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  1. In Defence of Linguistics as an Empirical Science in Light of Mario Bunge’s Defence of the Scientific Treatment of Biology.Dorota Zielińska - 2024 - Mεtascience: Scientific General Discourse 3:205-251.
    Although few linguists currently embrace the empirical paradigm, there are increasing calls for the development of tools for studying language that resemble those in exact sciences. This trend can be observed even in top mainstream linguistic journals, such as the Journal of Pragmatics, as exemplified by Xiang (2017). Today, however, linguists who adapt the methodologies from more advanced sciences face isolation from the mainstream linguistic community. This is because the majority of linguists in philological and philosophical departments remain convinced that (...)
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  2. Mixed-grain Property Collaboration: Reconstructing Multiple Realization after the Elimination of Levels.Robert D. Rupert - manuscript
  3. A quick overview of scientific representation and modelling. [REVIEW]Dimitri Coelho Mollo - 2023 - Metascience 32:321-324.
  4. A Defence of Manipulationist Noncausal Explanation: The Case for Intervention Liberalism.Nicholas Emmerson - 2023 - Erkenntnis 88 (8):3179-3201.
    Recent years have seen growing interest in modifying interventionist accounts of causal explanation in order to characterise noncausal explanation. However, one surprising element of such accounts is that they have typically jettisoned the core feature of interventionism: interventions. Indeed, the prevailing opinion within the philosophy of science literature suggests that interventions exclusively demarcate causal relationships. This position is so prevalent that, until now, no one has even thought to name it. We call it “intervention puritanism” (I-puritanism, for short). In this (...)
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  5. Mapping Explanatory Language in Neuroscience.Daniel Kostić & Willem Halffman - 2023 - Synthese 202 (112):1-27.
    The philosophical literature on scientific explanation in neuroscience has been dominated by the idea of mechanisms. The mechanist philosophers often claim that neuroscience is in the business of finding mechanisms. This view has been challenged in numerous ways by showing that there are other successful and widespread explanatory strategies in neuroscience. However, the empirical evidence for all these claims was hitherto lacking. Empirical evidence about the pervasiveness and uses of various explanatory strategies in neuroscience is particularly needed because examples and (...)
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  6. Explainable AI and Causal Understanding: Counterfactual Approaches Considered.Sam Baron - 2023 - Minds and Machines 33 (2):347-377.
    The counterfactual approach to explainable AI (XAI) seeks to provide understanding of AI systems through the provision of counterfactual explanations. In a recent systematic review, Chou et al. (Inform Fus 81:59–83, 2022) argue that the counterfactual approach does not clearly provide causal understanding. They diagnose the problem in terms of the underlying framework within which the counterfactual approach has been developed. To date, the counterfactual approach has not been developed in concert with the approach for specifying causes developed by Pearl (...)
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  7. Schopenhauer's Theory of Science.Timothy Stoll - 2023 - In David Bather Woods & Timothy Stoll (eds.), The Schopenhauerian mind. New York, NY: Routledge. pp. 53–67.
  8. Levels of Explanation.Alastair Wilson & Katie Robertson (eds.) - forthcoming - Oxford University Press.
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  9. From Life-Like to Mind-Like Explanation: Natural Agency and the Cognitive Sciences.Alex Djedovic - 2020 - Dissertation, University of Toronto, St. George Campus
    This dissertation argues that cognition is a kind of natural agency. Natural agency is the capacity that certain systems have to act in accordance with their own norms. Natural agents are systems that bias their repertoires in response to affordances in the pursuit of their goals. -/- Cognition is a special mode of this general phenomenon. Cognitive systems are agents that have the additional capacity to actively take their worlds to be certain ways, regardless of whether the world is really (...)
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  10. The meaning of "cause" in genetics.Kate E. Lynch - 2021 - Combining Human Genetics and Causal Inference to Understand Human Disease and Development. Cold Spring Harbor Perspectives in Medicine.
