Search results for 'Teddy Seidenfield' (try it on Scholar)

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  1. Joseph B. Kadane, Mark Schervish & Teddy Seidenfield (2008). Is Ignorance Bliss? Journal of Philosophy 105 (1):5-36.score: 240.0
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  2. Dagmar Schmauks (2000). Teddy Bears, Tarnagotchis, Transgenic Mice. Sign Systems Studies 28:309-324.score: 18.0
    The expression "artificial animal" denotes a range of different objects from teddy bears to the results of genetic engineering. As a basis for further investigation, this article first of all presents the main interpretations and traces their systematic interconnections. The subsequent sections concentrate on artificial animals in the context of play. The development of material toys is fueled by robotics. It gives toys artificial sense organs, limbs, and cognitive abilities, thus enabling them to act in the real world. The (...)
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  3. Teddy Stallard (2011). Teddy Stallard. Ethos 1 (29):1.score: 18.0
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  4. D. W. Lucas (1968). Teddy Brunius: Inspiration and Katharsis: The Interpretation of Aristotle's Poetics, Vi. 1449b26. (Acta Universitatis Upsaliensis: Swedish Studies in Aesthetics, 3.) Pp. 88. Uppsala: Almqvist & Wiksell, 1966. Paper, 25 Kr. [REVIEW] The Classical Review 18 (01):109-110.score: 15.0
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  5. Matthias Hild (2003). Rethinking the Foundations of Statistics, Joseph B. Kadane, Mark J. Schervish and Teddy Seidenfeld. Cambridge University Press, 1999, X + 388 Pages. [REVIEW] Economics and Philosophy 19 (1):149-155.score: 15.0
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  6. J. Grieves (1982). Style as Metaphor for Symbolic Action: Teddy Boys, Authenticity and Identity. Theory, Culture and Society 1 (2):35-49.score: 15.0
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  7. M. Hild (2003). Review of Joseph B. Kadane, Mark J. Schervish and Teddy Seidenfeld's Rethinking the Foundations of Statistics. [REVIEW] Economics and Philosophy 19 (1):149-155.score: 15.0
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  8. Carol Levine (1977). The First Ban: How Teddy Roosevelt Saved Saccharin. Hastings Center Report 7 (6):6-7.score: 15.0
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  9. David Jan McQuoid-Mason (2013). Decriminalisation of Consensual Sexual Conduct Between Children: What Should Doctors Do Regarding the Reporting of Sexual Offences Under the Sexual Offences Act Until the Constitutional Court Confirms the Judgement of the Teddy Bear Clinic Case? South African Journal of Bioethics and Law 6 (1):8.score: 15.0
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  10. Elisabet Petit (2011). Nace Una Nueva Raza de Conejo: El Teddy. In Ivano Dionigi & Guido Barbujani (eds.), Animalia. Biblioteca Universale Rizzoli. 231--72.score: 15.0
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  11. Anders Ramsay (forthcoming). Teddy Hates Jazz. Res Publica.score: 15.0
     
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  12. A. E. Strode, J. D. Toohey, C. Slack & S. Bhamjee (2013). Reporting Underage Consensual Sex After the Teddy Bear Case: A Different Perspective. South African Journal of Bioethics and Law 6 (2):45.score: 15.0
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  13. Teddy Seidenfeld, Getting to Know Your Probabilities: Three Ways to Frame Personal Probabilities for Decision Making.score: 6.0
    Teddy Seidenfeld – CMU An old, wise, and widely held attitude in Statistics is that modest intervention in the design of an experiment followed by simple statistical analysis may yield much more of value than using very sophisticated statistical analysis on a poorly designed existing data set.
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  14. Wlodek Rabinowicz (1997). On Seidenfeld‘s Criticism of Sophisticated Violations of the Independence Axiom. Theory and Decision 43 (3):279-292.score: 6.0
    An agent who violates independence can avoid dynamic inconsistency in sequential choice if he is sophisticated enough to make use of backward induction in planning. However, Seidenfeld has demonstrated that such a sophisticated agent with dependent preferences is bound to violate the principle of dynamic substitution, according to which admissibility of a plan is preserved under substitution of indifferent options at various choice nodes in the decision tree. Since Seidenfeld considers dynamic substitution to be a coherence condition on dynamic choice, (...)
