On the decision-making framework for policing: a proposal for improving police decision-making
This article introduces the Decision-Making Framework for Policing (DMFP), a comprehensive tool designed to enhance the decision-making understanding of police officers. The DMFP considers the principles of heuristic, naturalistic, and rational decision-making along a fluid cognitive continuum to cr...
| Autor principal: | |
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| Tipo de documento: | Electrónico Artículo |
| Lenguaje: | Inglés |
| Publicado: |
2024
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| En: |
International journal of law, crime and justice
Año: 2024, Volumen: 79, Páginas: 1-17 |
| Acceso en línea: |
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| Verificar disponibilidad: | HBZ Gateway |
| Palabras clave: |
| Sumario: | This article introduces the Decision-Making Framework for Policing (DMFP), a comprehensive tool designed to enhance the decision-making understanding of police officers. The DMFP considers the principles of heuristic, naturalistic, and rational decision-making along a fluid cognitive continuum to create a framework that addresses the limitations of the existing police National Decision Model (NDM). It achieves this by including 10 proposed typologies of police decision-making including: Routine, Tactical, Operational, Crisis, Investigative, Ethical, Interpersonal, Administrative, Managerial, and Strategic. These are integrated alongside existing and adapted decision-making models which are presented using a mnemonic letter strategy. Although the DMFP is theoretical, and its utility is presently untested in comparison to the existing NDM, it is presented to provide a tool to help improve officers' tacit knowledge, pattern recognition, and experiential learning through provision of easily recallable mnemonic decision-models. Thereby fostering a deeper understanding of cognitive processes and the factors influencing police decisions, potentially increasing consistency in reasoning, reducing decision errors, and enhancing policing outcomes. |
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| Notas: | Literaturverzeichnis: Seite 15-17 |
| Descripción Física: | Illustration |
| ISSN: | 1756-0616 |
| DOI: | 10.1016/j.ijlcj.2024.100702 |
