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  1. Jim Woodward (2002). What is a Mechanism? A Counterfactual Account. Proceedings of the Philosophy of Science Association 2002 (3):S366-S377.score: 1.18084
    This paper presents a counterfactual account of what a mechanism is. Mechanisms consist of parts, the behavior of which conforms to generalizations that are invariant under interventions, and which are modular in the sense that it is possible in principle to change the behavior of one part independently of the others. Each of these features can be captured by the truth of certain counterfactuals.
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  2.  32
    Jim Woodward (2006). Some Varieties of Robustness. Journal of Economic Methodology 13 (2):219-240.score: 1.1428
    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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  3.  2
    Jim Woodward (2008). Response to Strevens. Philosophy and Phenomenological Research 77 (1):193-212.score: 1.13875
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  4.  53
    Jim Woodward (1989). Data and Phenomena. Synthese 79 (3):393 - 472.score: 1.12258
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  5. Jim Woodward (2001). Law and Explanation in Biology: Invariance is the Kind of Stability That Matters. Philosophy of Science 68 (1):1-20.score: 1.12127
    This paper develops an account of explanation in biology which does not involve appeal to laws of nature, at least as traditionally conceived. Explanatory generalizations in biology must satisfy a requirement that I call invariance, but need not satisfy most of the other standard criteria for lawfulness. Once this point is recognized, there is little motivation for regarding such generalizations as laws of nature. Some of the differences between invariance and the related notions of stability and resiliency, due respectively to (...)
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  6.  59
    Jim Woodward (2007). Interventionist Theories of Causation in Psychological Perspective. In Alison Gopnik & Laura Schulz (eds.), Causal Learning: Psychology, Philosophy, and Computation. Oxford University Press 19--36.score: 1.12094
  7.  46
    Jim Woodward (2000). Data, Phenomena, and Reliability. Philosophy of Science 67 (3):179.score: 1.11597
    This paper explores how data serve as evidence for phenomena. In contrast to standard philosophical models which invite us to think of evidential relationships as logical relationships, I argue that evidential relationships in the context of data-to-phenomena reasoning are empirical relationships that depend on holding the right sort of pattern of counterfactual dependence between the data and the conclusions investigators reach on the phenomena themselves.
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  8.  56
    Jim Woodward (1997). Explanation, Invariance, and Intervention. Philosophy of Science 64 (4):41.score: 1.11158
    This paper defends a counterfactual account of explanation, according to which successful explanation requires tracing patterns of counterfactual dependence of a special sort, involving what I call active counterfactuals. Explanations having this feature must appeal to generalizations that are invariant--stable under certain sorts of changes. These ideas are illustrated by examples drawn from physics and econometrics.
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  9.  43
    Jim Woodward (2008). Response to Strevens. Philosophy and Phenomenological Research 77 (1):193-212.score: 1.11083
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  10. Jim Woodward, Barry Loewer, John Carroll & Marc Lange (2011). Counterfactuals All the Way Down? Metascience 20 (1):27-52.score: 1.11053
    Counterfactuals all the way down? Content Type Journal Article DOI 10.1007/s11016-010-9437-9 Authors Jim Woodward, History and Philosophy of Science, 1017 Cathedral of Learning, University of Pittsburgh, Pittsburgh, PA 15260, USA Barry Loewer, Department of Philosophy, Rutgers University, New Brunswick, NJ 08901, USA John W. Carroll, Department of Philosophy and Religious Studies, North Carolina State University, Raleigh, NC 27695-8103, USA Marc Lange, Department of Philosophy, University of North Carolina at Chapel Hill, CB#3125—Caldwell Hall, Chapel Hill, NC 27599-3125, USA Journal Metascience Online (...)
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  11. John Allman & Jim Woodward (2008). What Are Moral Intuitions and Why Should We Care About Them? A Neurobiological Perspective. Philosophical Issues 18 (1):164-185.score: 1.11029
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  12.  35
    James Bogen & Jim Woodward (2005). Evading the Irs. Poznan Studies in the Philosophy of the Sciences and the Humanities 86 (1):233-268.score: 1.10762
    'IRS' is our term for the logical empiricist idea that the best way to understand the epistemic bearing of observational evidence on scientific theories is to model it in terms of Inferential Relations among Sentences representing the evidence, and sentences representing hypotheses the evidence is used to evaluate. Developing ideas from our earlier work, including 'Saving the Phenomena'(Phil Review 97, 1988, p.303-52 )we argue that the bearing of observational evidence on theory depends upon causal connections and error characteristics of the (...)
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  13.  32
    Jim Bogen & Jim Woodward (1992). Observations, Theories and the Evolution of the Human Spirit. Philosophy of Science 59 (4):590-611.score: 1.10672
    Standard philosophical discussions of theory-ladeness assume that observational evidence consists of perceptual outputs (or reports of such outputs) that are sentential or propositional in structure. Theory-ladeness is conceptualized as having to do with logical or semantical relationships between such outputs or reports and background theories held by observers. Using the recent debate between Fodor and Churchland as a point of departure, we propose an alternative picture in which much of what serves as evidence in science is not perceptual outputs or (...)
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  14.  25
    Jim Woodward (1999). Causal Interpretation in Systems of Equations. Synthese 121 (1-2):199-247.score: 1.1049
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  15.  4
    Paul Humphreys & Jim Woodward (1993). The Chances of Explanation: Causal Explanation in the Social, Medical and Physical Sciences. Philosophy of Science 60 (4):659.score: 1.10165
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  16.  32
    Jim Woodward (2009). Why Do People Cooperate as Much as They Do? In Chrysostomos Mantzavinos (ed.), Philosophy of the Social Sciences: Philosophical Theory and Scientific Practice. Cambridge University Pressscore: 1.10114
    This paper makes use of recent empirical results, mainly from experimental economics, to expore the conditions under which people will cooperate and to assess competing explantions of this cooperation. It is argued that the evidence supports the claim that people differ in type, with some being conditional cooperators and others being motivated by more or less sophisticated forms of self-interest. Stable cooperation requires, among other things, rules and institutions that protect conditional cooperators from myopically self-interested types. Additional empirical features of (...)
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  17.  9
    Jim Woodward (1993). Book Review:The Chances of Explanation: Causal Explanation in the Social, Medical and Physical Sciences Paul Humphreys. [REVIEW] Philosophy of Science 60 (4):671-.score: 1.1004
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  18. Jim Woodward (2011). Causes, Conditions, and the Pragmatics of Causal Explanation. In Gregory J. Morgan (ed.), Philosophy of Science Matters: The Philosophy of Peter Achinstein. Oxford University Press 247.score: 1.1
     
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  19.  0
    Jim Woodward (2002). Ronald Giere: Science Without Laws. [REVIEW] Philosophy of Science 69 (2):379-384.score: 1.1
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