Search results for 'Anita Fetzer' (try it on Scholar)

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  1. Anita Fetzer & Etsuko Oishi (eds.) (2011). Context and Contexts: Parts Meet Whole? John Benjamins Pub. Co..score: 120.0
    This book departs from the premise that context represents a complex relational configuration which can no longer be conceived as an analytic prime but rather requires a parts-whole perspective to capture its inherent dynamism. The edited volume presents a collection of papers which examine the connectedness between context, contextualization and entextualization. They address the questions how meaning and speech acts are situated in context, how both are influenced by context, how context influences speech acts and meaning, how context is imported (...)
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  2. Anita Fetzer (2002). Micro Situations and Macro Structures: Natural-Language Communication and Context. Foundations of Science 7 (3):255-291.score: 120.0
    This contribution investigates the role ofcontext in natural-language communication bydifferentiating between linguistic andsociocultural contexts. It is firmly anchoredto a dialogue framework and based on arelational conception of context as astructured and interactionally organisedphenomenon. However, context is not onlyexamined from this bottom-up or microperspective, but also from a top-down or macroviewpoint as pre- and co-supposed socioculturalcontext. Here, context is not solely seen as aninteractionally organised phenomenon, butrather as a sociocultural apparatus whichstrongly influences the interpretation of microsituations.The section, micro building blocks andlocal (...)
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  3. Ellery Eells & James H. Fetzer (eds.) (2010). The Place of Probability in Science. Springer.score: 60.0
  4. James H. Fetzer (1990). The Frame Problem: Artificial Intelligence Meets David Hume. International Journal of Expert Systems 3:219-232.score: 30.0
  5. James H. Fetzer (1988). Program Verification: The Very Idea. Communications of the ACM 31 (9):1048--1063.score: 30.0
    The notion of program verification appears to trade upon an equivocation. Algorithms, as logical structures, are appropriate subjects for deductive verification. Programs, as causal models of those structures, are not. The success of program verification as a generally applicable and completely reliable method for guaranteeing program performance is not even a theoretical possibility.
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  6. James H. Fetzer (forthcoming). Evolution and Atheism: Has Griffin Reconciled Science and Religion? Synthese.score: 30.0
    The distinguished theologian, David Ray Griffin, has advanced a set of thirteen theses intended to characterize (what he calls) “Neo-Darwinism” and which he contrasts with “Intelligent Design”. Griffin maintains that Neo-Darwinism is “atheistic” in forgoing a creator but suggests that, by adopting a more modest scientific naturalism and embracing a more naturalistic theology, it is possible to find “a third way” that reconciles religion and science. The considerations adduced here suggest that Griffin has promised more than he can deliver. On (...)
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  7. James H. Fetzer (ed.) (2002). Consciousness Evolving. John Benjamins.score: 30.0
  8. James H. Fetzer (1991). Philosophical Aspects of Program Verification. Minds and Machines 1 (2):197-216.score: 30.0
    A debate over the theoretical capabilities of formal methods in computer science has raged for more than two years now. The function of this paper is to summarize the key elements of this debate and to respond to important criticisms others have advanced by placing these issues within a broader context of philosophical considerations about the nature of hardware and of software and about the kinds of knowledge that we have the capacity to acquire concerning their performance.
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  9. James H. Fetzer (1990). Artificial Intelligence: Its Scope and Limits. Kluwer.score: 30.0
    1. WHAT IS ARTIFICIAL INTELLIGENCE? One of the fascinating aspects of the field of artificial intelligence (AI) is that the precise nature of its subject ..
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  10. James H. Fetzer (2004). Information: Does It Have to Be True? Minds and Machines 14 (2):223-229.score: 30.0
    Luciano Floridi (2003) offers a theory of information as a strongly semantic notion, according to which information encapsulates truth, thereby making truth a necessary condition for a sentence to qualify as information. While Floridi provides an impressive development of this position, the aspects of his approach of greatest philosophical significance are its foundations rather than its formalization. He rejects the conception of information as meaningful data, which entails at least three theses – that information can be false; that tautologies are (...)
