Institutional Boundary Enforcement: A Theory of Authority Preservation under Distributed Administrative Execution

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Authors: Daron L. Davis
Cited by: 1
References: 5

Abstract

Contemporary public administration depends on distributed execution involving contractors, vendors, digital platforms, artificial intelligence systems, and institutional intermediaries. These arrangements can expand administrative capacity, but they also create an authority-preservation problem: how can public institutions maintain decision authority when execution occurs beyond traditional authority-bearing actors? This article develops Institutional Boundary Enforcement as a rule-based theory of authority preservation under distributed administrative execution. The framework explains how formal rules, procedures, authorization structures, and accountability mechanisms preserve the distinction between authority-bearing and non-authority-bearing actors within institutional decision systems. It identifies two boundary-defense strategies: Exclusionary Boundary Defense, which prohibits unauthorized participation in authority-sensitive functions, and Threshold Boundary Defense, which permits participation only when disclosure, attribution, verification, or human-contribution thresholds are satisfied. Using NIH restrictions on generative AI in peer review and U.S. Copyright Office guidance for AI-generated material as empirical illustrations, the article shows how institutions defend attribution, verification, responsibility, and authorization when administrative execution is technologically mediated. The article defines Authority Boundary Collapse as the failure condition in which institutional authorization persists even though boundary rules no longer preserve attributable decision authority. It contributes to public administration and governance theory by specifying how institutions preserve authority before distributed execution becomes authority displacement.

Fields of Study & Subjects

Ethics and Social Impacts of AI Cybersecurity and Cyber Warfare Studies Digital Economy and Work Transformation

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
6 June 2026
Document type
Preprint