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Disagreement in discipline-building processes

Synthese 198 (Suppl 25):6201-6224 (2019)

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  1. Philosophy and Computer Science.Timothy Colburn - 2000 - Routledge.
    Colburn has a doctorate in philosophy and an advanced degree in computer science; he's worked as a philosophy professor, a computer programmer, and a research scientist in artificial intelligence. Here he discusses the philosophical foundations of artificial intelligence; the new encounter of science and philosophy ; and the philosophy of computer science.
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  • Aspects of Scientific Explanation.Carl G. Hempel - 1965 - In Philosophy and Phenomenological Research. Free Press. pp. 504.
  • Epistemology of Disagreement: The Good News.David Christensen - 2007 - Philosophical Review 116 (2):187-217.
    How should one react when one has a belief, but knows that other people—who have roughly the same evidence as one has, and seem roughly as likely to react to it correctly—disagree? This paper argues that the disagreement of other competent inquirers often requires one to be much less confident in one’s opinions than one would otherwise be.
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  • The Structure and Logic of Interdisciplinary Research in Agent-Based Social Simulation.Nuno David, Maria Marietto, Jaime Sichman & Helder Coelho - 2004 - Journal of Artificial Societies and Social Simulation 7 (3).
    This article reports an exploratory survey of the structure of interdisciplinary research in Agent-Based Social Simulation. One hundred and ninety six researchers participated in the survey completing an on-line questionnaire. The questionnaire had three distinct sections, a classification of research domains, a classification of models, and an inquiry into software requirements for designing simulation platforms. The survey results allowed us to disambiguate the variety of scientific goals and modus operandi of researchers with a reasonable level of detail, and to identify (...)
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  • Extending Ourselves: Computational Science, Empiricism, and Scientific Method.Paul Humphreys - 2004 - Oxford University Press.
    Computational methods have become the dominant technique in many areas of science. This book contains the first systematic philosophical account of these new methods and their consequences for scientific method. This book will be of interest to philosophers of science and to anyone interested in the role played by computers in modern science.
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  • Science in the Age of Computer Simulation.Eric Winsberg - 2010 - University of Chicago Press.
    Introduction -- Sanctioning models : theories and their scope -- Methodology for a virtual world -- A tale of two methods -- When theories shake hands -- Models of climate : values and uncertainties -- Reliability without truth -- Conclusion.
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  • The Evolution of Cooperation.Robert M. Axelrod - 1984 - Basic Books.
    The 'Evolution of Cooperation' addresses a simple yet age-old question; If living things evolve through competition, how can cooperation ever emerge? Despite the abundant evidence of cooperation all around us, there existed no purely naturalistic answer to this question until 1979, when Robert Axelrod famously ran a computer tournament featuring a standard game-theory exercise called The Prisoner's Dilemma. To everyone's surprise, the program that won the tournament, named Tit for Tat, was not only the simplest but the most "cooperative" entrant. (...)
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  • Complexity: A Guided Tour.Melanie Mitchell - 2009 - Oxford University Press.
    What enables individually simple insects like ants to act with such precision and purpose as a group? How do trillions of individual neurons produce something as extraordinarily complex as consciousness? What is it that guides self-organizing structures like the immune system, the World Wide Web, the global economy, and the human genome? These are just a few of the fascinating and elusive questions that the science of complexity seeks to answer. In this remarkably accessible and companionable book, leading complex systems (...)
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  • The Structure of Scientific Revolutions.Thomas S. Kuhn - 1962 - University of Chicago Press.
  • The Advancement of Science: Science Without Legend, Objectivity Without Illusions.Philip Kitcher - 1993 - Oxford, England: Oxford University Press.
    During the last three decades, reflections on the growth of scientific knowledge have inspired historians, sociologists, and some philosophers to contend that scientific objectivity is a myth. In this book, Kitcher attempts to resurrect the notions of objectivity and progress in science by identifying both the limitations of idealized treatments of growth of knowledge and the overreactions to philosophical idealizations. Recognizing that science is done not by logically omniscient subjects working in isolation, but by people with a variety of personal (...)
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  • Knowledge Transfer in Agent-Based Computational Social Science.David Anzola - 2019 - Studies in History and Philosophy of Science Part A 77:29-38.
  • Advancing the Art of Simulation in the Social Sciences.Robert Axelrod - 1997 - Complexity 3 (2):16-22.
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  • Opaque and Translucent Epistemic Dependence in Collaborative Scientific Practice.Susann Wagenknecht - 2014 - Episteme 11 (4):475-492.
    This paper offers an analytic perspective on epistemic dependence that is grounded in theoretical discussion and field observation at the same time. When in the course of knowledge creation epistemic labor is divided, collaborating scientists come to depend upon one another epistemically. Since instances of epistemic dependence are multifarious in scientific practice, I propose to distinguish between two different forms of epistemic dependence, opaque and translucent epistemic dependence. A scientist is opaquely dependent upon a colleague if she does not possess (...)
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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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  • Review Article: Somaesthetics and the Critique of Cartesian Dualism: Body Consciousness: A Philosophy of Mindfulness and Somaesthetics by Richard Shusterman Cambridge: Cambridge University Press, 2008, Pp. 256, ISBN 978—0—521—67587—1 Paperback, $24.99 Reviewed by Bryan S. Turner, Asia Research Institute, National University of Singapore. [REVIEW]Bryan S. Turner - 2008 - Body and Society 14 (3):129-133.
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  • The Specificity of the Scientific Field and the Social Conditions of the Progress of Reason.Pierre Bourdieu - 1975 - Social Science Information 14 (6):19-47.
  • Does Matter Really Matter? Computer Simulations, Experiments, and Materiality.Wendy S. Parker - 2009 - Synthese 169 (3):483-496.
