Causal Explanation and Multi-Method Research in the Social Sciences
Year: 2009
Type: preprint
Abstract: After a long and often fiercely fought debate over the respective values of quantitative and qualitative methods in the social sciences, multi-method research (MMR) is emerging as a new methodological paradigm. The debate on MMR meets with the ongoing discussion about standards of good causal inference and explanation. It is now widely acknowledged in the philosophy of science as well as in the social sciences that one should strive for causal explanations that include propositions of both causal effects and causal processes. These developments notwithstanding and somewhat surprisingly, the actual potential of MMR to produce robust causal explanations has received little attention. We argue that the dimension to be discussed in light of the plea for causal explanations and MMR concerns the distinction between deterministic and probabilistic causality. A rigorous discussion of the relationship between causal explanation and deterministic and probabilistic causality should therefore be the next step in the debate about multi-method research. This is what we aim to provide in the first section of our paper. Based on the conceptual framework outlined in the first section, we evaluate the potential of MMR to develop and test causal explanations in the second part of our paper. In this we argue that chance to make a meaningful connection of the cross-case method and the within-case part is severely reduced if the causal relationship is probabilistic. Consequently, we conclude that the causal inferences generated through MMR are considerably less certain than the current state of the debate suggests.
Source: SSRN Electronic Journal
Authors: David Kuehn, Ingo Rohlfing
Institution: Heidelberg University
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2247470467