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  1. Goal-dependence in ontology.David Danks - 2015 - Synthese 192 (11):3601-3616.
    Our best sciences are frequently held to be one way, perhaps the optimal way, to learn about the world’s higher-level ontology and structure. I first argue that which scientific theory is “best” depends in part on our goals or purposes. As a result, it is theoretically possible to have two scientific theories of the same domain, where each theory is best for some goal, but where the two theories posit incompatible ontologies. That is, it is possible for us to have (...)
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  • Drift beyond Wright–Fisher.Hayley Clatterbuck - 2015 - Synthese 192 (11):3487-3507.
    Several recent arguments by philosophers of biology have challenged the traditional view that evolutionary factors, such as drift and selection, are genuine causes of evolutionary outcomes. In the case of drift, advocates of the statistical theory argue that drift is merely the sampling error inherent in the other stochastic processes of evolution and thus denotes a mathematical, rather than causal, feature of populations. This debate has largely centered around one particular model of drift, the Wright–Fisher model, and this has contributed (...)
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  • Where is the theory in our 'theories' of causality?Nancy Cartwright - 2007 - In Hunting Causes and Using Them: Approaches in Philosophy and Economics. New York: Cambridge University Press. pp. 43-56.
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  • “To navigate safely in the vast sea of empirical facts”: Ontology and methodology in behavioral economics.Erik Angner - 2015 - Synthese 192 (11):3557-3575.
    This paper examines issues of ontology and methodology in behavioral economics: the attempt to increase the explanatory and predictive power of economic theory by providing it with more psychologically plausible foundations. Of special interest is the epistemological status of neoclassical economic theory within behavioral economics, the runaway success story of contemporary economics. Behavioral economists aspire to replace the fundamental assumptions of orthodox, neoclassical economic theory. Yet, behavioral economists have gone out of their way to praise those very assumptions. Matthew Rabin, (...)
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  • Hunting Causes and Using Them: Approaches in Philosophy and Economics.Nancy Cartwright (ed.) - 2007 - New York: Cambridge University Press.
    Hunting Causes and Using Them argues that causation is not one thing, as commonly assumed, but many. There is a huge variety of causal relations, each with different characterizing features, different methods for discovery and different uses to which it can be put. In this collection of new and previously published essays, Nancy Cartwright provides a critical survey of philosophical and economic literature on causality, with a special focus on the currently fashionable Bayes-nets and invariance methods - and it exposes (...)
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  • Methodology, ontology, and interventionism.James Woodward - 2015 - Synthese 192 (11):3577-3599.
    This paper defends an interventionist account of causation by construing this account as a contribution to methodology, rather than as a set of theses about the ontology or metaphysics of causation. It also uses the topic of causation to raise some more general issues about the relation between, on the one hand, methodology, and, on the other hand, ontology and metaphysics, as these are understood in contemporary philosophical discussion, particularly among so-called analytic metaphysicians. It concludes with the suggestion that issues (...)
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  • Error statistical modeling and inference: Where methodology meets ontology.Aris Spanos & Deborah G. Mayo - 2015 - Synthese 192 (11):3533-3555.
    In empirical modeling, an important desiderata for deeming theoretical entities and processes as real is that they can be reproducible in a statistical sense. Current day crises regarding replicability in science intertwines with the question of how statistical methods link data to statistical and substantive theories and models. Different answers to this question have important methodological consequences for inference, which are intertwined with a contrast between the ontological commitments of the two types of models. The key to untangling them is (...)
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  • Scientific misrepresentation and guides to ontology: the need for representational code and contents.Elay Shech - 2015 - Synthese 192 (11):3463-3485.
    In this paper I show how certain requirements must be set on any tenable account of scientific representation, such as the requirement allowing for misrepresentation. I then continue to argue that two leading accounts of scientific representation— the inferential account and the interpretational account—are flawed for they do not satisfy such requirements. Through such criticism, and drawing on an analogy from non-scientific representation, I also sketch the outline of a superior account. In particular, I propose to take epistemic representations to (...)
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  • The Shaky Game +25, or: on locavoracity.Laura Ruetsche - 2015 - Synthese 192 (11):3425-3442.
    Taking Arthur Fine’s The Shaky Game as my inspiration, and the recent 25th anniversary of the publication of that work as the occasion to exercise that inspiration, I sketch an alternative to the “Naturalism” prevalent among philosophers of physics. Naturalism is a methodology eventuating in a metaphysics. The methodology is to seek the deep framework assumptions that make the best sense of science; the metaphysics is furnished by those assumptions and supported by their own support of science. The alternative presented (...)
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  • Methodological realism and modal resourcefulness: out of the web and into the mine.Lydia Patton - 2015 - Synthese 192 (11):3443-3462.
    Psillos, Kitcher, and Leplin have defended convergent scientific realism against the pessimistic meta-induction by arguing for the divide et impera strategy. I argue that DEI faces a problem more serious than the pessimistic meta-induction: the problem of accretion. When empirically successful theories and principles are combined, they may no longer make successful predictions or allow for accurate calculations, or the combination otherwise may be an empirical failure. The shift from classical mechanics to the new quantum theory does not reflect the (...)
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  • Projection, symmetry, and natural kinds.Benjamin C. Jantzen - 2015 - Synthese 192 (11):3617-3646.
    Scientific practice involves two kinds of induction. In one, generalizations are drawn about the states of a particular system of variables. In the other, generalizations are drawn across systems in a class. We can discern two questions of correctness about both kinds of induction: what distinguishes those systems and classes of system that are ‘projectible’ in Goodman’s sense from those that are not, and what are the methods by which we are able to identify kinds that are likely to be (...)
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  • The ontological status of shocks and trends in macroeconomics.Kevin D. Hoover - 2015 - Synthese 192 (11):3509-3532.
    Modern empirical macroeconomic models, known as structural autoregressions (SVARs) are dynamic models that typically claim to represent a causal order among contemporaneously valued variables and to merely represent non-structural (reduced-form) co-occurence between lagged variables and contemporaneous variables. The strategy is held to meet the minimal requirements for identifying the residual errors in particular equations in the model with independent, though otherwise not directly observable, exogenous causes (“shocks”) that ultimately account for change in the model. In nonstationary models, such shocks accumulate (...)
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  • Interpreting Quantum Theories: The Art of the Possible.Laura Ruetsche - 2011 - Oxford, GB: Oxford University Press UK.
    Philosophers of quantum mechanics have generally addressed exceedingly simple systems. Laura Ruetsche offers a much-needed study of the interpretation of more complicated systems, and an underexplored family of physical theories, such as quantum field theory and quantum statistical mechanics, showing why they repay philosophical attention. She guides those familiar with the philosophy of ordinary QM into the philosophy of 'QM infinity', by presenting accessible introductions to relevant technical notions and the foundational questions they frame--and then develops and defends answers to (...)
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  • Constructing Variables That Support Causal Inference.Stephen E. Fancsali - unknown
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