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  11. James H. Fetzer (2004). Disinformation: The Use of False Information. Minds and Machines 14 (2):231-240.score: 30.0
    The distinction between misinformation and disinformation becomes especially important in political, editorial, and advertising contexts, where sources may make deliberate efforts to mislead, deceive, or confuse an audience in order to promote their personal, religious, or ideological objectives. The difference consists in having an agenda. It thus bears comparison with lying, because lies are assertions that are false, that are known to be false, and that are asserted with the intention to mislead, deceive, or confuse. One context in which disinformation (...)
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  12. James H. Fetzer (2002). Propensities and Frequencies: Inference to the Best Explanation. Synthese 132 (1-2):27 - 61.score: 30.0
    An approach to inference to the best explanation integrating a Popperianconception of natural laws together with a modified Hempelian account of explanation, one the one hand, and Hacking's law of likelihood (in its nomicguise), on the other, which provides a robust abductivist model of sciencethat appears to overcome the obstacles that confront its inductivist,deductivist, and hypothetico-deductivist alternatives.This philosophy of scienceclarifies and illuminates some fundamental aspects of ontology and epistemology, especially concerning the relations between frequencies and propensities. Among the most important (...)
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  13. James H. Fetzer (ed.) (2000). Science, Explanation, and Rationality: Aspects of the Philosophy of Carl G. Hempel. Oxford University Press.score: 30.0
    Carl G. Hempel exerted greater influence upon philosophers of science than any other figure during the 20th century. In this far-reaching collection, distinguished philosophers contribute valuable studies that illuminate and clarify the central problems to which Hempel was devoted. The essays enhance our understanding of the development of logical empiricism as the major intellectual influence for scientifically-oriented philosophers and philosophically-minded scientists of the 20th century.
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  14. James H. Fetzer (2003). Consciousness and Cognition: Semiotic Conceptions of Bodies and Minds. In Quentin Smith & Aleksandar Jokic (eds.), Consciousness: New Philosophical Perspectives. Oxford University Press.score: 30.0
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  15. James H. Fetzer (1979). Chalmers' What is This Thing Called Science? Erkenntnis 14 (3).score: 30.0
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  16. James H. Fetzer (1983). Probability and Objectivity in Deterministic and Indeterministic Situations. Synthese 57 (3):367--86.score: 30.0
    This paper pursues the question, To what extent does the propensity approach to probability contribute to plausible solutions to various anomalies which occur in quantum mechanics? The position I shall defend is that of the three interpretations — the frequency, the subjective, and the propensity — only the third accommodates the possibility, in principle, of providing a realistic interpretation of ontic indeterminism. If these considerations are correct, then they lend support to Popper's contention that the propensity construction tends to remove (...)
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  17. James H. Fetzer (1997). Thinking and Computing: Computers as Special Kinds of Signs. Minds and Machines 7 (3):345-364.score: 30.0
    Cognitive science has been dominated by the computational conception that cognition is computation across representations. To the extent to which cognition as computation across representations is supposed to be a purposive, meaningful, algorithmic, problem-solving activity, however, computers appear to be incapable of cognition. They are devices that can facilitate computations on the basis of semantic grounding relations as special kinds of signs. Even their algorithmic, problem-solving character arises from their interpretation by human users. Strictly speaking, computers as such — apart (...)
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  18. James H. Fetzer (1981). Probability and Explanation. Synthese 48 (3):371 - 408.score: 30.0
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  19. James H. Fetzer (1990). Evolution, Rationality and Testability. Synthese 82 (3):423-39.score: 30.0
    Cosmides, Wason, and Johnson-Laird, among others, have suggested evidence that reasoning abilities tend to be domain specific, insofar as humans do not appear to acquire capacities for logical reasoning that are applicable across different contexts. Unfortunately, the significance of these findings depends upon the specific variety of logical reasoning under consideration. Indeed, there seem to be at least three grounds for doubting such conclusions, since: (1) tests of reasoning involving the use of material conditionals may not be appropriate for representing (...)
