SCC-CIVIC-FA Track B: Everyday Respect: Measuring & Improving Communication During Motor Vehicle Stops

SCC-CIVIC-FA 轨道 B：日常尊重：测量

• 批准号: 2322026
• 负责人: Morteza Dehghani
• 金额: $ 99.94万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2322026&HistoricalAwards=false
• 关键词: SCC; CIVIC; FA; Track; Everyday

Traffic stops carried out by law enforcement officers include routine encounters as well as situations that hold the potential for fatalities. This project aims to investigate the communication dynamics during traffic stops conducted using audio and video footage from body-worn cameras. The research builds on evidence that officers' initial communication influences the course of the interaction and whether it escalates or not. Additionally, the project will examine potential disparities in the treatment of community members based on demographic factors and other relevant variables. The project will also study the interplay among factors such as demographic characteristics, disability status, community context, and officer training in shaping officer and driver interactions. Collaboration with a training academy is integral to developing and implementing new training curricula based on the research findings. This study takes a community-informed approach by incorporating footage from body-worn cameras, as well as complementary data on stops, personnel, driver behavior, and community context. The project includes input from the department studied and other community stakeholders to define the dimensions of effective communication that should be evaluated. Human annotators from diverse backgrounds are employed to code the identified dimensions of officer communication. Machine learning tools, trained on these human annotations, enable the project team to analyze communication patterns at scale. The project team conducts statistical analyses to investigate the causes and consequences of officer communication, including factors that may contribute to differential treatment of different groups within the community, and to develop new training tools that can be tested at the training academy.The CIVIC Innovation Challenge is a collaboration with Department of Energy, Department of Homeland Security, and the National Science Foundation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

执法人员实施的交通拦截包括例行遭遇以及可能造成死亡的情况。该项目旨在调查交通停止期间的通信动态，使用随身携带的摄像机的音频和视频片段进行。这项研究的基础是，有证据表明，官员的最初沟通影响了互动的过程，以及互动是否升级。此外，该项目将根据人口因素和其他相关变量，审查社区成员待遇方面的潜在差异。该项目还将研究人口特征、残疾状况、社区环境和警官培训等因素之间的相互作用，以塑造警官和司机的互动。与培训学院的合作对于根据研究结果制定和实施新的培训课程是不可或缺的。这项研究采取了一种社区知情的方法，结合了身体佩戴式摄像机的镜头，以及关于停车、人员、司机行为和社区环境的补充数据。该项目包括来自所研究部门和其他社区利益攸关方的投入，以确定应进行评估的有效沟通的各个方面。来自不同背景的人类注释者被用来对军官沟通的识别维度进行编码。经过这些人类注释训练的机器学习工具使项目团队能够大规模分析通信模式。该项目小组进行统计分析，调查官员沟通的原因和后果，包括可能导致社区内不同群体受到不同待遇的因素，并开发可在培训学院测试的新培训工具。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。