A Social Network Analysis of Chronic Violent Offenders
Research indicates that a majority of serious crime events are committed by a small proportion of repeat offenders. Many chronic offenders collaborate with others, co-offending on an irregular basis or as part of an organized gang. Understanding the characteristics of these offenders and their crimi...
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| Medienart: | Elektronisch Aufsatz |
| Sprache: | Englisch |
| Veröffentlicht: |
2024
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| In: |
American journal of criminal justice
Jahr: 2024, Band: 49, Heft: 5, Seiten: 700-722 |
| Online-Zugang: |
Volltext (lizenzpflichtig) |
| Journals Online & Print: | Lade...
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| Verfügbarkeit prüfen: | HBZ Gateway |
| Schlagwörter: |
MARC
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| 245 | 1 | 2 | |a A Social Network Analysis of Chronic Violent Offenders |
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| 520 | |a Research indicates that a majority of serious crime events are committed by a small proportion of repeat offenders. Many chronic offenders collaborate with others, co-offending on an irregular basis or as part of an organized gang. Understanding the characteristics of these offenders and their criminality has significant implications for our understanding of chronic violence and the implementation of successful, evidence-based crime prevention efforts. To contribute to this ongoing effort, we apply social network analysis (SNA) to a sample of 2,217 people arrested more than once for a violent crime between 2014 and 2022. We explore co-offending relationships, investigating differences in demographics and crime characteristics between networked and non-networked chronic violent offenders. The results of this exploratory study indicate significant differences in age and crime type by network status. This analysis also indicates that SNA is an effective method for exploring co-offending in a general-purpose crime dataset. Implications for policymakers and future directions for research are presented. | ||
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| 650 | 4 | |a Co-offending | |
| 650 | 4 | |a Chronic violent offender | |
| 650 | 4 | |a Social Network Analysis | |
| 700 | 1 | |a Zhang, Yan |e VerfasserIn |4 aut | |
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