The State's Politics of"Fake Data"

2026-02-11

AI Summary

This study interrogates how ostensibly “false” data within state institutions serve institutional functions rather than merely deviating from truth. Drawing on ethnographic fieldwork in grassroots bureaucratic agencies in China and the United States, and integrating institutional analysis with a sociotechnical systems perspective, it reveals that state data practices prioritize “fitness for purpose” over absolute veracity across four interrelated processes: creation, correction, collusion, and amplification. The paper conceptualizes “false” data as relational, processual, and performative, advocating for their reframing as “useful fictions.” It further calls for making the political dimensions of such data explicit, rendering them contestable and accountable. By foregrounding the political context and practical utility of data, this work advances a novel paradigm for data governance and urges policymakers to attend to the situated politics of data production and use.

Technology Category

• Application Domains: Misinformation & Fake News
• Data Mining & Knowledge Management: Other Foundations of Data Mining & Knowledge Management
• Natural Language Processing: Fact-Checking / Misinformation Detection (NLP Focus)

Application Category

• Security and Privacy: Data transparency and provenance
• Web Mining and Content Analysis: Web data provenance, reliability, and authenticity
• Semantics and Knowledge: Provenance, trust, security and privacy, and ethical issues in managing semantic data

Abstract

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.

Problem

• fake data
• state bureaucracy
• data politics
• representational accuracy
• institutional work

Innovation

• fake data
• state bureaucracy
• fitness-for-purpose
• performative data
• institutional work