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  15. Wlodek Rabinowicz (2000). Preference Stability and Substitution of Indifferents: A Rejoinder to Seidenfeld. Theory and Decision 48 (4):311-318.score: 6.0
    Seidenfeld (Seidenfeld, T. [1988a], Decision theory without 'Independence' or without 'Ordering', Economics and Philosophy 4: 267-290) gave an argument for Independence based on a supposition that admissibility of a sequential option is preserved under substitution of indifferents at choice nodes (S). To avoid a natural complaint that (S) begs the question against a critic of Independence, he provided an independent proof of (S) in his (Seidenfeld, T. [1988b], Rejoinder [to Hammond and McClennen], Economics and Philosophy 4: 309-315). In reply to (...)
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  16. Donna Varga (2009). Babes in the Woods: Wilderness Aesthetics in Children's Stories and Toys, 1830-1915. Society and Animals 17 (3):187-205.score: 6.0
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  17. John Tyerman Williams (1996). Pooh and the Philosophers: In Which It is Shown That All of Western Philosophy is Merely a Preamble to Winnie-the-Pooh. Dutton Books.score: 6.0
     
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  18. John Tyerman Williams (1995). Pooh and the Philosophers. Methuen.score: 6.0
     
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  19. Teddy Seidenfeld, Proper Scoring Rules, Dominated Forecasts, and Coherence.score: 3.0
    De Finetti introduced the concept of coherent previsions and conditional previsions through a gambling argument and through a parallel argument based on a quadratic scoring rule. He shows that the two arguments lead to the same concept of coherence. When dealing with events only, there is a rich class of scoring rules which might be used in place of the quadratic scoring rule. We give conditions under which a general strictly proper scoring rule can replace the quadratic scoring rule while (...)
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  20. Teddy Seidenfeld (2001). Remarks on the Theory of Conditional Probability: Some Issues of Finite Versus Countable Additivity. In Vincent F. Hendricks, Stig Andur Pederson & Klaus Frovin Jørgensen (eds.), Probability Theory: Philosophy, Recent History and Relations to Science. Synthese Library, Kluwer.score: 3.0
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  21. James Liszka (2010). Lessons From the Exxon Valdez Oil Spill: A Case Study in Retributive and Corrective Justice for Harm to the Environment. Ethics and the Environment 15 (2):1-30.score: 3.0
    John Muir, who had seen enough natural beauty for ten life times, simply fumbles his words when it comes to describing Prince William Sound: one of the richest, most glorious mountain landscapes I ever beheld— peak over peak lying deep in the sky, a thousand of them, icy and shining…. and great breadth of sun-spangled, ice-dotted waters in front…. grandeur and beauty in a thousand forms awaiting us at every turn in this bright and spacious wonderland. Prince William Sound, which (...)
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  22. Teddy Seidenfeld (1985). Calibration, Coherence, and Scoring Rules. Philosophy of Science 52 (2):274-294.score: 3.0
    Can there be good reasons for judging one set of probabilistic assertions more reliable than a second? There are many candidates for measuring "goodness" of probabilistic forecasts. Here, I focus on one such aspirant: calibration. Calibration requires an alignment of announced probabilities and observed relative frequency, e.g., 50 percent of forecasts made with the announced probability of.5 occur, 70 percent of forecasts made with probability.7 occur, etc. To summarize the conclusions: (i) Surveys designed to display calibration curves, from which a (...)
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  23. Teddy Seidenfeld, Remarks on the Theory of Conditional Probability: Some Issues of Finite Versus Countable Additivity.score: 3.0
    This paper (based on joint work with M.J.Schervish and J.B.Kadane) discusses some differences between the received theory of regular conditional distributions, which is the countably additive theory of conditional probability, and a rival theory of conditional probability using the theory of finitely additive probability. The focus of the paper is maximally "improper" conditional probability distributions, where the received theory requires, in effect, that P{a: P(a|a) = 0} = 1. This work builds upon the results of Blackwell and Dubins (1975).
