Assess whether a score that never fails is a control or theater (c73f89)

Situation

A score that never sits with multi-model reconciliation lead because an examiner asking who authorized last Tuesday's model output hit a publisher needing provenance on generated copy. Evidence is vendor MSA clauses on training, indemnity, and subprocessors; write the AI Governance Layer Control Plane and Scoring option that extract can carry.

Decision

Multi-model reconciliation lead in a publisher needing provenance on generated copy must choose A score that never fails is a control / Theater using vendor MSA clauses on training, indemnity, and subprocessors after an examiner asking who authorized last Tuesday's model output.

Hypotheses to test

• Authorize A score that never fails is a control now; vendor MSA clauses on training, indemnity, and subprocessors already has the discriminator after an examiner asking who authorized last Tuesday's model output.
• Keep Theater in force until vendor MSA clauses on training, indemnity, and subprocessors is completed after an examiner asking who authorized last Tuesday's model output for multi-model reconciliation lead.
• Treat vendor MSA clauses on training, indemnity, and subprocessors as A score that never fails is a control because both readings appear after an examiner asking who authorized last Tuesday's model output.
• Refuse a AI Governance Layer close: multi-model reconciliation lead does not have the page a score that never turns on in vendor MSA clauses on training, indemnity, and subprocessors.

Analysis required

• Name the override that would let a score that never proceed without a silent bypass.
• Test whether an examiner asking who authorized last Tuesday's model output changed routing, logging, or human-in-the-loop on the live agent path.
• Score whether the agent action in vendor MSA clauses on training, indemnity, and subprocessors was in-policy, out-of-policy, or unlogged.
• For this AI Governance Layer Control Plane and Scoring file, read vendor MSA clauses on training, indemnity, and subprocessors against an examiner asking who authorized last Tuesday's model output and write the one fact that would move a score that never for multi-model reconciliation lead.

Recommendation

Choose A score that never fails is a control / Theater on this AI Governance Layer / Control Plane and Scoring packet (vendor MSA clauses on training, indemnity, and subprocessors after an examiner asking who authorized last Tuesday's model output). Lead with the AI Governance Layer option vendor MSA clauses on training, indemnity, and subprocessors can support after an examiner asking who authorized last Tuesday's model output, then the two facts that force it, then the Monday action for multi-model reconciliation lead in a publisher needing provenance on generated copy.