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.
- 01Canon and scopeDefinitions canon
- 02Evidence artifactai-governance.json
- 03Evidence artifactinterpretation-policy.json
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.
ai-governance.json
/.well-known/ai-governance.json
Published surface that contributes to making an evidence chain more reconstructible.
- Makes provable
- Part of the observation, trace, audit, or fidelity chain.
- Does not prove
- Neither total proof, obedience guarantee, nor implicit certification.
- Use when
- When a page needs to make its evidence regime explicit.
interpretation-policy.json
/.well-known/interpretation-policy.json
Published surface that contributes to making an evidence chain more reconstructible.
- Makes provable
- Part of the observation, trace, audit, or fidelity chain.
- Does not prove
- Neither total proof, obedience guarantee, nor implicit certification.
- Use when
- When a page needs to make its evidence regime explicit.
Defined authority
Defined authority designates authority explicitly declared through canonical sources, structured signals, governance artifacts, or source hierarchy rather than reconstructed from weak contextual cues.
It is the opposite of letting a system guess which source, date, scope, or modality should govern a response.
Definition
Authority is defined when a system can identify the governing source before synthesis. The declaration may come from:
- a canonical definition;
- a doctrine page;
- an identity or entity graph;
- a governance file;
- a source hierarchy;
- a response-legitimacy rule;
- an explicit boundary, negation, or non-response condition.
Why this concept matters
In human reading, authority is often carried by context. In machine interpretation, context is fragile. A domain, layout, author name, or page position may disappear once a fragment enters retrieval, summarization, citation, or recombination.
Defined authority makes the governing layer explicit enough to survive that movement.
Minimal rule
If a declared authority signal exists, it should have precedence over an authority reconstructed from popularity, proximity, stylistic confidence, or apparent relevance.
Corpus role and diagnostic use
In the corpus, Defined authority should be read as an authority-control term rather than as a generic description of credibility. It helps separate what a system may retrieve, what it may cite, what it may treat as governing, and what must remain subordinate to a stronger source. This distinction matters because AI outputs often collapse reputation, proximity, recency, frequency and explicit authority into a single fluent answer.
The diagnostic value of the term is highest when a response looks reasonable but the governing source is unclear. In that situation, the relevant question is not only whether the answer is true in isolation. The question is whether the answer preserved the right issuer, perimeter, timestamp, source hierarchy and response condition.
Failure pattern to detect
A failure occurs when weak signals become silently authoritative. Typical symptoms include an answer that privileges a derivative source over a canonical one, treats an extracted statement as if it still carried its original limits, or resolves a conflict without exposing the authority basis. These failures create a gap between apparent coherence and governed interpretation.
Reading rule
Use this definition with interpretive governance, interpretive risk, answer legitimacy, source hierarchy and proof of fidelity. The term does not replace those controls. It helps locate where authority is produced, lost, inferred, displaced or retained inside the path from source to answer.
Operational examples
A practical audit can use Defined authority in three situations. First, when comparing a canonical page with an AI answer that reuses the vocabulary but changes the governing perimeter. Second, when deciding whether a generated formulation should be accepted as a stable representation or treated as an ungoverned reconstruction. Third, when mapping internal links, service pages, definitions and observations so that the most authoritative route remains visible to both humans and machines.
The term should therefore be tested against concrete outputs, not only defined abstractly. A useful review asks: which source governed the statement, which inference was made, what uncertainty was hidden, and which page should be responsible for the final wording? If the answer to those questions is unclear, the output should be qualified, redirected, logged or refused rather than smoothed into a stronger claim.
Practical boundary
This definition does not create an automatic ranking, citation or recommendation effect. Its value is architectural: it gives the corpus a sharper way to name and test a specific interpretive control point. That sharper naming is what allows later audits, correction cycles and SERP routing decisions to remain consistent.