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  1. Holly Andersen (forthcoming). Complements, Not Competitors: Causal and Mathematical Explanations. British Journal for the Philosophy of Science.
    A finer-grained delineation of a given explanandum reveals a nexus of closely related causal and non- causal explanations, complementing one another in ways that yield further explanatory traction on the phenomenon in question. By taking a narrower construal of what counts as a causal explanation, a new class of distinctively mathematical explanations pops into focus; Lange’s characterization of distinctively mathematical explanations can be extended to cover these. This new class of distinctively mathematical explanations is illustrated with the Lotka-Volterra equations. There (...)
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  2. Holly Andersen (2012). The Case for Regularity in Mechanistic Causal Explanation. Synthese 189 (3):415-432.
    How regular do mechanisms need to be, in order to count as mechanisms? This paper addresses two arguments for dropping the requirement of regularity from the definition of a mechanism, one motivated by examples from the sciences and the other motivated by metaphysical considerations regarding causation. I defend a broadened regularity requirement on mechanisms that takes the form of a taxonomy of kinds of regularity that mechanisms may exhibit. This taxonomy allows precise explication of the degree and location of regular (...)
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  3. Holly Andersen (2011). Mechanisms, Laws, and Regularities. Philosophy of Science 78 (2):325-331.
    Leuridan (2010) argued that mechanisms cannot provide a genuine alternative to laws of nature as a model of explanation in the sciences, and advocates Mitchell’s (1997) pragmatic account of laws. I first demonstrate that Leuridan gets the order of priority wrong between mechanisms, regularity, and laws, and then make some clarifying remarks about how laws and mechanisms relate to regularities. Mechanisms are not an explanatory alternative to regularities; they are an alternative to laws. The existence of stable regularities in nature (...)
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  4. 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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  5. Marina Paola Banchetti-Robino (2011). Ontological Tensions in Sixteenth and Seventeenth Century Chemistry: Between Mechanism and Vitalism. Foundations of Chemistry 13 (3):173-186.
    The sixteenth and seventeenth centuries marks a period of transition between the vitalistic ontology that had dominated Renaissance natural philosophy and the Early Modern mechanistic paradigm endorsed by, among others, the Cartesians and Newtonians. This paper will focus on how the tensions between vitalism and mechanism played themselves out in the context of sixteenth and seventeenth century chemistry and chemical philosophy, particularly in the works of Paracelsus, Jan Baptista Van Helmont, Robert Fludd, and Robert Boyle. Rather than argue that these (...)
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  6. Jordan Bartol (2013). Causality in the Sciences. Edited by Russo, Williamson and Illari. Oxford University Press, 2011, Pp. 952, £95. ISBN: 978-0-19-957413-1. [REVIEW] Philosophy 88 (3):487-493.
  7. Maarten Boudry & Massimo Pigliucci (2013). The Mismeasure of Machine: Synthetic Biology and the Trouble with Engineering Metaphors. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (4):660-668.
    The scientific study of living organisms is permeated by machine and design metaphors. Genes are thought of as the ‘‘blueprint’’ of an organism, organisms are ‘‘reverse engineered’’ to discover their functionality, and living cells are compared to biochemical factories, complete with assembly lines, transport systems, messenger circuits, etc. Although the notion of design is indispensable to think about adaptations, and engineering analogies have considerable heuristic value (e.g., optimality assumptions), we argue they are limited in several important respects. In particular, (...)
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  8. Ingo Brigandt (2015). Evolutionary Developmental Biology and the Limits of Philosophical Accounts of Mechanistic Explanation. In P.-A. Braillard & C. Malaterre (eds.), Explanation in Biology: An Enquiry into the Diversity of Explanatory Patterns in the Life Sciences. Springer 135–173.
    Evolutionary developmental biology (evo-devo) is considered a ‘mechanistic science,’ in that it causally explains morphological evolution in terms of changes in developmental mechanisms. Evo-devo is also an interdisciplinary and integrative approach, as its explanations use contributions from many fields and pertain to different levels of organismal organization. Philosophical accounts of mechanistic explanation are currently highly prominent, and have been particularly able to capture the integrative nature of multifield and multilevel explanations. However, I argue that evo-devo demonstrates the need for a (...)
