LIBRI DI SERGIO MAUCERI

Il volume raccoglie e discute le interpretazioni dei principali risultati di una ricerca sociologica – a cui hanno partecipato, nella fase del lockdown, quasi quindicimila persone – su come l’emergenza Covid-19 abbia trasformato gli stili di vita, le relazioni sociali e le aspettative degli italiani. La pandemia ha reso evidente come l’origine e la produzione dei rischi, a differenza che nel passato, non sono imputabili a cause esterne, ma rimangono interne alla società stessa; e che gli stati di emergenza sono ormai la norma piuttosto che l’eccezione. Nello spazio globale sospeso, creato dalla pandemia, sia la società che la socialità escono stravolte e sollevano questioni che interrogano gli scienziati sociali.

Il volume sviluppa le implicazioni della convergenza tra approcci qualitativi e quantitativi e analizza quale ruolo possano avere le tecniche non standardizzate nel disegno della survey research. Combinando i contributi dei pionieri della survey con quelli del nuovo movimento della Mixed Methods Research, è possibile sostenere che la ricerca qualitativa, combinata opportunamente con l’indagine con questionario, può compensare i punti ciechi del questionario, rendere strategici i dati anomali, controllare e incrementare la qualità dei dati e supportare la possibilità di coniugare livelli di analisi diversi.

Combining the contributions of the survey pioneers with those of the new Mixed Methods Research movement, this paper explores the functions that nonstandardized techniques can have within survey research design. Qualitative research, conveniently combined with questionnaire surveys, allow for the following functions: 1) rendering anomalous data strategic; 2) controlling and increasing data quality; 3) offsetting the blind spots of the questionnaire. The mixed strategy makes up for the weaknesses of the survey research, contributing to a return to the golden age of social research.

Despite the undoubted benefits of Big Data, it may also pose the risk of a new divisive drift within social sciences. In the long term, the Big Data revolution could in fact lead to an eclipse of primary data collection procedures, with inevitable damage to the productivity of social research. This paper reconstructs a typology of strategies to integrate Big Data with conventional research pathways, re-evaluating the forgotten lessons of the American Schools of Chicago and Columbia. The typology is constructed by combining two criteria: the function of Big Data and the time order.

The main idea expressed in this article refers to - and elaborates on - the contributions of the Bureau of Applied Social Research and of its mentor and founder Paul Lazarsfeld. It underlines the importance of how, in social research, it is necessary to develop and maintain a multilevel and integrated approach to surveys. Using sociometry and contextual analysis in the design of surveys, enables us to connect three levels of observation/study - individual, relational and contextual - which are often kept isolated and separate in social research. A standard approach to surveys creates casual samples of individuals, as if they were isolated units living in social emptiness, and limits itself to conduct data analysis that creates relations between individual variables. This integrated multilevel approach is instead the solution proposed to overcome the atomism and micro-sociological reductionism of this standard approach to surveys.

Re-discovering deviant case analysis. A methodological strategy supporting theoretical-interpretative processes in standard social research - This article contains a reflection that intends to assert the heuristic fertility of integrating common procedural models with analysis of deviant cases. This analysis was originally proposed by Paul F. Lazarsfeld and promoted between the ’40s and the ’60s at Columbia School, without much impact on quantitative social research circles. Deviant cases are cases that do not display expected behaviour or attitudes. Instead of considering deviant cases irrelevant because they are residual, this procedural strategy accentuates their importance and promotes an in-depth study to maximize data quality and support interpretation processes of research results.