Search results for 'Jeffrey Sebo' (try it on Scholar)

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  1. Jeffrey Sebo (2006). The Ethics of Incest. Philosophy in the Contemporary World 13 (1):48-55.
    In this article I challenge two common arguments against incest: the genetics argument (that incest is immoral because it might lead to the conception of a genetically deformed child), and the family argument (that incest is immoral because it undermines the family, the emotional center for the individual). These arguments, I contend, commit us to condemning not only incest, but also a wide range ofbehaviors that we currently permit. I thus present the reader with a dilemma: on pain of inconsistency, (...)
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  2.  12
    Rudolf Carnap & Richard C. Jeffrey (1972). Book Review:Studies in Inductive Logic and Probability Rudolf Carnap, Richard C. Jeffrey. [REVIEW] Philosophy of Science 39 (4):549-.
  3. Domenico Costantini, Maria Carla Galavotti & Richard C. Jeffrey (1997). Probability, Dynamics, and Causality Essays in Honour of Richard C. Jeffrey.
     
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  4.  26
    Richard C. Jeffrey (2004). Formal Logic: Its Scope and Limits. Hackett Pub..
    This brief paperback is designed for symbolic/formal logic courses. It features the tree method proof system developed by Jeffrey. The new edition contains many more examples and exercises and is reorganized for greater accessibility.
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  5. Richard C. Jeffrey (1992). Probability and the Art of Judgment. Cambridge University Press.
    Richard Jeffrey is beyond dispute one of the most distinguished and influential philosophers working in the field of decision theory and the theory of knowledge. His work is distinctive in showing the interplay of epistemological concerns with probability and utility theory. Not only has he made use of standard probabilistic and decision theoretic tools to clarify concepts of evidential support and informed choice, he has also proposed significant modifications of the standard Bayesian position in order that it provide a (...)
     
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  6.  61
    Richard C. Jeffrey (1974). Preference Among Preferences. Journal of Philosophy 71 (13):377-391.
  7.  54
    Richard C. Jeffrey (1956). Valuation and Acceptance of Scientific Hypotheses. Philosophy of Science 23 (3):237-246.
  8.  28
    Richard Jeffrey (1981). The Logic of Decision Defended. Synthese 48 (3):473 - 492.
    The approach to decision theory floated in my 1965 book is reviewed (I), challenged in various related ways (II–V) and defended, firstad hoc (II–IV) and then by a general argument of Ellery Ells's (VI). Finally, causal decision theory (in a version sketched in VII) is exhibited as a special case of my 1965 theory, according to the Eellsian argument.
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  9. Richard Jeffrey (2002). Logicism Lite. Philosophy of Science 69 (3):474-496.
    Logicism Lite counts number‐theoretical laws as logical for the same sort of reason for which physical laws are counted as as empirical: because of the character of the data they are responsible to. In the case of number theory these are the data verifying or falsifying the simplest equations, which Logicism Lite counts as true or false depending on the logical validity or invalidity of first‐order argument forms in which no numbertheoretical notation appears.
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  10. Richard C. Jeffrey (1966). Goodman's Query. Journal of Philosophy 63 (11):281-288.
  11.  30
    Richard Jeffrey (1987). Indefinite Probability Judgment: A Reply to Levi. Philosophy of Science 54 (4):586-591.
    Isaac Levi and I have different views of probability and decision making. Here, without addressing the merits, I will try to answer some questions recently asked by Levi (1985) about what my view is, and how it relates to his.
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  12.  27
    Richard Jeffrey (1987). Alias Smith and Jones: The Testimony of the Senses. [REVIEW] Erkenntnis 26 (3):391 - 399.
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  13.  20
    Richard Jeffrey (1995). Probability Reparation: The Problem of New Explanation. [REVIEW] Philosophical Studies 77 (1):97 - 101.
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  14.  20
    Richard C. Jeffrey (1977). A Note on the Kinematics of Preference. Erkenntnis 11 (1):135 - 141.
