数据抑制规则对数据访问和重新识别风险的影响 在收养和托儿所的风险分析和报告系统年档案
1Department of Sociology, Duke University, Durham, NC, USA.
Child maltreatment
|July 29, 2024
概括
通过降低收养和寄养分析和报告系统 (AFCARS) 中的数据抑制门,可以增加研究人员对寄养数据的访问. 700个案例的门平衡了数据访问与儿童重新识别风险.
科学领域:
- 儿童福利研究 儿童福利研究
- 数据 隐私 数据 隐私 数据
- 社会政策分析 社会政策分析
背景情况:
- 收养和寄养分析报告系统 (AFCARS) 是儿童福利研究的关键数据来源.
- 目前的AFCARS数据删除规则,基于1000个案例的门,限制了对来自较小社区的数据的访问.
- 这种局限性阻碍了对影响家庭外安置的当地因素的研究.
研究的目的:
- 评估AFCARS数据隐藏规则对数据可访问性和重新识别风险的影响.
- 为了比较现有的1000个病例的门与其他抑制水平.
- 根据儿童福利研究中数据共享的政策决策.
主要方法:
- 使用非公开的收养和寄养分析和报告系统 (AFCARS) 数据集.
- 评估了数据访问和重新识别风险之间的权衡,跨越各种案例值.
- 将1000个案例的门与一系列潜在的替代方案进行比较 (例如,400-700个案例).
主要成果:
- 降低删除值显著增加了数据的可访问性,特别是对于较小的县.
- 400至700个案例之间的值提供了实质性的数据访问收益,随着重新识别风险的适度增加.
- 700个病例的门将可识别的县增加50%,同时将养育儿童的重新识别风险保持在1%以下.
结论:
- 调整AFCARS数据压制规则可以提高研究儿童福利在各种环境中的研究能力.
- 700个案例的门代表了增加数据访问和可管理的重新识别风险之间的可行的妥协.
- 从农村县发布数据需要更大的门降低,这引发了更大的重新识别问题.
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