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  1. Samuel Alexander (2013). Fast-Collapsing Theories. Studia Logica:1-21.
    Reinhardt’s conjecture, a formalization of the statement that a truthful knowing machine can know its own truthfulness and mechanicalness, was proved by Carlson using sophisticated structural results about the ordinals and transfinite induction just beyond the first epsilon number. We prove a weaker version of the conjecture, by elementary methods and transfinite induction up to a smaller ordinal.
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  2. Samuel A. Alexander (2014). A Machine That Knows Its Own Code. Studia Logica 102 (3):567-576.
    We construct a machine that knows its own code, at the price of not knowing its own factivity.
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  3. Patrick Allo (2008). Vincent Hendricks, Mainstream and Formal Epistemology. [REVIEW] Erkenntnis 69 (3):427-432.
    As Vincent Hendricks remarks early on in this book, the formal and mainstream traditions of epistemic theorising have mostly evolved independently of each other. This initial impression is confirmed by a comparison of the main problems and methods practitioners in each tradition are concerned with. Mainstream epistemol- ogy engages in a dialectical game of proposing and challenging definitions of knowledge. Formal epistemologists proceed differently, as they design a wide variety of axiomatic and model-theoretic methods whose consequences they investigate independently of (...)
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  4. Amalia Amaya (2007). Formal Models of Coherence and Legal Epistemology. Artificial Intelligence and Law 15 (4):429-447.
    This paper argues that formal models of coherence are useful for constructing a legal epistemology. Two main formal approaches to coherence are examined: coherence-based models of belief revision and the theory of coherence as constraint satisfaction. It is shown that these approaches shed light on central aspects of a coherentist legal epistemology, such as the concept of coherence, the dynamics of coherentist justification in law, and the mechanisms whereby coherence may be built in the course of legal decision-making.
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  5. Brad Armendt (2014). Pragmatic Interests and Imprecise Belief. Philosophy of Science 80 (5):758-768.
    Does the strength of a particular belief depend upon the significance we attach to it? Do we move from one context to another, remaining in the same doxastic state concerning p yet holding a stronger belief that p in one context than in the other? For that to be so, a doxastic state must have a certain sort of context-sensitive complexity. So the question is about the nature of belief states, as we understand them, or as we think a theory (...)
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  6. Prasanta S. Bandyopadhyay & Malcolm Forster (eds.) (forthcoming). Handbook of the Philosophy of Statistics. Elsevier.
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  7. Jean-Roch Beausoleil (1989). The Metamathematics-Popperian Epistemology Connection and its Relation to the Logic of Turing's Programme. British Journal for the Philosophy of Science 40 (3):307-322.
    Turing's programme, the idea that intelligence can be modelled computationally, is set in the context of a parallel between certain elements from metamathematics and Popper's schema for the evolution of knowledge. The parallel is developed at both the formal level, where it hinges on the recursive structuring of Popper's schema, and at the contentual level, where a few key issues common to both epistemology and metamathematics are briefly discussed. In light of this connection Popper's principle of transference, akin to Turing's (...)
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  8. José Luis Bermúdez (2011). Decision Theory and Rationality. OUP Oxford.
    The concept of rationality is a common thread through the human and social sciences -- from political science to philosophy, from economics to sociology, and from management science to decision analysis. But what counts as rational action and rational behavior? José Luis Bermúdez explores decision theory as a theory of rationality. Decision theory is the mathematical theory of choice and for many social scientists it makes the concept of rationality mathematically tractable and scientifically legitimate. Yet rationality is a concept with (...)
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  9. Francesco Berto (2014). On Conceiving the Inconsistent. Proceedings of the Aristotelian Society 114 (1pt1):103-121.
    I present an approach to our conceiving absolute impossibilities—things which obtain at no possible world—in terms of ceteris paribus intentional operators: variably restricted quantifiers on possible and impossible worlds based on world similarity. The explicit content of a representation plays a role similar in some respects to the one of a ceteris paribus conditional antecedent. I discuss how such operators invalidate logical closure for conceivability, and how similarity works when impossible worlds are around. Unlike what happens with ceteris paribus counterfactual (...)
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  10. Gregor Betz (2010). Petitio Principii and Circular Argumentation as Seen From a Theory of Dialectical Structures. Synthese 175 (3):327-349.
