Narrative Camouflage Over Representational Overflow: A Governing Principle for Bounded System

This paper introduces a governing principle for narrative-bearing bounded systems: unbounded state injected into a bounded representational channel produces drift, and when a narrative layer is present, that drift is camouflaged as coherence rather than exposed as failure. This principle generalizes across human, organizational, and agentic-AI substrates. It clarifies the formal role of the Emotional Indicators of Compromise (EIOC) framework as a detection system for narrative camouflage over representational overflow, complementing the Adaptive Privilege Revocation (APR) framework, which governs privilege overflow. Together, APR and EIOC constitute atwo-layer governance architecture for bounded systems: privilege physics (action constraints) and narrative physics (state-drift detection). This paper establishes the invariant, defines the architectural relationship between APR and EIOC, and argues that governance of bounded systems requires both layers. No binding logic, thresholds, or inter-model relationships are disclosed.