Abstract

In science all hypothesis-testing rely on a multitude of background assumptions.However, the Quine-Duhem thesis tells us that upon refutation, or disconfirma-tion, there is no principled way of determining which of these assumptions shouldbe abandoned in light of the evidence. Attempts have been made to provideBayesian models that can provide a logic to resolve this problem. In this paperI identify, describe, compare and evaluate two such models. The first is dueto John Dorling and the second to Michael Strevens. I argue that Dorling’ssolution to the problem presented by the Quine-Duhem thesis is preferable tothat proposed by Strevens.