    Causation has multiple distinct meanings in genetics. One reason for this is meaning slippage between two concepts of the gene: Mendelian and molecular. Another reason is that a variety of genetic methods address different kinds of causal relationships. Some genetic studies address causes of traits in individuals, which can only be assessed when single genes follow predictable inheritance patterns that reliably cause a trait. A second sense concerns the causes of trait differences within a population. Whereas some single genes can (...)
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  11. Thought Experiments and The Pragmatic Nature of Explanation.Panagiotis Karadimas - 2024 - Foundations of Science 29 (2):257-280.
    Different why-questions emerge under different contexts and require different information in order to be addressed. Hence a relevance relation can hardly be invariant across contexts. However, what is indeed common under any possible context is that all explananda require scientific information in order to be explained. So no scientific information is in principle explanatorily irrelevant, it only becomes so under certain contexts. In view of this, scientific thought experiments can offer explanations, should we analyze their representational strategies. Their representations involve (...)
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  12. Same-tracking real kinds in the social sciences.Theodore Bach - 2022 - Synthese 200 (2):1-26.
    The kinds of real or natural kinds that support explanation and prediction in the social sciences are difficult to identify and track because they change through time, intersect with one another, and they do not always exhibit their properties when one encounters them. As a result, conceptual practices directed at these kinds will often refer in ways that are partial, equivocal, or redundant. To improve this epistemic situation, it is important to employ open-ended classificatory concepts, to understand when different research (...)
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  13. Darwinism, Mind and Society.Louis Caruana - 2009 - In Darwin and Catholicism: The Past and Present Dynamics of a Cultural Encounter. London: T&T Clark. pp. 134-150.
    This paper seeks to clarity the extent to which we can legitimately apply evolutionary explanation to the realm of moral and social behavior. It evaluates two perspectives, one dealing with purely philosophical arguments, and the other with arguments from within the Catholic tradition. The challenges faced by evolutionary ethics discernible from the secular perspective turn out to be practically the same as those discernible from the religious perspective. Whether we discuss the issues in terms of intentional states or in terms (...)
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  14. Counterpossibles in Scientific Practice - Three Case Studies in support of Worldly Hyperintensionality.Giorgio Lenta - 2021 - Dissertation, University of Turin
    Hyperintensionality – the failure of substitutivity salva veritate of intensionally equivalent expressions – is one of the most debated topics in recent philosophy of language. Being a phenomenon that affects a wide variety of different sentential contexts, a question concerning its source arises: is hyperintensionality something that can originate from actual features of the world, or it is simply some kind of representational phenomenon, which entirely depends on our conceptual faculties and preferred semantics? After a brief general introduction to the (...)
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  15. Measuring Causal Invariance Formally.Pierrick Bourrat - 2021 - Entropy 23 (6):690.
    Invariance is one of several dimensions of causal relationships within the interventionist account. The more invariant a relationship between two variables, the more the relationship should be considered paradigmatically causal. In this paper, I propose two formal measures to estimate invariance, illustrated by a simple example. I then discuss the notion of invariance for causal relationships between non-nominal (i.e., ordinal and quantitative) variables, for which Information theory, and hence the formalism proposed here, is not well suited. Finally, I propose how (...)
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  16. The Unreasonable Effectiveness of Decoherence.Davide Romano -
    This paper aims to clarify some conceptual aspects of decoherence that seem largely overlooked in the recent literature. In particular, I want to stress that decoherence theory, in the standard framework, is rather silent with respect to the description of (sub)systems and associated dynamics. Also, the selection of position basis for classical objects is more problematic than usually thought: while, on the one hand, decoherence offers a pragmatic-oriented solution to this problem, on the other hand, this can hardly be seen (...)
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  17. Folk Psychology and the Interpretation of Decision Theory.Johanna Thoma - 2020 - Ergo: An Open Access Journal of Philosophy 7.
    Most philosophical decision theorists and philosophers of the social sciences believe that decision theory is and should be in the business of providing folk psychological explanations of choice behaviour, and that it can only do so if we understand the preferences, utilities and probabilities that feature in decision-theoretic models as ascriptions of mental states not reducible to choice. The behavioural interpretation of preference and related concepts, still common in economics, is consequently cast as misguided. This paper argues that even those (...)