  15.  20
    Richard Jeffrey (1992). Radical Probabilism (Prospectus for a User's Manual). Philosophical Issues 2:193-204.
  16.  30
    Richard Jeffrey (1986). Probabilism and Induction. Topoi 5 (1):51-58.
  17.  29
    Richard C. Jeffrey (1973). Carnap's Inductive Logic. Synthese 25 (3-4):299 - 306.
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  18.  26
    Richard Jeffrey (1996). Unknown Probabilities. Erkenntnis 45 (2-3):327 - 335.
    From a point of view like de Finetti's, what is the judgmental reality underlying the objectivistic claim that a physical magnitude X determines the objective probability that a hypothesis H is true? When you have definite conditional judgmental probabilities for H given the various unknown values of X, a plausible answer is sufficiency, i.e., invariance of those conditional probabilities as your probability distribution over the values of X varies. A different answer, in terms of conditional exchangeability, is offered for use (...)
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  19.  47
    Richard C. Jeffrey (1975). Probability and Falsification: Critique of the Popper Program. Synthese 30 (1-2):95 - 117.
  20.  25
    Richard C. Jeffrey (1971). On Interpersonal Utility Theory. Journal of Philosophy 68 (20):647-656.
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  21.  24
    Richard Jeffrey (1984). De Finetti's Probabilism. Synthese 60 (1):73 - 90.
  22.  19
    Richard C. Jeffrey (1965). Ethics and the Logic of Decision. Journal of Philosophy 62 (19):528-539.
  23.  29
    Richard C. Jeffrey (1991). After Carnap. Erkenntnis 35 (1-3):255 - 262.
  24.  15
    Richard C. Jeffrey (1975). Replies. Synthese 30 (1-2):149 - 157.
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  25.  8
    Richard Jeffrey (1989). Reading Probabilismo. Erkenntnis 31 (2-3):225 - 237.
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  26.  12
    Richard C. Jeffrey (1968). The Whole Truth. Synthese 18 (1):24 - 27.
  27.  12
    Richard C. Jeffrey (1963). On Indeterminate Conditionals. Philosophical Studies 14 (3):37 - 43.
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  28.  18
    Richard Jeffrey (1995). A Brief Guide to the Work of Carl Gustav Hempel. Erkenntnis 42 (1):3 - 7.
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  29.  19
    Richard Jeffrey (1993). Take Back the Day! Jon Dorling's Bayesian Solution of the Duhem Problem. Philosophical Issues 3:197-207.
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  30.  11
    Richard Jeffrey (1997). In Memoriam: Carl Gustav Hempel. [REVIEW] Erkenntnis 47 (3):281-283.
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  31.  12
    Richard C. Jeffrey (1964). Popper on the Rule of Succession. Mind 73 (289):129.
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  32.  9
    Maria Carla Galavotti & Richard Jeffrey (1989). Preface. Erkenntnis 31 (2-3):165-167.
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  33.  4
    Richard C. Jeffrey (1959). A Note on Finch's "an Explication of Counterfactuals by Probability Theory". Philosophy and Phenomenological Research 20 (1):116.
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  34.  84
    Franz Dietrich, Christian List & Richard Bradley, Belief Revision Generalized: A Joint Characterization of Bayes's and Jeffrey's Rules.
    We present a general framework for representing belief-revision rules and use it to characterize Bayes's rule as a classical example and Jeffrey's rule as a non-classical one. In Jeffrey's rule, the input to a belief revision is not simply the information that some event has occurred, as in Bayes's rule, but a new assignment of probabilities to some events. Despite their differences, Bayes's and Jeffrey's rules can be characterized in terms of the same axioms: "responsiveness", which requires (...)
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  35.  13
    Timothy Pawl (2015). Aquinas’s Ontology of the Material World: Change, Hylomorphism, and Material Objects. By Jeffrey E. Brower. American Catholic Philosophical Quarterly 89 (4):723-727.
