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  1. Evaluating Formal Models of Science.Michael Thicke - 2020 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 51 (2):315-335.
    This paper presents an account of how to evaluate formal models of science: models and simulations in social epistemology designed to draw normative conclusions about the social structure of scientific research. I argue that such models should be evaluated according to their representational and predictive accuracy. Using these criteria and comparisons with familiar models from science, I argue that most formal models of science are incapable of supporting normative conclusions.
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  • Structural uncertainty through the lens of model building.Marina Baldissera Pacchetti - forthcoming - Synthese:1-17.
    An important epistemic issue in climate modelling concerns structural uncertainty: uncertainty about whether the mathematical structure of a model accurately represents its target. How does structural uncertainty affect our knowledge and predictions about the climate? How can we identify sources of structural uncertainty? Can we manage the effect of structural uncertainty on our knowledge claims? These are some of the questions that an epistemology of structural uncertainty faces, and these questions are also important for climate scientists and policymakers. I develop (...)
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  • Scientific Models.Stephen M. Downes - 2011 - Philosophy Compass 6 (11):757-764.
    This contribution provides an assessment of the epistemological role of scientific models. The prevalent view that all scientific models are representations of the world is rejected. This view points to a unified way of resolving epistemic issues for scientific models. The emerging consensus in philosophy of science that models have many different epistemic roles in science is presented and defended.
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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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  • 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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  • Robustness and Independent Evidence.Jacob Stegenga & Tarun Menon - 2017 - Philosophy of Science 84 (3):414-435.
    Robustness arguments hold that hypotheses are more likely to be true when they are confirmed by diverse kinds of evidence. Robustness arguments require the confirming evidence to be independent. We identify two kinds of independence appealed to in robustness arguments: ontic independence —when the multiple lines of evidence depend on different materials, assumptions, or theories—and probabilistic independence. Many assume that OI is sufficient for a robustness argument to be warranted. However, we argue that, as typically construed, OI is not a (...)
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  • Robustness Analysis as Explanatory Reasoning.Jonah N. Schupbach - 2016 - British Journal for the Philosophy of Science:axw008.
    When scientists seek further confirmation of their results, they often attempt to duplicate the results using diverse means. To the extent that they are successful in doing so, their results are said to be robust. This paper investigates the logic of such "robustness analysis" [RA]. The most important and challenging question an account of RA can answer is what sense of evidential diversity is involved in RAs. I argue that prevailing formal explications of such diversity are unsatisfactory. I propose a (...)
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  • Robustness Analysis as Explanatory Reasoning.Jonah N. Schupbach - 2018 - British Journal for the Philosophy of Science 69 (1):275-300.
    ABSTRACT When scientists seek further confirmation of their results, they often attempt to duplicate the results using diverse means. To the extent that they are successful in doing so, their results are said to be ‘robust’. This article investigates the logic of such ‘robustness analysis’. The most important and challenging question an account of RA can answer is what sense of evidential diversity is involved in RAs. I argue that prevailing formal explications of such diversity are unsatisfactory. I propose a (...)
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  • Computer Models and the Evidence of Anthropogenic Climate Change: An Epistemology of Variety-of-Evidence Inferences and Robustness Analysis.Martin Vezer - 2016 - Computer Models and the Evidence of Anthropogenic Climate Change: An Epistemology of Variety-of-Evidence Inferences and Robustness Analysis MA Vezér Studies in History and Philosophy of Science 56:95-102.
    To study climate change, scientists employ computer models, which approximate target systems with various levels of skill. Given the imperfection of climate models, how do scientists use simulations to generate knowledge about the causes of observed climate change? Addressing a similar question in the context of biological modelling, Levins (1966) proposed an account grounded in robustness analysis. Recent philosophical discussions dispute the confirmatory power of robustness, raising the question of how the results of computer modelling studies contribute to the body (...)
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  • Model Robustness as a Confirmatory Virtue: The Case of Climate Science.Elisabeth A. Lloyd - 2015 - Studies in History and Philosophy of Science Part A 49:58-68.
    I propose a distinct type of robustness, which I suggest can support a confirmatory role in scientific reasoning, contrary to the usual philosophical claims. In model robustness, repeated production of the empirically successful model prediction or retrodiction against a background of independentlysupported and varying model constructions, within a group of models containing a shared causal factor, may suggest how confident we can be in the causal factor and predictions/retrodictions, especially once supported by a variety of evidence framework. I present climate (...)