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  20. James H. Fetzer & Donald E. Nute (1981). A Probabilistic Causal Calculus: Conflicting Conceptions. Synthese 48 (3):241 - 246.score: 30.0
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  21. James H. Fetzer & Donald E. Nute (1980). A Probabilistic Causal Calculus: Conflicting Conceptions. Synthese 44 (2):241 - 246.score: 30.0
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  22. James H. Fetzer (1974). Grünbaum's 'Defense' of the Symmetry Thesis. Philosophical Studies 25 (3):173 - 187.score: 30.0
    The purpose of this paper is to demonstrate that Grünbaum's purported defense of Hempel's thesis of the symmetry of explanation and prediction is fundamentally inadequate by virtue of the fact that Grünbaum adopts an extended and revised version of the thesis pertaining to scientific understanding in general in lieu of the original and restricted version advanced by Hempel pertaining to scientific explanation in particular. When Hempel's thesis rather than Grünbaum's revision is recognized as the relevant object of criticism, it becomes (...)
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  23. James H. Fetzer (1974). On “Epistemic Possibility”. Philosophia 4 (2-3):327-335.score: 30.0
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  24. James H. Fetzer (1979). Review: Chalmers' "What Is This Thing Called Science?". [REVIEW] Erkenntnis 14 (3):393 - 404.score: 30.0
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  25. James H. Fetzer & Donald E. Nute (1979). Syntax, Semantics, and Ontology: A Probabilistic Causal Calculus. Synthese 40 (3):453 - 495.score: 30.0
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  26. James H. Fetzer (1977). A World of Dispositions. Synthese 34 (4):397 - 421.score: 30.0
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  27. James H. Fetzer (1986). Methodological Individualism: Singular Causal Systems and Their Population Manifestations. Synthese 68 (1):99 - 128.score: 30.0
    The purpose of this essay is to investigate the properties of singular causal systems and their population manifestations, with special concern for the thesis of methodological individualism, which claims that there are no properties of social groups that cannot be adequately explained exclusively by reference to properties of individual members of those groups, i.e., at the level of individuals. Individuals, however, may be viewed as singular causal systems, i.e., as instantiations of (arrangements of) dispositional properties. From this perspective, methodological individualism (...)
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  28. Paul Sheldon Davies, James H. Fetzer & Thomas R. Foster (1995). Logical Reasoning and Domain Specificity. Biology and Philosophy 10 (1):1-37.score: 30.0
    The social exchange theory of reasoning, which is championed by Leda Cosmides and John Tooby, falls under the general rubric evolutionary psychology and asserts that human reasoning is governed by content-dependent, domain-specific, evolutionarily-derived algorithms. According to Cosmides and Tooby, the presumptive existence of what they call cheater-detection algorithms disconfirms the claim that we reason via general-purpose mechanisms or via inductively acquired principles. We contend that the Cosmides/Tooby arguments in favor of domain-specific algorithms or evolutionarily-derived mechanisms fail and that the notion (...)
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  29. James H. Fetzer (1999). Mental Models: Reasoning Without Rules. Minds and Machines 9 (1):119-126.score: 30.0
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  30. James Fetzer (forthcoming). Carl Hempel. Stanford Encyclopedia of Philosophy.score: 30.0
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  31. James H. Fetzer (1977). Reichenbach, Reference Classes, and Single Case 'Probabilities'. Synthese 34 (2):185 - 217.score: 30.0
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  32. James H. Fetzer, The TTT is Not the Final Word.score: 30.0
    My purpose is to explain, first, that there is an alternative to Harnad's version of the symbol grounding problem, which is known as the problem of primitives; second, that there is an alternative to his solution (which is externalist) in the form of a dispositional conception (which is internalist); and, third, that, while the TTT, properly understood, may provide partial and fallible evidence for the presence of similar mental powers, it cannot supply conclusive proof, because more than observable symbolic manipuation (...)
