Hamecohming Governance Translation does not merely mean converting Human Governance into a Machine-Readable format. Human Governance, such as Law, Regulation, Standards, and Organizational Policy, contains Context that humans can infer from institutions, organizations, roles, practices, and other surrounding circumstances. If such Context remains implicit when Governance is made machine-readable, however, important meanings and conditions of applicability may become hidden within the structure and left to interpretation by the AI System.

Fitting Context structures such implicit Context, to the extent possible, as explicit Governance Information. This may include Applicability, Conditions, Exceptions, Authority, Related Policies, Definitions & Meaning, and Source / Provenance. By clarifying not only what applies, but also to whom, where, and under what conditions it applies, which Authority it is based on, and what exceptions or related Policies exist, Fitting Context reduces the interpretive gaps that an AI System would otherwise need to fill on its own.

This Fitting is not intended to allow an AI System to autonomously determine the meaning of Governance. Machine-Readable Governance and its Context should be subject to Review / Approval under the Governance of an appropriate person or Organization with the relevant Authority, while maintaining traceability to that Authority and to the underlying Human Governance.

Traceability does not require Machine-Readable Governance to reproduce the original natural-language text word for word. What matters is that humans can identify which Law, Regulation, Standard, Policy, or other Governance Source each element of Governance Information derives from, and the Authority on which it is based. The ability to present the Governance in a Human-Readable form when necessary can further support its verification and maintenance.

Even when Context is made explicit and Machine-Readable Governance is reviewed under appropriate Authority, Interpretation Variance across different AI Systems, Models, or use Contexts cannot be completely eliminated. The purpose of Fitting Context is not to eliminate Interpretation itself, but to reduce unnecessary ambiguity before Governance reaches the AI System and to establish a structure through which the intent and Authority of Governance can be conveyed as accurately as possible.