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  9. Ingo Brigandt (2013). Systems Biology and the Integration of Mechanistic Explanation and Mathematical Explanation. Studies in History and Philosophy of Biological and Biomedical Sciences 44 (4):477-492.
    The paper discusses how systems biology is working toward complex accounts that integrate explanation in terms of mechanisms and explanation by mathematical models—which some philosophers have viewed as rival models of explanation. Systems biology is an integrative approach, and it strongly relies on mathematical modeling. Philosophical accounts of mechanisms capture integrative in the sense of multilevel and multifield explanations, yet accounts of mechanistic explanation (as the analysis of a whole in terms of its structural (...)
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  10. Daniel C. Burnston, Benjamin Sheredos, Adele Abrahamsen & William Bechtel (2014). Scientists’ Use of Diagrams in Developing Mechanistic Explanations: A Case Study From Chronobiology. Pragmatics and Cognition 22 (2):224-243.
  11. Noam Chomsky (2009). The Mysteries of Nature: How Deeply Hidden? Journal of Philosophy 106 (4):167-200.
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  12. Matteo Colombo, Stephan Hartmann & Robert van Iersel (2015). Models, Mechanisms, and Coherence. British Journal for the Philosophy of Science 66 (1):181-212.
    Life-science phenomena are often explained by specifying the mechanisms that bring them about. The new mechanistic philosophers have done much to substantiate this claim and to provide us with a better understanding of what mechanisms are and how they explain. Although there is disagreement among current mechanists on various issues, they share a common core position and a seeming commitment to some form of scientific realism. But is such a commitment necessary? Is it the best way to go about mechanistic (...)
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  13. Mark B. Couch (2011). Mechanisms and Constitutive Relevance. Synthese 183 (3):375-388.
    This paper will examine the nature of mechanisms and the distinction between the relevant and irrelevant parts involved in a mechanism’s operation. I first consider Craver’s account of this distinction in his book on the nature of mechanisms, and explain some problems. I then offer a novel account of the distinction that appeals to some resources from Mackie’s theory of causation. I end by explaining how this account enables us to better understand what mechanisms are and their various features.
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  14. Kelso Cratsley (forthcoming). The Shift to Mechanistic Explanation and Classification. In S. Tekin & J. Poland (eds.), Extraordinary Science: Responding to the Current Crisis in Psychiatric Research. MIT Press
    Despite widespread recognition that psychiatry would be better served by a classificatory system based on etiology rather than mere description, it goes without saying that much of the necessary work is yet to be done. Most of it will be empirical, but there are also conceptual issues that need to be addressed. In this chapter I take up the increasingly important question of how mechanistic explanation fits into the larger effort to build a scientifically sound etiological and nosological framework for (...)
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  15. Carl F. Craver (2006). When Mechanistic Models Explain. Synthese 153 (3):355-376.
    Not all models are explanatory. Some models are data summaries. Some models sketch explanations but leave crucial details unspecified or hidden behind filler terms. Some models are used to conjecture a how-possibly explanation without regard to whether it is a how-actually explanation. I use the Hodgkin and Huxley model of the action potential to illustrate these ways that models can be useful without explaining. I then use the subsequent development of the explanation of the action potential to show what is (...)
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  16. Monika Dullstein (2010). Verursachung und kausale Relevanz. Eine Analyse singulärer Kausalaussagen. Mentis.
    Die philosophische Kausaldebatte hat in den vergangenen vier Jahrzehnten eine neue Blüte erlebt. Kontrafaktische, interventionistische, mechanistische und transfertheoretische Ansätze haben sich neben den bislang dominierenden Regularitätstheorien etabliert. Vertreter aller dieser Ansätze sehen sich jedoch mit Gegenbeispielen konfrontiert, keine Theorie scheint allen unseren intuitiven Kausalurteilen gerecht werden zu können. Dieses Buch führt anhand ausgewählter Beispiele in die aktuelle Debatte ein und liefert eine Erklärung für die derzeitige Patt-Situation. Der Grund dafür, dass sich zu jedem Ansatz offenbar mühelos Gegenbeispiele finden lassen, liegt, (...)