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  33. James H. Fetzer (1991). Book Review:Scientific Explanation Philip Kitcher, Wesley C. Salmon; Four Decades of Scientific Explanation Wesley C. Salmon. [REVIEW] Philosophy of Science 58 (2):288-.score: 30.0
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  34. James H. Fetzer (1987). Book Review:Scientific Explanation and the Causal Structure of the World Wesley Salmon. [REVIEW] Philosophy of Science 54 (4):597-.score: 30.0
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  35. James H. Fetzer (1974). A Single Case Propensity Theory of Explanation. Synthese 28 (2):171 - 198.score: 30.0
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  36. James H. Fetzer (1978). On Mellor on Dispositions. Philosophia 7 (3-4):651-660.score: 30.0
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  37. James H. Fetzer (1982). Probabilistic Explanations. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1982:194 - 207.score: 30.0
    The purpose of this paper is (a) to provide a systematic defense of the single-case propensity account of probabilistic explanation from the criticisms advanced by Hanna and by Humphreys and (b) to offer a critical appraisal of the aleatory conception advanced by Humphreys and of the deductive-nomological-probabilistic approach Railton has proposed. The principal conclusion supported by this analysis is that the Requirements of Maximal Specificity and of Strict Maximal Specificity afford the foundation for completely objective explanations of probabilistic (...)
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  38. James H. Fetzer (1999). Deduction and Mental Models. Minds and Machines 9 (1):105-110.score: 30.0
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  39. James H. Fetzer (1970). Dispositional Probabilities. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1970:473 - 482.score: 30.0
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  40. James H. Fetzer & Paul W. Humphreys (1995). Editorial Preface. Synthese 104 (2):177-177.score: 30.0
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  41. James H. Fetzer (1983). Philosophical Foundations of Probability Theory. Philosophical Books 24 (3):165-167.score: 30.0
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  42. James H. Fetzer (2000). Computing is at Best a Special Kind of Thinking. In The Proceedings of the Twentieth World Congress of Philosophy, Volume 9: Philosophy of Mind. Charlottesville: Philosophy Doc Ctr.score: 30.0
    When computing is defined as the causal implementation of algorithms and algorithms are defined as effective decision procedures, human thought is mental computation only if it is governed by mental algorithms. An examination of ordinary thinking, however, suggests that most human thought processes are non-algorithmic. Digital machines, moreover, are mark-manipulating or string-processing systems whose marks or strings do not stand for anything for those systems, while minds are semiotic (or “signusing”) systems for which signs stand for other things for those (...)
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  43. James H. Fetzer (1996). Computer Reliability and Public Policy: Limits of Knowledge of Computer-Based Systems. Social Philosophy and Policy 13 (02):229-.score: 30.0
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  44. James H. Fetzer (2002). Introduction. Synthese 132 (1-2):5-8.score: 30.0
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  45. James H. Fetzer (2002). In Memoriam: Wesley C. Salmon (1925-2001). Synthese 132 (1-2):1 - 3.score: 30.0
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  46. James H. Fetzer (1999). The Role Of Models In Computer Science. The Monist 82 (1):20-36.score: 30.0
    Taking Brian Cantwell Smith’s study, “Limits of Correctness in Computers,” as its point of departure, this article explores the role of models in computer science. Smith identifies two kinds of models that play an important role, where specifications are models of problems and programs are models of possible solutions. Both presuppose the existence of conceptualizations as ways of conceiving the world “in certain delimited ways.” But high-level programming languages also function as models of virtual (or abstract) machines, while low-level programming (...)
