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  1. Avshalom M. Adam (2000). Farewell to Certitude: Einstein's Novelty on Induction and Deduction, Fallibilism. [REVIEW] Journal for General Philosophy of Science 31 (1):19-37.
    In the late 19th century great changes in theories of light and electricity were in direct conflict with certitude, the view that scientific knowledge is infallible. What is, then, the epistemic status of scientific theory? To resolve this issue Duhem and Poincaré proposed images of fallible knowledge, Instrumentalism and Conventionalism, respectively. Only in 1919–1922, after Einstein's relativity was published, he offered arguments to support Fallibilism, the view that certainty cannot be achieved in science. Though Einstein did not consider Duhem's Instrumentalism, (...)
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  2. T. R. Addis & D. C. Gooding (2008). Simulation Methods for an Abductive System in Science. Foundations of Science 13 (1):37-52.
    We argue that abduction does not work in isolation from other inference mechanisms and illustrate this through an inference scheme designed to evaluate multiple hypotheses. We use game theory to relate the abductive system to actions that produce new information. To enable evaluation of the implications of this approach we have implemented the procedures used to calculate the impact of new information in a computer model. Experiments with this model display a number of features of collective belief-revision leading to consensus-formation, (...)
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  3. Joseph Agassi (1973). Testing as a Bootstrap Operation in Physics. Journal for General Philosophy of Science 4 (1):1-24.
  4. F. Michael Akeroyd (1990). The Challenge to Lakatos Restated. British Journal for the Philosophy of Science 41 (3):437-439.
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  5. F. Michael Akeroyd (1986). A Challenge to the Followers of Lakatos. British Journal for the Philosophy of Science 37 (3):359-362.
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  6. Francisco J. Ayala (1994). On the Scientific Method, Its Practice and Pitfalls. History and Philosophy of the Life Sciences 16 (2):205 - 240.
    This paper sets forth a familiar theme, that science essentially consists of two interdependent episodes, one imaginative, the other critical. Hypotheses and other imaginative conjectures are the initial stage of scientific inquiry because they provide the incentive to seek the truth and a clue as to where to find it. But scientific conjectures must be subject to critical examination and empirical testing. There is a dialogue between the two episodes; observations made to test a hypothesis are the inspiration for new (...)
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  7. Arianna Betti (2010). Leśniewski's Characteristica Universalis. Synthese 174 (2):295-314.
    Leśniewski’s systems deviate greatly from standard logic in some basic features. The deviant aspects are rather well known, and often cited among the reasons why Leśniewski’s work enjoys little recognition. This paper is an attempt to explain why those aspects should be there at all. Leśniewski built his systems inspired by a dream close to Leibniz’s characteristica universalis: a perfect system of deductive theories encoding our knowledge of the world, based on a perfect language. My main claim is that Leśniewski (...)
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  8. Arianna Betti & Willem R. de Jong (2010). Introduction. Synthese 174 (2):181-183.
  9. Michael A. Bishop & J. D. Trout (2005). Epistemology and the Psychology of Human Judgment. OUP USA.
    Bishop and Trout here present a unique and provocative new approach to epistemology (the theory of human knowledge and reasoning). Their approach aims to liberate epistemology from the scholastic debates of standard analytic epistemology, and treat it as a branch of the philosophy of science. The approach is novel in its use of cost-benefit analysis to guide people facing real reasoning problems and in its framework for resolving normative disputes in psychology. Based on empirical data, Bishop and Trout show how (...)
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  10. David Botting (2012). The Paradox of Analogy. Informal Logic 32 (1):98-115.
    I will show that there is a type of analogical reasoning that instantiates a pattern of reasoning in confirmation theory that is considered at best paradoxical and at worst fatal to the entire syntactical approach to confirmation and explanation. However, I hope to elaborate conditions under which this is a sound (although not necessarily strong) method of reasoning.
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  11. Seamus Bradley, Scientific Uncertainty: A User's Guide. Grantham Institute on Climate Change Discussion Paper.
    There are different kinds of uncertainty. I outline some of the various ways that uncertainty enters science, focusing on uncertainty in climate science and weather prediction. I then show how we cope with some of these sources of error through sophisticated modelling techniques. I show how we maintain confidence in the face of error.
