The SVRNOS Governance Error Register

The Governance Error Register (GER) is part of the SVRNOS governance research published by Sushee Nzeutem (Sovereign OS LLC). It is the classification taxonomy that complements the SVRNOS 7-Layer Model architectural map and the Non-Content Safety Attestation (NCSA) evidentiary receipt format: the 7-Layer Model identifies where in the technical stack a governance failure or control sits, NCSA provides the signed receipt that the governance layer ran, and GER names what kind of structural governance failure occurred. v0.2 also publishes the TRACE Method — the five-step practitioner workflow that carries a public incident record through classification to the governance control that should now exist. Abstract AI safety discourse has a vocabulary problem. Failure modes at the governance layer, the policies, escalation paths, audit systems, and human review processes that wrap AI models, are poorly named, inconsistently described, and not shared across the engineering, legal, policy, and research communities that need to communicate about the same events. The SVRNOS AI Governance Error Register (GER) is a structured classification system for AI platform governance failures. v0.1 introduced twenty-seven codes organized as HTTP-derived numeric mnemonics across five tiers. v0.2 makes three contributions. The first is the register itself: a one-hundred-ten-code taxonomy (one hundred eight L1-L7 classification codes plus two Dimension Markers, GER-800 Human-Operational Dimension and GER-900 Institutional-Accountability Dimension), with every classification code assigned to a layer in the SVRNOS 7-Layer Model. The second is an annotation architecture that produces a single Index Governance Failure code per incident, zero or more Contributing Governance Failure codes, and optional Dimension Markers, and a written Selection Note. The third is the TRACE Method (Triage, Reconstruct, Assign, Corroborate, Enforce), a five-step practitioner workflow that applies the architecture to a public incident record and carries it through to the governance control that should now exist. The full register (110 codes) is maintained at docs.svrnos.com/ger and included as Appendix A; this paper presents the methodology, the framing, and a lean reading of the register through the 7-Layer Model. The annotation architecture and the TRACE workflow are the larger contribution; the vocabulary expansion is secondary. Engagement tracks and adoption pathway are detailed in Section 8, Adoption. Previously published as v0.1 at https://svrnos.com/research/governance-error-register on April 27, 2026. This v0.2 deposit on Zenodo introduces the three contributions named above.