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  1. 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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  • Re-engineering philosophy for limited beings: piecewise approximations to reality.William C. Wimsatt - 2007 - Cambridge: 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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  • Making models count.Anna Alexandrova - 2008 - Philosophy of Science 75 (3):383-404.
    What sort of claims do scientific models make and how do these claims then underwrite empirical successes such as explanations and reliable policy interventions? In this paper I propose answers to these questions for the class of models used throughout the social and biological sciences, namely idealized deductive ones with a causal interpretation. I argue that the two main existing accounts misrepresent how these models are actually used, and propose a new account. *Received July 2006; revised August 2008. †To contact (...)
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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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  • Robustness, Reliability, and Overdetermination (1981).William C. Wimsatt - 2012 - In Lena Soler (ed.), Characterizing the robustness of science: after the practice turn in philosophy of science. New York: Springer Verlag. pp. 61-78.
    The use of multiple means of determination to “triangulate” on the existence and character of a common phenomenon, object, or result has had a long tradition in science but has seldom been a matter of primary focus. As with many traditions, it is traceable to Aristotle, who valued having multiple explanations of a phenomenon, and it may also be involved in his distinction between special objects of sense and common sensibles. It is implicit though not emphasized in the distinction between (...)
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  • Confirmation and explaining how possible.Patrick Forber - 2010 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 41 (1):32-40.
    Confirmation in evolutionary biology depends on what biologists take to be the genuine rivals. Investigating what constrains the scope of biological possibility provides part of the story: explaining how possible helps determine what counts as a genuine rival and thus informs confirmation. To clarify the criteria for genuine rivalry I distinguish between global and local constraints on biological possibility, and offer an account of how-possibly explanation. To sharpen the connection between confirmation and explaining how possible I discuss the view that (...)
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  • If No Capacities Then No Credible Worlds. But Can Models Reveal Capacities?Nancy Cartwright - 2009 - Erkenntnis 70 (1):45-58.
    This paper argues that even when simple analogue models picture parallel worlds, they generally still serve as isolating tools. But there are serious obstacles that often stop them isolating in just the right way. These are obstacles that face any model that functions as a thought-experiment but they are especially pressing for economic models because of the paucity of economic principles. Because of the paucity of basic principles, economic models are rich in structural assumptions. Without these no interesting conclusions can (...)
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  • Economic Modelling as Robustness Analysis.Jaakko Kuorikoski, Aki Lehtinen & Caterina Marchionni - 2010 - British Journal for the Philosophy of Science 61 (3):541-567.
    We claim that the process of theoretical model refinement in economics is best characterised as robustness analysis: the systematic examination of the robustness of modelling results with respect to particular modelling assumptions. We argue that this practise has epistemic value by extending William Wimsatt's account of robustness analysis as triangulation via independent means of determination. For economists robustness analysis is a crucial methodological strategy because their models are often based on idealisations and abstractions, and it is usually difficult to tell (...)
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  • False models as explanatory engines.Frank Hindriks - 2008 - Philosophy of the Social Sciences 38 (3):334-360.
    Many models in economics are very unrealistic. At the same time, economists put a lot of effort into making their models more realistic. I argue that in many cases, including the Modigliani-Miller irrelevance theorem investigated in this paper, the purpose of this process of concretization is explanatory. When evaluated in combination with their assumptions, a highly unrealistic model may well be true. The purpose of relaxing an unrealistic assumption, then, need not be to move from a false model to a (...)
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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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  • 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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  • 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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  • Twilight of the perfect model model.Paul Teller - 2001 - Erkenntnis 55 (3):393-415.
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  • Confirmation and explaining how possible.Patrick Forber - 2008 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 41 (1):32-40.
    Confirmation in evolutionary biology depends on what biologists take to be the genuine rivals. Investigating what constrains the scope of biological possibility provides part of the story: explaining how possible helps determine what counts as a genuine rival and thus informs confirmation. To clarify the criteria for genuine rivalry I distinguish between global and local constraints on biological possibility, and offer an account of how-possibly explanation. To sharpen the connection between confirmation and explaining how possible I discuss the view that (...)
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  • When Analytic Narratives Explain.Anna Alexandrova - 2009 - Journal of the Philosophy of History 3 (1):1-24.
    Rational choice modeling originating in economics is sweeping across many areas of social science. This paper examines a popular methodological proposal for integrating formal models from game theory with more traditional narrative explanations of historical phenomena, known as “analytic narratives”. Under what conditions are we justified in thinking that an analytic narrative provides a good explanation? In this paper I criticize the existing criteria and provide a set of my own. Along the way, I address the critique of analytic narratives (...)
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