    This paper investigates in how far a theory of dialectical structures sheds new light on the old problem of giving a satisfying account of the fallacy of petitio principii, or begging the question. It defends that (i) circular argumentation on the one hand and petitio principii on the other hand are two distinct features of complex argumentation, and that (ii) it is impossible to make general statements about the defectiveness of an argumentation that exhibits these features. Such an argumentation, in (...)
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  11. Cristina Bicchieri, Richard C. Jeffrey & Brian Skyrms (eds.) (1999). The Logic of Strategy. Oxford University Press.
    Edited by three leading figures in the field, this exciting volume presents cutting-edge work in decision theory by a distinguished international roster of contributors. These mostly unpublished papers address a host of crucial areas in the contemporary philosophical study of rationality and knowledge. Topics include causal versus evidential decision theory, game theory, backwards induction, bounded rationality, counterfactual reasoning in games and in general, analyses of the famous common knowledge assumptions in game theory, and evaluations of the normal versus extensive form (...)
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  12. Jens Christian Bjerring (2010). Non-Ideal Epistemic Spaces. Dissertation, Australian National University
    In a possible world framework, an agent can be said to know a proposition just in case the proposition is true at all worlds that are epistemically possible for the agent. Roughly, a world is epistemically possible for an agent just in case the world is not ruled out by anything the agent knows. If a proposition is true at some epistemically possible world for an agent, the proposition is epistemically possible for the agent. If a proposition is true at (...)
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  13. Luc Bovens & Stephan Hartmann (2005). Why There Cannot Be a Single Probabilistic Measure of Coherence. Erkenntnis 63 (3):361-374.
    Bayesian Coherence Theory of Justification or, for short, Bayesian Coherentism, is characterized by two theses, viz. (i) that our degree of confidence in the content of a set of propositions is positively affected by the coherence of the set, and (ii) that coherence can be characterized in probabilistic terms. There has been a longstanding question of how to construct a measure of coherence. We will show that Bayesian Coherentism cannot rest on a single measure of coherence, but requires a vector (...)
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  14. D. J. Bradley (2012). Four Problems About Self-Locating Belief. Philosophical Review 121 (2):149-177.
    This article defends the Doomsday Argument, the Halfer Position in Sleeping Beauty, the Fine-Tuning Argument, and the applicability of Bayesian confirmation theory to the Everett interpretation of quantum mechanics. It will argue that all four problems have the same structure, and it gives a unified treatment that uses simple models of the cases and no controversial assumptions about confirmation or self-locating evidence. The article will argue that the troublesome feature of all these cases is not self-location but selection effects.
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  15. Darren Bradley (2009). Multiple Universes and Observation Selection Effects. American Philosophical Quarterly 46 (1):72.
    The fine-tuning argument can be used to support the Many Universe hypothesis. The Inverse Gambler’s Fallacy objection seeks to undercut the support for the Many Universe hypothesis. The objection is that although the evidence that there is life somewhere confirms Many Universes, the specific evidence that there is life in this universe does not. I will argue that the Inverse Gambler’s Fallacy is not committed by the fine-tuning argument. The key issue is the procedure by which the universe with life (...)
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  16. Lara Buchak (2013). Belief, Credence, and Norms. Philosophical Studies (2):1-27.
    There are currently two robust traditions in philosophy dealing with doxastic attitudes: the tradition that is concerned primarily with all-or-nothing belief, and the tradition that is concerned primarily with degree of belief or credence. This paper concerns the relationship between belief and credence for a rational agent, and is directed at those who may have hoped that the notion of belief can either be reduced to credence or eliminated altogether when characterizing the norms governing ideally rational agents. It presents a (...)
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  17. Lara Buchak (2010). Instrumental Rationality, Epistemic Rationality, and Evidence-Gathering. Philosophical Perspectives 24 (1):85-120.
  18. Panayot Butchvarov (2008). Epistemology Dehumanized. In Quentin Smith (ed.), Epistemology: New Essays. Oxford University Press. 301.
    Fundamental disagreements in epistemology arise from legitimate differences of interest, not genuine conflict. It is because of such differences that there are three varieties of epistemology: naturalistic, subjective, and what I shall call epistemology-as-logic. All three have been with us at least since Socrates. My chief concern will be with the third, but I must begin with the first and second, which constitute standard epistemology.
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  19. Jake Chandler (2013). Acceptance, Aggregation and Scoring Rules. Erkenntnis 78 (1):201 - 217.
