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  1. Laurent Mazliak & Glenn Shafer (2011). What Does the Arrest and Release of Emile Borel and His Colleagues in 1941 Tell Us About the German Occupation of France? Science in Context 24 (4):587-623.
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  2. Glenn Shafer (2010). A Betting Interpretation for Probabilities and Dempster-Shafer Degrees of Belief. International Journal of Approximate Reasoning.
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  3. Glenn Shafer (2009). Comments on Harman and Kulkarni's "Reliable Reasoning". Abstracta 5 (3):10-17.
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  4. Glenn Shafer (2008). Defensive Forecasting: How to Use Similarity to Make Forecasts That Pass Statistical Tests. In Giacomo Della Riccia, Didier Dubois & Hans-Joachim Lenz (eds.), Preferences and Similarities. Springer. 215--247.
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  5. Glenn Shafer (1995). Review Essay. Synthese 104 (1):161-176.
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  6. Glenn Shafer (1995). The Situation of Causality. Foundations of Science 1 (4):543-563.
    Causality in the abstract is a grand theme. We take it up when we want to penetrate to the bottom of things to understand general laws that govern the working at the world of the deepest and most detailed level.In this essay, I argue for a more situated understanding of causality. To counter our desire for ever greater generality, I suggest that causal relations, even those that hold only on average, require context. To counter our desire for ever greater detail, (...)
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  7. Glenn Shafer & Amos Tversky (1985). Languages and Designs for Probability Judgment. Cognitive Science 9 (3):309-339.
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  8. Glenn Shafer (1983). A Subjective Interpretation of Conditional Probability. Journal of Philosophical Logic 12 (4):453 - 466.
  9. Glenn Shafer (1983). A Theory of Probability Should Tutor Our Intuitions. Behavioral and Brain Sciences 6 (3):508.
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  10. Glenn Shafer (1981). Constructive Probability. Synthese 48 (1):1-60.
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  11. Glenn Shafer (1981). Jeffrey's Rule of Conditioning. Philosophy of Science 48 (3):337-362.
    Richard Jeffrey's generalization of Bayes' rule of conditioning follows, within the theory of belief functions, from Dempster's rule of combination and the rule of minimal extension. Both Jeffrey's rule and the theory of belief functions can and should be construed constructively, rather than normatively or descriptively. The theory of belief functions gives a more thorough analysis of how beliefs might be constructed than Jeffrey's rule does. The inadequacy of Bayesian conditioning is much more general than Jeffrey's examples of uncertain perception (...)
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  12. Glenn Shafer (1978). Two Theories of Probability. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1978:441 - 465.
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  13. Glenn Shafer (1976). A Mathematical Theory of Evidence. Princeton University Press.
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