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  17. Ronald P. Endicott (forthcoming). Developing The Explanatory Dimensions of Part-Whole Realization. Philosophical Studies.
    I use Carl Gillett's much heralded dimensioned theory of realization as a platform to develop a plausible part-whole theory. I begin with some basic desiderata for a theory of realization that its key terms should be defined and that it should be explanatory. I then argue that Gillett's original theory violates these conditions because its explanatory force rests upon an unspecified "in virtue of" relation. I then examine Gillett's later version that appeals instead to theoretical terms tied to "mechanisms." Yet (...)
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  18. Ronald P. Endicott (forthcoming). Functionalism, Superduperfunctionalism, and Physicalism: Lessons From Supervenience. Synthese:1-31.
    Philosophers almost universally believe that concepts of supervenience fail to satisfy the standards for physicalism because they offer mere property correlations that are left unexplained. They are thus compatible with non-physicalist accounts of those relations. Moreover, many philosophers not only prefer some kind of functional-role theory as a physically acceptable account of mind-body and other inter-level relations, but they use it as a form of “superdupervenience” to explain supervenience in a physically acceptable way. But I reject a central part of (...)
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  19. Luis H. Favela (2015). Understanding Cognition Via Complexity Science. Dissertation, University of Cincinnati
    Mechanistic frameworks of investigation and explanation dominate the cognitive, neural, and psychological sciences. In this dissertation, I argue that mechanistic frameworks cannot, in principle, explain some kinds of cognition. In its place, I argue that complexity science has methods and theories more appropriate for investigating and explaining some cognitive phenomena. -/- I begin with an examination of the term 'cognition.' I defend the idea that "cognition" has been a moving target of investigation in the relevant sciences. As such it is (...)
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  20. Carla Fehr, Sex and Explanatory Pluralism: Is It a Case of Causal Mechanism Versus Unifying Theories of Explanation?
    There is more than one explanation for the evolution of sexual reproduction. This paper investigates the possibility that this pluralism exists because these different explanations rely on intuitions provided by different philosophical theories of explanation, namely unifying views and causal mechanical views. I conclude that this is not the case.
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  21. Laura Felline (forthcoming). Mechanisms Meet Structural Explanation. Synthese:1-16.
    This paper investigates the relationship between Structural Explanation and the New Mechanistic account of explanation. The aim of this paper is twofold: firstly, to argue that some phenomena in the domain of fundamental physics, although mechanically brute, are structurally explained; and secondly, by elaborating on the contrast between SE and ME, to better clarify some features of SE. Finally, this paper will argue that, notwithstanding their apparently antithetical character, SE and ME can be reconciled within a unified account of general (...)
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  22. 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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  23. 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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  24. Carl Gillett (2007). A Mechanist Manifesto for the Philosophy of Mind: A Third Way for Functionalists. Journal of Philosophical Research 32:21-42.
    One of the main early forms of “functionalism,” developed by writers like Jerry Fodor and William Lycan, focused on “mechanistic” explanation in the special sciences and argued that “functional properties” in psychology were continuous in nature with the special science properties posited in such mechanistic explanations. I dub the latter position“Continuity Functionalism” and use it to critically examine the “Standard Picture” of the metaphysics of functionalism which takes “functional” properties to be second-order properties and claims there are two metaphysical forms (...)
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  25. James Griesemer (2011). Philosophy and Tinkering. Biology and Philosophy 26 (2):269-279.
    I characterize Wimsatt’s approach to philosophy of science as philosophy for science and then briefly consider a theme emerging from his work that informs just one of the many current developments in philosophy of biology that he inspired: scaffolding as a problem of mechanistic explanation for functionalists.
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  26. Peter Hedström & Petri Ylikoski (2011). Analytical Sociology. In Ian C. Jarvie & Jesus Zamoro Bonilla (eds.), The SAGE Handbook of the Philosophy of Social Sciences. SAGE
  27. 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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  28. Devin Henry (2005). Embryological Models in Ancient Philosophy. Phronesis 50 (1):1-42.
