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  1. The Logic of Explanatory Power.Jonah N. Schupbach & Jan Sprenger - 2011 - Philosophy of Science 78 (1):105-127.
    This article introduces and defends a probabilistic measure of the explanatory power that a particular explanans has over its explanandum. To this end, we propose several intuitive, formal conditions of adequacy for an account of explanatory power. Then, we show that these conditions are uniquely satisfied by one particular probabilistic function. We proceed to strengthen the case for this measure of explanatory power by proving several theorems, all of which show that this measure neatly corresponds to our explanatory intuitions. Finally, (...)
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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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  • Error and the Growth of Experimental Knowledge.Deborah Mayo - 1996 - International Studies in the Philosophy of Science 15 (1):455-459.
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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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  • 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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  • Comparing Probabilistic Measures of Explanatory Power.Jonah N. Schupbach - 2011 - Philosophy of Science 78 (5):813-829.
    Recently, in attempting to account for explanatory reasoning in probabilistic terms, Bayesians have proposed several measures of the degree to which a hypothesis explains a given set of facts. These candidate measures of "explanatory power" are shown to have interesting normative interpretations and consequences. What has not yet been investigated, however, is whether any of these measures are also descriptive of people’s actual explanatory judgments. Here, I present my own experimental work investigating this question. I argue that one measure in (...)
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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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  • Review of Scientific Explanation and the Causal Structure of the World. [REVIEW]James Woodward - 1988 - Noûs 22 (2):322-324.
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  • The Direction of Time.Hans Reichenbach - 1956 - Dover Publications.
    The final work of a distinguished physicist, this remarkable volume examines the emotive significance of time, the time order of mechanics, the time direction of thermodynamics and microstatistics, the time direction of macrostatistics, and the time of quantum physics. Coherent discussions include accounts of analytic methods of scientific philosophy in the investigation of probability, quantum mechanics, the theory of relativity, and causality. "[Reichenbach’s] best by a good deal."—Physics Today. 1971 ed.
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  • Robust Evidence and Secure Evidence Claims.Kent W. Staley - 2004 - Philosophy of Science 71 (4):467-488.
    Many philosophers have claimed that evidence for a theory is better when multiple independent tests yield the same result, i.e., when experimental results are robust. Little has been said about the grounds on which such a claim rests, however. The present essay presents an analysis of the evidential value of robustness that rests on the fallibility of assumptions about the reliability of testing procedures and a distinction between the strength of evidence and the security of an evidence claim. Robustness can (...)
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  • Robustness, Diversity of Evidence, and Probabilistic Independence.Jonah N. Schupbach - 2015 - In Mäki, Ruphy, Schurz & Votsis (eds.), Recent Developments in the Philosophy of Science: EPSA13 Helsinki. Springer. pp. 305-316.
    In robustness analysis, hypotheses are supported to the extent that a result proves robust, and a result is robust to the extent that we detect it in diverse ways. But what precise sense of diversity is at work here? In this paper, I show that the formal explications of evidential diversity most often appealed to in work on robustness – which all draw in one way or another on probabilistic independence – fail to shed light on the notion of diversity (...)
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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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  • The Elusive Basis of Inferential Robustness.James Justus - 2012 - Philosophy of Science 79 (5):795-807.
    Robustness concepts are often invoked to manage two obstacles confronting models of ecological systems: complexity and uncertainty. The intuitive idea is that any result derived from many idealized but credible models is thereby made more reliable or is better confirmed. An appropriate basis for this inference has proven elusive. Here, several representations of robustness analysis are vetted, paying particular attention to complex models of ecosystems and the global climate. The claim that robustness is itself confirmatory because robustness analysis employs a (...)
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  • Error and the Growth of Experimental Knowledge.Deborah G. Mayo - 1996 - University of Chicago.
    This text provides a critique of the subjective Bayesian view of statistical inference, and proposes the author's own error-statistical approach as an alternative framework for the epistemology of experiment. It seeks to address the needs of researchers who work with statistical analysis.
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  • Probability and Evidence.Paul Horwich - 1982 - Cambridge University Press.
    In this influential study of central issues in the philosophy of science, Paul Horwich elaborates on an important conception of probability, diagnosing the failure of previous attempts to resolve these issues as stemming from a too-rigid conception of belief. Adopting a Bayesian strategy, he argues for a probabilistic approach, yielding a more complete understanding of the characteristics of scientific reasoning and methodology. Presented in a fresh twenty-first-century series livery, and including a specially commissioned preface written by Colin Howson, illuminating its (...)
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  • Scientific Explanation and the Causal Structure of the World.Wesley C. 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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  • Confirmation, Heuristics, and Explanatory Reasoning.Timothy McGrew - 2003 - British Journal for the Philosophy of Science 54 (4):553-567.
