On-demand labor platforms are built around user-generated rating systems that entail consumers’ monitoring of workers as a tool for algorithmic labor management. The user-generated ratings can directly determine workers’ employability. Workers are thus under pressure to score well, though they may lack knowledge about the performance metrics. Using in-depth interviews with Uber drivers, this article examines how Uber’s rating system as an engine of anxiety shapes drivers’ work practices through processes of surveillance and normalization. Specifically, drivers are prompted to play the rating game, a game that pressures them toward the normalization of platform surveillance and self-discipline for maximizing their ratings. The internalization of ratings is channeled through drivers’ reactive practices in the rating game—that is, drivers’ modification of their behavior in response to being evaluated and monitored. This article considers the socio-technical conditions under which drivers are subject to the platform surveillance and disciplinary power.

中文翻译：

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评分游戏：Uber用户生成评分的纪律

按需劳动力平台是围绕用户生成的评分系统构建的，该系统要求消费者监视工人，以此作为算法劳动管理工具。用户生成的评分可以直接确定工人的就业能力。因此，尽管工人可能缺乏有关绩效指标的知识，但他们承受着得分高的压力。通过对Uber驾驶员的深入采访，本文探讨了Uber作为焦虑引擎的评分系统如何通过监视和规范化流程来塑造驾驶员的工作习惯。具体来说，系统会提示驾驶员玩评级游戏，该游戏向他们施加压力，要求他们朝着平台监控和自律规范化的方向努力，以最大化他们的评级。评分的内部化是通过评分游戏中驾驶员的反应性实践进行的，也就是说，驾驶员根据被评估和监控的行为对其行为进行修改。本文考虑了驾驶员受平台监视和纪律处分的社会技术条件。