Abstract

Record numbers of offenders are being released to community supervision. This poses a challenge to agencies and officers in charge of providing supervision because there are far more clients in need of supervision than officers can reasonably attend to. This challenge represents an opportunity for criminologists to work with agencies to find innovative ways to allocate their limited resources. Standardized risk assessments are the most commonly used tool for determining which clients receive the most resources (e.g., officer attention). But risk assessment is a static instrument that is incapable of making cross-client predictions. We offer a novel, dynamic approach by integrating the Elo-rating system into the risk assessment paradigm. Our study is meant to present a potential innovative solution and to demonstrate that it may have merit when applied in practice. We test our idea against data from the Pathways to Desistance Study and show that the Elo-rating system is a flexible tool that can be used to adjust to changes in risk more rapidly than standard risk assessment tools. We also show that the Elo-rating system, when combined with risk assessment, can increase the accuracy of prospective predictions of recidivism risk. We discuss how Elo-rating system could be used by community supervision agencies seeking to optimize decision-making.

摘要

创纪录数量的罪犯被释放以接受社区监督。这对负责提供监督的机构和官员提出了挑战，因为需要监督的客户远远超过官员能够合理处理的数量。这一挑战为犯罪学家提供了与机构合作寻找创新方法来分配其有限资源的机会。标准化风险评估是确定哪些客户获得最多资源（例如，官员关注）的最常用工具。但风险评估是一种静态工具，无法进行跨客户预测。我们通过将 Elo 评级系统集成到风险评估范例中，提供了一种新颖的动态方法。我们的研究旨在提出一个潜在的创新解决方案，并证明它在实践中可能具有价值。我们根据 Pathways to Desistance Study 的数据测试了我们的想法，并表明 Elo-rating 系统是一种灵活的工具，可用于比标准风险评估工具更快地适应风险变化。我们还表明，当 Elo-rating 系统与风险评估相结合时，可以提高对累犯风险的前瞻性预测的准确性。我们讨论了寻求优化决策的社区监督机构如何使用 Elo-rating 系统。我们还表明，当 Elo-rating 系统与风险评估相结合时，可以提高对累犯风险的前瞻性预测的准确性。我们讨论了寻求优化决策的社区监督机构如何使用 Elo-rating 系统。我们还表明，当 Elo-rating 系统与风险评估相结合时，可以提高对累犯风险的前瞻性预测的准确性。我们讨论了寻求优化决策的社区监督机构如何使用 Elo-rating 系统。