Comparative Causation at Multiple Levels and Across Scientific Disciplines

Abstract

In this paper, we analyse the fruitfulness of Ronald Giere’s comparative model for causation in populations. While the original model was primarily developed to capture the meaning of causal claims in the biomedical and health sciences, we want to show that the model is not only useful in these domains, but can also fruitfully be applied to other scientific domains. Specifically, we demonstrate that the model is fruitful for characterizing the meaning of causal claims found in classical genetics, epidemiology and electoral sociology. Additionally, we propose an adapted comparative model which is needed to get a grip on higher level causal claims. We show that such claims are present in population genetics, (environmental) epidemiology and electoral systems research. We conclude with some reflections on the implications of our findings for the issue of causal pluralism.