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  47. James H. Fetzer (1983). Wolgast's Paradoxes of Knowledge. Philosophia 12 (3-4):403-421.score: 30.0
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  48. James H. Fetzer (1975). Achinstein's Law and Explanation:Law and Explanation: An Essay in the Philosophy of Science Peter Achinstein. Philosophy of Science 42 (3):320-.score: 30.0
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  49. James H. Fetzer (1978). Book Review:The Philosophy of Karl Popper Robert John Ackermann. [REVIEW] Philosophy of Science 45 (3):491-.score: 30.0
  50. James H. Fetzer (ed.) (1993). Foundations of Philosophy of Science: Recent Developments. Paragon House.score: 30.0
  51. James H. Fetzer (1994). Mental Algorithms: Are Minds Computational Systems? Pragmatics and Cognition 21:1-29.score: 30.0
  52. James H. Fetzer (1975). Review: Achinstein's Law and Explanation. [REVIEW] Philosophy of Science 42 (3):320 - 333.score: 30.0
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  53. James H. Fetzer (1972). Statistical Explanations. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1972:337 - 347.score: 30.0
    The purpose of this paper is to provide a systematic appraisal of the covering law and statistical relevance theories of statistical explanation advanced by Carl G. Hempel and by Wesley C. Salmon, respectively. The analysis is intended to show that the difference between these accounts is inprinciple analogous to the distinction between truth and confirmation, where Hempel's analysis applies to what is taken to be the case and Salmon's analysis applies to what is the case. Specifically, it is argued (a) (...)
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  54. James H. Fetzer (1984). Book Review:The Nature of Explanation Peter Achinstein. [REVIEW] Philosophy of Science 51 (3):516-.score: 30.0
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  55. Mustafa U. Kiziltan, William J. Bain & Canizares M. Anita (1990). Postmodern Conditions: Rethinking Public Education. Educational Theory 40 (3):351-369.score: 30.0
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  56. James H. Fetzer (ed.) (1988). Aspects of AI. D.score: 30.0
  57. James H. Fetzer (1992). Connectionism and Cognition: Why Fodor and Pylyshyn Are Wrong. In A. Clark & Ronald Lutz (eds.), Connectionism in Context. Springer-Verlag.score: 30.0
  58. James H. Fetzer (1997). Escaping the Propositional Prison. The Monist 80 (3):368-388.score: 30.0
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  59. James H. Fetzer (1984). Freedom with Causation.score: 30.0
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  60. James H. Fetzer (1993). Glossary of Epistemology/Philosophy of Science. Paragon House.score: 30.0
     
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  61. Dirk Fetzer (2007). Jacobis Philosophie des Unbedingten. Schöningh.score: 30.0
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  62. James H. Fetzer (1989). Language and Mentality: Computational, Representational, and Dispositional Conceptions. Behaviorism 17:21-39.score: 30.0
  63. James H. Fetzer (1984). Macarthur Lecture No.score: 30.0
     
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  64. James H. Fetzer (1975). On the Historical Explanation of Unique Events. Theory and Decision 6 (1):87-97.score: 30.0
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  65. James H. Fetzer (1991). Philosophy and Cognitive Science. Paragon House.score: 30.0
  66. James H. Fetzer (ed.) (1984). Principles of Philosophical Reasoning. Rowman & Allanheld.score: 30.0
     
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  67. James H. Fetzer (1993). Philosophy of Science. Paragon House Publishers.score: 30.0
  68. James H. Fetzer (1974). The Likeness of Lawlikeness. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1974:377 - 391.score: 30.0
    The thesis of this paper is that extensional language alone provides an essentially inadequate foundation for the logical formalization of any lawlike statement. The arguments presented are intended to demonstrate that lawlike sentences are logically general dispositional statements requiring an essentially intensional reduction sentence formulation. By introducing a non-extensional logical operator, the 'fork', the difference between universal and statistical laws emerges in a distinction between dispositional predicates of universal strength as opposed to those of merely statistical strength. While the logical (...)
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  69. J. H. Fetzer & P. Humphreys (eds.) (1998). The New Theory of Reference: Kripke, Marcus, and its Origins. Kluwer.score: 30.0
  70. James H. Fetzer (2000). The Proceedings of the Twentieth World Congress of Philosophy, Volume 9: Philosophy of Mind. Charlottesville: Philosophy Doc Ctr.score: 30.0
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  71. James H. Fetzer (1992). What's Wrong with Salmon's History: The Third Decade. Philosophy of Science 59 (2):246-262.score: 30.0
    My purpose here is to elaborate the reasons I maintain that Salmon has not been completely successful in reporting the history of work on explanation. The most important limitation of his account is that it does not emphasize the critical necessity to embrace a suitable conception of probability in the development of the theory of probabilistic explanation.
