The quantity-quality debate in social sciences also concerns concept formation and operationalization. The first approach has strong naturalist assumptions, while the second one focuses on the historical specificity of concepts. The solution to overcome this divide would be finding a path which balances the two perspectives. In this article we argue that fuzzy set theory can be a helpful tool for concept formation and operationalization. The application of fuzzy set theory to concept formation and operationalization provides, first, the opportunity of looking at concepts as complex constructs made up of attributes logically interconnected one with the other and, second, of measuring them accordingly. Thus, after presenting our general argument, we show a theoretical and an empirical application of how to use fuzzy sets in concept formation and operationalization.
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For instance, Goertz (2006) uses the example of copper. This type of metal has an atomic structure that “produces” its reddish color, but we would be mistaken if we based the conceptualization upon this characteristic, which is the effect of the atomic structure and not a property itself.
See Komatsu (1992) for a review on cognitive approaches to concepts.
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The quantity-quality debate in social sciences also concerns concept formation and operationalization. The first approach has strong naturalist assumptions, while the second one focuses on the historical specificity of concepts. The solution to overcome this divide would be finding a path which balances the two perspectives. In this article we argue that fuzzy set theory can be a helpful tool for concept formation and operationalization. The application of fuzzy set theory to concept formation and operationalization provides, first, the opportunity of looking at concepts as complex constructs made up of attributes logically interconnected one with the other and, second, of measuring them accordingly. Thus, after presenting our general argument, we show a theoretical and an empirical application of how to use fuzzy sets in concept formation and operationalization.
All Time | Past Year | Past 30 Days | |
---|---|---|---|
Abstract Views | 328 | 274 | 21 |
Full Text Views | 20 | 9 | 2 |
PDF Views & Downloads | 37 | 19 | 2 |