RESIDENTIAL SEGREGATION IN MESSINA (SOUTHERN ITALY): AN INFORMATION THEORY BASED STUDY

Residential segregation stands out as one of the most noticeable and potentially concerning consequences of urbanization. Adopting the framework proposed by the Information Theory, the study investigates residential segregation patterns in the Italian municipality of Messina that has recently experienced deteriorating urban conditions. We rely on anonymized individual data sourced from the Population Register to examine the major immigrant groups residing in Messina in 2016 and 2022, Sri Lankans, Filipinos, Romanians, and Moroccans. The analysis computes the Shannon’s entropy index and Kullback-Leibler (KL) divergence, aiming at: 1. drawing comparisons in the residential segregation patterns among immigrant populations; 2. appraising changes in residential patterns between 2016 and 2022; 3. assessing to what extent ethnic concentration depends on the adoption of different territorial scales to classify metropolitan areas. Results reveal nuanced patterns of residential segregation among the selected migrant populations, with Filipinos and Moroccans remaining the most segregated groups, both in 2016 and 2022. However, two common dynamics are affecting all immigrant groups: a. the presence of micro-scale segregation; b. the increase of segregation degrees over time. Furthermore, when comparing the distribution of immigrant groups with native populations, concentration levels, detected by the Shannon’s entropy index, have not always implied significant KL divergence. These results suggest complex interactions between migrant and the local populations, challenging simplistic assumptions about segregation. Accounting for the multiscalar dimensionality of segregation, this study contributes to a deeper understanding of residential dynamics and provides insights for fostering social cohesion in diverse spatial urban settings.