Networked violence: A relational approach to explain serious violence in the UK

网络暴力：解释英国严重暴力的关系方法

• 批准号: ES/X012956/1
• 负责人: Paolo Campana
• 金额: $ 31.72万
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FX012956%2F1
• 关键词: Networked; violence; relational; approach; explain

Violence has been on the rise in the United Kingdom, generating a detrimental impact on the well-being of individuals and communities. Preventing serious violence is a crucial - yet difficult - task that calls for innovative thinking. This project aims at exploring the relational mechanisms underpinning serious violence (i.e., violence with injury) and then develop innovative evidence-based strategies to prevent individual involvement in such violence. Previous research has explored both individual characteristics of offenders and community-level factors. However, the role of relational factors in generating - and sustaining - violence has been largely neglected. Yet, an emerging yet still limited body of works (mostly on offenders outside the UK) has shown that relations can have a stronger effect than individual factors. As in the spread of epidemics, networks - and contacts - matter in explaining, and preventing, adverse outcomes. This project builds upon network thinking in transforming the way we address serious violence in the UK. It integrates network factors into a tailored multi-level approach modelling the risk of both committing violence and of being a victim of violence as a function of individual factors, community factors, and network (relational) factors. Ultimately, in keeping with the WHO socio-ecological model for violence prevention, we aim to understand how micro-, meso-, and macro-level factors affect the vulnerability of individuals to the risk of violence (both committing and being a victim of violence), and how this risk can be mitigated.The research will explore the emergence of violence both cross-sectionally and longitudinally, considering the dynamics underpinning violence escalation and contagion, clustering and cycles of violence over time. The main data source for the project is a large-scale police dataset containing data on crime events in Cambridgeshire with the associated anonymised information about victims and offenders. This dataset will be linked to ONS and Census data to bring community-level information into the picture, thus allowing for a multi-level approach to the study of the mechanisms underpinning violence. Such a study will generate a set of (relational) risk factors that can be actioned upon by practitioners to develop early interventions to prevent and break cycles of violence.

在联合王国，暴力行为一直在增加，对个人和社区的福祉产生了有害影响。预防严重暴力是一项关键但又困难的任务，需要创新思维。该项目旨在探讨严重暴力行为背后的关系机制（即，暴力致伤），然后制定创新的循证战略，以防止个人参与这种暴力。以往的研究探讨了罪犯的个人特征和社区层面的因素。然而，关系因素在产生和维持暴力方面的作用在很大程度上被忽视了。然而，一个新兴的但仍然有限的作品（主要是在联合王国以外的罪犯）表明，关系可以有一个比个人因素更强大的影响。就像流行病的传播一样，网络--和接触--在解释和预防不良后果方面很重要。该项目建立在网络思维的基础上，改变了我们解决英国严重暴力问题的方式。它将网络因素纳入一个有针对性的多层次方法，将实施暴力和成为暴力受害者的风险建模为个人因素、社区因素和网络（关系）因素的函数。最后，根据世卫组织预防暴力的社会生态模式，我们的目标是了解微观、中观和宏观因素如何影响个人对暴力风险的脆弱性（实施暴力和成为暴力受害者），以及如何减轻这种风险。研究将从横向和纵向两个方面探讨暴力的出现，考虑到暴力升级和蔓延、集群和暴力周期的动态基础。该项目的主要数据来源是一个大规模的警方数据集，其中包含剑桥郡犯罪事件的数据以及有关受害者和罪犯的相关匿名信息。这一数据集将与国家统计局和人口普查数据相联系，以便将社区一级的信息纳入其中，从而能够采取多层次的方法来研究暴力的根源。这种研究将产生一套（相关的）风险因素，从业人员可以根据这些因素采取行动，制定早期干预措施，以防止和打破暴力循环。