Linguistic Fuzzy-Logic and Causality

Abstract

We depend upon the notion of causation all the time to explain what happens to us. We use causal statements to draw realistic predictions about what might happen as well as to direct what should happen in the future. In short, we are in constant searches for causal explanation and behavior. A widespread motto is to put it formally ”X caused Y” or ”Y occurred because of X.” Not surprisingly then, studying and explaining as well as modeling causality is at the core of much of what counts as social sciences today. Although other types of analysis (such as constitutive) are important aspects of our inquiry about the social and political world, causal analysis absorbs much of our collective effort. Yet, the tools that have been designed for this purpose remain rather limited in social sciences, and more so in political science and international relations. For the most part scholars use statistical means to explore causality. While this has produced a wealth of knowledge and led to the design of powerful statistical tools and insights, there is still a need for other types of tools that would complement the achievements of statistical methods, as well as address issues that statistical analysis cannot reach.