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  12. Matthew J. Brown (2012). John Dewey's Logic of Science. Hopos 2 (2):258-306.
    In recent years, pragmatism in general and John Dewey in particular have been of increasing interest to philosophers of science. Dewey's work provides an interesting alternative package of views to those which derive from the logical empiricists and their critics, on problems of both traditional and more recent vintage. Dewey's work ought to be of special interest to recent philosophers of science committed to the program of analyzing ``science in practice.'' The core of Dewey's philosophy of science is his theory (...)
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  13. Wendy Cadge (2012). Possibilities and Limits of Medical Science: Debates Over Double-Blind Clinical Trials of Intercessory Prayer. Zygon 47 (1):43-64.
    Abstract. This article traces the intellectual history of scientific studies of intercessory prayer published in English between 1965 and the present by focusing on the conflict and discussion they prompted in the medical literature. I analyze these debates with attention to how researchers articulate the possibilities and limits medical science has for studying intercessory prayer over time. I delineate three groups of researchers and commentators: those who think intercessory prayer can and should be studied scientifically, those who are more skeptical (...)
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  14. H. G. Callaway (2014). Arthur S. Eddington, The Nature of the Physical World, An Annotated Edition. Cambridge Scholars Publishing.
    Arthur S. Eddington, FRS, (1882–1944) was one of the most prominent British scientists of his time. He made major contributions to astrophysics and to the broader understanding of the revolutionary theories of relativity and quantum mechanics. He is famed for his astronomical observations of 1919, confirming Einstein’s prediction of the curving of the paths of starlight, and he was the first major interpreter of Einstein’s physics to the English-speaking world. His 1928 book, The Nature of the Physical World, here re-issued (...)
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  15. Michael Carignan (2003). Analogical Reasoning in Victorian Historical Epistemology. Journal of the History of Ideas 64 (3):445-464.
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  16. J. Dance (1998). Barry Gower, Scientific Method: A N Historical and Philosophical Introduction. Journal of Consciousness Studies 5:121-121.
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  17. Marcelo Dascal (2001). Controversies and Epistemology. The Proceedings of the Twentieth World Congress of Philosophy 2001:159-192.
    I present and defend the thesis that the impasse at which the philosophy and history of science find themselves in the last couple of decades is due, to a large extent, either to the complete neglect or to a misguided treatment of the role of scientific controversies in the evolution of science. In order to do so, I first provide a preliminary clarification of the impasse to which I refer. I go on to explain why I see the study of (...)
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  18. Paul Dicken (2010). Constructive Empiricism: Epistemology and the Philosophy of Science. Palgrave Macmillan.
  19. Katherine Dunlop (2013). Isaac Newton's Scientific Method: Turning Data Into Evidence About Gravity and Cosmology by William L. Harper (Review). Journal of the History of Philosophy 51 (3):489-491.
    Not a full treatment of Newton’s scientific method, this book discusses his optical research only in passing (342–43). Its subtitle better indicates its scope: it focuses narrowly on the argument for universal gravitation in Book III of the Principia. The philosophical project is to set out an “ideal of empirical success” realized by the argument. Newton claims his method is to “deduce” propositions “from phenomena.” On Harper’s interpretation Newton’s phenomena are patterns of data, which are used to measure “parameters” by (...)
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  20. Michael Dunn & Jonathan Ives (2009). Methodology, Epistemology, and Empirical Bioethics Research: A Constructive/Ist Commentary. American Journal of Bioethics 9 (6):93-95.
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  21. Barbara Von Eckardt (1990). Some Remarks on Laudan's Theory of Scientific Rationality. Journal of Philosophical Research 15:153-167.
    When is it rational to pursue a research tradition? In Progress and Its Problems, Laudan suggests that if a research tradition RT has a higher rate of progress than any of its rivals, where the rate of progress of an RT is the problem solving effectiveness of its theories over time, then it is rational to pursue RT. In this paper I offer a number of criticisms of this suggestion, with special attention to the current controversy over the rational pursuability (...)
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  22. James K. Feibleman (1959). Darwin and Scientific Method. Tulane Studies in Philosophy 8:3-14.
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  23. John F. Fox (1996). Towards Metamethodology: For the History and Philosophy of Science. In P. Riggs (ed.), Natural Kinds, Laws of Nature and Scientific Methodology. Kluwer Academic Publishers. 103--121.
