A very confusing problem: interpreting Keynesian weight
Date
2022
Authors
Brekel, Josh, author
Kasser, Jeff, advisor
Shockley, Kenneth, committee member
Prytherch, Ben, committee member
Journal Title
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Abstract
Initially outlined by John Maynard Keynes in 1921, Keynesian weight is a measure intended to characterize evidence independently of probability. As a concept that is often immersed in confusion, Keynesian weight requires thorough philosophical explication prior to any sort of legitimate use in decision-making, legal proceedings, or scientific inquiry. In this thesis, I attempt to explicate Keynesian weight by arguing in favor of Jochen Runde's relative interpretation of Keynesian weight. The aim of Chapter 1 is to introduce the basic idea of Keynesian weight. In Chapter 2, I demonstrate that Keynes's initial analysis of Keynesian weight creates an interpretative puzzle—two viable interpretations of Keynesian weight exist. Chapter 3 aims to solve the interpretative puzzle by consideration of how the interpretations of Keynesian weight respond to I.J. Good's criticism of Keynesian weight. Ultimately, I argue that Good's criticism demonstrates that the best interpretation of Keynesian weight is the relative interpretation.
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Subject
higher-order evidence
probability
weight of evidence
Keynes
Bayesian
weight of argument