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  72. Paul Humphreys & James Fetzer (eds.) (1998). The New Theory of Reference. Kluwer.score: 30.0
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  73. James H. Fetzer (1981). Book Review:Causal Necessity Brian Skyrms. [REVIEW] Philosophy of Science 48 (2):329-.score: 30.0
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  74. P. Tolbert Leslie, A. Oland Lynne, C. Christensen Thomas & R. Goriely Anita (2003). Neuronal and Glial Morphology in Olfactory Systems: Significance for Information-Processing and Underlying Developmental Mechanisms. Brain and Mind 4 (1).score: 30.0
    The shapes of neurons and glial cells dictate many important aspects of their functions. In olfactory systems, certain architectural features are characteristics of these two cell types across a wide variety of species. The accumulated evidence suggests that these common features may play fundamental roles in olfactoryinformation processing. For instance, the primary olfactory neuropil in most vertebrate and invertebrate olfactory systems is organized into discrete modules called glomeruli. Inside each glomerulus, sensory axons and CNS neurons branch and synapse in patterns (...)
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  75. Jennifer Uleman (2006). Guilt, Love, and What We Want: Commentary on Anita Superson's "Privilege, Immorality, and Responsibility for Attending to the 'Facts About Humanity'". Symposia on Gender, Race, and Philosophy 2 (1).score: 9.0
  76. Eugene Rosam (1996). Reply to Anita Catlin. HEC Forum 8 (4):208-211.score: 9.0
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  77. Lisa Tessman (2011). The Moral Skeptic. By Anita Superson. Hypatia 26 (4):883-887.score: 9.0
  78. Claudia Card (2003). Anita M. Superson and Ann E. Cudd, Eds., Theorizing Backlash: Philosophical Reflections on the Resistance to Feminism:Theorizing Backlash: Philosophical Reflections on the Resistance to Feminism. [REVIEW] Ethics 114 (1):193-195.score: 9.0
  79. Neera K. Badhwar (2010). Superson, Anita M. The Moral Skeptic . Oxford: Oxford University Press, 2009 . Pp. 250. $24.95 (Paper). Ethics 120 (3):635-639.score: 9.0
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  80. Monima Chadha, Anita Avramides : Other Minds.score: 9.0
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  81. Jussi Suikkanen (2009). Review of Anita M. Superson, The Moral Skeptic. [REVIEW] Notre Dame Philosophical Reviews 2009 (7).score: 9.0
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  82. Darren Whobrey (2001). Machine Mentality and the Nature of the Ground Relation. Minds and Machines 11 (3):307-346.score: 9.0
    John Searle distinguished between weak and strong artificial intelligence (AI). This essay discusses a third alternative, mild AI, according to which a machine may be capable of possessing a species of mentality. Using James Fetzer's conception of minds as semiotic systems, the possibility of what might be called ``mild AI'' receives consideration. Fetzer argues against strong AI by contending that digital machines lack the ground relationship required of semiotic systems. In this essay, the implementational nature of semiotic processes (...)