    Much philosophy of science is methodology of science. How should one go about doing and evaluating it? The question is one of the methodology of methodology, i.e. of metamethodology. There is a vague thesis common to Descartes and more recent philosophers such as Quine and Lakatos: that what is good methodology, good evidence, good reason for accepting, rejecting or revising beliefs in mathematics and in the sciences properly so called, does not differ in significant kind from what is good methodology, (...)
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  24. Karyn Freedman (1999). Laudan's Naturalistic Axiology. Philosophy of Science 66 (3):537.
    Doppelt (1986,1990), Siegel (1990), and Rosenberg (1996) argue that the pivotal feature of Laudan's normative naturalism, namely his axiology, lacks a naturalistic foundation. In this paper I show that this objection turns on a misunderstanding of Laudan's use of the term 'naturalism'. Specifically, I argue that there are two important senses of naturalism running through Laudan's work. Once these two strands are made explicit, the objection raised by Doppelt and others simply disappears.
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  25. James W. Garrison (1988). Hintikka, Laudan and Newton: An Interrogative Model of Scientific Inquiry. Synthese 74 (2):145 - 171.
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  26. Hugh G. Gauch (2012). Scientific Method in Brief. Cambridge University Press.
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  27. Alexander Gebharter (2013). Solving the Flagpole Problem. Journal for General Philosophy of Science 44 (1):63-67.
    In this paper I demonstrate that the causal structure of flagpole-like systems can be determined by application of causal graph theory. Additional information about the ordering of events in time or about how parameters of the systems of interest can be manipulated is not needed.
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  28. Alexander Gebharter & Gerhard Schurz (2012). For a Better Understanding of Causality. Metascience 21 (3):643-648.
    For a better understanding of causality Content Type Journal Article Category Essay Review Pages 1-6 DOI 10.1007/s11016-012-9648-3 Authors Alexander Gebharter, Department of Philosophy, Heinrich-Heine-University Düsseldorf, Universitätsstraße 1, 40225 Düsseldorf, Germany Gerhard Schurz, Department of Philosophy, Heinrich-Heine-University Düsseldorf, Universitätsstraße 1, 40225 Düsseldorf, Germany Journal Metascience Online ISSN 1467-9981 Print ISSN 0815-0796.
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  29. Robert Geroch & James B. Hartle (1986). Computability and Physical Theories. Foundations of Physics 16 (6):533-550.
    The familiar theories of physics have the feature that the application of the theory to make predictions in specific circumstances can be done by means of an algorithm. We propose a more precise formulation of this feature—one based on the issue of whether or not the physically measurable numbers predicted by the theory are computable in the mathematical sense. Applying this formulation to one approach to a quantum theory of gravity, there are found indications that there may exist no such (...)
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  30. Clark Glymour (1991). The Hierarchies of Knowledge and the Mathematics of Discovery. Minds and Machines 1 (1):75-95.
    Rather than attempting to characterize a relation of confirmation between evidence and theory, epistemology might better consider which methods of forming conjectures from evidence, or of altering beliefs in the light of evidence, are most reliable for getting to the truth. A logical framework for such a study was constructed in the early 1960s by E. Mark Gold and Hilary Putnam. This essay describes some of the results that have been obtained in that framework and their significance for philosophy of (...)
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  31. Wenceslao J. Gonzalez (2012). Methodological Universalism in Science and its Limits Imperialism Versus Complexity. Poznan Studies in the Philosophy of the Sciences and the Humanities 100 (1):155-175.
    Universalism in science, when conceived in methodological terms, leads to the problem of the limits of science. On the one hand, there is “methodological imperialism” which in principle involves a form of universalism. On the other hand, there is the multivariate complexity – structural and dynamic, as well as epistemological and ontological – which represents a huge problem for methodological universalism, as may be seen with the obstacles for scientific prediction. Within the context of the limits of science, there is (...)
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  32. Adam Grobler (1990). Between Rationalism and Relativism. On Larry Laudan's Model of Scientific Rationality. British Journal for the Philosophy of Science 41 (4):493-507.
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  33. Patrick Grüneberg (2010). Die Ambivalenz zwischen Therapie und Leistung. In Christoph Asmuth (ed.), Was ist Doping? Fakten und Probleme der aktuellen Diskussion. Transcript. 117--137.
