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  1. Massimiliano Badino, How Typical! An Epistemological Analysis of Typicality in Statistical Mechanics.
    The recent use of typicality in statistical mechanics for foundational purposes has stirred an important debate involving both philosophers and physicists. While this debate customarily focuses on technical issues, in this paper I try to approach the problem from an epistemological angle. The discussion is driven by two questions: (1) What does typicality add to the concept of measure? (2) What kind of explanation, if any, does typicality yield? By distinguishing the notions of `typicality-as-vast-majority' and `typicality-as-best-exemplar', I argue that the (...)
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  2. Daniela Bailer-Jones, Monika Dullstein & Sabina Pauen (eds.) (2007). Kausales Denken: Philosophische und Psychologische Perspektiven. Mentis.
    Kausales Denken spielt sowohl im Alltag wie auch im wissenschaftlichen Forschungsprozess eine zentrale Rolle. Es erlaubt uns, Phänomene vorherzusagen, zu kontrollieren und zu verstehen. Kausales Denken geht über die Angabe der Ursachen eines Phänomens hinaus: Wollen wir verstehen, warum ein Fahrrad fährt, so versuchen wir, Schritt für Schritt nachzuvollziehen, wie die einzelnen Bestandteile des Fahrrads zusammenwirken, um miteinander die Bewegung zu produzieren. Wir sind an dem Mechanismus interessiert, durch den das Phänomen zustande kommt. Dieses Vorgehen wird in der Wissenschaftsphilosophie wie (...)
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  3. Clint Ballinger, Classifying Contingency in the Social Sciences: Diachronic, Synchronic, and Deterministic Contingency.
    This article makes three claims concerning the concept of contingency. First, we argue that the word contingency is used in far too many ways to be useful. Its many meanings are detrimental to clarity of discussion and thought in history and the social sciences. We show how there are eight distinct uses of the word and illustrate this with numerous examples from the social sciences and history, highlighting the scope for confusion caused by the many, often contradictory uses of the (...)
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  4. Eric Barnes (1994). Why P Rather Than Q? The Curiosities of Fact and Foil. Philosophical Studies 73 (1):35 - 53.
    In this paper I develop a theory of contrastive why questions that establishes under what conditions it is sensible to ask "why p rather than q?". p and q must be outcomes of a single type of causal process.
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  5. Sam Baron & Mark Colyvan (forthcoming). Time Enough for Explanation. Journal of Philosophy.
  6. Manuel Barrantes & Juan M. Durán (forthcoming). Reid on Causation and Scientific Explanation. Journal of Scottish Philosophy.
  7. Sara Bernstein (2015). The Metaphysics of Omissions. Philosophy Compass 10 (3):208-218.
    Omissions – any events, actions, or things that do not occur – are central to numerous debates in causation and ethics. This article surveys views on what omissions are, whether they are causally efficacious, and how they ground moral responsibility.
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  8. Ingo Brigandt (2013). Explanation in Biology: Reduction, Pluralism, and Explanatory Aims. Science and Education 22 (1):69-91.
    This essay analyzes and develops recent views about explanation in biology. Philosophers of biology have parted with the received deductive-nomological model of scientific explanation primarily by attempting to capture actual biological theorizing and practice. This includes an endorsement of different kinds of explanation (e.g., mathematical and causal-mechanistic), a joint study of discovery and explanation, and an abandonment of models of theory reduction in favor of accounts of explanatory reduction. Of particular current interest are philosophical accounts of complex explanations that appeal (...)
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  9. Alex Broadbent (2011). Inferring Causation in Epidemiology: Mechanisms, Black Boxes, and Contrasts. In Phyllis McKay Illari, Federica Russo & Jon Williamson (eds.), Causality in the Sciences. Oxford University Press 45--69.
    This chapter explores the idea that causal inference is warranted if and only if the mechanism underlying the inferred causal association is identified. This mechanistic stance is discernible in the epidemiological literature, and in the strategies adopted by epidemiologists seeking to establish causal hypotheses. But the exact opposite methodology is also discernible, the black box stance, which asserts that epidemiologists can and should make causal inferences on the basis of their evidence, without worrying about the mechanisms that might underlie their (...)
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  10. Eric G. Cavalcanti & Raymond Lal (2014). On Modifications of Reichenbach's Principle of Common Cause in Light of Bell's Theorem. Journal of Physics A: Mathematical and Theoretical 47 (42):424018.
