A Mixed Methods Social Network Analysis of San Diego Law Enforcement Task Forces and Agencies
DOI:
https://doi.org/10.56331/ijps.v2i1.7573Palabras clave:
social network analysis, task force, police, centrality, counternarcotics, San Diego County, CaliforniaResumen
The San Diego area has a long reputation as a highly networked, cooperative, and task force-oriented law enforcement region. Measuring and understanding how this region achieves its networked state could assist other regions in improving law enforcement functions. This article uses social network analysis to qualitatively and quantitatively map the network of law enforcement agency task forces in the San Diego County region. The analysis first provides an inventory and description of San Diego area law enforcement task forces and participating agencies, then analyzes the structure of the regional network. The analysis identified 33 law enforcement investigative task forces supported by 84 law enforcement and participating agencies in the San Diego area. These comprise a relatively dense network with a well-connected core of primarily federal and local agencies, with the Federal Bureau of Investigation, Drug Enforcement Administration, and Immigration and Customs Enforcement’s Homeland Security Investigations being the most central federal agencies, and the San Diego County District Attorney’s Office and Sheriff’s Department, as well as San Diego, National City, and Chula Vista police departments as the most central local agencies. State agencies were less central but included the California Department of Justice and the California Highway Patrol in the top 10 agencies for centrality, depending on the metric. The network mapping in this article provides a baseline for a highly connected task force region that will allow future comparison with other regions and similarly situated cities along the US-Mexico border and beyond. Policy recommendations based on network theory are provided.
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2023 Nathan P. Jones, Russell Lundberg, Matthew O’Deane
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial 4.0.
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a CC BY-NC 4.0 license.