论文标题
复合不公正：讽刺决策的历史和预测
Compounding Injustice: History and Prediction in Carceral Decision-Making
论文作者
论文摘要
刑事司法中的风险评估算法使人们的生命由简单的统计工具酌情决定。本文探讨了犯罪政策中的算法决策如何表现出反馈效应，在该州被认为是“高风险”的人之间的劣势积累。费城的证据表明，风险 - 而且，犯罪行为并不是基本的，也不是政治决策的任何外在的。仔细观察风险呼叫的地理和人口统计特性，质疑当前的刑事预测做法。使用费城的法院案例摘要，我们发现了监禁的犯罪作用的证据，甚至控制着现有的“刑事风险”决定因素。有证据表明犯罪待遇会影响未来的刑事定罪，我们探讨了重复策略中复合效应的理论含义。
Risk assessment algorithms in criminal justice put people's lives at the discretion of a simple statistical tool. This thesis explores how algorithmic decision-making in criminal policy can exhibit feedback effects, where disadvantage accumulates among those deemed 'high risk' by the state. Evidence from Philadelphia suggests that risk - and, by extension, criminality - is not fundamental or in any way exogenous to political decision-making. A close look at the geographical and demographic properties of risk calls into question the current practice of prediction in criminal policy. Using court docket summaries from Philadelphia, we find evidence of a criminogenic effect of incarceration, even controlling for existing determinants of 'criminal risk'. With evidence that criminal treatment can influence future criminal convictions, we explore the theoretical implications of compounding effects in repeated carceral decisions.
