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A Framework for Pragmatic Reliability

Published online by Cambridge University Press:  01 January 2022

Abstract

I propose a framework for pragmatic reliability in-the-limit criteria, extending the epistemic reliability framework. I identify some common scientific contexts that complicate the application or interpretation of epistemic reliability criteria, drawing heavily from economics for illustrative examples. I then propose an extension of the standard framework, where inquiry is constrained by both epistemic and nonepistemic factors. This provides analogous notions of pragmatic underdetermination and pragmatic reliability with respect to a particular goal, as well as a principled method for extracting solvable problems from unsolvable ones.

Type
Research Article
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

I am very grateful to David Danks and Kevin Kelly and the referees to this journal for their helpful feedback on previous drafts of this work.

References

Belloni, A., and Chernozhukov, V.. 2011. “High Dimensional Sparse Econometric Models: An Introduction.” In Inverse Problems and High-Dimensional Estimation, 121–56. Berlin: Springer.Google Scholar
Carnap, R. 1945. “On Inductive Logic.” Philosophy of Science 12 (2): 7297..CrossRefGoogle Scholar
Cartwright, N. 1995. “‘Ceteris Paribus’ Laws and Socio-Economic Machines.” Monist 78 (3): 276–94..CrossRefGoogle Scholar
Cartwright, N.. 2002. “In Favor of Laws That Are Not Ceteris Paribus after All.” In Ceteris Paribus Laws, ed. Earman, J., Glymour, C., and Mitchell, S., 149–63. Dordrecht: Springer.Google Scholar
Chalupka, K., Eberhardt, F., and Perona, P.. 2017. “Causal Feature Learning: An Overview.” Behaviormetrika 44 (1): 137–64..CrossRefGoogle Scholar
Clyde, M. A., and Wolpert, R. L.. 2007. “Nonparametric Function Estimation Using Overcomplete Dictionaries.” Bayesian Statistics 8:91114.Google Scholar
Dewey, J. 1973. The Philosophy of John Dewey, ed. McDermott, J. J.. New York: Putnam.Google Scholar
Earman, J., and Roberts, J.. 1999. “Ceteris Paribus, There Is No Problem of Provisos.” Synthese 118 (3): 439–78..CrossRefGoogle Scholar
Friedman, M. 1953. “The Methodology of Positive Economics.” In Essays in Positive Economics. Chicago: Cambridge University Press.Google Scholar
Genin, K., and Kelly, K.. 2015. “Theory Choice, Theory Change, and Inductive Truth-Conduciveness.” Presented at the 15th Conference on Theoretical Aspects of Rationality and Knowledge, Carnegie Mellon University, June 46.Google Scholar
Genin, K., and Kelly, K.. 2017. “The Topology of Statistical Verifiability.” arXiv.org, Cornell University. https://arxiv.org/abs/1707.09378.Google Scholar
Haavelmo, T. 1944. “The Probability Approach in Econometrics.” Econometrica 12:1115.CrossRefGoogle Scholar
Hausman, D. M. 1988. “Ceteris Paribus Clauses and Causality in Economics.” In PSA 1988: Proceedings of the 1988 Biennial Meeting of the Philosophy of Science Association, vol. 2. East Lansing, MI: Philosophy of Science Association.Google Scholar
Hausman, D. M.. 1992. The Inexact and Separate Science of Economics. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Hempel, C. G. 1945. “Studies in the Logic of Confirmation.” Pt. 1. Mind 54 (213): 126..CrossRefGoogle Scholar
Hendry, D. F. 1980. “Econometrics—Alchemy or Science?Economica 47:387406.CrossRefGoogle Scholar
Jones, M., and Love, B. C.. 2011. “Bayesian Fundamentalism or Enlightenment? On the Explanatory Status and Theoretical Contributions of Bayesian Models of Cognition.” Behavioral and Brain Sciences 34 (4): 169–88..CrossRefGoogle ScholarPubMed
Kelly, K. T. 1996. The Logic of Reliable Inquiry. Oxford: Oxford University Press.Google Scholar
Kelly, K. T.. 2000. “The Logic of Success.” In Philosophy of Science Today, ed. Clark, P. and Hawley, K., 1138. Oxford: Clarendon.Google Scholar
Kelly, K. T.. 2014. “A Computational Learning Semantics for Inductive Empirical Knowledge.” In Johan van Benthem on Logic and Information Dynamics, ed. Baltag, A. and Smets, S., 289337. Cham: Springer.CrossRefGoogle Scholar
Lewicki, M. S., and Sejnowski, T. J.. 2000. “Learning Overcomplete Representations.” Neural Computation 12 (2): 337–65..CrossRefGoogle ScholarPubMed
McCloskey, D. N. 1998. The Rhetoric of Economics. Madison: University of Wisconsin Press.Google Scholar
Putnam, H. 1963. “Degree of Confirmation and Inductive Logic.” In The Philosophy of Rudolf Carnap, ed. Schilpp, P. A., 761–83. La Salle, IL: Open Court.Google Scholar
Sawyer, K., Beed, C., and Sankey, H.. 1997. “Underdetermination in Economics: The Duhem-Quine Thesis.” Economics and Philosophy 13 (1): 123..CrossRefGoogle Scholar
Skinner, B. F. 1953. Science and Human Behavior. New York: Simon & Schuster.Google Scholar
Sugden, R. 2000. “Credible Worlds: The Status of Theoretical Models in Economics.” Journal of Economic Methodology 7 (1): 131..CrossRefGoogle Scholar
Valente, M. 2005. “Qualitative Simulation Modelling.” Presented at the Fourth European Meeting on Applied Evolutionary Economics, Utrecht University, February.Google Scholar
van Fraassen, B. C. 1980. The Scientific Image. Oxford: Oxford University Press.CrossRefGoogle Scholar
Wellen, S., and Danks, D.. 2016. “Adaptively Rational Learning.” Minds and Machines 26 (1–2): 87102.CrossRefGoogle Scholar
Windrum, P., Fagiolo, G., and Moneta, A.. 2007. “Empirical Validation of Agent-Based Models: Alternatives and Prospects.” Journal of Artificial Societies and Social Simulation 10 (2): 18..Google Scholar