The Lab's Quarterly, 2008, n. 1

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Il Trimestrale. The Lab's Quarterly, 1, 2008


fuzzy scores, and finally he chooses what level of memberships corresponds to what level of the measured variable. On one hand we find a series of operations that could be somehow considered biased towards subjectivism; on the other hand, however, we are making explicit and formalizing the operational steps used, in a more implicit way, in traditional quantitative researches, where often the final appearance of "objectivity" is given by the numerical form of data, while the decisions of the researcher remain hidden. I think it is really essential to allow a public screening of those element of the operationalization procedure, letting them available to other researchers, because that is the better guarantee of respect for the relationship between theory and facts, fundamental for the construction of any sociometric instrument. In a recent article outlining the standards of construction for a research based upon the comparative fuzzy procedure designed by Ragin, the authors (Wagemann and Schneider, 2007, pp.22-23) when writing about the determination of membership functions, merely indicate that the procedures for positioning of anchor points (0, 0.5 and 1membership values) and the definition of the rules by which we assign the membership values to cases must be transparent and explicit, must be based on empirical and theoretical information, and the researcher must keep in mind their interpretative, open to revision nature. I think this is not enough. The indications given by Ragin and by Wagemann and Schneider are certainly methodological accuracies much needed, but their compliance only ensures the post-hoc verifiability of theory-facts correspondence, and the adequacy of the research tool; it is not of great help to those who want to build a practical tool of social analysis based on fuzzy sets, no matter how well disposed he may be towards the explicitation of procedures and methods of determination of membership values for cases. Ragin wrote about this topic in a recent essay (Ragin 2007), where he identifies two specific methods for fuzzy sets calibration. Both are based on the use of natural logarithms of the odds of the membership values; this position would seem a similar to a probabilistic approach, as the logit function is usually used, although here the difference between probability and membership functions is well marked.

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