    Recent work on inference to the best explanation has come to an impasse regarding the proper way to coordinate the theoretical virtues in explanatory inference with probabilistic confirmation theory, and in particular with aspects of Bayes's Theorem. I argue that the theoretical virtues are best conceived heuristically and that such a conception gives us the resources to explicate the virtues in terms of ceteris paribus theorems. Contrary to some Bayesians, this is not equivalent to identifying the virtues with likelihoods or (...)
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  • Simulation and Similarity: Using Models to Understand the World.Michael Weisberg - 2013 - Oxford University Press.
    one takes to be the most salient, any pair could be judged more similar to each other than to the third. Goodman uses this second problem to showthat there can be no context-free similarity metric, either in the trivial case or in a scientifically ...
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  • Some Varieties of Robustness.James 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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  • Probability and Evidence.Paul Horwich - 1973 - Philosophical Review 82 (4):547.
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  • A Bayesian Account of Independent Evidence with Applications.Branden Fitelson - 2001 - Philosophy of Science 68 (S3):S123-S140.
    A Bayesian account of independent evidential support is outlined. This account is partly inspired by the work of C. S. Peirce. I show that a large class of quantitative Bayesian measures of confirmation satisfy some basic desiderata suggested by Peirce for adequate accounts of independent evidence. I argue that, by considering further natural constraints on a probabilistic account of independent evidence, all but a very small class of Bayesian measures of confirmation can be ruled out. In closing, another application of (...)
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  • A Second Look at the Logic of Explanatory Power (with Two Novel Representation Theorems).Vincenzo Crupi & Katya Tentori - 2012 - Philosophy of Science 79 (3):365-385.
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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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  • Strategies of Model Building in Population Genetics.Anya Plutynski - 2006 - Philosophy of Science 73 (5):755-764.
    In 1966, Richard Levins argued that there are different strategies in model building in population biology. In this paper, I reply to Orzack and Sober’s (1993) critiques of Levins, and argue that his views on modeling strategies apply also in the context of evolutionary genetics. In particular, I argue that there are different ways in which models are used to ask and answer questions about the dynamics of evolutionary change, prospectively and retrospectively, in classical versus molecular evolutionary genetics. Further, I (...)
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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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  • A Bayesian Account of Independent Evidence with Applications.Branden Fitelson - 2001 - Proceedings of the Philosophy of Science Association 2001 (3):S123-.
    outlined. This account is partly inspired by the work of C.S. Peirce. When we want to consider how degree of confirmation varies with changing I show that a large class of quantitative Bayesian measures of con-.
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  • Probability, Confirmation, and the Conjunction Fallacy.Vincenzo Crupi, Branden Fitelson & Katya Tentori - 2007 - Thinking and Reasoning 14 (2):182 – 199.
    The conjunction fallacy has been a key topic in debates on the rationality of human reasoning and its limitations. Despite extensive inquiry, however, the attempt to provide a satisfactory account of the phenomenon has proved challenging. Here we elaborate the suggestion (first discussed by Sides, Osherson, Bonini, & Viale, 2002) that in standard conjunction problems the fallacious probability judgements observed experimentally are typically guided by sound assessments of _confirmation_ relations, meant in terms of contemporary Bayesian confirmation theory. Our main formal (...)
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  • Error and the Growth of Experimental Knowledge.Deborah Mayo - 1997 - British Journal for the Philosophy of Science 48 (3):455-459.
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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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  • Robust Re-Engineering: A Philosophical Account?: W. Wimsatt, Re-Engineering Philosophy for Limited Beings: Piecewise Approximations to Reality. Harvard, 2007.W. C. Wimsatt - 2011 - Biology and Philosophy 26 (2):295-303.
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  • The Logic of Scientific Discovery.Patterns of Discovery.Karl R. Popper & Norwood R. Hanson - 1960 - Philosophy and Phenomenological Research 21 (2):266-268.
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  • Representing and Intervening.Ian Hacking - 1987 - Revue de Métaphysique et de Morale 92 (2):279-279.
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  • Representing and Intervening.Ian Hacking - 1984 - British Journal for the Philosophy of Science 35 (4):381-390.
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  • Defending Robustness: The Bacterial Mesosome as a Test Case.Sylvia Culp - 1994 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1994:46 - 57.
    Rasmussen (1993) argues that, because electron microscopists did not use robustness and would not have been warranted in using it as a criterion for the reality or the artifactuality of mesosomes, the bacterial mesosome serves as a test case for robustness that it fails. I respond by arguing that a more complete reading of the research literature on the mesosome shows that ultimately the more robust body of data did not support the mesosome and that electron microscopists used and were (...)
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  • Les Atomes.Jean Perrin - 1913 - Revue de Métaphysique et de Morale 21 (4):4-6.
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