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Predicting Gun Violence in Stockholm, Sweden, Using Sociodemographics, Crime and Drug Market Locations
Malmö University, Faculty of Health and Society (HS), Unit for Police Work.ORCID iD: 0000-0002-2955-1223
2023 (English)In: European Journal on Criminal Policy and Research, ISSN 0928-1371, E-ISSN 1572-9869Article in journal (Refereed) Epub ahead of print
Abstract [en]

The well-being of neighbourhoods in terms of socioeconomic conditions constitutes an important element in analyses focused on the explanation of crime trends and public safety. Recent developments in Sweden concerning gun violence and open drug scenes are worrying and the police are under a great deal of pressure to resolve the situation in many neighbourhoods, which is in turn affecting Swedish society as a whole. This study focuses on micro areas in terms of sociodemographic factors and the presence of drug markets and gun violence. The aim is to explore the relationship between these factors and what characterises areas that are experiencing the greatest difficulties. The study develops an index for the prediction of gun violence in micro areas, in this study portrayed by vector grids. The findings show an overlap between gun violence and drug markets and that micro areas in that overlap share harsh sociodemographic conditions. The study produces an index indicating the probability that a grid cell would experience gun violence. The index was then validated using recent gun incidents, and was found to have high accuracy. The resulting grids constitute a suitable target for resource allocation by police and other actors. This could facilitate a more accurate and precise focus for measures to prevent areas from becoming—or to disrupt already existing—hot spots for gun violence.

Place, publisher, year, edition, pages
Springer Nature, 2023.
Keywords [en]
Open drug scenes, Gun violence, Prediction, Micro areas, Sociodemographics
National Category
Social Work
Research subject
Criminology
Identifiers
URN: urn:nbn:se:mau:diva-62034DOI: 10.1007/s10610-023-09560-yISI: 001042777000001Scopus ID: 2-s2.0-85166923324OAI: oai:DiVA.org:mau-62034DiVA, id: diva2:1790018
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Malmö UniversityAvailable from: 2023-08-22 Created: 2023-08-22 Last updated: 2023-09-18Bibliographically approved

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Magnusson, Mia-Maria

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CiteExportLink to record
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Citation style
  • apa
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  • de-DE
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  • Other locale
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Output format
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