    Historically embryogenesis has been among the most philosophically intriguing phenomena. In this paper I focus on one aspect of biological development that was particularly perplexing to the ancients: self-organisation. For many ancients, the fact that an organism determines the important features of its own development required a special model for understanding how this was possible. This was especially true for Aristotle, Alexander, and Simplicius who all looked to contemporary technology to supply that model. However, they did not all agree on (...)
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  29. Mitchell Herschbach (2012). On the Role of Social Interaction in Social Cognition: A Mechanistic Alternative to Enactivism. [REVIEW] Phenomenology and the Cognitive Sciences 11 (4):467-486.
    Researchers in the enactivist tradition have recently argued that social interaction can constitute social cognition, rather than simply serve as the context for social cognition. They contend that a focus on social interaction corrects the overemphasis on mechanisms inside the individual in the explanation of social cognition. I critically assess enactivism’s claims about the explanatory role of social interaction in social cognition. After sketching the enactivist approach to cognition in general and social cognition in particular, I identify problems (...)
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  30. Mitchell Herschbach & William Bechtel (2014). Mental Mechanisms and Psychological Construction. In Lisa Feldman Barrett & James Russell (eds.), The Psychological Construction of Emotion. Guilford Press 21-44.
    Psychological construction represents an important new approach to psychological phenomena, one that has the promise to help us reconceptualize the mind both as a behavioral and as a biological system. It has so far been developed in the greatest detail for emotion, but it has important implications for how researchers approach other mental phenomena such as reasoning, memory, and language use. Its key contention is that phenomena that are characterized in (folk) psychological vocabulary are not themselves basic (...)
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  31. Frank Hindriks, Concretization, Explanation, and Mechanisms.
    Traditional accounts of explanation fail to illuminate the explanatory relevance of “models that are descriptively false” in the sense that the regularities they entail fail to obtain. In this paper, I propose an account of explanation, which I call ‘explanation by concretization’, that serves to explicate the explanatory relevance of such models. Starting from a highly abstract and idealized model, causal explanations of the absence of regularities are sought by adding complexity to the model or by concretizing it. Whether this (...)
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  32. Nicholaos Jones (2014). Bowtie Structures, Pathway Diagrams, and Topological Explanation. Erkenntnis 79 (5):1135-1155.
    While mechanistic explanation and, to a lesser extent, nomological explanation are well-explored topics in the philosophy of biology, topological explanation is not. Nor is the role of diagrams in topological explanations. These explanations do not appeal to the operation of mechanisms or laws, and extant accounts of the role of diagrams in biological science explain neither why scientists might prefer diagrammatic representations of topological information to sentential equivalents nor how such representations might facilitate important processes of explanatory reasoning unavailable to (...)
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  33. Marie I. Kaiser & Beate Krickel (2016). The Metaphysics of Constitutive Mechanistic Phenomena. British Journal for the Philosophy of Science:axv058.
    The central aim of this article is to specify the ontological nature of constitutive mechanistic phenomena (that is, of phenomena that are explained in constitutive mechanistic explanations). After identifying three criteria of adequacy that any plausible approach to constitutive mechanistic phenomena must satisfy, we present four different suggestions, found in the mechanistic literature, of what mechanistic phenomena might be. We argue that none of these suggestions meets the criteria of adequacy. According to our analysis, constitutive mechanistic phenomena are best understood (...)
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  34. David Michael Kaplan (2012). How to Demarcate the Boundaries of Cognition. Biology and Philosophy 27 (4):545-570.
    Advocates of extended cognition argue that the boundaries of cognition span brain, body, and environment. Critics maintain that cognitive processes are confined to a boundary centered on the individual. All participants to this debate require a criterion for distinguishing what is internal to cognition from what is external. Yet none of the available proposals are completely successful. I offer a new account, the mutual manipulability account, according to which cognitive boundaries are determined by relationships of mutual manipulability between (...)
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  35. David Michael Kaplan (2011). Explanation and Description in Computational Neuroscience. Synthese 183 (3):339-373.
