Which Clients are Deserving of Help? A Theoretical Model and Experimental Test

• 成果类型: Article
• 署名作者: Jilke, Sebastian; Tummers, Lars
• 署名单位: Rutgers University System; Rutgers University Newark; Utrecht University
• 刊物名称: JOURNAL OF PUBLIC ADMINISTRATION RESEARCH AND THEORY
• ISSN/ISSBN: 1053-1858
• DOI: 10.1093/jopart/muy002
• 发表日期: 2018
• 页码: 226-238
• 关键词: street-level bureaucracy; CONJOINT-MEASUREMENT; welfare; DISCRETION; work; RACE; perceptions; Frontline; feedback; GENDER

摘要

Street-level bureaucrats have to cope with high workloads, role conflicts, and limited resources. An important way in which they cope with this is by prioritizing some clients, while disregarding others. When deciding on whom to prioritize, street-level bureaucrats often assess whether a client is deserving of help. However, to date the notion of the deserving client is in a black box as it is largely unclear which client attributes activate the prevailing social/professional category of deservingness. This article, therefore, proposes a theoretical model of three deservingness cues that street-level bureaucrats employ to determine whom to help: earned deservingness (i.e., the client is deserving because (s)he earned it: the hardworking client), needed deservingness (i.e., the client is deserving because (s) he needs help: the needy client), and resource deservingness (i.e., the client is deserving as (s) he is probably successful according to bureaucratic success criteria: the successful client). We test the effectiveness of these deservingness cues via an experimental conjoint design among a nationwide sample of US teachers. Our results suggest that needed deservingness is the most effective cue in determining which students to help, as teachers especially intend to prioritize students with low academic performance and members of minority groups. Earned deservingness was also an effective cue, but to a lesser extent. Resource deservingness, in contrast, did not affect teachers' decisions whom to help. The theoretical and practical implications of our findings for discretionary biases in citizen-state interactions are discussed.