Measurement of Statistical Evidence: Picking Up Where Hacking and Others Left Off. - Vieland, Veronica J. (Philosophy of Science, 2017)
Hacking's Law of Likelihood says--paraphrasing--that data support hypothesis H1 over hypothesis H2 whenever the likelihood ratio (LR) for H1 over H exceeds 1. But Hacking later noted a seemingly fatal flaw in the LR itself: it cannot be interpreted as the degree of "evidential significance" across applications. I agree with Hacking about the problem, but I do not believe the condition is incurable. I argue here that the LR can be properly calibrated with respect to the underlying evidence, and I sketch the rudiments of a methodology for so doing.