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  18. Won’t Get Fooled Again: Wittgensteinian Philosophy and the Rhetoric of Empiricism.Russell P. Johnson - 2020 - Sophia 59 (2):345-363.
    The debate surrounding eliminative materialism, and the role of empiricism more broadly, has been one of the more prominent philosophical debates of the last half-century. But too often what is at stake in this debate has been left implicit. This essay surveys the rhetoric of two participants in this debate, Paul Churchland and Thomas Nagel, on the question of whether or not scientific explanations will do away with the need for nonscientific descriptions. Both philosophers talk about this possibility in language (...)
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  19. Resenha/Book Review: De Regt, H.W. Understanding Scientific Understanding. New York: Oxford University Press, 2017. [REVIEW]Luana Poliseli - 2020 - Principia: An International Journal of Epistemology 24 (1):239-245.
    Book Review: De Regt, H. W. Understanding Scientific Understanding. New York: Oxford University Press, 2017.
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  20. Unifying the essential concepts of biological networks: biological insights and philosophical foundations.Daniel Kostic, Claus Hilgetag & Marc Tittgemeyer - 2020 - Philosophical Transactions of the Royal Society B: Biological Sciences 375 (1796):1-8.
    Over the last decades, network-based approaches have become highly popular in diverse fields of biology, including neuroscience, ecology, molecular biology and genetics. While these approaches continue to grow very rapidly, some of their conceptual and methodological aspects still require a programmatic foundation. This challenge particularly concerns the question of whether a generalized account of explanatory, organisational and descriptive levels of networks can be applied universally across biological sciences. To this end, this highly interdisciplinary theme issue focuses on the definition, motivation (...)
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  21. Contrastivism and non‐contrastivism in scientific explanation.Yafeng Shan - 2019 - Philosophy Compass 14 (8):e12613.
    The nature of scientific explanation is controversial. Some maintain that all scientific explanations have to be contrastive in nature (contrastivism). However, others argue that no scientific explanation is genuinely contrastive (non-contrastivism). In addition, a compatibilist view has been recently devloped. It is argued that the debate between contrastivism and non-contrastivism is merely a linguistic dispute rather than a genuine disagreement on the nature of scientific explanation. Scientific explanations are both contrastive and non-contrastive in some sense (compatibilism). This paper examines the (...)
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  22. Mechanistic Explanation in Physics.Laura Felline - 2022 - In Eleanor Knox & Alastair Wilson (eds.), The Routledge Companion to Philosophy of Physics. London, UK: Routledge.
    The idea at the core of the New Mechanical account of explanation can be summarized in the claim that explaining means showing ‘how things work’. This simple motto hints at three basic features of Mechanistic Explanation (ME): ME is an explanation-how, that implies the description of the processes underlying the phenomenon to be explained and of the entities that engage in such processes. These three elements trace a fundamental contrast with the view inherited from Hume and later from strict logical (...)
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  23. Explanatory value in context: the curious case of Hotelling’s location model.Emrah Aydinonat & Emin Köksal - 2019 - European Journal of the History of Economic Thought 26 (5):1-32.
    There is a striking contrast between the significance of Harold Hotelling’s contribution to industrial economics and the fact that his location model was invalid, unrealistic and non-robust. It is difficult to make sense of the explanatory value of Hotelling’s model based on philosophical accounts that emphasize logical validity, representational adequacy, and robustness as determinants of explanatory value. However, these accounts are misleading because they overlook the context within which the explanatory value added of a model is apprehensible. We present Hotelling’s (...)
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  24. Emergence without limits: The case of phonons.Alexander Franklin & Eleanor Knox - 2018 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 64 (C):68-78.
    Recent discussions of emergence in physics have focussed on the use of limiting relations, and often particularly on singular or asymptotic limits. We discuss a putative example of emergence that does not fit into this narrative: the case of phonons. These quasi-particles have some claim to be emergent, not least because the way in which they relate to the underlying crystal is almost precisely analogous to the way in which quantum particles relate to the underlying quantum field theory. But there (...)
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  25. Horizontal Surgicality and Mechanistic Constitution.Michael Baumgartner, Lorenzo Casini & Beate Krickel - 2020 - Erkenntnis 85:417-430.
