The overall aim of this project is to establish empirical knowledge on the concentration of social problems in neighbourhoods, and the consequences of such environment for those who live there. The main focus is on crime, both in terms of criminal incidents as well as geographical concentration of residential active offenders.
Most known offenders commit only one or a few offences, while a smaller group commit a large number of crimes over time. Neither are all offenders well connected with other offenders to such an extent that one can say that they are part of a criminal network. This project will first provide a thorough empirical analyses on each these two elements: criminal careers and social networks, and more specifically: co-offending networks of high-rate offenders. Geographical concentrations of social problems combined with the presence of informal networks of active offenders are sometimes referred to as 'vulnerable areas', with the potential for developing even more serious social problems, related to sub-cultures of social excluded groups. The project then aims at combining the empirical insight of criminal careers and offender networks into analyses of the changes in neighbourhoods over time, and assessing the consequences of neighbourhood characteristics on other residents.
The overall aim of this project is to establish a thorough knowledgebase on the nationwide prevalence and development of concentration of multiple social problems in neighbourhoods, these areas' development and consequences for the inhabitants. A particular focus is on crime, and the concentrations of social problems combined with the presence of informal networks of offenders (or even more organized gangs) are often referred to as 'vulnerable areas', with the potential for developing even more serious social problems, related to sub-cultures of social excluded groups. We will analyse the dynamics of individuals' criminal careers (wp1), co-offending networks (wp2), how they are geographically connected, and the ways these networks affect and are affected by social neighbourhoods (wp3).
The results from the project are expected to be directly informative for policy regarding urban development and area-based initiatives. The results will also be informative for the police by providing both analyses of crime patterns, offenders and networks, as well as putting these into local geographical context.
This project will make use of standard Norwegian registerdata, but expanding by making use of less used police data with additional details and also utilizing less commonly used information on social ties and geographical locations. This will entails combining statistical techniques for panel data, social network analyses, geographical information system, and machine learning. Before data are collected, key analyses will be pre-registered at osf.io and updated with full code and documentation. We regard this as important part of method development in register-based social science by ensuring transparency and reproducibility, although the current system for access to register data poses particular challenges for exact reproducibility. In this way, the project will adhere to the highest methodological standards and research integrity.