    I review Jeffrey Brower's book, "Aquinas's Ontology of the Material World".
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  36.  97
    Ittay Nissan-Rozen (2013). Jeffrey Conditionalization, the Principal Principle, the Desire as Belief Thesis, and Adams's Thesis. British Journal for the Philosophy of Science 64 (4):axs039.
    I show that David Lewis’s principal principle is not preserved under Jeffrey conditionalization. Using this observation, I argue that Lewis’s reason for rejecting the desire as belief thesis and Adams’s thesis applies also to his own principal principle. 1 Introduction2 Adams’s Thesis, the Desire as Belief Thesis, and the Principal Principle3 Jeffrey Conditionalization4 The Principal Principles Not Preserved under Jeffrey Conditionalization5 Inadmissible Experiences.
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  37.  21
    Lydia McGrew (2014). Jeffrey Conditioning, Rigidity, and the Defeasible Red Jelly Bean. Philosophical Studies 168 (2):569-582.
    Jonathan Weisberg has argued that Jeffrey Conditioning is inherently “anti-holistic” By this he means, inter alia, that JC does not allow us to take proper account of after-the-fact defeaters for our beliefs. His central example concerns the discovery that the lighting in a room is red-tinted and the relationship of that discovery to the belief that a jelly bean in the room is red. Weisberg’s argument that the rigidity required for JC blocks the defeating role of the red-tinted light (...)
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  38.  13
    Ilho Park (2013). Simultaneous Belief Updates Via Successive Jeffrey Conditionalization. Synthese 190 (16):3511-3533.
    This paper discusses simultaneous belief updates. I argue here that modeling such belief updates using the Principle of Minimum Information can be regarded as applying Jeffrey conditionalization successively, and so that, contrary to what many probabilists have thought, the simultaneous belief updates can be successfully modeled by means of Jeffrey conditionalization.
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  39.  7
    Christopher F. French (2015). Explicating Formal Epistemology: Carnap's Legacy as Jeffrey's Radical Probabilism. Studies in History and Philosophy of Science Part A 53:33–42.
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  40.  7
    Jeffrey Church (2014). Nietzsche, Nihilism, and the Philosophy of the Future Ed. By Jeffrey Metzger (Review). Journal of Nietzsche Studies 44 (3):495-497.
    In his introduction, Jeffrey Metzger states that “at some point in the past 20 or 30 years … Nietzsche’s name [became] no longer associated primarily with nihilism” (1). Metzger is pointing to the increasing contemporary scholarly interest in Nietzsche’s epistemology, naturalism, and metaethics. The worthy aim of this volume is to ask us to examine once again the underlying philosophical problem to which these views are a response, namely, nihilism. This volume helpfully reminds us that Nietzsche’s philosophical motivation still (...)
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  41.  77
    Hartry Field (1978). A Note on Jeffrey Conditionalization. Philosophy of Science 45 (3):361-367.
    Bayesian decision theory can be viewed as the core of psychological theory for idealized agents. To get a complete psychological theory for such agents, you have to supplement it with input and output laws. On a Bayesian theory that employs strict conditionalization, the input laws are easy to give. On a Bayesian theory that employs Jeffrey conditionalization, there appears to be a considerable problem with giving the input laws. However, Jeffrey conditionalization can be reformulated so that the problem (...)
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  42.  25
    Carl Wagner (2010). Jeffrey Conditioning and External Bayesianity. Logic Journal of the IGPL 18 (2):336-345.
    Suppose that several individuals who have separately assessed prior probability distributions over a set of possible states of the world wish to pool their individual distributions into a single group distribution, while taking into account jointly perceived new evidence. They have the option of first updating their individual priors and then pooling the resulting posteriors or first pooling their priors and then updating the resulting group prior. If the pooling method that they employ is such that they arrive at the (...)
