Administrative Burden and Uncertainty

• In Event: Reducing the Psychological Burden of Administrative Processes

Abstract

Uncertainty is a fundamental, but surprisingly under-examined and under-theorized, feature of administrative encounters. Stemming from an information asymmetry during, but also before, citizen-state interactions occur, uncertainty is conceptualized as an informational state that is shaped by incomplete knowledge about facts related to administrative processes. This includes questions like “am I eligible to apply?”, “what documents do I need?”, “what are my rights?”, “have I been approved?”, “what do I get if I’m approved”, “how long will this process take?”, or “what happens if my application is denied?”. Such ‘epistemological uncertainty’ (Cecchini 2024) manifests across various domains of citizen-state interaction, including tax compliance, police encounters, immigration proceedings or social safety net programs. Indeed, administrative processes and their often complex rules, specialized language and at times opaque procedures create environments where people frequently lack the information to confidently navigate processes and predict outcomes. Yet, despite its pervasive influence on how people experience and navigate government services, uncertainty as a distinct empirical concept has received limited scholarly attention within the public management literature. This gap is particularly consequential as uncertainty fundamentally shapes peoples’ ability to understand, anticipate and respond to administrative requirements in ways that significantly alter both program participation and their broader relationship with the state.

We employ a multi-method approach to examine how uncertainty manifests and affects applicants for the Supplemental Nutrition Assistance Program (SNAP; also known as Food Stamps). Our empirical strategy combines analysis of unstructured text from the r/foodstamps subreddit (a public online discussion forum) with survey data from SNAP applicants collected during their benefit enrollment. Doing so, we triangulate findings across different contexts and data sources. The Reddit data is used to generate broad themes of uncertainty and their psychological correlates, while the SNAP survey data zooms in on one particular facet of administrative uncertainty. To analyze Reddit data we employ a large language model (GPT-4o-mini) using few-shot learning techniques to classify posts according to specific uncertainty stages. This approach allows us to systematically categorize thousands of posts while maintaining sensitivity to the nuanced language used by applicants to describe their experiences. To complement this landscape analysis, we draw on survey data from approximately 19,000 SNAP applicants, with responses linked to administrative records to verify their application outcomes. The survey includes both structured questions measuring administrative burdens (based on Jilke et al. 2024) and open-ended text responses where applicants were asked to describe their application and enrollment experiences in their own words. On this basis, we examine how administrative uncertainty shapes applicants' perceptions of burdens, as well as their psychological responses, by comparing applicants who experience outcome uncertainty with regard to their benefit applications versus those who are certain about their application outcomes.

Authors

• Sebastian Jilke, Georgetown University
  Presenting Author

• Zhaowen Guo, Georgetown University
  Non-Presenting Co-Author

• Pamela Herd, Georgetown University
  Non-Presenting Co-Author

• Donald Moynihan, University of Michigan
  Non-Presenting Co-Author