    Bellʼs 1964 theorem causes a severe problem for the notion that correlations require explanation, encapsulated in Reichenbachʼs principle of common cause. Despite being a hallmark of scientific thought, dropping the principle has been widely regarded as much less bitter medicine than the perceived alternative—dropping relativistic causality. Recently, however, some authors have proposed that modified forms of Reichenbachʼs principle could be maintained even with relativistic causality. Here we break down Reichenbachʼs principle into two independent assumptions—the principle of common cause proper and (...)
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  11. L. R. Franklin-Hall (forthcoming). New Mechanistic Explanation and the Need for Explanatory Constraints. In Ken Aizawa & Carl Gillett (eds.), Scientific Composition and Metaphysical Ground. Palgrave
    This paper critiques the new mechanistic explanatory program on grounds that, even when applied to the kinds of examples that it was originally designed to treat, it does not distinguish correct explanations from those that blunder. First, I offer a systematization of the explanatory account, one according to which explanations are mechanistic models that satisfy three desiderata: they must 1) represent causal relations, 2) describe the proper parts, and 3) depict the system at the right ‘level.’ Second, I argue that (...)
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  12. L. R. Franklin-Hall (2015). Explaining Causal Selection with Explanatory Causal Economy: Biology and Beyond. In P.-A. Braillard & C. Malaterre (eds.), Explanation in Biology: An Enquiry into the Diversity of Explanatory Patterns in the Life Sciences. Springer 413-438.
    Among the factors necessary for the occurrence of some event, which of these are selectively highlighted in its explanation and labeled as causes — and which are explanatorily omitted, or relegated to the status of background conditions? Following J. S. Mill, most have thought that only a pragmatic answer to this question was possible. In this paper I suggest we understand this ‘causal selection problem’ in causal-explanatory terms, and propose that explanatory trade-offs between abstraction and stability can provide a principled (...)
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  13. L. R. Franklin-Hall (2014). High-Level Explanation and the Interventionist's 'Variables Problem'. British Journal for the Philosophy of Science:axu040.
    The interventionist account of causal explanation, in the version presented by Jim Woodward, has been recently claimed capable of buttressing the widely felt—though poorly understood—hunch that high-level, relatively abstract explanations, of the sort provided by sciences like biology, psychology and economics, are in some cases explanatorily optimal. It is the aim of this paper to show that this is mistaken. Due to a lack of effective constraints on the causal variables at the heart of the interventionist causal-explanatory scheme, as presently (...)
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  14. Toby Handfield, Charles R. Twardy, Kevin B. Korb & Graham Oppy (2008). The Metaphysics of Causal Models: Where's the Biff? Erkenntnis 68 (2):149-68.
    This paper presents an attempt to integrate theories of causal processes—of the kind developed by Wesley Salmon and Phil Dowe—into a theory of causal models using Bayesian networks. We suggest that arcs in causal models must correspond to possible causal processes. Moreover, we suggest that when processes are rendered physically impossible by what occurs on distinct paths, the original model must be restricted by removing the relevant arc. These two techniques suffice to explain cases of late preëmption and other cases (...)
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  15. Richard Healey (2013). How Quantum Theory Helps Us Explain. British Journal for the Philosophy of Science (1):axt031.
    I offer an account of how the quantum theory we have helps us explain so much. The account depends on a pragmatist interpretation of the theory: this takes a quantum state to serve as a source of sound advice to physically situated agents on the content and appropriate degree of belief about matters concerning which they are currently inevitably ignorant. The general account of how to use quantum states and probabilities to explain otherwise puzzling regularities is then illustrated by showing (...)
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  16. Peter Hedström & Petri Ylikoski (2010). Causal Mechanisms in the Social Sciences. Annual Review of Sociology 36:49–67.
    During the past decade, social mechanisms and mechanism-based ex- planations have received considerable attention in the social sciences as well as in the philosophy of science. This article critically reviews the most important philosophical and social science contributions to the mechanism approach. The first part discusses the idea of mechanism- based explanation from the point of view of philosophy of science and relates it to causation and to the covering-law account of explanation. The second part focuses on how the idea (...)
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  17. M. C. W. Janssen & Y. -H. Tan (1991). Why Friedman's Non-Monotonic Reasoning Defies Hempel's Covering Law Model. Synthese 86 (2):255 - 284.
