两种监狱数据收集制度

Kaneesha R. Johnson
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引用次数: 0

摘要

从风险评估分数到面部识别,数据驱动的工具在上个世纪已经成为警务和惩罚的核心,它们也是斗争和争论的迫切场所。事实证明,有关犯罪的假设——以及以追踪犯罪行为为名收集的数据——与其他类型的数据集(从人口普查和市政记录到保险和抵押贷款公司的数据)紧密交织在一起。在本专栏中,政治学家和历史学家卡内莎·约翰逊(Kaneesha Johnson)追溯了监狱数据形式和内容的变化,并对不同社区和机构收集数据的方式和原因提出了质疑。特别是,她将美国政府收集的有关犯罪和监禁的数据与被监禁的人及其社区收集的数据进行了比较,在一定程度上表明,我们衡量、收集和统计的数据始终反映了我们正在努力创造的世界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Two Regimes of Prison Data Collection
Column Editors’ Note: From risk assessment scores to facial recognition, data-driven tools have become central to policing and punishment over the last century, and they are also urgent sites of struggle and contestation. Presumptions about criminality—and the data collected in the name of tracking criminal behavior—prove to be deeply intertwined with other kinds of data sets, from the census and municipal records to that of insurance and mortgage companies. In this column, political scientist and historian Kaneesha Johnson traces the changing form and content of prison data and questions how and why different communities and institutions collect the data they do. In particular, she compares the data gathered about crime and incarceration by the U.S. government with data gathered by incarcerated people and their communities in part to show that what we measure, collect, and count is always a reflection of the world we are trying to create.
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