Primed to (re)act: Can changes in procedural language prevent adverse events between police and minority male youth?

项目总结 尽管研究人员继续研究与执法部门不成比例的少数族裔接触对 一系列与健康相关的结果，最近对这项工作的审查质疑了 大多数关于这一主题的研究。这些担忧中的许多集中在(A)对警察不切实际的假设 和(B)质量差的数据。该项目通过引入基于人类发展的 执法人员(LEO)行为模型及其应用研究 男性少数民族青年(MMY)使用一种新的公开数据来源：广播警察通信 (Bpc)。我们的长期目标是(1)评估BPC的可行性，以了解狮子座人如何感知 通过在LEO-MMY之前和期间使用的反思前程序语言，MMY都是在当下 通过开发一种测量狮子座与少数族裔认同的调查仪器，实现遭遇和“静止” 青年，以及(2)确定是否可以使用BPC来代替非公开数据源来研究警察行为 通过开发一种新的计算策略来从BPC中提取有意义的信息， 其他战略，首创的自动语音识别(ASR)模型和大规模(&gt；100小时) 培训转录的BPC语料库，供计算社会科学家和ASR研究人员使用。 我们之前的研究表明，一套复杂的心理社会机制控制着儿童的发展 MYS的运动轨迹表明MYS对特定的应激事件采取了反应性的应对策略(例如 遇到警察)，这可能是不适应的(例如，男子汉气概)，取决于 互动。我们的研究还表明，所有人类都经历了类似的过程。因为结果是 狮子座-MMY相遇的最终责任是狮子座，这个项目寻求提高质量 通过研究一些公认的狮子座反应性应对来减少这些遭遇(即减少青年创伤) 策略：用于通过以下方式向LEOS提供特定事件信息的程序性语言的特点 Bpc。这种概念性的方法源于我们的理论框架(即斯宾塞的现象学 生态系统理论的变体，或PVEST)，强调反应性的开发和利用 应对策略--尤其是--应对MMY相关压力。我们的前提是BPC可以 Leos将MMY的行为错误地解释为威胁，增加了 不良事件。这种不准确的评估很难与之作斗争，因为狮子座的人是按照最好的方式行事的 可用的信息。因此，BPC的程序语言给油井带来了未被承认的风险-- 作为MMY的一员。因此，这项研究将对BPC进行首创的分析，以同时评估其 确定警察中种族歧视的可行性和开发一种新的测量工具 Leos能够认同MMY，供全国各地的研究人员和警察组织使用。

PROJECT SUMMARY While researchers continue to study the effects of disproportionate minority contact with law enforcement on a range of health-related outcomes, a recent review of this work questions the methodological validity of most studies on this topic. Many of these concerns focus on (a) unrealistic assumptions about police behavior and (b) poor quality data. This project addresses both by introducing a human development based model of law enforcement officer (LEO) behavior and applying this model to study how LEOs identify with male minority youth (MMY) using a novel publicly available data source: broadcast police communications (BPC). Our long-term goals are (1) to assess the viability of BPC for understanding how LEOs perceive MMY both “in the moment” via the pre-reflective procedural language used before and during LEO-MMY encounters and “at rest” via development of a survey instrument measuring LEO identification with minority youth, and (2) to determine if BPC may be used in lieu of non-public data sources to study police behavior by developing a novel computational strategy for extracting meaningful information from BPC via, among other strategies, a first-of-its-kind automatic speech recognition (ASR) model and large scale (>100 hours) training corpus of transcribed BPC for use by computational social scientists and ASR researchers. Our previous research revealed that a complex set of psychosocial mechanisms govern the developmental trajectories of MMYs, indicating MMYs adopt reactive coping strategies to particular stressful events (e.g. encounters with police) that can be maladaptive (e.g. hypermasculinity) depending on context of interactions. Our work also suggests that all humans are subject to similar processes. Since the outcomes of LEO-MMY encounters are ultimately the responsibility of LEOs, this project seeks to improve the quality of these encounters (i.e. reduce youth trauma) by studying a little acknowledged LEO reactive coping strategy: the character of procedural language used to provide LEOs with incident-specific information via BPC. This conceptual approach derives from our theoretical framing (i.e. Spencer’s phenomenological variant of ecological systems theory, or PVEST) that highlights the development and utilization of reactive coping strategies in response—particularly—to MMY associated stress. It is our premise that BPC can prime LEOs to inaccurately interpret the behavior of MMY as threatening, increasing the potential for adverse events. Such inaccurate assessments are hard to combat since LEOs are acting on the best information available. As a result, the procedural language of BPC pose unacknowledged risks to the well- being of MMY. This study will thus perform a first-of-its-kind analysis of BPC to simultaneously assess its viability for determining racial discrimination in policing and develop a novel survey instrument measuring LEOs ability to identify with MMY for use by researchers and policing organizations across the country.