A very confusing problem: interpreting Keynesian weight - Brekel, Josh, author; Kasser, Jeff, advisor; Shockley, Kenneth, committee member; Prytherch, Ben, committee member (Colorado State University. Libraries, 2022)
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.
Keywords: higher-order evidence; probability; weight of evidence; Keynes; Bayesian; weight of argument