     
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  24. Teddy Seidenfeld (1986). Entropy and Uncertainty. Philosophy of Science 53 (4):467-491.score: 3.0
    This essay is, primarily, a discussion of four results about the principle of maximizing entropy (MAXENT) and its connections with Bayesian theory. Result 1 provides a restricted equivalence between the two: where the Bayesian model for MAXENT inference uses an "a priori" probability that is uniform, and where all MAXENT constraints are limited to 0-1 expectations for simple indicator-variables. The other three results report on an inability to extend the equivalence beyond these specialized constraints. Result 2 established a sensitivity of (...)
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  25. Joseph B. Kadane, Mark J. Schervish & Teddy Seidenfeld, What Experiment Did We Just Do?score: 3.0
    Experimenters sometimes insist that it is unwise to examine data before determining how to analyze them, as it creates the potential for biased results. I explore the rationale behind this methodological guideline from the standpoint of an error statistical theory of evidence, and I discuss a method of evaluating evidence in some contexts when this predesignation rule has been violated. I illustrate the problem of potential bias, and the method by which it may be addressed, with an example from the (...)
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  26. Teddy Seidenfeld, Mark J. Schervish & Joseph B. Kadane, Preference for Equivalent Random Variables: A Price for Unbounded Utilities.score: 3.0
    When real-valued utilities for outcomes are bounded, or when all variables are simple, it is consistent with expected utility to have preferences defined over probability distributions or lotteries. That is, under such circumstances two variables with a common probability distribution over outcomes – equivalent variables – occupy the same place in a preference ordering. However, if strict preference respects uniform, strict dominance in outcomes between variables, and if indifference between two variables entails indifference between their difference and the status quo, (...)
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  27. Teddy Seidenfeld, Three Contrasts Between Two Senses of Coherence.score: 3.0
    = { 1, …, n} is a finite partition of the sure event: a set of states. Consider two acts A1, A2 defined by the their outcomes relative to.
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  28. Mark Schervish, Teddy Seidenfeld & Mark Schervish Joseph, Coherence with Proper Scoring Rules.score: 3.0
    • Coherence1 for previsions of random variables with generalized betting; • Coherence2 for probability forecasts of events with Brier score penalty; • Coherence3 probability forecasts of events with various proper scoring rules.
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  29. Mark J. Schervish, Teddy Seidenfeld & Joseph B. Kadane, State-Dependent Utilities.score: 3.0
    Several axiom systems for preference among acts lead to a unique probability and a state-independent utility such that acts are ranked according to their expected utilities. These axioms have been used as a foundation for Bayesian decision theory and subjective probability calculus. In this article we note that the uniqueness of the probability is relative to the choice of whatcounts as a constant outcome. Although it is sometimes clear what should be considered constant, in many cases there are several possible (...)
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  30. Teddy Seidenfeld, Mark J. Schervish & Joseph B. Kadane (2010). Coherent Choice Functions Under Uncertainty. Synthese 172 (1):157 - 176.score: 3.0
    We discuss several features of coherent choice functions —where the admissible options in a decision problem are exactly those that maximize expected utility for some probability/utility pair in fixed set S of probability/utility pairs. In this paper we consider, primarily, normal form decision problems under uncertainty—where only the probability component of S is indeterminate and utility for two privileged outcomes is determinate. Coherent choice distinguishes between each pair of sets of probabilities regardless the “shape” or “connectedness” of the sets of (...)
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  31. Teddy Seidenfeld, Extensions of Expected Utility Theory and Some Limitations of Pairwise Comparisons.score: 3.0
    We contrast three decision rules that extend Expected Utility to contexts where a convex set of probabilities is used to depict uncertainty: Γ-Maximin, Maximality, and E-admissibility. The rules extend Expected Utility theory as they require that an option is inadmissible if there is another that carries greater expected utility for each probability in a (closed) convex set. If the convex set is a singleton, then each rule agrees with maximizing expected utility. We show that, even when the option set is (...)