    In this paper we will show that Hempel's covering law model can't deal very well with explanations that are based on incomplete knowledge. In particular the symmetry thesis, which is an important aspect of the covering law model, turns out to be problematic for these explanations. We will discuss an example of an electric circuit, which clearly indicates that the symmetry of explanation and prediction does not always hold. It will be argued that an alternative logic for causal explanation is (...)
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  18. Monte Ransome Johnson (2009). The Aristotelian Explanation of the Halo. Apeiron 42 (4):325-357.
    For an Aristotelian observer, the halo is a puzzling phenomenon since it is apparently sublunary, and yet perfectly circular. This paper studies Aristotle's explanation of the halo in Meteorology III 2-3 as an optical illusion, as opposed to a substantial thing (like a cloud), as was thought by his predecessors and even many successors. Aristotle's explanation follows the method of explanation of the Posterior Analytics for "subordinate" or "mixed" mathematical-physical sciences. The accompanying diagram described by Aristotle is one of the (...)
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  19. Kareem Khalifa (2011). Contrastive Explanations as Social Accounts. Social Epistemology 24 (4):263-284.
    Explanatory contrastivists hold that we often explain phenomena of the form p rather than q. In this paper, I present a new, social‐epistemological model of contrastive explanation—accountabilism. Specifically, my view is inspired by social‐scientific research that treats explanations fundamentally as accounts; that is, communicative actions that restore one's social status when charged with questionable behaviour. After developing this model, I show how accountabilism provides a more comprehensive model of contrastive explanation than the causal models of contrastive explanation that are currently (...)
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  20. Harold Kincaid (2004). Contextualism, Explanation and the Social Sciences. Philosophical Explorations 7 (3):201 – 218.
    Debates about explanation in the social sciences often proceed without any clear idea what an 'account' of explanation should do. In this paper I take a stance - what I will call contextualism - that denies there are purely formal and conceptual constraints on explanation and takes standards of explanation to be substantive empirical claims, paradigmatically claims about causation. I then use this standpoint to argue for position on issues in the philosophy of social science concerning reduction, idealized models, social (...)
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  21. Jeff Kochan (2010). Contrastive Explanation and the 'Strong Programme' in the Sociology of Scientific Knowledge. Social Studies of Science 40 (1):127-44.
    In this essay, I address a novel criticism recently levelled at the Strong Programme by Nick Tosh and Tim Lewens. Tosh and Lewens paint Strong Programme theorists as trading on a contrastive form of explanation. With this, they throw valuable new light on the explanatory methods employed by the Strong Programme. However, as I shall argue, Tosh and Lewens run into trouble when they accuse Strong Programme theorists of unduly restricting the contrast space in which legitimate historical and sociological explanations (...)
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  22. Jaakko Kuorikoski & Petri Ylikoski (2013). How Organization Explains. In Vassilios Karakostas & Dennis Dieks (eds.), Epsa11 Perspectives and Foundational Problems in Philosophy of Science. Springer 69--80.
  23. James Ladyman (2003). Stathis Psillos,Causation and Explanation. Chesham: Acumen, 2002. [REVIEW] Metascience 12 (3):431-434.
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  24. Marc Lange (2012). Abstraction and Depth in Scientific Explanation. [REVIEW] Philosophy and Phenomenological Research 84 (2):483-491.
  25. Arnon Levy (2014). Machine-Likeness and Explanation by Decomposition. Philosophers' Imprint 14 (6).
    Analogies to machines are commonplace in the life sciences, especially in cellular and molecular biology — they shape conceptions of phenomena and expectations about how they are to be explained. This paper offers a framework for thinking about such analogies. The guiding idea is that machine-like systems are especially amenable to decompositional explanation, i.e., to analyses that tease apart underlying components and attend to their structural features and interrelations. I argue that for decomposition to succeed a system must exhibit causal (...)
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  26. Arnon Levy & William Bechtel (2013). Abstraction and the Organization of Mechanisms. Philosophy of Science 80 (2):241-261.
  27. David Lewis (1986). Causal Explanation. In Philosophical Papers Vol. Ii. Oxford University Press 214-240.
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  28. David Lewis (1986). Philosophical Papers Vol. II. Oxford University Press.
  29. Christian Loew (forthcoming). Causation, Physics, and Fit. Synthese:1-21.
    Our ordinary causal concept seems to fit poorly with how our best physics describes the world. We think of causation as a time-asymmetric dependence relation between relatively local events. Yet fundamental physics describes the world in terms of dynamical laws that are, possible small exceptions aside, time symmetric and that relate global time slices. My goal in this paper is to show why we are successful at using local, time-asymmetric models in causal explanations despite this apparent mismatch with fundamental physics. (...)
