• Proceedings of the Collaboration in Experimental Design Research Symposium (edited book)
    with Rod Bamford, Karina Clarke, Jacqueline Clayton, Katherine Moline, and Liz Williamson
    . 2012.
  •  30
    Freezing fertility or freezing false hope? A content analysis of social egg freezing in U.S. print media
    with Lisa Campo-Engelstein, Rohia Aziz, Shilpa Darivemula, Jennifer Raffaele, and Rajani Bhatia
    AJOB Empirical Bioethics 9 (3): 181-193. 2018.
  •  253
    How Uncertainty Interacts with Ethical Values in Climate Change Research
    In Linda Mearns, Chris Forest, Hayley Fowler, Robert Lempert & Robert Wilby (eds.), Uncertainty in Climate Change Research: An Integrated Approach, Springer. forthcoming.
    Like all human activities, scientific research is infused with values. Scientific discovery can, for example, be valued as an end in itself. The phrase ethical values is an umbrella term for much of what people care about aside from knowledge for its own sake. Ethical values encompass reasons for caring about the harms caused by climate impacts or the injustice of how those harms are distributed. The closer that research gets to informing real-world actions, the more the design of that research …Read more
  •  111
    The future of climate modeling
    Climatic Change 132 475-487. 2015.
    Recently a number of scientists have proposed substantial changes to the practice of climate modeling, though they disagree over what those changes should be. We provide an overview and critical examination of three leading proposals: the unified approach, the hierarchy approach and the pluralist approach. The unified approach calls for an accelerated development of high-resolution models within a seamless prediction framework. The hierarchy approach calls for more attention to the development a…Read more
  •  32
    Introduction
    with Elay Shech
    Studies in History and Philosophy of Science Part A 85 30-33. 2021.
  •  709
    Data models, representation and adequacy-for-purpose
    European Journal for Philosophy of Science 11 (1): 1-26. 2021.
    We critically engage two traditional views of scientific data and outline a novel philosophical view that we call the pragmatic-representational view of data. On the PR view, data are representations that are the product of a process of inquiry, and they should be evaluated in terms of their adequacy or fitness for particular purposes. Some important implications of the PR view for data assessment, related to misrepresentation, context-sensitivity, and complementary use, are highlighted. The PR …Read more
  •  14
    Local Model-Data Symbiosis in Meteorology and Climate Science
    Philosophy of Science 87 (5): 807-818. 2020.
    I introduce a distinction between general and local model-data symbiosis and offer three examples of local symbiosis in the fields of meteorology and climate science. Local model-data symbiosis ref...
  •  137
    Model Evaluation: An Adequacy-for-Purpose View
    Philosophy of Science 87 (3): 457-477. 2020.
    According to an adequacy-for-purpose view, models should be assessed with respect to their adequacy or fitness for particular purposes. Such a view has been advocated by scientists and philosophers...
  •  11
    The Significance of Robust Climate Projections
    In Elisabeth A. Lloyd & Eric Winsberg (eds.), Climate Modelling: Philosophical and Conceptual Issues, Springer Verlag. pp. 273-296. 2018.
    This chapter identifies conditions under which robust predictive modeling results have special epistemic significance—related to truth, confidence, and security—and considers whether those conditions are met in the context of climate modeling today. 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, nor that …Read more
  •  34
    Philosophical Perspectives on Earth System Modeling: Truth, Adequacy and Understanding.
    with G. Gramelsberger and J. Lenhard
    Journal of Advances in Modeling Earth Systems 12 (1). 2020.
    We explore three questions about Earth system modeling that are of both scientific and philosophical interest: What kind of understanding can be gained via complex Earth system models? How can the limits of understanding be bypassed or managed? How should the task of evaluating Earth system models be conceptualized?
  •  8
    Incorporating user values into climate services
    with Greg Lusk
    Bulletin of the American Meteorological Society 100 (9): 1643-1650. 2019.
    Increasingly there are calls for climate services to be “co-produced” with users, taking into account not only the basic information needs of users but also their value systems and decision contexts. What does this mean in practice? One way that user values can be incorporated into climate services is in the management of inductive risk. This involves understanding which errors in climate service products would have particularly negative consequences from the users’ perspective (e.g., underestim…Read more
  •  65
    Evidence and Knowledge from Computer Simulation
    Erkenntnis 87 (4): 1521-1538. 2020.
    Can computer simulation results be evidence for hypotheses about real-world systems and phenomena? If so, what sort of evidence? Can we gain genuinely new knowledge of the world via simulation? I argue that evidence from computer simulation is aptly characterized as higher-order evidence: it is evidence that other evidence regarding a hypothesis about the world has been collected. Insofar as particular epistemic agents do not have this other evidence, it is possible that they will gain genuinely…Read more
  •  7
    Preface
    Philosophy of Science 85 (5): 739-740. 2018.