    Die Frage nach der Definition von Doping basiert nicht zuletzt auf naturwissenschaftlicher Forschung. Aus einer naturwissenschaftlichen Perspektive könnte man sogar behaupten, dass die aktuelle Dopingdebatte ihre Ursachen gerade in der pharmazeutischen Forschung hat, da sich das Problem des Dopings erst mit dem Vorhandensein entsprechender Mittel bzw. Methoden zur Leistungssteigerung stellt. Allerdings wird die Frage der Dopingdefinition im Folgenden nicht auf einen naturwissenschaftlichen Referenzrahmen reduziert, wie dies in den aktuellen Dopingdefinitionen häufig der Fall ist. Vielmehr werde ich die spezifische Rolle naturwissenschaftlicher (...)
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  34. Hélène Guillemot (2010). Connections Between Simulations and Observation in Climate Computer Modeling. Scientist's Practices and “Bottom-Up Epistemology” Lessons. Studies in History and Philosophy of Science Part B 41 (3):242-252.
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  35. Mario Günther, A Defence of Falsificationism Against Feyerabend's Epistemological Anarchism Using the Example of Galilei's Observations with the Telescope.
    I confront Feyerabend's position and critical rationalism in order to have a foundation or starting point for my (historical) investigation. The main difference of his position towards falsificationism is the belief that different theories cannot be discussed rationally. Feyerabend is convinced that Galilei's observations with the telescope in the historical context of the Copernican revolution supports his criticism. In particular, he argues that the Copernican theory was supported by deficient hypotheses, and falsifications were disposed by ad hoc hypotheses and propaganda. (...)
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  36. Ian Hacking (1965). Salmon's Vindication of Induction. Journal of Philosophy 62 (10):260-266.
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  37. Gilbert Harman (1973). Thought. Princeton University Press.
  38. Stephan Hartmann (2005). Transdisziplinarität – Eine Herausforderung für Die Wissenschaftstheorie. In Gereon Wolters & Martin Carrier (eds.), Homo Sapiens und Homo Faber. de Gruyter. 335--343.
    Die zeitgenössische Wissenschaftstheorie leidet unter ähnlichen Problemen wie die Wissenschaften, mit denen sie sich befasst. So nimmt auch in der Wissenschaftstheorie die Spezialisierung stark zu, und bei vielen der behandelten Fragestellungen geht es einzig um Detailprobleme, die sich aus einem sich verselbständigenden Diskussionszusammenhang entwickelt haben, wobei der Bezug zur jeweiligen Ausgangsfrage und die größere philosophische Perspektive leicht aus den Augen verloren geht.
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  39. José Hernandez-Orallo (1998). A Computational Definition of 'Consilience'. Philosophica 61 (1):19-37.
    This paper defines in a formal and computational way the notion of ‘consilience’, a term introduced by Whewell in 1847 for the evaluation of scientific theories. Informally, as has been used to date, a model or theory is ‘consilient’ if it is predictive, explanatory and unifies the evide-nce. Centred in a constructive framework, where new terms can be intro-duced, we essay a formalisation of the idea of unification based on the avoidance of ‘sepa-ration’. However, it is soon manifest that this (...)
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  40. Mary B. Hesse (1974). The Structure of Scientific Inference. [London]Macmillan.
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  41. Gábor Hofer-Szabó & Miklós Rédei (2006). Reichenbachian Common Cause Systems of Arbitrary Finite Size Exist. Foundations of Physics 36 (5):745-756.
    A partition $\{C_i\}_{i\in I}$ of a Boolean algebra Ω in a probability measure space (Ω, p) is called a Reichenbachian common cause system for the correlation between a pair A,B of events in Ω if any two elements in the partition behave like a Reichenbachian common cause and its complement; the cardinality of the index set I is called the size of the common cause system. It is shown that given any non-strict correlation in (Ω, p), and given any finite (...)
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  42. Marcus Hutter (2010). Observer Localization in Multiverse Theories. In Harald Fritzsch & K. K. Phua (eds.), Proceedings of the Conference in Honour of Murray Gell-Mann's 80th Birthday. World Scientific.
