Crediting or blaming theories or auxiliary assumptions for empirical victories or defeats

Abstract

There is no direct way for researchers to test theories. One reason is that theories contain nonobservational terms that refer to unobservable entities. Consequently, researchers add auxiliary assumptions to aid in traversing the distance between theories and empirical hypotheses. The results may confirm the empirical hypothesis, an empirical victory, or the results may disconfirm the empirical hypothesis, an empirical defeat. Either way, it is not clear whether to make an attribution to the theory, the auxiliary assumptions, or both. The present goal is to review techniques researchers have employed, or could employ, that aid in assessing the weight of the evidence with respect to crediting or blaming theories or auxiliary assumptions for empirical victories or defeats.