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  1. Understanding with theoretical models.Petri Ylikoski & N. Emrah Aydinonat - 2014 - Journal of Economic Methodology 21 (1):19-36.
    This paper discusses the epistemic import of highly abstract and simplified theoretical models using Thomas Schelling’s checkerboard model as an example. We argue that the epistemic contribution of theoretical models can be better understood in the context of a cluster of models relevant to the explanatory task at hand. The central claim of the paper is that theoretical models make better sense in the context of a menu of possible explanations. In order to justify this claim, we introduce a distinction (...)
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  • Dissecting explanatory power.Petri Ylikoski & Jaakko Kuorikoski - 2010 - Philosophical Studies 148 (2):201–219.
    Comparisons of rival explanations or theories often involve vague appeals to explanatory power. In this paper, we dissect this metaphor by distinguishing between different dimensions of the goodness of an explanation: non-sensitivity, cognitive salience, precision, factual accuracy and degree of integration. These dimensions are partially independent and often come into conflict. Our main contribution is to go beyond simple stipulation or description by explicating why these factors are taken to be explanatory virtues. We accomplish this by using the contrastive-counterfactual approach (...)
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  • Making things happen: a theory of causal explanation.James F. Woodward - 2003 - New York: Oxford University Press.
    Woodward's long awaited book is an attempt to construct a comprehensive account of causation explanation that applies to a wide variety of causal and explanatory claims in different areas of science and everyday life. The book engages some of the relevant literature from other disciplines, as Woodward weaves together examples, counterexamples, criticisms, defenses, objections, and replies into a convincing defense of the core of his theory, which is that we can analyze causation by appeal to the notion of manipulation.
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  • Review of Woodward, Making Things Happen. [REVIEW]Michael Strevens - 2007 - Philosophy and Phenomenological Research 74 (1):233-249.
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  • Computing the perfect model: Why do economists Shun simulation?Aki Lehtinen & Jaakko Kuorikoski - 2007 - Philosophy of Science 74 (3):304-329.
    Like other mathematically intensive sciences, economics is becoming increasingly computerized. Despite the extent of the computation, however, there is very little true simulation. Simple computation is a form of theory articulation, whereas true simulation is analogous to an experimental procedure. Successful computation is faithful to an underlying mathematical model, whereas successful simulation directly mimics a process or a system. The computer is seen as a legitimate tool in economics only when traditional analytical solutions cannot be derived, i.e., only as a (...)
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  • Foundations of Social Theory.James Samuel Coleman - 1990 - Belknap Press.
    Combining principles of individual rational choice with a sociological conception of collective action, James Coleman recasts social theory in a bold new way. The result is a landmark in sociological theory, capable of describing both stability and change in social systems. This book provides for the first time a sound theoretical foundation for linking the behavior of individuals to organizational behavior and then to society as a whole. The power of the theory is especially apparent when Coleman analyzes corporate actors, (...)
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  • Models and Cognition: Prediction and Explanation in Everyday Life and in Science.Jonathan A. Waskan - 2006 - Bradford.
    Jonathan Walkan challenges cognitive science's dominant model of mental representation and proposes a novel, well-devised alternative. The traditional view in the cognitive sciences uses a linguistic model of mental representation. That logic-based model of cognition informs and constrains both the classical tradition of artificial intelligence and modeling in the connectionist tradition. It falls short, however, when confronted by the frame problem---the lack of a principled way to determine which features of a representation must be updated when new information becomes available. (...)
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  • The invisible hand in economics: how economists explain unintended social consequences.N. Emrah Aydinonat - 2008 - New York: Routledge.
    Introduction -- Unintended consequences -- The origin of money -- Segregation -- The invisible hand -- The origin of money reconsidered -- Models and representation -- Game theory and conventions -- Conclusion.
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  • Causal Mechanisms in the Social Sciences.Peter Hedström & Petri Ylikoski - 2010 - 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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  • Simulation and the sense of understanding.Jaakko Kuorikoski - 2011 - In Paul Humphreys & Cyrille Imbert (eds.), Models, Simulations, and Representations. London: Routledge. pp. 168-187.
    Whether simulation models provide the right kind of understanding comparable to that of analytic models has been and remains a contentious issue. The assessment of understanding provided by simulations is often hampered by a conflation between the sense of understanding and understanding proper. This paper presents a deflationist conception of understanding and argues for the need to replace appeals to the sense of understanding with explicit criteria of explanatory relevance and for rethinking the proper way of conceptualizing the role of (...)
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  • The Illusion of Depth of Understanding in Science.Petri Ylikoski - 2009 - In Henk De Regt, Sabina Leonelli & Kai Eigner (eds.), Scientific Understanding: Philosophical Perspectives. University of Pittsburgh Press. pp. 100--119.
    In this chapter I will employ a well-known scientific research heuristic that studies how something works by focusing on circumstances in which it does not work. Rather than trying to describe what scientific understanding would ideally look like, I will try to learn something about it by observing mundane cases where understanding is partly illusory. My main thesis is that scientists are prone to the illusion of depth of understanding (IDU), and as a consequence they sometimes overestimate the detail, coherence, (...)
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