Research project Spatial integration and segregation
Disadvantaged groups in Sweden in the 2000s.
It can be argued that a society is never better than how individuals at its spatial outskirts are treated: a society benefits socially and economically on equality and loses on inequality. The purpose of the project is to study, from a life course trajectory perspective, how vulnerable groups are affected by spatial segregation. What role does spatial segregation and integration play in the risk of being linked into vulnerability trajectories or the opportunities to leave vulnerability? What factors influence the spatial integration and separation of vulnerable groups?
In the area of welfare policy, integration has been a guiding principle, as has the ideas of equal upbringing and welfare. Recently, however, the development of income in Sweden has shown increasing gaps. An important part of the integration has always been the spatial integration, both to create equal living conditions and to promote the social cohesion needed for socially sustainable societies. Thus, integration is a basic idea of welfare policy.
Project description
In recent years, the idea of integration has met various challenges: new population groups, a liberalization of housing policy (sales, financialization), and disadvantaged housing areas. In parallel with these changes, interest in understanding how spatial segregation affects people's vulnerability has increased.
In the project, we will map the spatial dimensions of vulnerability using partially new methods. To identify life trajectories associated with vulnerability in registry data, we will use latent class analysis. This means that we find classes with life courses that are similar to each other and that can give a better picture of spatial segregation than before. The spatial sorting of vulnerable individuals will then be analyzed using individualized neighborhoods, a method where one can examine tailored neighborhoods for each individual, which can be varied in scale according to what one analyzes and which may be composed of multiple variables.
Project members
Project managers
Eva Andersson
Professor
Members
Ida Borg
Researcher
Bo Malmberg
Professor
More about this project
Researchers:
Eva Andersson, Ida Borg and Bo Malmberg