    While ideal interventions are acknowledged by many as valuable tools for the analysis of causation, recent discussions have shown that, since there are no ideal interventions on upper-level phenomena that non-reductively supervene on their underlying mechanisms, interventions cannot—contrary to a popular opinion—ground an informative analysis of constitution. This has led some to abandon the project of analyzing constitution in interventionist terms. By contrast, this paper defines the notion of a horizontally surgical intervention, and argues that, when combined with some innocuous (...)
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  26. Philosophy, Certainty and Semantic Stretch.Michaelis Michael - 2017 - Australasian Philosophical Review 1 (3):281-290.
    ABSTRACTLloyd encourages us to look anew at philosophy and science by using a comparative methodology, comparing the familiar Western form of philosophy, for example, with the forms found in ancient China. Taking lessons from comparative biology, this paper attempts to show that such comparison can only take place when we understand what we are looking at in the familiar case. The question of the centrality of the drive for certainty is addressed. Why has certainty been so attractive and what does (...)
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  27. Minimal Models and the Generalized Ontic Conception of Scientific Explanation.Mark Povich - 2018 - British Journal for the Philosophy of Science 69 (1):117-137.
    Batterman and Rice ([2014]) argue that minimal models possess explanatory power that cannot be captured by what they call ‘common features’ approaches to explanation. Minimal models are explanatory, according to Batterman and Rice, not in virtue of accurately representing relevant features, but in virtue of answering three questions that provide a ‘story about why large classes of features are irrelevant to the explanandum phenomenon’ ([2014], p. 356). In this article, I argue, first, that a method (the renormalization group) they propose (...)
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  28. Causality and Explanation in the Sciences.Bert Leuridan & Erik Weber - 2012 - Theoria 27 (2):133-136.
    Editors’ introduction to the special issue on the Causality and Explanation in the Sciences conference, held at the University of Ghent in September 2011.
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  29. Diversifying the picture of explanations in biological sciences: ways of combining topology with mechanisms.Philippe Huneman - 2018 - Synthese 195 (1):115-146.
    Besides mechanistic explanations of phenomena, which have been seriously investigated in the last decade, biology and ecology also include explanations that pinpoint specific mathematical properties as explanatory of the explanandum under focus. Among these structural explanations, one finds topological explanations, and recent science pervasively relies on them. This reliance is especially due to the necessity to model large sets of data with no practical possibility to track the proper activities of all the numerous entities. The paper first defines topological explanations (...)
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  30. Mechanistic and topological explanations: an introduction.Daniel Kostić - 2018 - Synthese 195 (1).
    In the last 20 years or so, since the publication of a seminal paper by Watts and Strogatz :440–442, 1998), an interest in topological explanations has spread like a wild fire over many areas of science, e.g. ecology, evolutionary biology, medicine, and cognitive neuroscience. The topological approach is still very young by all standards, and even within special sciences it still doesn’t have a single methodological programme that is applicable across all areas of science. That is why this special issue (...)
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  31. How do we Have to Investigate Scientific Explanation?Erik Weber, Leen De Vreese & Jeroen Van Bouwel - 2016 - Tijdschrift Voor Filosofie 78 (3):489-524.
    This paper investigates the working-method of three important philosophers of explanation: Carl Hempel, Philip Kitcher, and Wesley Salmon. We argue that they do three things: construct an explication in the sense of Carnap, which then is used as a tool to make descriptive and normative claims about the explanatory practice of scientists. We also show that they did well with respect to, but that they failed to give arguments for their descriptive and normative claims. We think it is the responsibility (...)
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  32. It's a Matter of Principle: Scientific Explanation in Information‐Theoretic Reconstructions of Quantum Theory.Laura Felline - 2016 - Dialectica 70 (4):549-575.
    The aim of this paper is to explore the ways in which Axiomatic Reconstructions of Quantum Theory in terms of Information-Theoretic principles can contribute to explaining and understanding quantum phenomena, as well as to study their explanatory limitations. This is achieved in part by offering an account of the kind of explanation that axiomatic reconstructions of Quantum Theory provide, and re-evaluating the epistemic status of the program in light of this explanation. As illustrative case studies, I take Clifton's, Bub's and (...)
