How are data-driven policing systems constructed through systems of data gathering, classification, and categorisation?

如何通过数据收集、分类和分类系统构建数据驱动的警务系统？

基本信息

批准号：
2442711
负责人：
金额：
--
依托单位：
Royal Holloway University of London
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2020
资助国家：
英国
起止时间：
2020 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2442711
关键词：
How data driven policing systems

项目摘要

1. To identify the types of data captured within a data-driven policing system in England and create a data map which represents this.2. To critically assess where such data has come from, how it is being used, and for what purpose(s).3. To identify and assess the different points of friction and translation that affects data on its journey from creation to police system/application.4. To explore and compare how different data approaches relating to collection, categorisation and classification are occurring and to investigate the meaning and inferences made because of such approaches.5. To assess how these data practices and processes are reconfiguring policing. This project is taking a multi-methods approach combining van Es and de Lange's (2020) idea of datawalking as a way to study data, datafication, and infrastructures of datafication, merged with the idea of data journeys (Bates et al., 2016 p.2) to track data from its initial creation at "sites of production" and through "sites of data practice", whilst identifying the changes that occurred to the data (mutability), and then how the data was later distributed or used. Through a mixture of document analysis, interviews, and observant practice a data map will be created that will visualise how data travels around and through various organisations and institutions before entering a data-driven policing system.Key Areas: Data-sharing, Dataveillance, pre-crime, data-driven policing, classification, profiling

1. 识别英格兰数据驱动的警务系统中捕获的数据类型，并创建代表这一点的数据地图。2.严格评估此类数据的来源、使用方式以及目的。3。识别和评估影响数据从创建到警察系统/应用程序的过程中的不同摩擦点和转换点。4。探索和比较与收集、分类和分类相关的不同数据方法是如何发生的，并调查这些方法的含义和推论。5．评估这些数据实践和流程如何重新配置警务。该项目采用多种方法，结合了 van Es 和 de Lange (2020) 的数据行走理念，作为研究数据、数据化和数据化基础设施的一种方式，并与数据旅程的理念相结合（Bates et al., 2016 p） .2) 跟踪数据从其在“生产地点”最初创建到“数据实践地点”的过程，同时识别数据发生的变化（可变性），然后如何数据随后被分发或使用。通过文件分析、访谈和观察实践的结合，将创建一个数据地图，该地图将可视化数据在进入数据驱动的警务系统之前如何在各个组织和机构中传播。关键领域：数据共享、数据监视、预授权-犯罪、数据驱动的警务、分类、侧写