Police excessive force, unlawful stops and searches, false arrests, and other forms of misconduct remain significant issues in American law enforcement. Abuses of power by even a few police officers erode public trust, reduce the legitimacy of law enforcement, and…
Police excessive force, unlawful stops and searches, false arrests, and other forms of misconduct remain significant issues in American law enforcement. Abuses of power by even a few police officers erode public trust, reduce the legitimacy of law enforcement, and expose individual officers and law enforcement agencies to criminal and civil liability. When misconduct occurs, inadequate police leadership and supervision are often cited as contributing causes. First-line supervisors have direct, positional authority to influence the behavior of officers they lead, yet little is known about what actions first-line supervisors are expected to take to prevent misconduct. Federal consent decrees have been a promising area of police reform knowledge for researchers and practitioners. While these documents enumerate dozens of police reform measures in multiple subject areas, the role of the first-line supervisor remains disparate and unclear, ultimately hampering the effectiveness of first-line supervisors in operationalizing the reforms prescribed by these documents. The aim of this study was to develop a conceptual model that enhances understanding of actions police first-line supervisors are expected to take to prevent officer misconduct. A qualitative content analysis of federal consent decrees led to the development of six themes and a conceptual model that describe expected first-line supervisor behavior. This paper contributes to the body of knowledge about police leadership in the context of misconduct prevention and consent decree reform. It proposes a conceptual model helpful to police practitioners seeking to better define the role of first-line supervisors in an unpredictable, complex work environment that leaves little room for error.
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A realistic simulation of snow cover and its thermal properties are important for accurate modelling of permafrost. We analyse simulated relationships between air and near-surface (20 cm) soil temperatures in the Northern Hemisphere permafrost region during winter, with a particular…
A realistic simulation of snow cover and its thermal properties are important for accurate modelling of permafrost. We analyse simulated relationships between air and near-surface (20 cm) soil temperatures in the Northern Hemisphere permafrost region during winter, with a particular focus on snow insulation effects in nine land surface models, and compare them with observations from 268 Russian stations. There are large cross-model differences in the simulated differences between near-surface soil and air temperatures (ΔT; 3 to 14 °C), in the sensitivity of soil-to-air temperature (0.13 to 0.96 °C °C-1), and in the relationship between ΔT and snow depth. The observed relationship between ΔT and snow depth can be used as a metric to evaluate the effects of each model's representation of snow insulation, hence guide improvements to the model's conceptual structure and process parameterisations. Models with better performance apply multilayer snow schemes and consider complex snow processes. Some models show poor performance in representing snow insulation due to underestimation of snow depth and/or overestimation of snow conductivity. Generally, models identified as most acceptable with respect to snow insulation simulate reasonable areas of near-surface permafrost (13.19 to 15.77 million km2). However, there is not a simple relationship between the sophistication of the snow insulation in the acceptable models and the simulated area of Northern Hemisphere near-surface permafrost, because several other factors, such as soil depth used in the models, the treatment of soil organic matter content, hydrology and vegetation cover, also affect the simulated permafrost distribution.
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)