Swedish conditions? Characteristics of locations the Swedish police label as vulnerable

Deprived neighborhoods where criminal networks have a negative impact on local residents are in Sweden labeled as vulnerable neighborhoods by the police. The method used by the police to classify such neighborhoods is largely based on police perceptions, which raises issues around subjectivity and potential biases. The present study explores the characteristics of such neighborhoods based on registry data over sociodemographics and crime. The data used is a grid (N=116 660) of 250x250 meter vector grids with data on population, foreign background, employment, age characteristics, household types and eight types of crime. Generalized mixed effect models of vector grids nested in municipalities were fitted to analyze the characteristics of vector grids classified as vulnerable (N=1678). Several variables are significantly associated with a vector grid being classified as vulnerable, with the share of population that is foreign born and share with parents foreign born being the strongest predictors. In addition, we consider whether there are systematic differences between municipalities, and develop a model based on regression coefficients to predict whether a vector grid is vulnerable or not. The model re-classifies 39.8% of the vector grids, identifying locations that statistically resemble vulnerable neighborhoods but are not classified as such and vice versa.