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  43.  66
    Antje Kahl (2014). Jeffrey P. Bishop, The Anticipatory Corpse: Medicine, Power and the Care of the Dying. Human Studies 37 (4):589-596.
    “[T]here is something rotten at the heart of medicine” —this is one of the central statements of Jeffrey Paul Bishop in his book The Anticipatory Corpse. Medicine, Power and the Care of the Dying. The obvious, if somewhat morbid, thought that “rotten” would refer to the decaying body as the central subject of investigation is, however, misleading. Instead, Bishop aims to demonstrate that the modern trend of medicalizing dying and death is the wrong way.The book explores contemporary medicine’s practices, (...)
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  44.  9
    Constantinos Hadjichristidis, Steven A. Sloman & David E. Over (2014). Categorical Induction From Uncertain Premises: Jeffrey's Doesn't Completely Rule. Thinking and Reasoning 20 (4):405-431.
    Studies of categorical induction typically examine how belief in a premise (e.g., Falcons have an ulnar artery) projects on to a conclusion (e.g., Robins have an ulnar artery). We study induction in cases in which the premise is uncertain (e.g., There is an 80% chance that falcons have an ulnar artery). Jeffrey's rule is a normative model for updating beliefs in the face of uncertain evidence. In three studies we tested the descriptive validity of Jeffrey's rule and a (...)
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  45. J. Williamson (2006). From Bayesianism to the Epistemic View of Mathematics: Review of R. Jeffrey, Subjective Probability: The Real Thing. [REVIEW] Philosophia Mathematica 14 (3):365-369.
    Subjective Probability: The Real Thing is the last book written by the late Richard Jeffrey, a key proponent of the Bayesian interpretation of probability.Bayesians hold that probability is a mental notion: saying that the probability of rain is 0.7 is just saying that you believe it will rain to degree 0.7. Degrees of belief are themselves cashed out in terms of bets—in this case you consider 7:3 to be fair odds for a bet on rain. There are two extreme (...)
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  46.  20
    Nicholas Wolterstorff (2005). Jeffrey Stout on Democracy and its Contemporary Christian Critics. Journal of Religious Ethics 33 (4):633-647.
    Jeffrey Stout addresses two of the main criticisms of liberal democracy by its contemporary neotraditionalist Christian critics: that liberal democracy is destructive of social tradition, and thereby of virtue in the citizenry, and that liberal democracy is inherently secular, committed to expunging religious voices from the public arena. I judge that Stout effectively answers these charges: liberal democracy has its own tradition, it cultivates the virtues relevant to that, and it is not inherently hostile to piety. What Stout does (...)
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  47.  24
    Daniel Osherson, Order Dependence and Jeffrey Conditionalization.
    A glance at the sky raises my probability of rain to .7. As it happens, the conditional probabilities of each state given rain remain the same, and similarly for their conditional probabilities given no rain. As Jeffrey (1983, Ch. 11) points out, my new distribution P2 is therefore fixed by the law of total probability. For example, P2(RC) = P2(RC | R)P2(R)+P2(RC | ¯.
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  48.  15
    David E. Over & Constantinos Hadjichristidis (2009). Uncertain Premises and Jeffrey's Rule. Behavioral and Brain Sciences 32 (1):97-98.
    Oaksford & Chater (O&C) begin in the halfway Bayesian house of assuming that minor premises in conditional inferences are certain. We demonstrate that this assumption is a serious limitation. They additionally suggest that appealing to Jeffrey's rule could make their approach more general. We present evidence that this rule is not limited enough to account for actual probability judgements.
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  49.  26
    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 (...)
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  50.  13
    Ron Eyerman (2004). Jeffrey Alexander and the Cultural Turn in Social Theory. Thesis Eleven 79 (1):25-30.
    This paper traces developments in Jeffrey Alexander’s cultural sociology. The aim is to introduce the reader to the key components of this theory as it developed from a functionalist focus on societal values through semiotics and linguistic structuralism to a theory of cultural trauma and collective performance.
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