Work

How citizens’ discursive strategies influence street-level bureaucrats’ prioritization: evidence from the government service hotline system in China

Year: 2026

Type: article

Abstract: This study examines how citizens’ discursive strategies influence street-level bureaucrats’ (SLBs) prioritization decisions. Drawing on the research regarding deservingness heuristics, citizen voice behavior, and citizen resistance strategies, we conceptualize discursive strategies as showing deservingness, threatening to petition higher-level authorities, and threatening to engage in self-harm. Using a dataset of 254,257 transcribed interactions between citizens and hotline operators recorded on the government service hotline system (similar to the US 311 system) across 2019 in China, we identify discursive strategies in citizen complaints through a supervised machine learning (SML) algorithm. Our analysis shows that SLBs are significantly more likely to prioritize responding to citizens’ complaints that include the discursive cues of showing deservingness, petitioning higher-level authorities, and engaging in self-harm, with deservingness exerting the weakest effect. These findings contribute to our understanding of SLBs’ prioritization decisions in government-citizen interactions.

Source: Journal of Public Policy

DOI: 10.1017/s0143814x26101147

Authors: Xinghua Zhao, Zheng Cheng, Yanwei Li

Institutions: Yangzhou University, Shandong University

Language: English

Topic: Public Policy and Administration Research

Subfield: Public Administration

Field: Social Sciences

Domain: Social Sciences

SDGs: Peace, justice, and strong institutions, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $3,550