    A number of recent discussions comparing computer simulation and traditional experimentation have focused on the significance of “materiality.” I challenge several claims emerging from this work and suggest that computer simulation studies are material experiments in a straightforward sense. After discussing some of the implications of this material status for the epistemology of computer simulation, I consider the extent to which materiality (in a particular sense) is important when it comes to making justified inferences about target systems on the basis (...)
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  • Prediction Versus Accommodation and the Risk of Overfitting.Christopher Hitchcock & Elliott Sober - 2004 - British Journal for the Philosophy of Science 55 (1):1-34.
    an observation to formulate a theory, it is no surprise that the resulting theory accurately captures that observation. However, when the theory makes a novel prediction—when it predicts an observation that was not used in its formulation—this seems to provide more substantial confirmation of the theory. This paper presents a new approach to the vexed problem of understanding the epistemic difference between prediction and accommodation. In fact, there are several problems that need to be disentangled; in all of them, the (...)
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  • Agent-Based Computational Economics: A Constructive Approach to Economic Theory.Leigh Tesfatsion - 2006 - In Leigh Tesfatsion & Kenneth L. Judd (eds.), Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics. Elsevier.
    Economies are complicated systems encompassing micro behaviors, interaction patterns, and global regularities. Whether partial or general in scope, studies of economic systems must consider how to handle difficult real-world aspects such as asymmetric information, imperfect competition, strategic interaction, collective learning, and the possibility of multiple equilibria. Recent advances in analytical and computational tools are permitting new approaches to the quantitative study of these aspects. One such approach is Agent-based Computational Economics (ACE), the computational study of economic processes modeled as dynamic (...)
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  • Prediction and Accommodation Revisited.John Worrall - 2014 - Studies in History and Philosophy of Science Part A 45 (1):54-61.
    The paper presents a further articulation and defence of the view on prediction and accommodation that I have proposed earlier. It operates by analysing two accounts of the issue-by Patrick Maher and by Marc Lange-that, at least at first sight, appear to be rivals to my own. Maher claims that the time-order of theory and evidence may be important in terms of degree of confirmation, while that claim is explicitly denied in my account. I argue, however, that when his account (...)
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  • Prediction and Accommodation Revisited.John Worrall - 2014 - Studies in History and Philosophy of Science Part A 45 (1):54-61.
    The paper presents a further articulation and defence of the view on prediction and accommodation that I have proposed earlier. It operates by analysing two accounts of the issue-by Patrick Maher and by Marc Lange-that, at least at first sight, appear to be rivals to my own. Maher claims that the time-order of theory and evidence may be important in terms of degree of confirmation, while that claim is explicitly denied in my account. I argue, however, that when his account (...)
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  • Error, Tests and Theory Confirmation.John Worrall - 2010 - In Deborah G. Mayo & Aris Spanos (eds.), Error and Inference: Recent Exchanges on Experimental Reasoning, Reliability, and the Objectivity and Rationality of Science. Cambridge University Press. pp. 125-154.
  • What’s Really at Issue with Novel Predictions?Robert G. Hudson - 2007 - Synthese 155 (1):1 - 20.
    In this paper I distinguish two kinds of predictivism, ‘timeless’ and ‘historicized’. The former is the conventional understanding of predictivism. However, I argue that its defense in the works of John Worrall (Scerri and Worrall 2001, Studies in History and Philosophy of Science 32, 407–452; Worrall 2002, In the Scope of Logic, Methodology and Philosophy of Science, 1, 191–209) and Patrick Maher (Maher 1988, PSA 1988, 1, pp. 273) is wanting. Alternatively, I promote an historicized predictivism, and briefly defend such (...)
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  • Disciplinarity and the Growth of Knowledge.Fred D'Agostino - 2012 - Social Epistemology 26 (3-4):331-350.
    I want to consider how the general characteristics of a discipline might facilitate ?social mechanisms for distributing knowledge? that do not depend on uniformity of use, but, in fact, on different uses by different people. Indeed, I want to show that the ways in which a discipline is organized afford the growth of knowledge and do so, in particular, by facilitating an approach to what Thomas Kuhn described as ?the essential tension? between, on the one hand, the traditional or customary (...)
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  • Knowledge Formations: An Analytic Framework.Stephen Turner - 2017 - In R. Frodeman (ed.), The Oxford Handbook of Interdisciplinarity (2nd Ed.). Oxford University Press. pp. 9-20.
    Knowledge is socially distributed, and the distribution of knowledge is socially structured, but the distribution and the structures within which it is produced and reproduced—often two separate things—have varied enormously. Disciplines are one knowledge formation of special significance. They can be thought of as very old, or as a very recent phenomenon: In the very old sense, disciplines begin with the creation of rituals of certification and exclusion related to knowledge; in the more recent sense, they are the product of (...)
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  • The Sociology of Scientific Disciplines: On the Genesis and Stability of the Disciplinary Structure of Modern Science.Rudolf Stichweh - 1992 - Science in Context 5 (1):3-15.
  • What’s Really at Issue with Novel Predictions?Robert G. Hudson - 2007 - Synthese 155 (1):1-20.
    In this paper I distinguish two kinds of predictivism, 'timeless' and 'historicized'. The former is the conventional understanding of predictivism. However, I argue that its defense in the works of John Worrall and Patrick Maher is wanting. Alternatively, I promote an historicized predictivism, and briefly defend such a predictivism at the end of the paper.
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  • A Short History of Knowledge Formations.Peter Weingart - 2010 - In Julie Thompson Klein & Carl Mitcham (eds.), The Oxford Handbook of Interdisciplinarity. Oxford University Press. pp. 3--14.
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