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？

• 批准号: 2442711
• 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

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.确定在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。批判性地评估这些数据是从哪里来的，如何使用，以及用于什么目的(S)。确定和评估在数据从创建到警察系统/应用的过程中影响数据的不同摩擦点和转换。探索和比较与收集、分类和分类有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。评估这些数据做法和流程如何重塑警务。该项目采用多种方法结合van es和de Lange(2020)的数据共享思想，将其作为研究数据、数据通信和数据通信基础设施的一种方式，与数据旅程(Bates等人，2016 p.2)的思想相结合，以跟踪数据从最初在“生产地点”和通过“数据实践地点”创建的过程，同时确定数据发生的变化(易变性)，以及数据后来是如何分布或使用的。通过文件分析、访谈和观察实践的混合，将创建一个数据地图，该数据地图将显示数据在进入数据驱动的警务系统之前如何在不同的组织和机构中传播。关键领域：数据共享、数据监控、犯罪前、数据驱动的警务、分类、概况分析