    As the ongoing literature on the paradoxes of the Lottery and the Preface reminds us, the nature of the relation between probability and rational acceptability remains far from settled. This article provides a novel perspective on the matter by exploiting a recently noted structural parallel with the problem of judgment aggregation. After offering a number of general desiderata on the relation between finite probability models and sets of accepted sentences in a Boolean sentential language, it is noted that a number (...)
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  20. Jake Chandler (2010). The Transmission of Support: A Bayesian Re-Analysis. [REVIEW] Synthese 176 (3):333 - 343.
    Crispin Wright’s discussion of the notion of ‘transmission-failure’ promises to have important philosophical ramifications, both in epistemology and beyond. This paper offers a precise, formal characterisation of the concept within a Bayesian framework. The interpretation given avoids the serious shortcomings of a recent alternative proposal due to Samir Okasha.
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  21. David Christensen (2007). Epistemic Self-Respect. Proceedings of the Aristotelian Society 107 (1pt3):319-337.
  22. David Christensen (1991). Clever Bookies and Coherent Beliefs. Philosophical Review 100 (2):229-247.
  23. John Corcoran (2007). 2007. Notes on the Founding of Logics and Metalogic: Aristotle, Boole, and Tarski. Eds. C. Martínez Et Al. Current Topics in Logic and Analytic Philosophy / Temas Actuales de Lógica y Filosofía Analítica. Imprenta Univeridade Santiago de Compostela. In C. Martínez (ed.), Current Topics in Logic and Analytic Philosophy /. 145-178.
  24. John Corcoran (1973). Meanings of Implication. Dialogos 9 (1):59-76.
    Thirteen meanings of 'implication' are described and compared. Among them are relations that have been called: logical implication, material implication,deductive implication, formal implication, enthymemic implication, and factual implication. In a given context, implication is the homogeneous two-place relation expressed by the relation verb 'implies'. For heuristic and expository reasons this article skirts many crucial issues including use-mention, the nature of the entities that imply and are implied, and the processes by which knowledge of these relations are achieved. This paper is (...)
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  25. John Corcoran (1972). Conceptual Structure of Classical Logic. Philosophy and Phenomenological Research 33 (1):25-47.
  26. George Couvalis (2011). A Modern Malignant Demon? Hume's Scepticism with Regard to Reason (Partly) Vindicated. In Craig Taylor Stephen Buckle (ed.), Hume and the Enlightenment. Chatto and Pickering. 105-115.
  27. Charles B. Cross (2004). A Correction to “Nonmonotonic Inconsistency” [Artificial Intelligence 149 (2003) 161–178]. Artificial Intelligence 160 (1-2):191-192.
    This note corrects an error in the statement and proof of Propositions 9 and 10 of [C. Cross, Nonmonotonic inconsistency, Artificial Intelligence 149 (2) (2003) 161–178]. Both results turn out to depend on the postulate of Consistency Preservation.
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  28. Charles B. Cross (2003). Nonmonotonic Inconsistency. Artificial Intelligence 149 (2):161-178.
    Nonmonotonic consequence is the subject of a vast literature, but the idea of a nonmonotonic counterpart of logical inconsistency—the idea of a defeasible property representing internal conflict of an inductive or evidential nature—has been entirely neglected. After considering and dismissing two possible analyses relating nonmonotonic consequence and a nonmonotonic counterpart of logical inconsistency, this paper offers a set of postulates for nonmonotonic inconsistency, an analysis of nonmonotonic inconsistency in terms of nonmonotonic consequence, and a series of results showing that nonmonotonic (...)
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  29. Henk de Regt, Samir Okasha & Stephan Hartmann (eds.) (forthcoming). Proceedings of EPSA09. Springer.
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  30. Franz Dietrich & Christian List, Probabilistic Opinion Pooling Generalised -- Part Two: The Premise-Based Approach.
    How can different individuals' probability functions on a given sigma-algebra of events be aggregated into a collective probability function? Classic approaches to this problem often require 'event-wise independence': the collective probability for each event should depend only on the individuals' probabilities for that event. In practice, however, some events may be 'basic' and others 'derivative', so that it makes sense first to aggregate the probabilities for the former and then to let these constrain the probabilities for the latter. We formalize (...)
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  31. Franz Dietrich & Christian List, Probabilistic Opinion Pooling.
