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  1. Philosophy for the Rest of Cognitive Science.Nigel Stepp, Anthony Chemero & Michael T. Turvey - 2011 - Topics in Cognitive Science 3 (2):425-437.
    Cognitive science has always included multiple methodologies and theoretical commitments. The philosophy of cognitive science should embrace, or at least acknowledge, this diversity. Bechtel’s (2009a) proposed philosophy of cognitive science, however, applies only to representationalist and mechanist cognitive science, ignoring the substantial minority of dynamically oriented cognitive scientists. As an example of nonrepresentational, dynamical cognitive science, we describe strong anticipation as a model for circadian systems (Stepp & Turvey, 2009). We then propose a philosophy of science appropriate to nonrepresentational, dynamical (...)
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  • Getting Interaction Theory (IT) Together: Integrating Developmental, Phenomenological, Enactive, and Dynamical Approaches to Social Interaction.Tom Froese & Shaun Gallagher - 2012 - Interaction Studies 13 (3):436-468.
    We argue that progress in our scientific understanding of the `social mind' is hampered by a number of unfounded assumptions. We single out the widely shared assumption that social behavior depends solely on the capacities of an individual agent. In contrast, both developmental and phenomenological studies suggest that the personal-level capacity for detached `social cognition' (conceived as a process of theorizing about and/or simulating another mind) is a secondary achievement that is dependent on more immediate processes of embodied social interaction. (...)
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  • Heuristics, Descriptions, and the Scope of Mechanistic Explanation.Carlos Zednik - 2015 - In P. Braillard & C. Malaterre (eds.), Explanation in Biology. An Enquiry into the Diversity of Explanatory Patterns in the Life Sciences. Dordrecht: Springer. pp. 295-318.
    The philosophical conception of mechanistic explanation is grounded on a limited number of canonical examples. These examples provide an overly narrow view of contemporary scientific practice, because they do not reflect the extent to which the heuristic strategies and descriptive practices that contribute to mechanistic explanation have evolved beyond the well-known methods of decomposition, localization, and pictorial representation. Recent examples from evolutionary robotics and network approaches to biology and neuroscience demonstrate the increasingly important role played by computer simulations and mathematical (...)
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  • Explanation in Computational Neuroscience: Causal and Non-Causal.M. Chirimuuta - 2018 - British Journal for the Philosophy of Science 69 (3):849-880.
    This article examines three candidate cases of non-causal explanation in computational neuroscience. I argue that there are instances of efficient coding explanation that are strongly analogous to examples of non-causal explanation in physics and biology, as presented by Batterman, Woodward, and Lange. By integrating Lange’s and Woodward’s accounts, I offer a new way to elucidate the distinction between causal and non-causal explanation, and to address concerns about the explanatory sufficiency of non-mechanistic models in neuroscience. I also use this framework to (...)
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  • Why One Model is Never Enough: A Defense of Explanatory Holism.Hochstein Eric - 2017 - Biology and Philosophy 32 (6):1105-1125.
    Traditionally, a scientific model is thought to provide a good scientific explanation to the extent that it satisfies certain scientific goals that are thought to be constitutive of explanation. Problems arise when we realize that individual scientific models cannot simultaneously satisfy all the scientific goals typically associated with explanation. A given model’s ability to satisfy some goals must always come at the expense of satisfying others. This has resulted in philosophical disputes regarding which of these goals are in fact necessary (...)
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  • Explaining Features of Fine-Grained Phenomena Using Abstract Analyses of Phenomena and Mechanisms: Two Examples From Chronobiology.William Bechtel - 2017 - Synthese:1-23.
    Explanations of biological phenomena such as cell division, protein synthesis or circadian rhythms commonly take the form of models of the responsible mechanisms. Recently philosophers of science have attempted to analyze this practice, presenting mechanisms as organized collections of parts performing operations that together produce the phenomenon. But in some cases what researchers seek to explain is not a general phenomenon, but a specific feature of a more fine-grained phenomenon. In some of these cases, it is not the model of (...)
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  • The Structure of Sensorimotor Explanation.Alfredo Vernazzani - 2018 - Synthese.
    The sensorimotor theory of vision and visual consciousness is often described as a radical alternative to the computational and connectionist orthodoxy in the study of visual perception. However, it is far from clear whether the theory represents a significant departure from orthodox approaches or whether it is an enrichment of it. In this study, I tackle this issue by focusing on the explanatory structure of the sensorimotor theory. I argue that the standard formulation of the theory subscribes to the same (...)