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  33. Explanation: a mechanist alternative.William Bechtel & Adele Abrahamsen - 2005 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 36 (2):421-441.
    Explanations in the life sciences frequently involve presenting a model of the mechanism taken to be responsible for a given phenomenon. Such explanations depart in numerous ways from nomological explanations commonly presented in philosophy of science. This paper focuses on three sorts of differences. First, scientists who develop mechanistic explanations are not limited to linguistic representations and logical inference; they frequently employ diagrams to characterize mechanisms and simulations to reason about them. Thus, the epistemic resources for presenting mechanistic explanations are (...)
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  34. Enriching the Strategies for Creating Mechanistic Explanations in Biology.William Bechtel - unknown
    To demonstrate that a proposed mechanism could explain a phenomenon, biologists must recompose the mechanism. Traditionally they have relied on mentally rehearsing the operations, often aided by a mechanism diagram. Such a strategy has reached its limits in contemporary biology. For example, through mental rehearsal alone researchers cannot determine whether a feedback mechanism will generate sustained oscillation. Accordingly, mechanistic inclined biologists are enriching their strategies, relying on computational simulation and graph-theoretical analyses of networks. The limitations of traditional approaches and the (...)
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  35. Mechanists Must be Holists Too! Perspectives from Circadian Biology.William Bechtel - 2016 - Journal of the History of Biology 49 (4):705-731.
    The pursuit of mechanistic explanations in biology has produced a great deal of knowledge about the parts, operations, and organization of mechanisms taken to be responsible for biological phenomena. Holist critics have often raised important criticisms of proposed mechanistic explanations, but until recently holists have not had alternative research strategies through which to advance explanations. This paper argues both that the results of mechanistic strategies has forced mechanists to confront ways in which whole systems affect their components and that new (...)
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  36. The Applicability of Mathematics to Physical Modality.Nora Berenstain - 2017 - Synthese 194 (9):3361-3377.
    This paper argues that scientific realism commits us to a metaphysical determination relation between the mathematical entities that are indispensible to scientific explanation and the modal structure of the empirical phenomena those entities explain. The argument presupposes that scientific realism commits us to the indispensability argument. The viewpresented here is that the indispensability of mathematics commits us not only to the existence of mathematical structures and entities but to a metaphysical determination relation between those entities and the modal structure of (...)
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  37. Explaining Explanation.David-Hillel Ruben - 1990 - Abingdon, UK: Routledge.
    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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  38. Definitions, Explanations and Theories.Michael Scriven - 1956 - In Herbert Feigl & Michael Scriven (eds.), Minnesota Studies in the Philosophy of Science. , Vol. pp. 99 – 195.
  39. Models and Inferences in Science.Emiliano Ippoliti, Fabio Sterpetti & Thomas Nickles (eds.) - 2016 - Cham: Springer.
    The book answers long-standing questions on scientific modeling and inference across multiple perspectives and disciplines, including logic, mathematics, physics and medicine. The different chapters cover a variety of issues, such as the role models play in scientific practice; the way science shapes our concept of models; ways of modeling the pursuit of scientific knowledge; the relationship between our concept of models and our concept of science. The book also discusses models and scientific explanations; models in the semantic view of theories; (...)
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  40. Measuring Causal Specificity.Paul E. Griffiths, Arnaud Pocheville, Brett Calcott, Karola Stotz, Hyunju Kim & Rob Knight - 2015 - Philosophy of Science 82 (4):529-555.
    Several authors have argued that causes differ in the degree to which they are ‘specific’ to their effects. Woodward has used this idea to enrich his influential interventionist theory of causal explanation. Here we propose a way to measure causal specificity using tools from information theory. We show that the specificity of a causal variable is not well-defined without a probability distribution over the states of that variable. We demonstrate the tractability and interest of our proposed measure by measuring the (...)
