The analysis of social inequalities is a topic of current interest and is studied as a factor in the evolution and measurement of the level of well-being. A fundamental prerequisite for a correct statistical analysis of this phenomenon is the need to share a univocal definition of the concept of social inequalities. This work starts from the need to identify territorial areas and/or population subgroups characterized by situations of hardship or strong social exclusion through the construction of indicators that can estimate situations of social inequalities in small areas. Scientific research options have been oriented towards the establishment of a multidimensional approach, sometimes renouncing dichotomous logic to go as far as fuzzy classifications in which each unit simultaneously belongs and does not belong to the selected category. Multidimensional statistical analysis methodologies (TFR method) and Density Based Spatial Clustering methods (DBSCAN) will therefore be used to aggregate adjacent spatial units with high intensity of social inequalities.

Multidimensional statistical analysis of social inequalities in Italy / Perchinunno, Paola; L'Abbate, Samuela; Crocetta, Corrado; Alaimo, Leonardo Salvatore. - In: SOCIO-ECONOMIC PLANNING SCIENCES. - ISSN 0038-0121. - 95:(2024), pp. 1-7. [10.1016/j.seps.2024.102005]

Multidimensional statistical analysis of social inequalities in Italy

Alaimo, Leonardo Salvatore
2024

Abstract

The analysis of social inequalities is a topic of current interest and is studied as a factor in the evolution and measurement of the level of well-being. A fundamental prerequisite for a correct statistical analysis of this phenomenon is the need to share a univocal definition of the concept of social inequalities. This work starts from the need to identify territorial areas and/or population subgroups characterized by situations of hardship or strong social exclusion through the construction of indicators that can estimate situations of social inequalities in small areas. Scientific research options have been oriented towards the establishment of a multidimensional approach, sometimes renouncing dichotomous logic to go as far as fuzzy classifications in which each unit simultaneously belongs and does not belong to the selected category. Multidimensional statistical analysis methodologies (TFR method) and Density Based Spatial Clustering methods (DBSCAN) will therefore be used to aggregate adjacent spatial units with high intensity of social inequalities.
2024
Statistical methods; Social inequalities; Fuzzy logic; Spatial clustering
01 Pubblicazione su rivista::01a Articolo in rivista
Multidimensional statistical analysis of social inequalities in Italy / Perchinunno, Paola; L'Abbate, Samuela; Crocetta, Corrado; Alaimo, Leonardo Salvatore. - In: SOCIO-ECONOMIC PLANNING SCIENCES. - ISSN 0038-0121. - 95:(2024), pp. 1-7. [10.1016/j.seps.2024.102005]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1720864
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