Many methods are used in research on complexity. One of these is QCA. Although many authors allude to the relationships between complexity and QCA, these links are rarely made explicit. We propose that one way of doing so is by using critical realism as a meta-framework. This article discusses the viability of this approach by examining the extent to which QCA is a complexity-informed method. This question is answered in three steps. First, we discuss the nature of complexity and its epistemological implications. Second, we focus on Bhaskar’s perspective on critical realism and show how it can be used as a framework for understanding social complexity. Third, we examine the ontological and epistemological assumptions underlying QCA and synthesize these with our critical realist approach to complexity. We argue that complex reality is non-decomposable, contingent, non-compressible and time-asymmetric. We conclude that, although QCA is inevitably reductive (i.e. it compresses reality) and partial (i.e. it decomposes reality), its core premises are built upon the notions of contingency and time-asymmetry. Therefore, it is not only a powerful method for doing complexity-informed research, but is also a complexity-informed method by itself.
Publication | Gerrits, L.M. & Verweij, S. (2013). Critical realism as a meta-framework for understanding the relationships between complexity and qualitative comparative analysis. Journal of Critical Realism, 12 (2), 166-182.