Routinized Deference: Predictive Screening and Bureaucratic Capacity in Child Protective Services

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ID: 332541
2026
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Abstract
Abstract Predictive algorithms are increasingly used to support frontline decision-making in public administration, but evidence remains limited on how they affect bureaucratic capacity. This study examines county-level adoption of predictive screening tools in U.S. Child Protective Services using NCANDS data (2010–2023) and a stacked difference-in-differences design. Leveraging staggered adoption, I find no change in the total number of investigations opened and a sizable decline (about 15%) in the share of investigations that are substantiated. These results are inconsistent with operational capacity gains and more consistent with misclassification that erodes analytical capacity. These findings are consistent with a mechanism of routinized deference: under workload and accountability pressures, algorithmic recommendations can become procedurally defensible defaults. Overall, this study argues that predictive screening is not capacity-enhancing by default, as routinized deference can undermine the professional judgment central to bureaucratic work.
Reference Key
openalex_W7222519002 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Jiaen Wu
Journal journal of public administration research and theory
Year 2026
DOI
10.1093/jopart/muag032
URL
https://doi.org/10.1093/jopart/muag032
Keywords Keywords not found

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