Synthese 200 (2):1-23 (2022)

Authors
Rosa W. Runhardt
Leiden University
Abstract
Evidential pluralists, like Federica Russo and Jon Williamson, argue that causal claims should be corroborated by establishing both the existence of a suitable correlation and a suitable mechanism complex. At first glance, this fits well with mixed method research in the social sciences, which often involves a pluralist combination of statistical and mechanistic evidence. However, statistical evidence concerns a population of cases, while mechanistic evidence is found in individual case studies. How should researchers combine such general statistical evidence and specific mechanistic evidence? This article discusses a very recent answer to this question, ‘multi-method large-N qualitative analysis’ or multi-method LNQA, popular in political science and international relations studies of rare events like democratic transitions and cease-fire agreements. Multi-method LNQA combines a comprehensive study of all relevant event cases with statistical analysis, in an attempt to solve the issues of generalization faced by other types of qualitative research, such as selection bias and lack of representativeness. I will argue that the kind of general causal claim that multi-method LNQA is after, however, is crucially different from the average treatment effect found in statistical analysis and can in fact only be supported with mechanistic evidence. I conclude from this that mixed method research, and thereby evidential pluralism, may be inappropriate in this context.
Keywords evidential pluralism  causal mechanism  case study research  mixed methods research  multi-method research  large-N qualitative research
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DOI 10.1007/s11229-022-03650-w
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References found in this work BETA

Thinking About Mechanisms.Peter Machamer, Lindley Darden & Carl F. Craver - 2000 - Philosophy of Science 67 (1):1-25.
Interpreting Causality in the Health Sciences.Federica Russo & Jon Williamson - 2007 - International Studies in the Philosophy of Science 21 (2):157 – 170.
Probabilistic Causality.Ellery Eells - 1991 - Cambridge, England: Cambridge University Press.

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