Χ-Ω — Structural Limits of Attribution in Irreversible Systems: A Classification of Invariant-Satisfied Global Failure

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Authors: Kelly Rhys
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Abstract

This paper introduces Χ-Ω, a structural classification of failure in irreversible systems where global collapse can occur despite full local invariant compliance and audit success. Challenging the assumption that all system-level failures must be locally attributable, Χ-Ω defines a precise boundary where attribution, intervention, and prevention become undefined—not due to epistemic limitation or oversight, but due to the expressive limits of the governing descriptive language. Key contributions include: Invariant-Satisfied Global Failure (ISGF): A condition where all local rules are upheld, yet the system irreversibly fails without any accountable violation. Core Structural Patterns: Defines a minimal pattern basis—Interaction Expressivity Mismatch (IEM), Explanatory Language Exhaustion (ELE), and Attribution Surface Nullity (ASN)—that underpins the Χ-Ω classification. Non-Intervention Closure: Proves that within certain descriptive regimes, no admissible intervention operators can be defined without extending the language or violating its invariants. Minimal Witness Language ℒ₀: Constructs a deliberately austere language to demonstrate that Χ-Ω failure is not an artifact of complexity, but a predictable limit within common governance frameworks. Language-Relative Jurisdiction: Χ-Ω is not a critique of governance, but a boundary condition—failure is not misbehavior, but unrepresentability under current descriptive constraints. By formalizing when and how governance languages lose their capacity to characterize failure, Χ-Ω offers a profound reframing: some systemic collapses cannot be explained within the very rules designed to prevent them—not due to failure of enforcement, but because of structural mismatch between language and reality.

Fields of Study & Subjects

Diverse Interdisciplinary Research Studies Complex Systems and Dynamics Complex Systems and Decision Making

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
28 January 2026