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  • Variety-of-Evidence Reasoning About the Distant Past: A Case Study in Paleoclimate Reconstruction.Martin Vezér - 2017 - European Journal for Philosophy of Science 7 (2):257-265.
    The epistemology of studies addressing questions about historical and prehistorical phenomena is a subject of increasing discussion among philosophers of science. A related field of inquiry that has yet to be connected to this topic is the epistemology of climate science. Branching these areas of research, I show how variety-of-evidence reasoning accounts for scientific inferences about the past by detailing a case study in paleoclimate reconstruction. This analysis aims to clarify the logic of historical inquiry in general and, by focusing (...)
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  • Aggregating Evidence in Climate Science: Consilience, Robustness and the Wisdom of Multiple Models.A. Vezér Martin - unknown
    The goal of this dissertation is to contribute to the epistemology of science by addressing a set of related questions arising from current discussions in the philosophy and science of climate change: Given the imperfection of computer models, how do they provide information about large and complex target systems? What is the relationship between consilient reasoning and robust evidential support in the production of scientific knowledge? Does taking the mean of a set of model outputs provide epistemic advantages over using (...)
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  • Similarity, Adequacy, and Purpose: Understanding the Success of Scientific Models.Melissa Jacquart - 2016 - Dissertation, University of Western Ontario
    A central component to scientific practice is the construction and use of scientific models. Scientists believe that the success of a model justifies making claims that go beyond the model itself. However, philosophical analysis of models suggests that drawing inferences about the world from successful models is more complex. In this dissertation I develop a framework that can help disentangle the related strands of evaluation of model success, model extendibility, and the ability to draw ampliative inferences about the world from (...)
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  • The Argument From Surprise.Adrian Currie - 2018 - Canadian Journal of Philosophy 48 (5):639-661.
    I develop an account of productive surprise as an epistemic virtue of scientific investigations which does not turn on psychology alone. On my account, a scientific investigation is potentially productively surprising when results can conflict with epistemic expectations, those expectations pertain to a wide set of subjects. I argue that there are two sources of such surprise in science. One source, often identified with experiments, involves bringing our theoretical ideas in contact with new empirical observations. Another, often identified with simulations, (...)
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  • Introduction to Assessing Climate Models: Knowledge, Values and Policy.Joel Katzav & Wendy S. Parker - 2015 - European Journal for Philosophy of Science 5 (2):141-148.
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  • Melinda Fagan Philosophy of Stem Cell Biology: Knowledge in Flesh and Blood.Adrian Currie - 2016 - British Journal for the Philosophy of Science 67 (2):651-655.
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  • II—Wendy S. Parker: Confirmation and Adequacy-for-Purpose in Climate Modelling.Wendy S. Parker - 2009 - Aristotelian Society Supplementary Volume 83 (1):233-249.
    Lloyd (2009) contends that climate models are confirmed by various instances of fit between their output and observational data. The present paper argues that what these instances of fit might confirm are not climate models themselves, but rather hypotheses about the adequacy of climate models for particular purposes. This required shift in thinking—from confirming climate models to confirming their adequacy-for-purpose—may sound trivial, but it is shown to complicate the evaluation of climate models considerably, both in principle and in practice.
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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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  • Computer Models and the Evidence of Anthropogenic Climate Change: An Epistemology of Variety-of-Evidence Inferences and Robustness Analysis.Martin A. Vezér - 2016 - Studies in History and Philosophy of Science Part A 56:95-102.
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  • The Elusive Basis of Inferential Robustness.James Justus - 2012 - Philosophy of Science 79 (5):795-807.
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  • The Epistemology of Climate Models and Some of its Implications for Climate Science and the Philosophy of Science.Joel Katzav - 2014 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 46 (2):228-238.
    I bring out the limitations of four important views of what the target of useful climate model assessment is. Three of these views are drawn from philosophy. They include the views of Elisabeth Lloyd and Wendy Parker, and an application of Bayesian confirmation theory. The fourth view I criticise is based on the actual practice of climate model assessment. In bringing out the limitations of these four views, I argue that an approach to climate model assessment that neither demands too (...)
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  • Computer Simulation and the Philosophy of Science.Eric Winsberg - 2009 - Philosophy Compass 4 (5):835-845.
    There are a variety of topics in the philosophy of science that need to be rethought, in varying degrees, after one pays careful attention to the ways in which computer simulations are used in the sciences. There are a number of conceptual issues internal to the practice of computer simulation that can benefit from the attention of philosophers. This essay surveys some of the recent literature on simulation from the perspective of the philosophy of science and argues that philosophers have (...)
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