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  32. Teddy Seidenfeld & Mark J. Schervish (1983). A Conflict Between Finite Additivity and Avoiding Dutch Book. Philosophy of Science 50 (3):398-412.score: 3.0
    For Savage (1954) as for de Finetti (1974), the existence of subjective (personal) probability is a consequence of the normative theory of preference. (De Finetti achieves the reduction of belief to desire with his generalized Dutch-Book argument for Previsions.) Both Savage and de Finetti rebel against legislating countable additivity for subjective probability. They require merely that probability be finitely additive. Simultaneously, they insist that their theories of preference are weak, accommodating all but self-defeating desires. In this paper we dispute these (...)
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  33. Teddy Seidenfeld (1978). Direct Inference and Inverse Inference. Journal of Philosophy 75 (12):709-730.score: 3.0
    The JSTOR Archive is a trusted digital repository providing for long-term preservation and access to leading academic journals and scholarly literature from around the world. The Archive is supported by libraries, scholarly societies, publishers, and foundations. It is an initiative of JSTOR, a not-for-profit organization with a mission to help the scholarly community take advantage of advances in technology. For more information regarding JSTOR, please contact support@jstor.org.
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  34. Teddy Seidenfeld & Mark Schervish, Extending Bayesian Theory to Cooperative Groups: An Introduction to Indeterminate/Imprecise Probability Theories [IP] Also See Www.Sipta.Org.score: 3.0
    Pi(AS) = Pi(A)Pi(S) for i = 1, 2. But the Linear Pool created a group opinion P3 with positive dependence. P3(A|S) > P3(A).
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  35. Teddy Seidenfeld (1984). Comments on Causal Decision Theory. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1984:201 - 212.score: 3.0
    PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association, Vol. 1984, Volume Two: Symposia and Invited Papers. (1984), pp. 201-212.
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  36. Teddy Seidenfeld, Mark Schervish & Jay Kadane, Forecasting with Imprecise/Indeterminate Probabilities [IP] – Some Preliminary Findings.score: 3.0
    Part 1 Background on de Finetti’s twin criteria of coherence: Coherence1: 2-sided previsions free from dominance through a Book. Coherence2: Forecasts free from dominance under Brier (squared error) score. Part 2 IP theory based on a scoring rule.
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  37. Teddy Seidenfeld, P's in a Pod: Some Recipes for Cooking Mendel's Data.score: 3.0
    In 1936 R.A.Fisher asked the pointed question, "Has Mendel's Work Been Rediscovered?" The query was intended to open for discussion whether someone altered the data in Gregor Mendel's classic 1866 research report on the garden pea, "Experiments in Plant-Hybridization." Fisher concluded, reluctantly, that the statistical counts in Mendel's paper were doctored in order to create a better intuitive fit between Mendelian expected values and observed frequencies. That verdict remains the received view among statisticians, so I believe. Fisher's analysis is a (...)
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  38. Teddy Brunius (1970). The Aesthetics of Roman Ingarden. Philosophy and Phenomenological Research 30 (4):590-595.score: 3.0
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  39. Martin Peterson & Sven Ove Hansson (2005). Order-Independent Transformative Decision Rules. Synthese 147 (2):323-342.score: 3.0
    A transformative decision rule alters the representation of a decision problem, either by changing the set of alternative acts or the set of states of the world taken into consideration, or by modifying the probability or value assignments. A set of transformative decision rules is order-independent in case the order in which the rules are applied is irrelevant. The main result of this paper is an axiomatic characterization of order-independent transformative decision rules, based on a single axiom. It is shown (...)
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  40. Teddy Seidenfeld, Independence for Full Conditional Measures, Graphoids and Bayesian Networks.score: 3.0
    This paper examines definitions of independence for events and variables in the context of full conditional measures; that is, when conditional probability is a primitive notion and conditioning is allowed on null events. Several independence concepts are evaluated with respect to graphoid properties; we show that properties of weak union, contraction and intersection may fail when null events are present. We propose a concept of “full” independence, characterize the form of a full conditional measure under full independence, and suggest how (...)