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  30. Lennart Nordenfelt & B. Ingemar B. Lindahl (eds.) (1984). Health, Disease, and Causal Explanations in Medicine. Reidel.
  31. Robert Northcott (2013). Degree of Explanation. Synthese 190 (15):3087-3105.
    Partial explanations are everywhere. That is, explanations citing causes that explain some but not all of an effect are ubiquitous across science, and these in turn rely on the notion of degree of explanation. I argue that current accounts are seriously deficient. In particular, they do not incorporate adequately the way in which a cause’s explanatory importance varies with choice of explanandum. Using influential recent contrastive theories, I develop quantitative definitions that remedy this lacuna, and relate it to existing measures (...)
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  32. Garrett Pendergraft (2011). In Defense of a Causal Requirement on Explanation. In Phyllis McKay Illari Federica Russo (ed.), Causality in the Sciences. Oxford University Press 470.
    Causalists about explanation claim that to explain an event is to provide information about the causal history of that event. Some causalists also endorse a proportionality claim, namely that one explanation is better than another insofar as it provides a greater amount of causal information. In this chapter I consider various challenges to these causalist claims. There is a common and influential formulation of the causalist requirement – the ‘Causal Process Requirement’ – that does appear vulnerable to these anti-causalist challenges, (...)
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  33. Joseph C. Pitt (ed.) (1988). Theories of Explanation. Oxford University Press.
    Since the publication of Carl Hempel and Paul Oppenheim's ground-breaking work "Studies in the Logic of Explanation," the theory of explanation has remained a major topic in the philosophy of science. This valuable collection provides readers with the opportunity to study some of the classic essays on the theory of explanation along with the best examples of the most recent work being done on the topic. In addition to the original Hempel and Oppenheim paper, the volume includes Scriven's critical reaction (...)
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  34. Angela Potochnik (2015). Causal Patterns and Adequate Explanations. Philosophical Studies 172 (5):1163-1182.
    Causal accounts of scientific explanation are currently broadly accepted (though not universally so). My first task in this paper is to show that, even for a causal approach to explanation, significant features of explanatory practice are not determined by settling how causal facts bear on the phenomenon to be explained. I then develop a broadly causal approach to explanation that accounts for the additional features that I argue an explanation should have. This approach to explanation makes sense of several aspects (...)
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  35. Angela Potochnik (2011). Explanation and Understanding. European Journal for Philosophy of Science 1 (1):29-38.
    Michael Strevens offers an account of causal explanation according to which explanatory practice is shaped by counterbalanced commitments to representing causal influence and abstracting away from overly specific details. In this paper, I challenge a key feature of that account. I argue that what Strevens calls explanatory frameworks figure prominently in explanatory practice because they actually improve explanations. This suggestion is simple but has far-reaching implications. It affects the status of explanations that cite multiply realizable properties; changes the explanatory role (...)
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  36. Angela Potochnik (2010). Explanatory Independence and Epistemic Interdependence: A Case Study of the Optimality Approach. British Journal for the Philosophy of Science 61 (1):213-233.
    The value of optimality modeling has long been a source of contention amongst population biologists. Here I present a view of the optimality approach as at once playing a crucial explanatory role and yet also depending on external sources of confirmation. Optimality models are not alone in facing this tension between their explanatory value and their dependence on other approaches; I suspect that the scenario is quite common in science. This investigation of the optimality approach thus serves as a case (...)
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  37. Stathis Psillos (2007). Causal Explanation and Manipulation. In Johannes Persson & Petri Ylikoski (eds.), Rethinking Explanation. Springer 93--107.
  38. Henk W. De Regt & Dennis Dieks (2005). A Contextual Approach to Scientific Understanding. Synthese 144 (1):137 - 170.
    Achieving understanding of nature is one of the aims of science. In this paper we offer an analysis of the nature of scientific understanding that accords with actual scientific practice and accommodates the historical diversity of conceptions of understanding. Its core idea is a general criterion for the intelligibility of scientific theories that is essentially contextual: which theories conform to this criterion depends on contextual factors, and can change in the course of time. Our analysis provides a general account of (...)
