Listening to bureaucratic noise: (Auto-)ethnographic reflections on legal advice encounters in the Dutch data welfare state

Abstract Through an (auto-)ethnographic study of welfare-related legal advising in the city of Rotterdam, the Netherlands, this study shows how the data infrastructures that shape interactions between welfare recipients and the state simultaneously shape what is deemed unwanted or irrelevant interference that disrupts citizen-state communication. The concept of “bureaucratic noise” is proposed to describe the citizen information that is filtered out by the restrictive data infrastructures of the welfare state. By incorporating (auto-)ethnographic reflections from the author’s dual role as both researcher and legal advisor, three different forms of bureaucratic noise are discussed here: emotions, noisy data that is strategically or coercively cleaned from benefit applications, and discarded data that citizens filter back in through administrative objections. The study argues that tuning into bureaucratic noise could serve as an inroad into often-touted but seldom-practiced people-centered and customizable welfare policies, often referred to in Dutch as de menselijke maat and maatwerk.