    The progression of theories suggested for our world, from ego- to geo- to helio-centric models to universe and multiverse theories and beyond, shows one tendency: The size of the described worlds increases, with humans being expelled from their center to ever more remote and random locations. If pushed too far, a potential theory of everything (TOE) is actually more a theories of nothing (TON). Indeed such theories have already been developed. I show that including observer localization into such theories is (...)
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  43. Nicholaos Jones (2013). Don't Blame the Idealizations. Journal for General Philosophy of Science 44 (1):85-100.
    Idealizing conditions are scapegoats for scientific hypotheses, too often blamed for falsehood better attributed to less obvious sources. But while the tendency to blame idealizations is common among both philosophers of science and scientists themselves, the blame is misplaced. Attention to the nature of idealizing conditions, the content of idealized hypotheses, and scientists’ attitudes toward those hypotheses shows that idealizing conditions are blameless when hypotheses misrepresent. These conditions help to determine the content of idealized hypotheses, and they do so in (...)
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  44. John R. Josephson (1998). Abduction-Prediction Model of Scientific Inference Reflected in a Prototype System for Model-Based Diagnosis. Philosophica 61.
    This paper describes in some detail a pattern of justification which seems to be part of common sense logic and also part of the logic of scientific investigations. Calling this pattern “abduction,” the paper lays out an “abduction-prediction” model of scientific inference as an update to the traditional hypothetico-deductive model. According to this newer model, scientific theories receive their claims for acceptance and belief from the abductive arguments that support them, and the processes of scientific discovery aim to develop theories (...)
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  45. Geert Keil (2003). 'Science Itself Teaches'. A Fresh Look at Quine's Naturalistic Metaphilosophy. Grazer Philosophische Studien 66 (1):253-280.
    Quine famously holds that "philosophy is continuous with natural science". In order to find out what exactly the point of this claim is, I take up one of his preferred phrases and trace it through his writings, i.e., the phrase "Science itself teaches that …". Unlike Wittgenstein, Quine did not take much interest in determining what might be distinctive of philosophical investigations, or of the philosophical part of scientific investigations. I find this indifference regrettable, and I take a fresh look (...)
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  46. Kevin Kelly, Naturalism Logicized.
    The approach to scientific methodology developed in my recent book The Logic of Reliable Inquiry (LRI) shares many general features with that summarized in Larry Laudan’s concurrently published collection of papers Beyond Positivism and Relativism (BPR). Nonetheless, this fact might not be apparent, as my own work emphasizes mathematical theorems, whereas Laudan’s draws primarily upon historiography. It is, therefore, of some interest to discuss the extent of the agreement and the significance of the differences. More generally, the discussion will (I) (...)
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  47. Robert Klee (2000). Problems with Formal Models of Epistemic Entrenchment as Applied to Scientific Theories. Synthese 122 (3):313 - 320.
    Formal models of theory contraction entered the philosophicalliterature with the prototype model by Alchourrón, Gärdenfors,and Makinson (Alchourrón et al. 1985). One influential modelinvolves theory contraction with respect to a relation calledepistemic entrenchment which orders the propositions of a theoryaccording to their relative degrees of theoretical importance.Various postulates have been suggested for characterizingepistemic entrenchment formally. I argue here that threesuggested postulates produce inappropriately bizarre results whenapplied to scientific theories. I argue that the postulates callednoncovering, continuing up, and continuing down, implyrespectively that, (...)
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  48. Kevin B. Korb (2004). Introduction: Machine Learning as Philosophy of Science. Minds and Machines 14 (4):433-440.
    I consider three aspects in which machine learning and philosophy of science can illuminate each other: methodology, inductive simplicity and theoretical terms. I examine the relations between the two subjects and conclude by claiming these relations to be very close.
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  49. Henry Ely Kyburg (1990). Science & Reason. Oxford University Press.
    In this work Henry Kyburg presents his views on a wide range of philosophical problems associated with the study and practice of science and mathematics. The main structure of the book consists of a presentation of Kyburg's notions of epistemic probability and its use in the scientific enterprise i.e., the effort to modify previously adopted beliefs in the light of experience. Intended for cognitive scientists and people in artificial intelligence as well as for technically oriented philosophers, the book also provides (...)
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  50. Larry Laudan (1971). William Whewell on the Consilience of Inductions. The Monist 55 (3):368-391.
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