    The central aim of this paper is to shed light on the nature of explanation in computational neuroscience. I argue that computational models in this domain possess explanatory force to the extent that they describe the mechanisms responsible for producing a given phenomenon—paralleling how other mechanistic models explain. Conceiving computational explanation as a species of mechanistic explanation affords an important distinction between computational models that play genuine explanatory roles and those that merely provide accurate descriptions or predictions of phenomena. It (...)
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  36. Machiel Keestra (2015). Understanding Human Action. Integrating Meanings, Mechanisms, Causes, and Contexts. In V. Bazhanov & R. W. Scholz (eds.), Transdisciplinarity in philosophy and science: approaches, problems, prospects. Russian Academy of Science 201-235.
    Humans are capable of understanding an incredible variety of actions performed by other humans. Even though these range from primary biological actions, like eating and fleeing, to acts in parliament or in poetry, humans generally can make sense of each other’s actions. Action understanding is the cognitive ability to make sense of another person’s action by integrating perceptual information about the behavior with knowledge about the immediate and sociocultural contexts of the action, understanding of relevant meanings and one’s own experience. (...)
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  37. Beate Krickel (forthcoming). A Regularist Approach to Mechanistic Type-Level Explanation. British Journal for the Philosophy of Science.
    Most defenders of the new mechanistic approach accept ontic constraints for successful scientific explanation (Illari 2013; Craver 2014). The minimal claim is that scientific explanations have objective truthmakers, namely mechanisms that exist in the physical world independently of any observer and that cause or constitute the phenomena-to- be-explained. How can this idea be applied to type-level explanations? Many authors at least implicitly assume that in order for mechanisms to be the truthmakers of type-level explanation they need to be regular (Andersen (...)
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  38. 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.
    Constitutivemechanisticexplanationsexplainapropertyofawholewith the properties of its parts and their organization. Carl Craver’s mutual manipulability criterion for constitutive relevance only captures the explanatory relevance of causal properties of parts and leaves the organization side of mechanistic explanation unaccounted for. We use the contrastive counterfactual theory of explanation and an account of the dimensions of organization to build a typology of organizational dependence. We analyse organizational explanations in terms of such dependencies and emphasize the importance of modular organizational motifs. We (...)
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  39. Jaakko Kuorikoski & Petri Ylikoski (2010). Explanatory Relevance Across Disciplinary Boundaries: The Case of Neuroeconomics. Journal of Economic Methodology 17 (2):219–228.
    Many of the arguments for neuroeconomics rely on mistaken assumptions about criteria of explanatory relevance across disciplinary boundaries and fail to distinguish between evidential and explanatory relevance. Building on recent philosophical work on mechanistic research programmes and the contrastive counterfactual theory of explanation, we argue that explaining an explanatory presupposition or providing a lower-level explanation does not necessarily constitute explanatory improvement. Neuroscientific findings have explanatory relevance only when they inform a causal and explanatory account of the psychology of human decision-making.
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  40. Arnon Levy (2013). Three Kinds of New Mechanism. Biology and Philosophy 28 (1):99-114.
    I distinguish three theses associated with the new mechanistic philosophy – concerning causation, explanation and scientific methodology. Advocates of each thesis are identified and relationships among them are outlined. I then look at some recent work on natural selection and mechanisms. There, attention to different kinds of New Mechanism significantly affects of what is at stake.
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  41. Peter K. Machamer, Lindley Darden & Carl F. Craver (2000). Thinking About Mechanisms. Philosophy of Science 67 (1):1-25.
    The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.
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  42. John Matthewson & Brett Calcott, Mechanistic Explanation Without Mechanisms.
    We provide an account of mechanistic representation and explanation that has several advantages over previous proposals. In our view, explaining mechanistically is not simply giving an explanation of a mechanism. Rather, an explanation is mechanistic because of particular relations that hold between a mechanical representation, or model, and the target of explanation. Under this interpretation, mechanistic explanation is possible even when the explanatory target is not a mechanism. We argue that taking this view is not only coherent and plausible, it (...)
