Data have power. As such, most discussions of data presume that records should mirror some idealized ground truth. Deviations are viewed as failure. Drawing on two ethnographic studies of state data-making in a Chinese street-level bureaucrat agency and at the US Census Bureau we show how seemingly "fake" state data perform institutional work. We map four moments in which actors negotiate between representational accuracy and organizational imperatives: creation, correction, collusion, and augmentation. Bureaucrats routinely privilege what data do over what they represent, creating fictions that serve civil servants' self-interest and enable constrained administrations. We argue that "fakeness" of state data is relational (context dependent), processual (emerging through workflows), and performative (brought into being through labeling and practice). We urge practitioners to center fitness-for-purpose in assessments of data and contextual governance. Rather than chasing impossible representational accuracy, sociotechnical systems should render the politics of useful fictions visible, contestable, and accountable.

翻译：数据具有力量。因此，大多数关于数据的讨论都预设记录应反映某种理想化的客观事实。偏离这一标准被视为失败。基于对中国某基层官僚机构与美国人口普查局的国家数据制造过程的两项民族志研究，我们展示了看似“虚假”的国家数据如何执行制度性工作。我们描绘了行动者在表征准确性与组织需求之间进行协商的四个关键环节：创建、修正、共谋与扩充。官僚们通常优先考虑数据的功用而非其表征内容，创造出服务于公务员自身利益并赋能受约束的行政体系的虚构产物。我们认为，国家数据的“虚假性”具有关系性（依赖情境）、过程性（通过工作流程涌现）与操演性（通过标签与实践得以生成）。我们敦促从业者在数据评估与情境治理中以“适用性”为核心。社会技术系统不应追求不可能的表征准确性，而应使有用虚构的政治性变得可见、可争议且可问责。