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  83. P. Bloomfield (2011). The Moral Skeptic, by Anita M. Superson. Mind 120 (479):914-917.score: 9.0
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  84. Paul Teller (1974). Professor Fetzer on Epistemic Possibility. Philosophia 4 (2-3):337-338.score: 9.0
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  85. Alan H. Goldman (2000). Review of Anita Silvers, David Wasserman, and Mary Mahowald, Disability, Difference, Discrimination: Perspectives on Justice in Bioethics and Public Policy:Disability, Difference, Discrimination: Perspectives on Justice in Bioethics and Public Policy. [REVIEW] Ethics 110 (4):873-875.score: 9.0
  86. J. Keown (2000). Physician-Assisted Suicide: Expanding the Debate: Edited by Margaret P Battin, Rosamund Rhodes and Anita Silvers, New York and London, Routledge, 1998, 463 Pages, Pound45. [REVIEW] Journal of Medical Ethics 26 (4):291-291.score: 9.0
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  87. Joan Callahan (2001). Book Review: Leslie Pickering Francis and Anita Silvers. Americans with Disabilities: Exploring Implications of the Law for Individuals and Institutions New York: Routledge, 2000. [REVIEW] Hypatia 16 (4):147-155.score: 9.0
  88. Judith Wagner DeCew (2006). Book Review: Anita Allen. Why Privacy Isn't Everything: Feminist Reflections on Personal Accountability. Lanham, Md.: Rowman & Littlefield, 2003. [REVIEW] Hypatia 21 (1):227-231.score: 9.0
  89. Richard Wyatt (2003). James H. Fetzer, Computers and Cognition: Why Minds Are Not Machines, Dordrecht: Kluwer, 2001, XIX + 323 Pp., $128.00 (Hardcover), ISBN 0-792-36615-. [REVIEW] Minds and Machines 13 (3):435-441.score: 9.0
  90. Mary Ann Gardell Cutter (1996). Ambiguities and Irresolvable Tensions in the Ada: A Reply to Loretta M. Kopelman and Anita Silvers. Journal of Medicine and Philosophy 21 (2).score: 9.0
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  91. David Wasserman (1994). Impairment, Disadvantage, and Equality: A Reply to Anita Silvers. Journal of Social Philosophy 25 (3):181-188.score: 9.0
  92. Eva Feder Kittay (2002). Book Review: Anita Silvers, David Wasserman, and Mary B. Mahowald. Disability, Difference, and Discrimination: Perspectives on Justice in Bioethics and Public Policy. New York: Rowman & Littlefield, 1998. [REVIEW] Hypatia 17 (1):209-213.score: 9.0
  93. H. J. Rose (1955). Virgile: Choix de Bucoliques. Texte Commenté Par Anita Ruelle. Pp. 70. Namur: Wesmael-Charlier, 1954. Paper, 34 B. Fr. The Classical Review 5 (3-4):320-321.score: 9.0
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  94. Douglas Shrader (1983). Book Review:Scientific Knowledge: Causation, Explanation, and Corroboration James H. Fetzer. [REVIEW] Philosophy of Science 50 (4):660-.score: 9.0
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  95. Nadine Faulkner (2005). Theorizing Backlash: Philosophical Reflections on the Resistance to Feminism Edited by Anita M. Superson and Ann E. Cudd Studies in Social, Political, and Legal Philosophy Lanham, MD: Rowman & Littlefield, 2002, Xxiii + 269 Pp. [REVIEW] Dialogue 44 (01):201-.score: 9.0
  96. H. B. Enderton (2002). Review: Anita Burdman Feferman, From Trotsky to Godel. The Life of Jean van Heijenoort. [REVIEW] Bulletin of Symbolic Logic 8 (1):104-104.score: 9.0
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  97. James H. Moor (2000). Thinking Must Be Computation of the Right Kind. In The Proceedings of the Twentieth World Congress of Philosophy, Volume 9: Philosophy of Mind. Charlottesville: Philosophy Doc Ctr.score: 9.0
    In this paper I argue for a computational theory of thinking that does not eliminate the mind. In doing so, I will defend computationalism against the arguments of John Searle and James Fetzer, and briefly respond to other common criticisms.
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  98. Joan C. Callahan (2001). Review of Americans with Disabilities: Exploring Implications of the Law for Individuals and Institutions by Anita Silvers and Leslie Pickering Francis. [REVIEW] Hypatia 16 (4).score: 9.0
  99. Tony Doyle (forthcoming). Anita Allen: Unpopular Privacy: What Must We Hide? Ethics and Information Technology.score: 9.0
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  100. E. Mendelson (2005). Anita Burdman Feferman and Solomon Feferman. Shape Alfred Tarski: Life and Logic. Cambridge: Cambridge University Press, 2004. Pp. VI + 435. Isbn 0-521-80240-. [REVIEW] Philosophia Mathematica 13 (2):231-232.score: 9.0
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