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  1. Scientific Explanation and the Causal Structure of the World.Wesley Salmon - 1984 - Princeton University Press.
    The philosophical theory of scientific explanation proposed here involves a radically new treatment of causality that accords with the pervasively statistical character of contemporary science. Wesley C. Salmon describes three fundamental conceptions of scientific explanation--the epistemic, modal, and ontic. He argues that the prevailing view is untenable and that the modal conception is scientifically out-dated. Significantly revising aspects of his earlier work, he defends a causal/mechanical theory that is a version of the ontic conception. Professor Salmon's theory furnishes a robust (...)
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  • The Scientific Image.Michael Friedman - 1982 - Journal of Philosophy 79 (5):274-283.
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  • Wimsatt and the Robustness Family: Review of Wimsatt’s Re-Engineering Philosophy for Limited Beings. [REVIEW]Brett Calcott - 2011 - Biology and Philosophy 26 (2):281-293.
    This review of Wimsatt’s book Re-engineering Philosophy for Limited Beings focuses on analysing his use of robustness, a central theme in the book. I outline a family of three distinct conceptions of robustness that appear in the book, and look at the different roles they play. I briefly examine what underwrites robustness, and suggest that further work is needed to clarify both the structure of robustness and the relation between it various conceptions.
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  • Understanding Pluralism in Climate Modeling.W. S. Parker - 2006 - Foundations of Science 11 (4):349-368.
    To study Earth’s climate, scientists now use a variety of computer simulation models. These models disagree in some of their assumptions about the climate system, yet they are used together as complementary resources for investigating future climatic change. This paper examines and defends this use of incompatible models. I argue that climate model pluralism results both from uncertainty concerning how to best represent the climate system and from difficulties faced in evaluating the relative merits of complex models. I describe how (...)
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  • Buyer Beware: Robustness Analyses in Economics and Biology.Jay Odenbaugh & Anna Alexandrova - 2011 - Biology and Philosophy 26 (5):757-771.
    Theoretical biology and economics are remarkably similar in their reliance on mathematical models, which attempt to represent real world systems using many idealized assumptions. They are also similar in placing a great emphasis on derivational robustness of modeling results. Recently philosophers of biology and economics have argued that robustness analysis can be a method for confirmation of claims about causal mechanisms, despite the significant reliance of these models on patently false assumptions. We argue that the power of robustness analysis has (...)
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  • Strategies of Abstraction.Richard Levins - 2006 - Biology and Philosophy 21 (5):741-755.
    Abstraction is seen as an active process which both enlightens and obscures. Abstractions are not true or false but relatively enlightening or obscuring according to the problem under study; different abstractions may grasp different aspects of a problem. Abstractions may be useless if they can answer questions only about themselves. A theoretical enterprise explores reality through acluster of abstractions that use different perspectives, temporal and horizontal scales, and assumes different givens.
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  • Incredible Worlds, Credible Results.Jaakko Kuorikoski & Aki Lehtinen - 2009 - Erkenntnis 70 (1):119-131.
    Robert Sugden argues that robustness analysis cannot play an epistemic role in grounding model-world relationships because the procedure is only a matter of comparing models with each other. We posit that this argument is based on a view of models as being surrogate systems in too literal a sense. In contrast, the epistemic importance of robustness analysis is easy to explicate if modelling is viewed as extended cognition, as inference from assumptions to conclusions. Robustness analysis is about assessing the reliability (...)
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  • Scientific Perspectivism.Ronald N. Giere - 2006 - University of Chicago Press.
    Many people assume that the claims of scientists are objective truths. But historians, sociologists, and philosophers of science have long argued that scientific claims reflect the particular historical, cultural, and social context in which those claims were made. The nature of scientific knowledge is not absolute because it is influenced by the practice and perspective of human agents. Scientific Perspectivism argues that the acts of observing and theorizing are both perspectival, and this nature makes scientific knowledge contingent, as Thomas Kuhn (...)
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  • How Models Are Used to Represent Reality.Ronald N. Giere - 2002 - Philosophy of Science 71 (5):742-752.
    Most recent philosophical thought about the scientific representation of the world has focused on dyadic relationships between language-like entities and the world, particularly the semantic relationships of reference and truth. Drawing inspiration from diverse sources, I argue that we should focus on the pragmatic activity of representing, so that the basic representational relationship has the form: Scientists use models to represent aspects of the world for specific purposes. Leaving aside the terms "law" and "theory," I distinguish principles, specific conditions, models, (...)
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  • Confirmation and Robustness of Climate Models.Elisabeth A. Lloyd - 2010 - Philosophy of Science 77 (5):971–984.
    Recent philosophical attention to climate models has highlighted their weaknesses and uncertainties. Here I address the ways that models gain support through observational data. I review examples of model fit, variety of evidence, and independent support for aspects of the models, contrasting my analysis with that of other philosophers. I also investigate model robustness, which often emerges when comparing climate models simulating the same time period or set of conditions. Starting from Michael Weisberg’s analysis of robustness, I conclude that his (...)
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  • The Robust Volterra Principle.Michael Weisberg & Kenneth Reisman - 2008 - Philosophy of Science 75 (1):106-131.
    Theorizing in ecology and evolution often proceeds via the construction of multiple idealized models. To determine whether a theoretical result actually depends on core features of the models and is not an artifact of simplifying assumptions, theorists have developed the technique of robustness analysis, the examination of multiple models looking for common predictions. A striking example of robustness analysis in ecology is the discovery of the Volterra Principle, which describes the effect of general biocides in predator-prey systems. This paper details (...)