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  • Mechanisms in Cognitive Science.Carlos Zednik - 2017 - In Phyllis McKay Illari & Stuart Glennan (eds.), The Routledge Handbook of Mechanisms and Mechanical Philosophy. London: Routledge. pp. 389-400.
    This chapter subsumes David Marr’s levels of analysis account of explanation in cognitive science under the framework of mechanistic explanation: Answering the questions that define each one of Marr’s three levels is tantamount to describing the component parts and operations of mechanisms, as well as their organization, behavior, and environmental context. By explicating these questions and showing how they are answered in several different cognitive science research programs, this chapter resolves some of the ambiguities that remain in Marr’s account, and (...)
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  • Hegelian Phenomenology and Robotics.Donald S. Borrett, David Shih, Michael Tomko, Sarah Borrett & Hon C. Kwan - 2011 - International Journal of Machine Consciousness 3 (01):219-235.
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  • Explanatory Power of Extended Cognition.Samuli Pöyhönen - 2014 - Philosophical Psychology 27 (5):735-759.
    I argue that examining the explanatory power of the hypothesis of extended cognition (HEC) offers a fruitful approach to the problem of cognitive system demarcation. Although in the discussions on HEC it has become common to refer to considerations of explanatory power as a means for assessing the plausibility of the extended cognition approach, to date no satisfying account of explanatory power has been presented in the literature. I suggest that the currently most prominent theory of explanation in the special (...)
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  • One Mechanism, Many Models: A Distributed Theory of Mechanistic Explanation.Eric Hochstein - 2016 - Synthese 193 (5):1387-1407.
    There have been recent disagreements in the philosophy of neuroscience regarding which sorts of scientific models provide mechanistic explanations, and which do not. These disagreements often hinge on two commonly adopted, but conflicting, ways of understanding mechanistic explanations: what I call the “representation-as” account, and the “representation-of” account. In this paper, I argue that neither account does justice to neuroscientific practice. In their place, I offer a new alternative that can defuse some of these disagreements. I argue that individual models (...)
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  • Explanation and Description in Computational Neuroscience.David Michael Kaplan - 2011 - 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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  • The Extended Mind: Born to Be Wild? A Lesson From Action-Understanding. [REVIEW]Nivedita Gangopadhyay - 2011 - Phenomenology and the Cognitive Sciences 10 (3):377-397.
    The extended mind hypothesis (Clark and Chalmers in Analysis 58(1):7–19, 1998; Clark 2008) is an influential hypothesis in philosophy of mind and cognitive science. I argue that the extended mind hypothesis is born to be wild. It has undeniable and irrepressible tendencies of flouting grounding assumptions of the traditional information-processing paradigm. I present case-studies from social cognition which not only support the extended mind proposal but also bring out its inherent wildness. In particular, I focus on cases of action-understanding and (...)
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  • The Consciousness of Embodied Cognition, Affordances, and the Brain.Valerie Gray Hardcastle - forthcoming - Topoi:1-11.
    Tony Chemero advances the radical thesis that cognition and consciousness are actually the same thing. I question this conclusion. Even if we are the brain–body environmental synergies that Chemero and others claim, we will not be able to conclude that consciousness is just cognition because this view actually expands cognition beyond being the sort of natural kind upon which to hook phenomenal experience. Identifying consciousness with cognition either means consciousness exists at multiple levels of organization in the universe, or more (...)
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  • Breaking Explanatory Boundaries: Flexible Borders and Plastic Minds.Michael D. Kirchhoff & Russell Meyer - 2019 - Phenomenology and the Cognitive Sciences 18 (1):185-204.
    In this paper, we offer reasons to justify the explanatory credentials of dynamical modeling in the context of the metaplasticity thesis, located within a larger grouping of views known as 4E Cognition. Our focus is on showing that dynamicism is consistent with interventionism, and therefore with a difference-making account at the scale of system topologies that makes sui generis explanatory differences to the overall behavior of a cognitive system. In so doing, we provide a general overview of the interventionist approach. (...)
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  • Extended Functionalism, Radical Enactivism, and the Autopoietic Theory of Cognition: Prospects for a Full Revolution in Cognitive Science.Mario Villalobos & David Silverman - 2018 - Phenomenology and the Cognitive Sciences 17 (4):719-739.
