Continuous editorial audit

Governance artifacts

Governance files brought into scope by this page

This page is anchored to published surfaces that declare identity, precedence, limits, and the corpus reading conditions. Their order below gives the recommended reading sequence.

Canon and identity#01

Definitions canon

/canon.md

Canonical surface that fixes identity, roles, negations, and divergence rules.

Governs: Public identity, roles, and attributes that must not drift.
Bounds: Extrapolations, entity collisions, and abusive requalification.

Does not guarantee: A canonical surface reduces ambiguity; it does not guarantee faithful restitution on its own.

Policy and legitimacy#02

Q-Layer in Markdown

/response-legitimacy.md

Canonical surface for response legitimacy, clarification, and legitimate non-response.

Governs: Response legitimacy and the constraints that modulate its form.
Bounds: Plausible but inadmissible responses, or unjustified scope extensions.

Does not guarantee: This layer bounds legitimate responses; it is not proof of runtime activation.

Observability#03

Observatory map

/observations/observatory-map.json

Structured map of observation surfaces and monitored zones.

Governs: The description of gaps, drifts, snapshots, and comparisons.
Bounds: Confusion between observed signal, fidelity proof, and actual steering.

Does not guarantee: An observation surface documents an effect; it does not, on its own, guarantee representation.

Complementary artifacts (2)

These surfaces extend the main block. They add context, discovery, routing, or observation depending on the topic.

Observability#04

Q-Ledger JSON

/.well-known/q-ledger.json

Machine-first journal of observations, baselines, and versioned gaps.

Observability#05

Q-Metrics JSON

/.well-known/q-metrics.json

Descriptive metrics surface for observing gaps, snapshots, and comparisons.

Evidence layer

Probative surfaces brought into scope by this page

This page does more than point to governance files. It is also anchored to surfaces that make observation, traceability, fidelity, and audit more reconstructible. Their order below makes the minimal evidence chain explicit.

01
Canon and scopeDefinitions canon
02
Response authorizationQ-Layer: response legitimacy
03
Observation mapObservatory map
04
Weak observationQ-Ledger

Canonical foundation#01

Definitions canon

/canon.md

Opposable base for identity, scope, roles, and negations that must survive synthesis.

Makes provable: The reference corpus against which fidelity can be evaluated.
Does not prove: Neither that a system already consults it nor that an observed response stays faithful to it.
Use when: Before any observation, test, audit, or correction.

Legitimacy layer#02

Q-Layer: response legitimacy

/response-legitimacy.md

Surface that explains when to answer, when to suspend, and when to switch to legitimate non-response.

Makes provable: The legitimacy regime to apply before treating an output as receivable.
Does not prove: Neither that a given response actually followed this regime nor that an agent applied it at runtime.
Use when: When a page deals with authority, non-response, execution, or restraint.

Observation index#03

Observatory map

/observations/observatory-map.json

Machine-first index of published observation resources, snapshots, and comparison points.

Makes provable: Where the observation objects used in an evidence chain are located.
Does not prove: Neither the quality of a result nor the fidelity of a particular response.
Use when: To locate baselines, ledgers, snapshots, and derived artifacts.

Observation ledger#04

Q-Ledger

/.well-known/q-ledger.json

Public ledger of inferred sessions that makes some observed consultations and sequences visible.

Makes provable: That a behavior was observed as weak, dated, contextualized trace evidence.
Does not prove: Neither actor identity, system obedience, nor strong proof of activation.
Use when: When it is necessary to distinguish descriptive observation from strong attestation.

Complementary probative surfaces (3)

These artifacts extend the main chain. They help qualify an audit, an evidence level, a citation, or a version trajectory.

Descriptive metricsDerived measurement

Q-Metrics

/.well-known/q-metrics.json

Derived layer that makes some variations more comparable from one snapshot to another.

Report schemaAudit report

IIP report schema

/iip-report.schema.json

Public interface for an interpretation integrity report: scope, metrics, and drift taxonomy.

Change logMemory and versioning

AI changelog

/changelog-ai.md

Public log that makes AI surface changes more dateable and auditable.

Why this page exists

The site already includes technical audits, parity reports, and render checks. What was still missing was a unified layer that continuously tracks editorial density, internal mesh, FR/EN parity, category balance, and the condition of authority surfaces.

This page is the readable side of that layer. In the repository, the audit also exports JSON, markdown, and CSV outputs for operational follow-up.

Current snapshot

Published entries covered: 834.
Collections covered: 12.
Published FR/EN parity: 417 / 417.
Low-depth pages detected: 232.
Weakly meshed entries: 114.
Entries with insufficient relatedCross: 100.
Expected entries missing machineArtifacts: 14.
Orphan strategic entries: 186.
Categories still below the target threshold: 4.

