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Profile: Wendy Parker (Ohio University)
  1. Henk W. de Regt & Wendy S. Parker (2014). Introduction: Simulation, Visualization, and Scientific Understanding. Perspectives on Science 22 (3):311-317.
    Only a decade ago, the topic of scientific understanding remained one that philosophers of science largely avoided. Earlier discussions by Hempel and others had branded scientific understanding a mere subjective state or feeling, one to be studied by psychologists perhaps, but not an important or fruitful focus for philosophers of science. Even as scientific explanation became a central topic in philosophy of science, little attention was given to understanding. Over the last decade, however, this situation has changed. Analyses of scientific (...)
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  2. Wendy S. Parker (2014). Simulation and Understanding in the Study of Weather and Climate. Perspectives on Science 22 (3):336-356.
    In 1904, Norwegian physicist Vilhelm Bjerknes published what would become a landmark paper in the history of meteorology. In that paper, he proposed that daily weather forecasts could be made by calculating later states of the atmosphere from an earlier state using the laws of hydrodynamics and thermodynamics (Bjerknes 1904). He outlined a set of differential equations to be solved and advocated the development of graphical and numerical solution methods, since analytic solution was out of the question. Using these theory-based (...)
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  3. Wendy S. Parker (2013). Getting (Even More) Serious About Similarity. Biology and Philosophy:1-10.
    This paper critically examines Weisberg’s weighted feature matching account of model-world similarity. A number of concerns are raised, including that Weisberg provides an account of what underlies scientific judgments of relative similarity, when what is desired is an account of the sorts of model-target similarities that are necessary or sufficient for achieving particular types of modeling goal. Other concerns relate to the details of the account, in particular to the content of feature sets, the nature of shared features and the (...)
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  4. Wendy S. Parker (2011). When Climate Models Agree: The Significance of Robust Model Predictions. 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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  5. Wendy S. Parker (2010). An Instrument for What? Digital Computers, Simulation and Scientific Practice. Spontaneous Generations 4 (1):39-44.
    As a device used by scientists in the course of performing research, the digital computer might be considered a scientific instrument. But if so, what is it an instrument for? This paper explores a number of answers to this question, focusing on the use of computers in a simulating mode.
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  6. Wendy S. Parker (2010). Comparative Process Tracing and Climate Change Fingerprints. Philosophy of Science 77 (5):1083-1095.
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  7. Wendy S. Parker (2010). Predicting Weather and Climate: Uncertainty, Ensembles and Probability. Studies in History and Philosophy of Science Part B 41 (3):263-272.
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  8. Wendy S. Parker (2010). Scientific Models and Adequacy-for-Purpose. Modern Schoolman 87 (3-4):285-293.
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  9. Wendy S. Parker (2010). Whose Probabilities? Predicting Climate Change with Ensembles of Models. Philosophy of Science 77 (5):985-997.
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  10. Wendy S. Parker (2009). Confirmation and Adequacy-for-Purpose in Climate Modelling. 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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  11. Wendy S. Parker (2009). Does Matter Really Matter? Computer Simulations, Experiments, and Materiality. 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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  12. Wendy S. Parker (2008). Computer Simulation Through an Error-Statistical Lens. Synthese 163 (3):371 - 384.
    After showing how Deborah Mayo’s error-statistical philosophy of science might be applied to address important questions about the evidential status of computer simulation results, I argue that an error-statistical perspective offers an interesting new way of thinking about computer simulation models and has the potential to significantly improve the practice of simulation model evaluation. Though intended primarily as a contribution to the epistemology of simulation, the analysis also serves to fill in details of Mayo’s epistemology of experiment.
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  13. Wendy S. Parker (2008). Franklin, Holmes, and the Epistemology of Computer Simulation. International Studies in the Philosophy of Science 22 (2):165 – 183.
    Allan Franklin has identified a number of strategies that scientists use to build confidence in experimental results. This paper shows that Franklin's strategies have direct analogues in the context of computer simulation and then suggests that one of his strategies—the so-called 'Sherlock Holmes' strategy—deserves a privileged place within the epistemologies of experiment and simulation. In particular, it is argued that while the successful application of even several of Franklin's other strategies (or their analogues in simulation) may not be sufficient for (...)
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