    Recently, Michael Wheeler has argued that despite its sometimes revolutionary rhetoric, the so called 4E cognitive movement, even in the guise of ‘radical’ enactivism, cannot achieve a full revolution in cognitive science. A full revolution would require the rejection of two essential tenets of traditional cognitive science, namely internalism and representationalism. Whilst REC might secure antirepresentationalism, it cannot do the same, so Wheeler argues, with externalism. In this paper, expanding on Wheeler’s analysis, we argue that what compromises REC’s externalism is (...)
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  • Explanatory Pluralism in Cognitive Science.Rick Dale, Eric Dietrich & Anthony Chemero - 2009 - Cognitive Science 33 (2):739-742.
    This brief commentary has three goals. The first is to argue that ‘‘framework debate’’ in cognitive science is unresolvable. The idea that one theory or framework can singly account for the vast complexity and variety of cognitive processes seems unlikely if not impossible. The second goal is a consequence of this: We should consider how the various theories on offer work together in diverse contexts of investigation. A final goal is to supply a brief review for readers who are compelled (...)
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  • What is a Cognitive Ontology, Anyway?Annelli Janssen, Colin Klein & Marc Slors - 2017 - Philosophical Explorations 20 (2):123-128.
    This special issue brings together philosophical perspectives on the debate over cognitive ontology. We contextualize the papers in this issue by considering several different senses of the term “cognitive ontology” and linking those debates to traditional debates in philosophy of mind.
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  • Mechanistic and Non-Mechanistic Varieties of Dynamical Models in Cognitive Science: Explanatory Power, Understanding, and the ‘Mere Description’ Worry.Raoul Gervais - 2015 - Synthese 192 (1):43-66.
    In the literature on dynamical models in cognitive science, two issues have recently caused controversy. First, what is the relation between dynamical and mechanistic models? I will argue that dynamical models can be upgraded to be mechanistic as well, and that there are mechanistic and non-mechanistic dynamical models. Second, there is the issue of explanatory power. Since it is uncontested the mechanistic models can explain, I will focus on the non-mechanistic variety of dynamical models. It is often claimed by proponents (...)
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  • Intentional Models as Essential Scientific Tools.Eric Hochstein - 2013 - International Studies in the Philosophy of Science 27 (2):199-217.
    In this article, I argue that the use of scientific models that attribute intentional content to complex systems bears a striking similarity to the way in which statistical descriptions are used. To demonstrate this, I compare and contrast an intentional model with a statistical model, and argue that key similarities between the two give us compelling reasons to consider both as a type of phenomenological model. I then demonstrate how intentional descriptions play an important role in scientific methodology as a (...)
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  • A Property Cluster Theory of Cognition.Cameron Buckner - 2013 - Philosophical Psychology (3):1-30.
    Our prominent definitions of cognition are too vague and lack empirical grounding. They have not kept up with recent developments, and cannot bear the weight placed on them across many different debates. I here articulate and defend a more adequate theory. On this theory, behaviors under the control of cognition tend to display a cluster of characteristic properties, a cluster which tends to be absent from behaviors produced by non-cognitive processes. This cluster is reverse-engineered from the empirical tests that comparative (...)
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  • Functional Analysis and Mechanistic Explanation.David Barrett - 2014 - Synthese 191 (12):2695-2714.
    Piccinini and Craver (Synthese 183:283–311, 2011) argue for the surprising view that psychological explanation, properly understood, is a species of mechanistic explanation. This contrasts with the ‘received view’ (due, primarily, to Cummins and Fodor) which maintains a sharp distinction between psychological explanation and mechanistic explanation. The former is typically construed as functional analysis, the analysis of some psychological capacity into an organized series of subcapacities without specifying any of the structural features that underlie the explanandum capacity. The latter idea, of (...)
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  • How We Remember: Brain Mechanisms of Episodic Memory.Sarah Robins - 2015 - Philosophical Psychology 28 (6):903-915.
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  • Dynamics and Cognition.Lawrence A. Shapiro - 2013 - Minds and Machines 23 (3):353-375.
    Many who advocate dynamical systems approaches to cognitive science believe themselves committed to the thesis of extended cognition and to the rejection of representation. I argue that this belief is false. In part, this misapprehension rests on a warrantless re-conception of cognition as intelligent behavior. In part also, it rests on thinking that conceptual issues can be resolved empirically. Once these issues are sorted out, the way is cleared for a dynamical systems approach to cognition that is free to retain (...)
