一个考虑在儿童福利中使用预测风险模型的实用框架。
A Practical Framework for Considering the Use of Predictive Risk Modeling in Child Welfare.
作者信息
Drake Brett, Jonson-Reid Melissa, Ocampo María Gandarilla, Morrison Maria, Dvalishvili Darejan Daji
机构信息
professor at the Brown School at Washington University in St. Louis.
Ralph and Muriel Pumphrey Professor of Social Work Research and director of the PhD program in social work at the Brown School at Washington University in St. Louis.
出版信息
Ann Am Acad Pol Soc Sci. 2020 Nov;692(1):162-181. doi: 10.1177/0002716220978200. Epub 2021 Jan 29.
Predictive risk modeling (PRM) is a new approach to data analysis that can be used to help identify risks of abuse and maltreatment among children. Several child welfare agencies have considered, piloted, or implemented PRM for this purpose. We discuss and analyze the application of PRM to child protection programs, elaborating on the various misgivings that arise from the application of predictive modeling to human behavior, and we present a framework to guide the application of PRM in child welfare systems. Our framework considers three core questions: (1) Is PRM more accurate than current practice? (2) Is PRM ethically equivalent or superior to current practice? and (3) Are necessary evaluative and implementation procedures established prior to, during, and following introduction of the PRM?
预测性风险建模（PRM）是一种新的数据分析方法，可用于帮助识别儿童遭受虐待和 maltreatment 的风险。几个儿童福利机构已为此考虑、试点或实施了 PRM。我们讨论并分析了 PRM 在儿童保护项目中的应用，阐述了将预测性建模应用于人类行为所产生的各种疑虑，并提出了一个框架来指导 PRM 在儿童福利系统中的应用。我们的框架考虑三个核心问题：（1）PRM 比当前做法更准确吗？（2）PRM 在伦理上与当前做法相当还是优于当前做法？以及（3）在引入 PRM 之前、期间和之后是否建立了必要的评估和实施程序？
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