  •  70
    Computer simulation and philosophy of science Content Type Journal Article Pages 1-4 DOI 10.1007/s11016-011-9567-8 Authors Wendy S. Parker, Department of Philosophy, Ellis Hall 202, Ohio University, Athens, OH 45701, USA Journal Metascience Online ISSN 1467-9981 Print ISSN 0815-0796
  •  104
    Computer simulation through an error-statistical lens
    Synthese 163 (3): 371-384. 2008.
    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…Read more
  •  297
    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…Read more
  •  10
    Preface
    Philosophy of Science 84 (5): 795-796. 2017.
  •  308
    Issues in the theoretical foundations of climate science
    Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 63 141-149. 2018.
    The theoretical foundations of climate science have received little attention from philosophers thus far, despite a number of outstanding issues. We provide a brief, non-technical overview of several of these issues – related to theorizing about climates, climate change, internal variability and more – and attempt to make preliminary progress in addressing some of them. In doing so, we hope to open a new thread of discussion in the emerging area of philosophy of climate science, focused on theor…Read more
  •  132
    Values and evidence: how models make a difference
    European Journal for Philosophy of Science 8 (1): 125-142. 2018.
    We call attention to an underappreciated way in which non-epistemic values influence evidence evaluation in science. Our argument draws upon some well-known features of scientific modeling. We show that, when scientific models stand in for background knowledge in Bayesian and other probabilistic methods for evidence evaluation, conclusions can be influenced by the non-epistemic values that shaped the setting of priorities in model development. Moreover, it is often infeasible to correct for this…Read more
  •  159
    Computer Simulation, Measurement, and Data Assimilation
    British Journal for the Philosophy of Science 68 (1): 273-304. 2017.
    This article explores some of the roles of computer simulation in measurement. A model-based view of measurement is adopted and three types of measurement—direct, derived, and complex—are distinguished. It is argued that while computer simulations on their own are not measurement processes, in principle they can be embedded in direct, derived, and complex measurement practices in such a way that simulation results constitute measurement outcomes. Atmospheric data assimilation is then considered …Read more
  •  213
    When Climate Models Agree: The Significance of Robust Model Predictions
    Philosophy of Science 78 (4): 579-600. 2011.
    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 o…Read more
  •  66
    Getting serious about similarity
    Biology and Philosophy 30 (2): 267-276. 2015.
    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,…Read more
  •  131
    Scientific Models and Adequacy-for-Purpose
    Modern Schoolman 87 (3-4): 285-293. 2010.
  •  1
    Computer Modeling in Climate Science: Experiment, Explanation, Pluralism
    Dissertation, University of Pittsburgh. 2003.
    Computer simulation modeling is an important part of contemporary scientific practice but has not yet received much attention from philosophers. The present project helps to fill this lacuna in the philosophical literature by addressing three questions that arise in the context of computer simulation of Earth's climate. Computer simulation experimentation commonly is viewed as a suspect methodology, in contrast to the trusted mainstay of material experimentation. Are the results of computer simu…Read more
  •  90
    Whose Probabilities? Predicting Climate Change with Ensembles of Models
    Philosophy of Science 77 (5): 985-997. 2010.
    Today’s most sophisticated simulation studies of future climate employ not just one climate model but a number of models. I explain why this “ensemble” approach has been adopted—namely, as a means of taking account of uncertainty—and why a comprehensive investigation of uncertainty remains elusive. I then defend a middle ground between two camps in an ongoing debate over the transformation of ensemble results into probabilistic predictions of climate change, highlighting requirements that I refe…Read more
  •  30
    False Precision, Surprise and Improved Uncertainty Assessment
    with James S. Risbey
    Philosophical Transactions of the Royal Society A 373 (2055): 20140453. 2015.
    An uncertainty report describes the extent of an agent’s uncertainty about some matter. We identify two basic requirements for uncertainty reports, which we call faithfulness and completeness. We then discuss two pitfalls of uncertainty assessment that often result in reports that fail to meet these requirements. The first involves adopting a one-size-fits-all approach to the representation of uncertainty, while the second involves failing to take account of the risk of surprises. In connection …Read more
  •  174
    Understanding pluralism in climate modeling
    Foundations of Science 11 (4): 349-368. 2006.
    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 me…Read more
  •  30
    Comparative Process Tracing and Climate Change Fingerprints
    Philosophy of Science 77 (5): 1083-1095. 2010.
    Climate change fingerprint studies investigate the causes of recent climate change. I argue that these studies have much in common with Steel’s (2008) streamlined comparative process tracing, illustrating a mechanisms-based approach to extrapolation in which the mechanisms of interest are simulated rather than physically instantiated. I then explain why robustness and variety-of-evidence considerations turn out to be important for understanding the evidential value of climate change fingerprint …Read more
  •  109
    Predicting weather and climate: Uncertainty, ensembles and probability
    Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 41 (3): 263-272. 2010.
    Simulation-based weather and climate prediction now involves the use of methods that reflect a deep concern with uncertainty. These methods, known as ensemble prediction methods, produce multiple simulations for predictive periods of interest, using different initial conditions, parameter values and/or model structures. This paper provides a non-technical overview of current ensemble methods and considers how the results of studies employing these methods should be interpreted, paying special at…Read more