Social mobility and spatial inequalities in France: an interdisciplinary approach – MOSIS

MOSIS brings together an interdisciplinary consortium (sociologist, statistician, geographer, data scientist, and expert in multi-agent models) firstly to analyze the evolution of spatial inequalities of intergenerational social mobility in France, secondly to improve statistical and mathematical methods for studying social mobility. From a sociological point of view, the aim is to understand the effects of globalization and technological changes on the spatial variations of social mobility. Thus, this project seeks to study social mobility within the broader context of social, economic, and cultural shifts in French territories by taking into account migratory behaviors.

This project has five complementary and interrelated objectives. 1) To combine data from public statistics with digital data, mainly collected on social media. 2) To improve statistical methods for analyzing social mobility. This includes two sub-objectives. The first is to propose a spatial and temporal multilevel specification of the log-linear models traditionally used for analyzing social mobility tables. The second is to demonstrate the advantage of machine learning methods to study social mobility tables, the “object” traditionally studied in quantitative sociology. 3) To identify empirically the relationship between intergenerational social mobility and territorial characteristics and how this relation is affected by globalization and technological changes. 4) To describe the relationship between intergenerational social mobility and spatial mobility, and how this relation impacts the spatial inequalities of social mobility. 5) To build theoretical formal models that explain the link between globalization, technological changes and social mobility and use these models to reproduce observed results and to predict future scenarios.

To have a very important amount of individual data so as to be able to analyze social mobility at a fine territorial level, we will combine the most important official data sources on social mobility: the Labor Force Survey, the Permanent Demographic Sample (EDP), the "Déclaration Annuelle de Données Sociales" (DADS) and the survey "Formation and Qualification Professionnelle" (FQP). These data will describe several million individuals. They will be complemented by data on the use of information and communication technologies by companies, and the access to services in different territories (Base Permanente des équipements). Additionally, we will use digital data obtained from Facebook, and LinkedIn advertising to measure detailed socio-demographical, economic and cultural characteristics of territories. Finally, LinkedIn advertising and Chatgpt will be used to collect data on ordinary descriptions of occupations.

The interdisciplinary team's first aim is to gain a better understanding of spatial inequalities in social mobility in France by describing the impact of economic, geographical and sociological factors that shape social mobility. The project will also provide the first modern analysis of the relationship between spatial and social mobility in France. This project is inserted in the framework of computational social sciences and aims to renew research on a classic subject in sociology by developing new statistical and mathematical analysis tools. This project will thus enable parallel advances in sociological knowledge and in the fields of mathematics and data science.