Maintainers of Stability: The Labor of China's Data-Driven Governance and Dynamic Zero-COVID

This paper examines the social, technological, and emotional labor of maintaining China's data-driven governance broadly, and dynamic zero-COVID management in particular. Drawing on ethnographic research in China, we examine the sociotechnical work of maintenance during the 2022 Shanghai lockdown. This labor included coordinating mass testing, quarantine, and lockdown procedures as well as implementing ad-hoc technological workarounds and managing public sentiments. We demonstrate that, far from being efected from the top down, China's data-driven governance relies on the circumscribed participation of citizens. During Shanghai's lockdown, citizens with relevant expertise helped to maintain technological stability by fxing or programming data systems, but also to ensure the ongoing production of "positive feelings" about social stability through data-driven governance. In so doing, such citizens simultaneously enacted an ambivalent and circumscribed form of agency, and maintained social and by extension political stability. This article sheds light on data-driven governance and political processes of maintenance.

• Human-centered computing → HCI theory, concepts and models; Empirical studies in HCI.