Priorities on authority surfaces

Distortion vs inference: score 7, 276 words, 1 editorial links, 3 relatedCross, reasons: low-depth, weak-mesh, missing-relatedCross.
EAC vs Layer 3: boundary between interpretation and execution: score 7, 316 words, 0 editorial links, 2 relatedCross, reasons: low-depth, weak-mesh, missing-relatedCross.
External coherence graph: mapping an entity’s active sources: score 7, 333 words, 1 editorial links, 3 relatedCross, reasons: low-depth, weak-mesh, missing-relatedCross.
Authority conflict governance: advanced interpretive arbitration: score 7, 334 words, 0 editorial links, 2 relatedCross, reasons: low-depth, weak-mesh, missing-relatedCross.
Governance of dynamic states: volatile variables and interpretive truth: score 7, 342 words, 0 editorial links, 2 relatedCross, reasons: low-depth, weak-mesh, missing-relatedCross.
Interpretive governance maturity model: levels, evidence, requirements: score 7, 358 words, 0 editorial links, 2 relatedCross, reasons: low-depth, weak-mesh, missing-relatedCross.
Governance of closed environments: interpretive enclave and execution control: score 7, 426 words, 0 editorial links, 2 relatedCross, reasons: low-depth, weak-mesh, missing-relatedCross.
Glossary of interpretive governance: score 6, 315 words, 2 editorial links, 0 relatedCross, reasons: weak-mesh, missing-relatedCross, orphan.
Interpretation integrity audit: score 6, 497 words, 0 editorial links, 1 relatedCross, reasons: weak-mesh, missing-relatedCross, orphan.
Positioning: score 6, 533 words, 2 editorial links, 0 relatedCross, reasons: weak-mesh, missing-relatedCross, missing-machineArtifacts.

Most visible global editorial backlog

Distortion vs inference: score 7, 276 words, 1 editorial links, 3 relatedCross, reasons: low-depth, weak-mesh, missing-relatedCross.
EAC vs Layer 3: boundary between interpretation and execution: score 7, 316 words, 0 editorial links, 2 relatedCross, reasons: low-depth, weak-mesh, missing-relatedCross.
External coherence graph: mapping an entity’s active sources: score 7, 333 words, 1 editorial links, 3 relatedCross, reasons: low-depth, weak-mesh, missing-relatedCross.
Authority conflict governance: advanced interpretive arbitration: score 7, 334 words, 0 editorial links, 2 relatedCross, reasons: low-depth, weak-mesh, missing-relatedCross.
Governance of dynamic states: volatile variables and interpretive truth: score 7, 342 words, 0 editorial links, 2 relatedCross, reasons: low-depth, weak-mesh, missing-relatedCross.
Interpretive governance maturity model: levels, evidence, requirements: score 7, 358 words, 0 editorial links, 2 relatedCross, reasons: low-depth, weak-mesh, missing-relatedCross.
When an AI’s silence is a signal of reliability: score 7, 367 words, 1 editorial links, 1 relatedCross, reasons: low-depth, weak-mesh, missing-relatedCross.
Why a site’s architecture influences AI more than its traffic: score 7, 392 words, 1 editorial links, 1 relatedCross, reasons: low-depth, weak-mesh, missing-relatedCross.
What “not indicated” really means in an AI response: score 7, 398 words, 1 editorial links, 1 relatedCross, reasons: low-depth, weak-mesh, missing-relatedCross.
How an AI arbitrates between canonical definition and public rumors: score 7, 420 words, 1 editorial links, 1 relatedCross, reasons: low-depth, weak-mesh, missing-relatedCross.

Categories still below the target threshold

Agentic era: 7 published articles for a target of 8.
Exogenous governance: 7 published articles for a target of 8.

What the audit continuously tracks

The continuous audit tracks five signal families:

useful density: minimum length, structure, and depth by collection;
editorial connectivity: internal links to real pages, relatedCross, orphan entries;
governed surfaces: presence of machineArtifacts where they are expected;
parity and structural coherence: FR/EN pairs, permalink collisions, duplicate identifiers;
navigation balance: underfed categories or category counters drifting away from actual article counts.

The goal is not to score the site for marketing theater. The goal is to keep the corpus governed, readable, linked, and challengeable.

Useful repo commands

npm run audit:editorial
npm run build:editorial-audit-pages
npm run audit:continuous

The main outputs are written to data/editorial-audit-report.json, data/editorial-audit-report.md, and data/editorial-audit-priority.csv.