Empirical significance, predictive power, and explication

Abstract

Criteria of empirical significance are supposed to state conditions under which (putative) reference to an unobservable object or property is "empirically meaningful." The intended kind of empirical meaningfulness should be necessary for admissibility into the selective contexts of scientific inquiry. I defend Justus's recent argument that the reasons generally given for rejecting the project of defining a significance criterion are unpersuasive. However, as I show, this project remains wedded to an overly narrow conception of its subject matter. Even the most cutting edge significance criteria identify empirical significance with predictive power, and thereby rule out vocabulary with legitimate scientific functions. In a nutshell, the problem is that there are ("shortcut") terms that reduce the computational burden of extracting predictions from theory, and that may therefore be scientifically useful, but that do not produce any novel predictions, and so are ruled scientifically inadmissibility by existing significance criteria. I spell out this objection by specifying shortcut terms that are ruled inadmissible by Creath's and Schurz's criteria. Having objected in this way to extant criteria, and to the equation of empirical significance with predictive power in general, I discuss an approach to defining empirical significance that is capable of avoiding my objection and, more ambitiously, that may break the cycle of "punctures and patches" that has plagued the project from the beginning. I gloss Goldfarb and Ricketts's idea of "case-by-case" delineations of empirically significant terms as the provision of special rather than general explications of the informal concept of empirical significance.