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  • Robust! -- Handle with Care.Wybo Houkes & Krist Vaesen - 2012 - Philosophy of Science 79 (3):1-20.
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  • Scientific Representation: Paradoxes of Perspective.B. C. van Fraassen - 2010 - Analysis 70 (3):511-514.
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  • Holism, Entrenchment, and the Future of Climate Model Pluralism.Johannes Lenhard & Eric Winsberg - 2010 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 41 (3):253-262.
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  • The Role of 'Complex' Empiricism in the Debates About Satellite Data and Climate Models.Elisabeth A. Lloyd - 2012 - Studies in History and Philosophy of Science Part A 43 (2):390-401.
    climate scientists have been engaged in a decades-long debate over the standing of satellite measurements of the temperature trends of the atmosphere above the surface of the earth. This is especially significant because skeptics of global warming and the greenhouse effect have utilized this debate to spread doubt about global climate models used to predict future states of climate. I use this case from an under-studied science to illustrate two distinct philosophical approaches to the relation among data, scientists, measurement, models, (...)
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  • When Climate Models Agree: The Significance of Robust Model Predictions.Wendy S. Parker - 2011 - Philosophy of Science 78 (4):579-600.
    This article identifies conditions under which robust predictive modeling results have special epistemic significance---related to truth, confidence, and security---and considers whether those conditions hold in the context of present-day climate modeling. The findings are disappointing. When today’s climate models agree that an interesting hypothesis about future climate change is true, it cannot be inferred---via the arguments considered here anyway---that the hypothesis is likely to be true or that scientists’ confidence in the hypothesis should be significantly increased or that a claim (...)
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  • Varieties of Support and Confirmation of Climate Models.Elisabeth A. Lloyd - 2009 - Aristotelian Society Supplementary Volume 83 (1):213-232.
    Today's climate models are supported in a couple of ways that receive little attention from philosophers or climate scientists. In addition to standard 'model fit', wherein a model's simulation is compared to observational data, there is an additional type of confirmation available through the variety of instances of model fit. When a model performs well at fitting first one variable and then another, the probability of the model under some standard confirmation function, say, likelihood, goes up more than under each (...)
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  • Objectivity in Experimental Inquiry: Breaking Data-Technique Circles.Sylvia Culp - 1995 - Philosophy of Science 62 (3):438-458.
    I respond to H. M. Collins's claim (1985, 1990, 1993) that experimental inquiry cannot be objective because the only criterium experimentalists have for determining whether a technique is "working" is the production of "correct" (i.e., the expected) data. Collins claims that the "experimenters' regress," the name he gives to this data-technique circle, cannot be broken using the resources of experiment alone. I argue that the data-technique circle, can be broken even though any interpretation of the raw data produced by techniques (...)
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  • The Structure and Confirmation of Evolutionary Theory.Elisabeth A. Lloyd - 1992 - Noûs 26 (1):132-133.
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  • Comparative Process Tracing and Climate Change Fingerprints.Wendy S. Parker - 2010 - Philosophy of Science 77 (5):1083-1095.
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  • Some Varieties of Robustness.Jim Woodward - 2006 - Journal of Economic Methodology 13 (2):219-240.
    It is widely believed that robustness (of inferences, measurements, models, phenomena and relationships discovered in empirical investigation etc.) is a Good Thing. However, there are many different notions of robustness. These often differ both in their normative credentials and in the conditions that warrant their deployment. Failure to distinguish among these notions can result in the uncritical transfer of considerations which support one notion to contexts in which another notion is being deployed. This paper surveys several different notions of robustness (...)
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  • True Lies: Realism, Robustness, and Models.Jay Odenbaugh - 2011 - Philosophy of Science 78 (5):1177-1188.
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  • Science as Representation: Flouting the Criteria.Bas van Fraassen - 2002 - Philosophy of Science 71 (5):794-804.
    Criteria of adequacy for scientific representation of the phenomena pertain to accuracy and truth. But that representation is selective and may require distortion even in the selected parameters; this point is intimately connected with the fact that representation is intentional, and its adequacy relative to its particular purpose. Since observation and measurement are perspectival and the appearances to be saved are perspectival measurement outcomes, the question whether this “saving” is an explanatory relation provides a new focus for the realist/antirealist debate. (...)
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  • Robustness Analysis.Michael Weisberg - 2006 - Philosophy of Science 73 (5):730-742.
    Modelers often rely on robustness analysis, the search for predictions common to several independent models. Robustness analysis has been characterized and championed by Richard Levins and William Wimsatt, who see it as central to modern theoretical practice. The practice has also been severely criticized by Steven Orzack and Elliott Sober, who claim that it is a nonempirical form of confirmation, effective only under unusual circumstances. This paper addresses Orzack and Sober's criticisms by giving a new account of robustness analysis and (...)
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  • Re-Engineering Philosophy for Limited Beings: Piecewise Approximations to Reality.William C. Wimsatt - 2007 - Harvard University Press.
    This book offers a philosophy for error-prone humans trying to understand messy systems in the real world.
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  • Re-Engineering Philosophy for Limited Beings. Piecewise Approximations to Reality.William C. Wimsatt - 2010 - Critica 42 (124):108-117.
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  • Climate Models and Their Evaluation.S. Bony, R. Colman & T. Fichefet - 2007 - In S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor & H. L. Miller (eds.), Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press. pp. 623--624.
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