Given that the core issues of attention research have been recognized for millenia, we do not know as much about attention as we should. I argue that the reasons for this failure are 1) we create spurious dichotomies, 2) we reify attention, treating it as a cause, when it is an effect, and 3) we equate a collection of facts with a theory. In order to correct these errors, we need a new technical vocabulary that allows for attentional effects to be continuously distributed, rather than merelypresent or absent, and that provides a basis for quantitative behavioral predictions that map onto neural substrates. The terminology of the Bayesian Decision Process has already proved useful for structuring conceptual discussions in other psychological domains, such as perception and decision making under uncertainty, and it had demonstrated early success in the domain of attention. By rejecting a reified, causal conception of attention, in favor of theories that produce attentionaleffects as consequences, psychologists will be able to conduct more definitive experiments. Such conceptual advances will then enhance the productivity of neuroscientists by allowing them to concentrate their data collection efforts on the richest soil.