Data Science Approaches in Criminal Justice and Public Health Research: Lessons Learned From Opioid Projects
The persistence of the nation’s opioid epidemic has called on criminal justice and public health agencies to collaborate more than ever. This epidemiological criminology framework highlights the surveillance of public health and safety, often using data science approaches, to inform best practices....
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| Otros Autores: | ; ; |
| Tipo de documento: | Electrónico Artículo |
| Lenguaje: | Inglés |
| Publicado: |
2021
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| En: |
Journal of contemporary criminal justice
Año: 2021, Volumen: 37, Número: 2, Páginas: 175-191 |
| Acceso en línea: |
Volltext (lizenzpflichtig) |
| Journals Online & Print: | Gargar...
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| Verificar disponibilidad: | HBZ Gateway |
| Palabras clave: |
| Sumario: | The persistence of the nation’s opioid epidemic has called on criminal justice and public health agencies to collaborate more than ever. This epidemiological criminology framework highlights the surveillance of public health and safety, often using data science approaches, to inform best practices. The purpose of our article is to delineate the main benefits and challenges of adopting data science approaches for epidemiological criminology partnerships, research, and policy. We offer “lessons learned” from our opioid research in Delaware and Florida to advise future researchers, especially those working closely with policymakers and practitioners in translating science into impactful best practices. We begin with a description of our projects, pivot to the challenges we have faced in contributing to science and policy, and close with recommendations for future research, public advocacy, and practice. |
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| ISSN: | 1552-5406 |
| DOI: | 10.1177/1043986221999858 |