the Transformative Potential of the Human Brain Project.Philipp Haueis & Jan Slaby - 2015 - In Philipp Haueis & Jan Slaby (eds.), Neuroscience and Critique. London: pp. 117–140.
    The “Human Brain Project” (HBP) is a large-scale European neuroscience and information communication technology (ICT) project that has been a matter of heated controversy since its inception. With its aim to simulate the entire human brain with the help of supercomputing technologies, the HBP plans to fundamentally change neuroscientific research practice, medical diagnosis, and eventually the use of computers itself. Its controversial nature and its potential impacts render the HBP a subject of crucial importance for critical studies of science and (...)
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  • Challenging Incommensurability: What We Can Learn from Ludwik Fleck for the Analysis of Configurational Innovation.Alexander Peine - 2011 - Minerva 49 (4):489-508.
    This paper argues that Ludwik Fleck’s concepts of thought collectives and proto-ideas are surprisingly topical to tackle some conceptual challenges in analyzing contemporary innovation. The objective of this paper is twofold: First, it strives to establish Ludwik Fleck as an important classic on the map of innovation analysis. A systematic comparison with Thomas Kuhn’s work on paradigms, a concept highly influential in various branches of innovation studies, suggests a number of pronounced yet under-researched advantages of a Fleckian perspective in the (...)
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  • Scientific models, simulation, and the experimenter's regress.Axel Gelfert - 2011 - In Paul Humphreys & Cyrille Imbert (eds.), Models, Simulations, and Representations. New York: Routledge.
    According to the "experimenter's regress", disputes about the validity of experimental results cannot be closed by objective facts because no conclusive criteria other than the outcome of the experiment itself exist for deciding whether the experimental apparatus was functioning properly or not. Given the frequent characterization of simulations as "computer experiments", one might worry that an analogous regress arises for computer simulations. The present paper analyzes the most likely scenarios where one might expect such a "simulationist's regress" to surface, and, (...)
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  • Situated Knowledge Production, International Impact: Changing Publishing Practices in a German Engineering Department.Wolfgang Kaltenbrunner - 2018 - Minerva 56 (3):283-303.
    In this paper, I analyze how recent calls to internationalize publication behavior affect research practices at an automotive engineering department in Germany. Automotive engineering is a field with traditionally rather scarce publication activity and strong connections to industry. Substantial authority to define suitable research problems and ways of organizing knowledge production on a daily basis was therefore reserved for local academic elites as well as corporate partners. However, as engineers are increasingly expected to prove their performance through publishing in international (...)
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