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  • Minimal Models and Canonical Neural Computations: The Distinctness of Computational Explanation in Neuroscience.M. Chirimuuta - 2014 - Synthese 191 (2):127-153.
    In a recent paper, Kaplan (Synthese 183:339–373, 2011) takes up the task of extending Craver’s (Explaining the brain, 2007) mechanistic account of explanation in neuroscience to the new territory of computational neuroscience. He presents the model to mechanism mapping (3M) criterion as a condition for a model’s explanatory adequacy. This mechanistic approach is intended to replace earlier accounts which posited a level of computational analysis conceived as distinct and autonomous from underlying mechanistic details. In this paper I discuss work in (...)
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  • Complexity and Extended Phenomenological‐Cognitive Systems.Michael Silberstein & Anthony Chemero - 2012 - Topics in Cognitive Science 4 (1):35-50.
    The complex systems approach to cognitive science invites a new understanding of extended cognitive systems. According to this understanding, extended cognitive systems are heterogenous, composed of brain, body, and niche, non-linearly coupled to one another. This view of cognitive systems, as non-linearly coupled brain–body–niche systems, promises conceptual and methodological advances. In this article we focus on two of these. First, the fundamental interdependence among brain, body, and niche makes it possible to explain extended cognition without invoking representations or computation. Second, (...)
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  • The Nonmechanistic Option: Defending Dynamical Explanation.Russell Meyer - 2018 - British Journal for the Philosophy of Science:0-0.
    This paper demonstrates that nonmechanistic, dynamical explanations are a viable approach to explanation in the special sciences. The claim that dynamical models can be explanatory without reference to mechanisms has previously been met with three lines of criticism from mechanists: the causal relevance concern, the genuine laws concern, and the charge of predictivism. I argue, however, that these mechanist criticisms fail to defeat nonmechanistic, dynamical explanation. Using the examples of Haken et al.’s ([1985]) HKB model of bimanual coordination, and Thelen (...)
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  • The Explanatory Force of Dynamical and Mathematical Models in Neuroscience: A Mechanistic Perspective.David Michael Kaplan & Carl F. Craver - 2011 - Philosophy of Science 78 (4):601-627.
    We argue that dynamical and mathematical models in systems and cognitive neuro- science explain (rather than redescribe) a phenomenon only if there is a plausible mapping between elements in the model and elements in the mechanism for the phe- nomenon. We demonstrate how this model-to-mechanism-mapping constraint, when satisfied, endows a model with explanatory force with respect to the phenomenon to be explained. Several paradigmatic models including the Haken-Kelso-Bunz model of bimanual coordination and the difference-of-Gaussians model of visual receptive fields are (...)
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  • Structures, Dynamics and Mechanisms in Neuroscience: An Integrative Account.Holger Lyre - 2018 - Synthese 195 (12):5141-5158.
    Proponents of mechanistic explanations have recently proclaimed that all explanations in the neurosciences appeal to mechanisms. The purpose of the paper is to critically assess this statement and to develop an integrative account that connects a large range of both mechanistic and dynamical explanations. I develop and defend four theses about the relationship between dynamical and mechanistic explanations: that dynamical explanations are structurally grounded, that they are multiply realizable, possess realizing mechanisms and provide a powerful top-down heuristic. Four examples shall (...)
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  • Metaphysics or Science: The Battle for the Soul of Philosophy of Mind.Michael Silberstein - 2011 - Philosophical Psychology 24 (4):561-573.
    Philosophical Psychology, Volume 24, Issue 4, Page 561-573, August 2011.
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  • Monism Versus Emergence? The One and the Many.Michael Silberstein - 2015 - Metascience 24 (1):43-48.
    This will be an admittedly opinionated review that gives with one hand and takes with the other. Let me be clear though from the outset that there is much to admire and agree with here. Perhaps, the biggest complaint is the failure of the author to engage with other highly relevant literature in philosophy of science and metaphysics that would yield her natural allies or would provide natural foils that ought to be named and engaged. On the allies side, there (...)
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  • The Cognitive Neuroscience Revolution.Worth Boone & Gualtiero Piccinini - 2016 - Synthese 193 (5):1509-1534.
