ADR UK Data First Evaluation Fellowship

ADR 英国数据第一评估奖学金

基本信息

  • 批准号:
    ES/X011348/1
  • 负责人:
  • 金额:
    $ 18.26万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Fellowship
  • 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

项目摘要

Until recently, the large amounts of administrative data routinely collected about offenders as they are moved through the Criminal Justice System have been inaccessible to research. Instead, our understanding has largely been restricted to static insights into particular points in the journey. The Ministry of Justice ADR UK linkage project has transformed this picture, allowing offenders to be tracked across all stages of the Criminal Justice System. This opens up vast potentials for cutting edge research that recognises the complex interconnections that exist between different parts of the Criminal Justice System. For example, this could help us to understand how and why some of those people that are sentenced by the courts return quickly (and repeatedly) following the completion of their sentence, whilst other offenders are never seen again. The effects of more complex criminal justice histories including multiple transitions back through the system can also be examined as well as the impacts of particular interventions on particular types of individual. But the complexity and scale of this new wave of linked data necessitates new working approaches and understanding of new analytic techniques. The fellowship is an unrivalled opportunity to work directly alongside Ministry of Justice analysts to realise the full potential of this linked data. Working collaboratively, I will identify a number of clearly defined research questions that meet Ministry of Justice priorities and can be addressed with this data. In particular, the opportunities afforded by linking information from across different Criminal Justice stages will be exploited. The specific questions will be guided by my own academic understanding of individuals journeys through the Criminal Justice System built up over more than 15 years as an empirical criminologist. They will also appropriately reflect the structural complexities inherent in the linked data sources including correctly engaging with the role of context (the effect of being dealt with in a specific court and/or prison) and the fact that prior experiences shape subsequent ones. Research questions will be refined in consultation with Ministry of Justice analysts in an interactive workshop. This will be informed by some initial 'proof of concept' data analysis exercises with the available data. Here the emphasis will be on providing a rapid evidence base for further discussion rather than on selecting the most technically sophisticated analysis solutions. These rapid data deep-dives will help to highlight specific data challenges, clarify the central research question, and facilitate further discussion and question development. The most promising questions would then be worked up into full-scale empirical projects supported by more statistically robust analytic approaches that appropriately reflect the patterns that emerge in the data. Crucial to the fellowship is ensuring a legacy for future research. To achieve this, in addition to the more standard publication of key findings in academic and policy outlets, all work will be written up within data analysis worksheets. These worksheets link directly to the raw data and will run the computational code required to complete the data analysis, whilst also including explanatory text and publishable outputs. Keeping all elements of the data processing, analysis, and reporting within the same worksheet will ensure fully replicability of the empirical work, whilst also allowing new users to quickly adapt the code and/ or text to generate new reports. I will also run workshops for Ministry of Justice analysts where relevant.
直到最近,在罪犯通过刑事司法系统时例行收集的大量行政数据还无法进行研究。相反,我们的理解在很大程度上仅限于对旅程中特定点的静态洞察。英国司法部 ADR 联动项目改变了这一情况,允许在刑事司法系统的各个阶段对罪犯进行追踪。这为尖端研究开辟了巨大的潜力,认识到刑事司法系统不同部分之间存在的复杂相互联系。例如,这可以帮助我们了解一些被法院判刑的人如何以及为何在刑满后迅速(且反复)返回,而其他罪犯却再也没有出现过。还可以检查更复杂的刑事司法历史的影响,包括通过系统返回的多次过渡,以及特定干预措施对特定类型个人的影响。但这一新一波关联数据的复杂性和规模需要新的工作方法和对新分析技术的理解。该奖学金是一个无与伦比的机会,可以直接与司法部分析师一起工作,以充分发挥这些关联数据的潜力。通过合作,我将确定一些符合司法部优先事项并可以用这些数据解决的明确定义的研究问题。特别是,将利用连接不同刑事司法阶段的信息所提供的机会。具体问题将以我作为经验犯罪学家 15 年多来对个人刑事司法系统历程的学术理解为指导。它们还将适当地反映链接数据源中固有的结构复杂性,包括正确地参与上下文的角色(在特定法院和/或监狱中处理的效果)以及先前的经验塑造后续经验的事实。研究问题将在互动研讨会上与司法部分析师协商进行完善。这将通过一些初步的“概念验证”数据分析练习和可用数据来告知。这里的重点是为进一步讨论提供快速的证据基础,而不是选择技术上最复杂的分析解决方案。这些快速的数据深入研究将有助于突出具体的数据挑战,阐明中心研究问题,并促进进一步的讨论和问题的发展。然后,最有希望的问题将被处理成全面的实证项目,并由统计上更稳健的分析方法支持,这些方法适当地反映了数据中出现的模式。该奖学金的关键是确保为未来的研究留下遗产。为了实现这一目标,除了在学术和政策媒体上更标准地发布主要发现之外,所有工作都将写在数据分析工作表中。这些工作表直接链接到原始数据,并将运行完成数据分析所需的计算代码,同时还包括解释性文本和可发布的输出。将数据处理、分析和报告的所有要素保留在同一工作表中将确保实证工作的完全可复制性,同时还允许新用户快速调整代码和/或文本以生成新报告。我还将在相关情况下为司法部分析师举办研​​讨会。

项目成果

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Ian Brunton-Smith其他文献

Ian Brunton-Smith的其他文献

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{{ truncateString('Ian Brunton-Smith', 18)}}的其他基金

Re-counting crime: New methods to improve the accuracy of estimates of crime
重新统计犯罪:提高犯罪估计准确性的新方法
  • 批准号:
    ES/T015667/1
  • 财政年份:
    2021
  • 资助金额:
    $ 18.26万
  • 项目类别:
    Research Grant

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