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Limits to Evidential Pluralism: Multi-Method Large-N Qualitative Analysis and the Primacy of Mechanistic Studies

Runhardt, Rosa W. (2022) Limits to Evidential Pluralism: Multi-Method Large-N Qualitative Analysis and the Primacy of Mechanistic Studies. [Preprint]

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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 (or most) 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.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Runhardt, Rosa W.rosa.runhardt@ru.nl0000-0002-8679-4977
Additional Information: Preprint of article forthcoming in Synthese as part of the special collection on Evidential Diversity.
Keywords: evidential pluralism; causal mechanisms; case study research; large-N qualitative analysis; LNQA; mixed-methods research; multi-method research; causal inference; social science; political science; international relations
Subjects: General Issues > Causation
Depositing User: Dr Rosa W. Runhardt
Date Deposited: 13 Mar 2022 05:50
Last Modified: 13 Mar 2022 05:50
Item ID: 20326
Subjects: General Issues > Causation
Date: 2022
URI: https://philsci-archive-dev.library.pitt.edu/id/eprint/20326

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