    Suppose several individuals (e.g., experts on a panel) each assign probabilities to some events. How can these individual probability assignments be aggregated into a single collective probability assignment? This article reviews several proposed solutions to this problem. We focus on three salient proposals: linear pooling (the weighted or unweighted linear averaging of probabilities), geometric pooling (the weighted or unweighted geometric averaging of probabilities), and multiplicative pooling (where probabilities are multiplied rather than averaged). We present axiomatic characterisations of each class of (...)
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  32. Franz Dietrich & Christian List (2013). Reasons for (Prior) Belief in Bayesian Epistemology. Synthese 190 (5):781-786.
    Bayesian epistemology tells us with great precision how we should move from prior to posterior beliefs in light of new evidence or information, but says little about where our prior beliefs come from. It offers few resources to describe some prior beliefs as rational or well-justified, and others as irrational or unreasonable. A different strand of epistemology takes the central epistemological question to be not how to change one’s beliefs in light of new evidence, but what reasons justify a given (...)
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  33. Franz Dietrich & Christian List (2011). A Model of Non-Informational Preference Change. Journal of Theoretical Politics 23 (2):145-164.
    According to standard rational choice theory, as commonly used in political science and economics, an agent's fundamental preferences are exogenously fixed, and any preference change over decision options is due to Bayesian information learning. Although elegant and parsimonious, such a model fails to account for preference change driven by experiences or psychological changes distinct from information learning. We develop a model of non-informational preference change. Alternatives are modelled as points in some multidimensional space, only some of whose dimensions play a (...)
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  34. Franz Dietrich & Luca Moretti (2005). On Coherent Sets and the Transmission of Confirmation. Philosophy of Science 72 (3):403-424.
    In this paper, we identify a new and mathematically well-defined sense in which the coherence of a set of hypotheses can be truth-conducive. Our focus is not, as usually, on the probability but on the confirmation of a coherent set and its members. We show that, if evidence confirms a hypothesis, confirmation is "transmitted" to any hypotheses that are sufficiently coherent with the former hypothesis, according to some appropriate probabilistic coherence measure such as Olsson’s or Fitelson’s measure. Our findings have (...)
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  35. Simone Duca & Hannes Leitgeb (2012). How Serious Is the Paradox of Serious Possibility? Mind 121 (481):1-36.
    The so-called Paradox of Serious Possibility is usually regarded as showing that the standard axioms of belief revision do not apply to belief sets that are introspectively closed. In this article we argue to the contrary: we suggest a way of dissolving the Paradox of Serious Possibility so that introspective statements are taken to express propositions in the standard sense, which may thus be proper members of belief sets, and accordingly the normal axioms of belief revision apply to them. Instead (...)
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  36. Jeffrey Dunn (2014). Inferential Evidence. American Philosophical Quarterly 51 (3):203-213.
    Consider: -/- The Evidence Question: When, and under what conditions does an agent have proposition E as evidence (at t)? -/- Timothy Williamson's (2000) answer to this question is the well-known E = K thesis: -/- E = K: E is a member of S's evidence set at t iff S knows E at t. -/- I will argue that this answer is inconsistent with the version of Bayesianism that Williamson advocates. This is because E = K allows an agent (...)
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  37. Nicolas Fillion & Robert M. Corless (2014). On the Epistemological Analysis of Modeling and Computational Error in the Mathematical Sciences. Synthese 191 (7):1451-1467.
    Interest in the computational aspects of modeling has been steadily growing in philosophy of science. This paper aims to advance the discussion by articulating the way in which modeling and computational errors are related and by explaining the significance of error management strategies for the rational reconstruction of scientific practice. To this end, we first characterize the role and nature of modeling error in relation to a recipe for model construction known as Euler’s recipe. We then describe a general model (...)
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  38. Branden Fitelson (2010). Pollock on Probability in Epistemology. [REVIEW] Philosophical Studies 148 (3):455 - 465.
    In Thinking and Acting John Pollock offers some criticisms of Bayesian epistemology, and he defends an alternative understanding of the role of probability in epistemology. Here, I defend the Bayesian against some of Pollock's criticisms, and I discuss a potential problem for Pollock's alternative account.
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  39. Richard Foley (1993). Working Without a Net: A Study of Egocentric Epistemology. Oxford University Press.