    We outline a framework of multilevel neurocognitive mechanisms that incorporates representation and computation. We argue that paradigmatic explanations in cognitive neuroscience fit this framework and thus that cognitive neuroscience constitutes a revolutionary break from traditional cognitive science. Whereas traditional cognitive scientific explanations were supposed to be distinct and autonomous from mechanistic explanations, neurocognitive explanations aim to be mechanistic through and through. Neurocognitive explanations aim to integrate computational and representational functions and structures across multiple levels of organization in order to explain (...)
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  • Making Too Many Enemies: Hutto and Myin’s Attack on Computationalism.Jesse Kuokkanen & Anna-Mari Rusanen - 2018 - Philosophical Explorations 21 (2):282-294.
    We analyse Hutto & Myin's three arguments against computationalism [Hutto, D., E. Myin, A. Peeters, and F. Zahnoun. Forthcoming. “The Cognitive Basis of Computation: Putting Computation In Its Place.” In The Routledge Handbook of the Computational Mind, edited by M. Sprevak, and M. Colombo. London: Routledge.; Hutto, D., and E. Myin. 2012. Radicalizing Enactivism: Basic Minds Without Content. Cambridge, MA: MIT Press; Hutto, D., and E. Myin. 2017. Evolving Enactivism: Basic Minds Meet Content. Cambridge, MA: MIT Press]. The Hard Problem (...)
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  • Moving Parts: The Natural Alliance Between Dynamical and Mechanistic Modeling Approaches.David Michael Kaplan - 2015 - Biology and Philosophy 30 (6):757-786.
    Recently, it has been provocatively claimed that dynamical modeling approaches signal the emergence of a new explanatory framework distinct from that of mechanistic explanation. This paper rejects this proposal and argues that dynamical explanations are fully compatible with, even naturally construed as, instances of mechanistic explanations. Specifically, it is argued that the mathematical framework of dynamics provides a powerful descriptive scheme for revealing temporal features of activities in mechanisms and plays an explanatory role to the extent it is deployed for (...)
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  • The Nature of Dynamical Explanation.Carlos Zednik - 2011 - Philosophy of Science 78 (2):238-263.
    The received view of dynamical explanation is that dynamical cognitive science seeks to provide covering law explanations of cognitive phenomena. By analyzing three prominent examples of dynamicist research, I show that the received view is misleading: some dynamical explanations are mechanistic explanations, and in this way resemble computational and connectionist explanations. Interestingly, these dynamical explanations invoke the mathematical framework of dynamical systems theory to describe mechanisms far more complex and distributed than the ones typically considered by philosophers. Therefore, contemporary dynamicist (...)
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  • Constraints on Localization and Decomposition as Explanatory Strategies in the Biological Sciences.Michael Silberstein & Anthony Chemero - 2013 - Philosophy of Science 80 (5):958-970.
    Several articles have recently appeared arguing that there really are no viable alternatives to mechanistic explanation in the biological sciences (Kaplan and Bechtel; Kaplan and Craver). We argue that mechanistic explanation is defined by localization and decomposition. We argue further that systems neuroscience contains explanations that violate both localization and decomposition. We conclude that the mechanistic model of explanation needs to either stretch to now include explanations wherein localization or decomposition fail or acknowledge that there are counterexamples to mechanistic explanation (...)
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  • Interdisciplinary Collaboration in Philosophy.Andrew Higgins & Alexis Dyschkant - 2014 - Metaphilosophy 45 (3):372-398.
    Many philosophers would, in theory, agree that the methods and tools of philosophy ought to be supplemented by those of other academic disciplines. In practice, however, the sociological data suggest that most philosophers fail to engage or collaborate with other academics, and this article argues that this is problematic for philosophy as a discipline. In relation to the value of interdisciplinary collaboration, the article highlights how experimental philosophers can benefit the field, but only insofar as they draw from the distinctive (...)
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  • Emergence and Reduction in Context: Philosophy of Science and/or Analytic Metaphysics. [REVIEW]Michael Silberstein - 2012 - Metascience 21 (3):627-642.
    Emergence and reduction in context: Philosophy of science and/or analytic metaphysics Content Type Journal Article Category Survey Review Pages 1-16 DOI 10.1007/s11016-012-9671-4 Authors Michael Silberstein, Elizabethtown College, Elizabethtown, PA 17022, USA Journal Metascience Online ISSN 1467-9981 Print ISSN 0815-0796.
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