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Description: Empirical researchers using Qualitative Comparative Analysis can work with crisp, multi-value and fuzzy sets. The relative advantages and disadvantages of crisp and multi-value sets have been discussed in the QCA literature. There has been little reflection on the more frequently encountered decision between crisp and fuzzy sets. Empirical researchers often prefer fuzzy over crisp sets because they contain more information. This meets with the methodological argument that fuzzy sets produce more conservative consistency measures and constitute tougher tests. In my paper, I take an analytical perspective and use data from published QCA studies to demonstrate that the relationship between crisp and fuzzy sets and the consistency score is ambiguous. It depends on the distribution of cases whether the consistency value is more or less conservative for fuzzy sets than for crisp sets. Based on this insight, I outline the implications of the ambiguous relationship for empirical QCA research.

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