TY - JOUR

T1 - Social interaction effects on immigrant integration

AU - Agliari, Elena

AU - Barra, Adriano

AU - Contucci, Pierluigi

AU - Pizzoferrato, Andrea

AU - Vernia, Cecilia

N1 - Funding Information:
EA, AB, AP are grateful to GNFM-INdAM Progetto-Giovani Agliari-2016; AB further acknowledges support by Salento University; AP further acknowledges support by the Engineering and Physical Sciences Research Council (EPSRC), Grant No. EP/L505110/1, by The Alan Turing Institute EPSRC grant EP/N510129/1 and seed project SF029 “Predictive graph analytics and propagation of information in networks”; CV acknowledges financial supports from Fondo di Ateneo per la ricerca 2015, Università di Modena e Reggio Emilia and FIRB Grant RBFR10N90W. PC acknowledges financial support from PRIN project Statistical Mechanics and Complexity (2015K7KK8L). Finally and most importantly we want to dedicate this work to our missed colleague and friend Ignacio Gallo. Ignacio has been a driving force in the mathematical approach to quantitative sociology and his ideas had a profound impact on our understanding of the field.
Publisher Copyright:
© The Author(s) 2018.

PY - 2018/5/8

Y1 - 2018/5/8

N2 - In recent years Italy has been involved in massive migration flows and, consequently, migrant integration is becoming a urgent political, economic and social issue. In this paper we apply quantitative methods, based on probability theory and statistical mechanics, to study the relative integration of migrants in Italy. In particular, we focus on the probability distribution of a classical quantifier that social scientists use to measure migrant integration, that is, the fraction of mixed (natives and immigrants) married couples, and we study, in particular, how it changes with respect to the migrant density. The analysed dataset collected yearly by ISTAT (Italian National Institute of Statistics), from 2002 to 2010, provides information on marriages and population compositions for all Italian municipalities. Our findings show that there are strong differences according to the size of the municipality. In fact, in large cities the occurrence of mixed marriages grows, on average, linearly with respect to the migrant density and its fluctuations are always Gaussian; conversely, in small cities, growth follows a square-root law and the fluctuations, which have a much larger scale, approach an exponential quartic distribution at very small densities. Following a quantitative approach, whose origins trace back to the probability theory of interacting systems, we argue that the difference depends on how connected the social tissue is in the two cases: large cities present a highly fragmented social network made of very small isolated components while villages behave as percolated systems with a rich tie structure where isolation is rare or completely absent. Our findings are potentially useful for policy makers; for instance, the incentives towards a smooth integration of migrants or the size of nativist movements should be predicted based on the size of the targeted population.

AB - In recent years Italy has been involved in massive migration flows and, consequently, migrant integration is becoming a urgent political, economic and social issue. In this paper we apply quantitative methods, based on probability theory and statistical mechanics, to study the relative integration of migrants in Italy. In particular, we focus on the probability distribution of a classical quantifier that social scientists use to measure migrant integration, that is, the fraction of mixed (natives and immigrants) married couples, and we study, in particular, how it changes with respect to the migrant density. The analysed dataset collected yearly by ISTAT (Italian National Institute of Statistics), from 2002 to 2010, provides information on marriages and population compositions for all Italian municipalities. Our findings show that there are strong differences according to the size of the municipality. In fact, in large cities the occurrence of mixed marriages grows, on average, linearly with respect to the migrant density and its fluctuations are always Gaussian; conversely, in small cities, growth follows a square-root law and the fluctuations, which have a much larger scale, approach an exponential quartic distribution at very small densities. Following a quantitative approach, whose origins trace back to the probability theory of interacting systems, we argue that the difference depends on how connected the social tissue is in the two cases: large cities present a highly fragmented social network made of very small isolated components while villages behave as percolated systems with a rich tie structure where isolation is rare or completely absent. Our findings are potentially useful for policy makers; for instance, the incentives towards a smooth integration of migrants or the size of nativist movements should be predicted based on the size of the targeted population.

UR - http://www.scopus.com/inward/record.url?scp=85054100823&partnerID=8YFLogxK

U2 - 10.1057/s41599-018-0097-5

DO - 10.1057/s41599-018-0097-5

M3 - Article

AN - SCOPUS:85054100823

VL - 4

JO - Palgrave Communications

JF - Palgrave Communications

SN - 2055-1045

IS - 1

M1 - 55

ER -