Abstract

An aim of science is to increase our understanding of the natural world. A primary means for doing so is by providing explanations, which often proceed by tracing the causes of phenomena. How can a causal explanation lead to understanding? While explanations can take many forms, I argue that to succeed they must embody a conception of causation shared with their audience. The challenge then, is to describe this conception and detail its role in explanation. While there is good evidence that scientists employ more than one causal concept, I argue that the concept of productive causation (centered on the notion of bringing about change via a connection) has a primary role in natural science explanations. After critiquing other philosophical accounts, I develop a new theory of productive causation and show how it provides an underpinning for successful explanations. The heart of the theory is a network of persisting processes that possess dispositions toward change-producing mutual interactions. I argue that in a good explanation, the scientific entities, properties and activities invoked will correspond to the theory’s depiction of causal structure. One important dimension of the theory describes how repeated patterns of interaction can give rise to a hierarchy of composite processes. This allows the theory to account for stabilized entities at various spatio-temporal scales. In turn, this enables the approach to be applicable throughout the natural sciences. After starting with simple examples, I show how the theory deals with more challenging cases from physics to biology. I conclude that the approach illuminates how explanations of various forms across diverse disciplines can lead to scientific understanding.