Explanation and Color-Naming Research

Abstract

Perhaps one of the central assumptions when one comes to think about scientific explanations—an assumption made by philosophers and scientists alike—is that a causal explanation is an optimal explanation. It seems, after all, that an explanation tells us why something happens and that to do so is to specify causes. Although there is nothing wrong with causal explanations per se, many good explanations in science are not in any important sense causal. What I mean by this is that many good explanations in science are compatible with a variety of causal mechanisms and, as such, ignore the details of such mechanisms. I develop this claim in the discussion of color-naming research that follows, where I distinguish between explanation types that are (more) close to causality (actual sequence explanations) and those that are (more) removed from causal details (robust process explanations).