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  39. Alexander Reutlinger (2014). Why Is There Universal Macrobehavior? Renormalization Group Explanation as Noncausal Explanation. Philosophy of Science 81 (5):1157-1170.
    Renormalization group (RG) methods are an established strategy to explain how it is possible that microscopically different systems exhibit virtually the same macro behavior when undergoing phase-transitions. I argue – in agreement with Robert Batterman – that RG explanations are non-causal explanations. However, Batterman misidentifies the reason why RG explanations are non-causal: it is not the case that an explanation is non- causal if it ignores causal details. I propose an alternative argument, according to which RG explanations are non-causal explanations (...)
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  40. David-Hillel Ruben (2003, 2012). Explaining Explanation. Routledge; Paradigm Publishers.
    This book introduces readers to the topic of explanation. The insights of Plato, Aristotle, J.S. Mill and Carl Hempel are examined, and are used to argue against the view that explanation is merely a problem for the philosophy of science. Having established its importance for understanding knowledge in general, the book concludes with a bold and original explanation of explanation.
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  41. David-Hillel Ruben (1994). A Counterfactual Theory of Causal Explanation. Noûs 28 (4):465-481.
  42. David-Hillel Ruben (1989). The Ontology of Explanation. In Fred D'Agostino & I. C. Jarvie (eds.), Freedom and Rationality. Reidel 67--85.
    In an explanation, what does the explaining and what gets explained? What are the relata of the explanation relation? Candidates include: people, events, facts, sentences, statements, and propositions.
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  43. Juha Saatsi (forthcoming). On Explanations From 'Geometry of Motion'. British Journal for the Philosophy of Science.
    This paper examines explanations that turn on non-local geometrical facts about the space of possible configurations a system can occupy. I argue that it makes sense to contrast such explanations from "geometry of motion" with causal explanations. I also explore how my analysis of these explanations cuts across the distinction between kinematics and dynamics.
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  44. Wesley C. Salmon (1998). Causality and Explanation. Oxford University Press.
    Wesley Salmon is renowned for his seminal contributions to the philosophy of science. He has powerfully and permanently shaped discussion of such issues as lawlike and probabilistic explanation and the interrelation of explanatory notions to causal notions. This unique volume brings together twenty-six of his essays on subjects related to causality and explanation, written over the period 1971-1995. Six of the essays have never been published before and many others have only appeared in obscure venues. The volume includes a section (...)
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  45. Wesley C. Salmon (1997). Causality and Explanation: A Reply to Two Critiques. Philosophy of Science 64 (3):461-477.
    This paper discusses several distinct process theories of causality offered in recent years by Phil Dowe and me. It addresses problems concerning the explication of causal process, causal interaction, and causal transmission, whether given in terms of transmission of marks, transmission of invariant or conserved quantities, or mere possession of conserved quantities. Renouncing the mark-transmission and invariant quantity criteria, I accept a conserved quantity theory similar to Dowe's--differing basically with respect to causal transmission. This paper also responds to several fundamental (...)
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  46. Wesley C. Salmon (1985). Conflicting Conceptions of Scientific Explanation. Journal of Philosophy 82 (11):651-654.
  47. David H. Sanford (2009). Causation. In Jaegwon Kim, Ernest Sosa & Gary S. Rosenkrantz (eds.), A Companion to Metaphysics. Wiley-Blackwell
    Twenty-one paragraphs in this entry begin with a statement of a view about causation. To help organize the entry, the next sentence then classifies the view as 'prevailing, majority, controversial', or 'minority'. The following brief discussions attempt to be clear and fair. Respect for fairness, however, does not prevent the author from referring to his own views. For example, the author classifies "There is no element of genuine a priori reasoning in causal inference" as a majority view. After expounded the (...)
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  48. Bradford Skow (2013). The Role of Chance in Explanation. Australasian Journal of Philosophy (1):1-21.
    ?Those ice cubes melted because by melting total entropy increased and entropy increase has a very high objective chance.? What role does the chance in this explanation play? I argue that it contributes to the explanation by entailing that the melting was almost necessary, and defend the claim that the fact that some event was almost necessary can, in the right circumstances, constitute a causal explanation of that event.
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  49. Michael Strevens (2012). Précis of Depth. [REVIEW] Philosophy and Phenomenological Research 84 (2):447-460.
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  50. Michael Strevens (2012). Replies to Weatherson, Hall, and Lange. [REVIEW] Philosophy and Phenomenological Research 84 (2):492-505.
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