Ri-scoprire l'analisi dei casi devianti. Una strategia metodologica di supporto dei processi teorico-interpretativi nella ricerca sociale di tipo standard

Deviant case analysis (DCA) is a research strategy originally proposed by Lazarsfeld and promoted within the Colombia School from the 1940s to the 1960s, unfortunately without subsequently achieving full acceptance within the area of survey research in general. Unexpectedly, however, the importance of DCA in the fine-tuning of interpretive models has been acknowledged in contemporary qualitative research (Lincon and Guba, 1985, Creswell, 1998, Patton, 1999, 2001, Silverman, 2000, Gobo, 2008, Corbin and Strauss, 2008). DCA refers to searching outside the collected empirical base for clues able to shed light on why statistical analysis of the data has revealed anomalous responses that either deviate from research hypotheses or give rise to contradictory classificatory results. Unlike procedures for checking the validity of the indicators and the reliability of the answers within the data matrix, DCA focuses once more on the individual cases and achieves the full integration of quantitative and qualitative research strategies. The two main functions of DCA are: 1) Refining the explicative-predictive capabilities of the study, through the introduction of additional factors not initially foreseen (re-conceptualization). 2) Identifying bias in order to increase the reliability of data-collection procedures. This essay aims to recover this important means of improving the traditional survey model so as to be able retrospectively to monitor and improve the quality of the data collected and thus the quality of the results as well.