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  43. Dana Matthiessen (forthcoming). Mechanistic Explanation in Systems Biology: Cellular Networks. British Journal for the Philosophy of Science:axv011.
    It is argued that once biological systems reach a certain level of complexity, mechanistic explanations provide an inadequate account of many relevant phenomena. In this article, I evaluate such claims with respect to a representative programme in systems biological research: the study of regulatory networks within single-celled organisms. I argue that these networks are amenable to mechanistic philosophy without need to appeal to some alternate form of explanation. In particular, I claim that we can understand the mathematical modelling techniques of (...)
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  44. Nancy L. Maull (1982). Berkeley on the Limits of Mechanistic Explanation. In Colin M. Turbayne (ed.), Berkeley: Critical and Interpretive Essays.
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  45. Alexander Mebius (2015). Philosophical Controversies in the Evaluation of Medical Treatments : With a Focus on the Evidential Roles of Randomization and Mechanisms in Evidence-Based Medicine. Dissertation, KTH Royal Institute of Technology
    This thesis examines philosophical controversies surrounding the evaluation of medical treatments, with a focus on the evidential roles of randomised trials and mechanisms in Evidence-Based Medicine. Current 'best practice' usually involves excluding non-randomised trial evidence from systematic reviews in cases where randomised trials are available for inclusion in the reviews. The first paper challenges this practice and evaluates whether adding of evidence from non-randomised trials might improve the quality and precision of some systematic reviews. The second paper compares the alleged (...)
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  46. Steph Menken, Machiel Keestra, Lucas Rutting, Ger Post, Mieke de Roo, Sylvia Blad & Linda de Greef (eds.) (2016). An Introduction to Interdisciplinary Research. Theory and Practice. Amsterdam University Press.
    This book (128 pp.) serves as an introduction and manual to guide students through the interdisciplinary research process. We are becoming increasingly aware that, as a result of technological developments and globalisation, problems are becoming so complex that they can only be solved through cooperation between multiple disciplines. Healthcare, climate change, food security, energy, financial markets and quality of life are just a few examples of issues that require scientists and academics to work in a crossdisciplinary way. As a result (...)
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  47. Roberta L. Millstein (2007). Review of Lindley Darden, Reasoning in Biological Discoveries: Essays on Mechanisms, Interfield Relations, and Anomaly Resolution. [REVIEW] Notre Dame Philosophical Reviews 2007 (7).
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  48. Marcin Miłkowski (forthcoming). Explanatory Completeness and Idealization in Large Brain Simulations: A Mechanistic Perspective. Synthese:1-22.
    The claim defended in the paper is that the mechanistic account of explanation can easily embrace idealization in big-scale brain simulations, and that only causally relevant detail should be present in explanatory models. The claim is illustrated with two methodologically different models: Blue Brain, used for particular simulations of the cortical column in hybrid models, and Eliasmith’s SPAUN model that is both biologically realistic and able to explain eight different tasks. By drawing on the mechanistic theory of computational explanation, I (...)
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  49. Marcin Miłkowski (2015). Satisfaction Conditions in Anticipatory Mechanisms. Biology and Philosophy 30 (5):709-728.
    The purpose of this paper is to present a general mechanistic framework for analyzing causal representational claims, and offer a way to distinguish genuinely representational explanations from those that invoke representations for honorific purposes. It is usually agreed that rats are capable of navigation because they maintain a cognitive map of their environment. Exactly how and why their neural states give rise to mental representations is a matter of an ongoing debate. I will show that anticipatory mechanisms involved in rats’ (...)
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  50. Marcin Miłkowski (2015). Evaluating Artificial Models of Cognition. Studies in Logic, Grammar and Rhetoric 40 (1):43-62.
    Artificial models of cognition serve different purposes, and their use determines the way they should be evaluated. There are also models that do not represent any particular biological agents, and there is controversy as to how they should be assessed. At the same time, modelers do evaluate such models as better or worse. There is also a widespread tendency to call for publicly available standards of replicability and benchmarking for such models. In this paper, I argue that proper evaluation ofmodels (...)
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