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  41. Explanatory Conditionals: A Logical View of the Interventionist Account of Explanation.Holger Andreas - unknown
  42. Explanation in Neurobiology: An Interventionist Perspective.James Woodward - unknown
    This paper employs an interventionist framework to elucidate some issues having to do with explanation in neurobiology and with the differences between mechanistic and non-mechanistic explanations.
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  43. Strevens. 2009. Depth. An account of scientific explanations. [REVIEW]Federica Russo - 2011 - Theoria : An International Journal for Theory, History and Fundations of Science 26 (2):261-263.
  44. Constraints on Localization and Decomposition as Explanatory Strategies in the Biological Sciences.Michael Silberstein & Tony Chemero - unknown
    Several articles have recently appeared arguing that there really are no viable alternatives to mechanistic explanation in the biological sciences. This claim is meant to hold both in principle and in practice. The basic claim is that any explanation of a particular feature of a biological system, including dynamical explanations, must ultimately be grounded in mechanistic explanation. There are several variations on this theme, some stronger and some weaker. In order to avoid equivocation and miscommunication, in section 1 we will (...)
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  45. Wondrous Truths: The Improbable Triumph of Modern Science.J. D. Trout - 2016 - New York, US: Oxford University Press USA.
    A fresh, daring, and genuine alternative to the traditional story of scientific progress Explaining the world around us, and the life within it, is one of the most uniquely human drives, and the most celebrated activity of science. Good explanations are what provide accurate causal accounts of the things we wonder at, but explanation's earthly origins haven't grounded it: we have used it to account for the grandest and most wondrous mysteries in the natural world. Explanations give us a sense (...)
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  46. Regularity Constitution and the Location of Mechanistic Levels.Jens Harbecke - 2015 - Foundations of Science 20 (3):323-338.
    This paper discusses the role of levels and level-bound theoretical terms in neurobiological explanations under the presupposition of a regularity theory of constitution. After presenting the definitions for the constitution relation and the notion of a mechanistic level in the sense of the regularity theory, the paper develops a set of inference rules that allow to determine whether two mechanisms referred to by one or more accepted explanations belong to the same level, or to different levels. The rules are characterized (...)
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  47. Reconciling Ontic and Epistemic Constraints on Mechanistic Explanation, Epistemically.Dingmar van Eck - 2015 - Axiomathes 25 (1):5-22.
    In this paper I address the current debate on ontic versus epistemic conceptualizations of mechanistic explanation in the mechanisms literature. Illari recently argued that good explanations are subject to both ontic and epistemic constraints: they must describe mechanisms in the world in such fashion that they provide understanding of their workings. Elaborating upon Illari’s ‘integration’ account, I argue that causal role function discovery of mechanisms and their components is an epistemic prerequisite for achieving these two aims. This analysis extends Illari’s (...)
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  48. Prisoner's dilemma doesn't explain much.Robert Northcott & Anna Alexandrova - 2015 - In Martin Peterson (ed.), The Prisoner’s Dilemma. Classic philosophical arguments. Cambridge University Press. pp. 64-84.
    We make the case that the Prisoner’s Dilemma, notwithstanding its fame and the quantity of intellectual resources devoted to it, has largely failed to explain any phenomena of social scientific or biological interest. In the heart of the paper we examine in detail a famous purported example of Prisoner’s Dilemma empirical success, namely Axelrod’s analysis of WWI trench warfare, and argue that this success is greatly overstated. Further, we explain why this negative verdict is likely true generally and not just (...)
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  49. Beyond Belief: Randomness, Prediction and Explanation in Science.John L. Casti & Anders Karlqvist (eds.) - 2018 - Crc-Press.
    How can we predict and explain the phenomena of nature? What are the limits to this knowledge process? The central issues of prediction, explanation, and mathematical modeling, which underlie all scientific activity, were the focus of a conference organized by the Swedish Council for the Planning and Coordination of Research, held at the Abisko Research Station in May of 1989. At this forum, a select group of internationally known scientists in physics, chemistry, biology, economics, sociology and mathematics discussed and debated (...)
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  50. Mechanistic Science and Metaphysical Romance.Jacques Loeb - 1915 - Philosophical Review 24:570.
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1 — 50 / 388