Abstract

This paper introduces a novel framework for causal selection based on an analysis of different ways in which causes interact. Some causal interactions function to enable the operation of a mechanism, while others modify the behavior or outcome of that mechanism, allowing fine-grained descriptions of causal relationships. Distinguishing between enabling and modifying makes it possible to separate distinct causal functions that are wrongly grouped into an undifferentiated category of background conditions. Drawing on case studies from ecology, the framework offers new insights into why some factors should be cited in explanations while others remain implicit, despite being causally indispensable.