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  41. Teddy Seidenfeld, Mark Schervish & Joseph Kadane, When Coherent Preferences May Not Preserve Indifference Between Equivalent Random Variables: A Price for Unbounded Utilities.score: 3.0
    We extend de Finetti’s (1974) theory of coherence to apply also to unbounded random variables. We show that for random variables with mandated infinite prevision, such as for the St. Petersburg gamble, coherence precludes indifference between equivalent random quantities. That is, we demonstrate when the prevision of the difference between two such equivalent random variables must be positive. This result conflicts with the usual approach to theories of Subjective Expected Utility, where preference is defined over lotteries. In addition, we explore (...)
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  42. Teddy Seidenfeld (1988). Decision Theory Without “Independence” or Without “Ordering”. Economics and Philosophy 4 (02):267-.score: 3.0
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  43. Jane Bailey & Ian Kerr (2007). Seizing Control?: The Experience Capture Experiments of Ringley & Mann. [REVIEW] Ethics and Information Technology 9 (2):129-139.score: 3.0
    Will the proliferation of devices that provide the continuous archival and retrieval of personal experiences (CARPE) improve control over, access to and the record of collective knowledge as Vannevar Bush once predicted with his futuristic memex? Or is it possible that their increasing ubiquity might pose fundamental risks to humanity, as Donald Norman contemplated in his investigation of an imaginary CARPE device he called the “Teddy”? Through an examination of the webcam experiment of Jenni Ringley and the EyeTap experiments (...)
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  44. Noam Chomsky, Telling the Truth About Imperialism.score: 3.0
    DAVID BARSAMIAN: REGIME CHANGE is a new term in the lexicon. Kind of like change of address. It sounds somewhat innocuous. It certainly sounds a lot better than invasion, overthrow and occupation. The U.S. is an old hand at regime change. We’re in a year that marks a couple of anniversaries. Today is the 30th anniversary of the U.S.-backed coup in Chile. October 25 marks the 20th anniversary of the U.S. invasion of Grenada. But I’m particularly thinking of regime change (...)
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  45. Teddy Seidenfeld, 1. Introduction.score: 3.0
    This paper offers a comparison between two decision rules for use when uncertainty is depicted by a non-trivial, convex2 set of probability functions Γ. This setting for uncertainty is different from the canonical Bayesian decision theory of expected utility, which uses a singleton set, just one probability function to represent a decision maker’s uncertainty. Justifications for using a non-trivial set of probabilities to depict uncertainty date back at least a half century (Good, 1952) and a foreshadowing of that idea can (...)
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  46. Jessi Cisewski, Joseph B. Kadane, Mark J. Schervish, Teddy Seidenfeld & Rafael Stern, The Rest of Sleeping Beauty.score: 3.0
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  47. Mark J. Schervish, Teddy Seidenfeld & Joseph B. Kadane (forthcoming). Stopping to Reflect. Journal of Philosophy.score: 3.0
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  48. Mark J. Schervish, Teddy Seidenfeld & Joseph B. Kadane (2013). The Effect of Exchange Rates on Statistical Decisions. Philosophy of Science 80 (4):504-532.score: 3.0
  49. Teddy Seidenfeld, The Fundamental Theorems of Prevision and Asset Pricing.score: 3.0
    DeFinetti took the concept of random variables as gambles very seriously, and used the concept to motivate the familiar concepts of probability and expectation. For each gamble X, he assumed that “You” would assign a value P (X), called the prevision of X so that you would be willing to accept the gamble β[X − P (X)] as fair for all positive and negative values β. The only constraint that deFinetti envisioned for you and your previsions is that you insisted (...)
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  50. Teddy Seidenfeld (1979). Why I Am Not an Objective Bayesian; Some Reflections Prompted by Rosenkrantz. Theory and Decision 11 (4):413-440.score: 3.0
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