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Causality in social theory via linguistic fuzzy logic
Authors:Badredine Arfi
Institution:1. Department of Political Science, University of Florida, 234 Anderson Hall, P.O. Box 117325, Gainesville, FL, 32611, USA
Abstract:I present a new approach to the study of causality in social theory using linguistic fuzzy logic as a framework. This approach differs from conventional analysis of causality on two fronts. First, all variables are considered to possess two degrees of freedom (or variation): a linguistic nuance value, which corresponds to what we conventionally refer to as interval or categorical value, and a linguistic truth value, which measures our confidence level in this nuance value. Second, combining this double fuzzification of variables with linguistic fuzzy logic I propose new tools for studying fuzzy causality. The linguistic fuzzy logic approach is illustrated through a re-examination of Skocpol’s (1979, States and social revolutions: a comparative analysis of France, Russia, and China. Cambridge University Press, Cambridge) theory of social revolution.
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