What makes some explanations better than others? Although hugely important, detailed
assessments of the (comparative) 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 can be found in the literature on the explanatory power of
mechanistic and functional explanations. 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 be incorrect. This project aims to develop an in-depth account of the explanatory power of mechanistic and functional explanations.
The means employed include relevant notions from the explanation, scientific experimentation, and modeling literatures; and detailed 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, and provides means for
assessing the utility of engineering design methods.