What makes some explanations better than others? Although hugely important, detailed assessments of the strength of specific explanations or explanation types are scarce in the philosophy of explanation. In this project I address this topic of explanatory power in the context of mechanistic and functional explanation, which are main explanation types in the life sciences.
Two competing perspectives on the explanatory power of mechanistic and functional explanations have been advanced. One side argues that the more complete a mechanistic explanation is, the better. The opposition argues that less elaborate mechanistic, i.e., functional, explanations that abstract from many details are often better.
However, both perspectives have been argued to apply to specific explanatory contexts only and ill-suited for other ones. This project aims to develop an in-depth account of the explanatory power of mechanistic and functional explanations across a variety of scientific disciplines.
The means employed include relevant notions from the explanation, scientific experimentation, and modeling literatures; and case studies from neuroscience, cognitive science, biology, and engineering.
This account innovates the explanatory power debate in the philosophy of explanation, contributes to cognitive science research on explanatory reasoning, provides means for assessing the utility of engineering design methods, and contributes to design analyses on the utility of design representations.