People experiencing homelessness seek support from homeless services systems that increasingly rely on prioritization algorithms to determine who is the most deserving of scarce resources. In this paper, we argue that algorithmic harms in homeless services require a reparative approach that takes the data work of care workers seriously. Building on Davis, Williams, and Yang's concept of algorithmic reparation, we present a qualitative study that examines the intertwining of data work and care labor of 15 care workers. We show how they wrestle with the ethics of algorithmic prioritization and develop workarounds that allow them to advocate for their clients. We contribute an empirical understanding of how care workers provide care under homeless services systems that equate data work with care labor to justify work intensification. Our findings have implications for understanding the future of care labor in datafied conditions and the social and political ramifications of algorithmically mediated care.

中文翻译：

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自动化之后：无家可归者优先算法和护理劳动力的未来

无家可归的人寻求无家可归者服务系统的支持，这些系统越来越依赖优先级算法来确定谁最应该获得稀缺资源。在本文中，我们认为无家可归者服务中的算法危害需要采取修复方法，认真对待护理人员的数据工作。基于 Davis、Williams 和 Yang 的算法修复概念，我们提出了一项定性研究，考察了 15 名护理人员的数据工作和护理劳动之间的相互交织。我们展示了他们如何与算法优先级的道德问题作斗争，并开发出让他们能够为客户辩护的变通办法。我们对护理人员如何在无家可归者服务系统下提供护理提供了实证理解，该系统将数据工作与护理劳动等同起来，以证明工作集约化的合理性。我们的研究结果对于理解数据化条件下护理劳动的未来以及算法介导的护理的社会和政治影响具有重要意义。