    In this new book, Foley defends an epistemology that takes seriously the perspectives of individual thinkers. He argues that having rational opinions is a matter of meeting our own internal standards rather than standards that are somehow imposed upon us from the outside. It is a matter of making ourselves invulnerable to intellectual self-criticism. Foley also shows how the theory of rational belief is part of a general theory of rationality. He thus avoids treating the rationality of belief as a (...)
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  40. Abraham A. Fraenkel (1960). Epistemology and Logic. Synthese 12 (4):333 - 337.
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  41. Dietrich Franz & Christian List, From Degrees of Belief to Beliefs: Lessons From Judgment-Aggregation Theory.
    What is the relationship between degrees of belief and (all-or-nothing) beliefs? Can the latter be expressed as a function of the former, without running into paradoxes? We reassess this “belief-binarization” problem from the perspective of judgment-aggregation theory. Although some similarities between belief binarization and judgment aggregation have been noted before, the literature contains no general study of the implications of aggregation-theoretic impossibility and possibility results for belief binarization. We seek to fill this gap. At the centre of this paper is (...)
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  42. Michael Friedman (1992). Epistemology in Theaufbau. Synthese 93 (1-2):15 - 57.
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  43. Maria Carla Galavotti (2003). Harold Jeffreys' Probabilistic Epistemology: Between Logicism and Subjectivism. British Journal for the Philosophy of Science 54 (1):43-57.
    Harold Jeffreys' ideas on the interpretation of probability and epistemology are reviewed. It is argued that with regard to the interpretation of probability, Jeffreys embraces a version of logicism that shares some features of the subjectivism of Ramsey and de Finetti. Jeffreys also developed a probabilistic epistemology, characterized by a pragmatical and constructivist attitude towards notions such as ‘objectivity’, ‘reality’ and ‘causality’. 1 Introductory remarks 2 The interpretation of probability 3 Jeffreys' probabilistic epistemology.
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  44. Anthony Gillies, Shifty Epistemology.
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  45. Peter Godfrey-Smith, Progress and Procedures in Scientific Epistemology.
    My title is intended to echo Hans Reichenbach's The Rise of Scientific Philosophy (1951), and the phrase "scientific epistemology" is intended in two Reichenbachian senses. One involves the epistemology of science; the other involves epistemology undertaken with a scientific orientation. Talk of "progress and procedures" is intended in a similar dual sense. I start by looking back over the last century, at how a family of problems was tackled by scientifically oriented philosophers. These are problems with the nature of evidence (...)
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  46. Alan Hájek & Stephan Hartmann (2010). Bayesian Epistemology. In J. Dancy et al (ed.), A Companion to Epistemology. Blackwell.
    Bayesianism is our leading theory of uncertainty. Epistemology is defined as the theory of knowledge. So “Bayesian Epistemology” may sound like an oxymoron. Bayesianism, after all, studies the properties and dynamics of degrees of belief, understood to be probabilities. Traditional epistemology, on the other hand, places the singularly non-probabilistic notion of knowledge at centre stage, and to the extent that it traffics in belief, that notion does not come in degrees. So how can there be a Bayesian epistemology?
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  47. M. Hammerton (1968). Bayesian Statistics and Popper's Epistemology. Mind 77 (305):109-112.
  48. William F. Harms (1998). The Use of Information Theory in Epistemology. Philosophy of Science 65 (3):472-501.
    Information theory offers a measure of "mutual information" which provides an appropriate measure of tracking efficiency for the naturalistic epistemologist. The statistical entropy on which it is based is arguably the best way of characterizing the uncertainty associated with the behavior of a system, and it is ontologically neutral. Though not appropriate for the naturalization of meaning, mutual information can serve as a measure of epistemic success independent of semantic maps and payoff structures. While not containing payoffs as terms, mutual (...)
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  49. James Hawthorne, Voting in Search of the Public Good: The Probabilistic Logic of Majority Judgments.
    I argue for an epistemic conception of voting, a conception on which the purpose of the ballot is at least in some cases to identify which of several policy proposals will best promote the public good. To support this view I first briefly investigate several notions of the kind of public good that public policy should promote. Then I examine the probability logic of voting as embodied in two very robust versions of the Condorcet Jury Theorem and some related results. (...)
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  50. Jeffrey Helzner, Uncertainty in the Context of Pragmatist Philosophy and Rational Choice Theory.
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