The chapter discusses the principle of conservatism and traces how the general principle is related to the specific one. This tracing suggests that the principle of conservatism needs to be refined. Connecting the principle in cognitive science to more general questions about scientific inference also allows us to revisit the question of realism versus instrumentalism. The framework deployed in model selection theory is very general; it is not specific to the subject matter of science. The chapter outlines some non-Bayesian ideas that have been developed in model selection theory. The principle of conservatism, like C. Lloyd Morgan's canon, describes a preference concerning kinds of parameters. It says that a model that postulates only lower-level intentionality is preferable to one that postulates higher-level intentionality if both fit the data equally well. The model selection approach to parsimony helps explain why unification is a theoretical virtue.