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
- 02Response authorizationQ-Layer: response legitimacy
- 03Evidence artifactclaims.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.
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.
claims.json
/claims.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.
Contextual relation
A contextual relation is a bounded link between an entity and an external condition that becomes material to interpretation: time, place, audience, use, availability, event, dependency, compatibility, regulation or constraint.
The relation must not be confused with an intrinsic property. It describes how the entity stands relative to something under a defined scope.
Minimum components
A contextual relation should declare or make reconstructible:
- the source entity;
- the related object or condition;
- relation type;
- competent source;
- observation date;
- temporal, spatial, functional or population scope;
- uncertainty level;
- expiry or reversal condition;
- authorized interpretive use.
Example:
hotel → located 600 m from → station SThis relation is not enough to conclude that the hotel is practical. Destination, schedule, station accessibility, service status and traveller constraints still matter.
Relation classes
Contextual relations may be:
- spatial: distance, zone, geographic accessibility;
- temporal: opening, closure, availability, seasonality;
- functional: compatibility with a use or capability;
- population-based: fit under an explicitly declared audience constraint;
- regulatory: admissibility under jurisdiction or status;
- event-based: dependency on a temporary event;
- comparative: relative position under a bounded criterion and symmetrical data.
Authority and freshness
The entity’s official source is not necessarily competent for every relation. It may declare its amenities but cannot alone impose an assessment of the neighbourhood, traffic or competitor quality.
Each relation must follow the appropriate authority scope. The more volatile the relation, the greater the freshness requirement.
Frequent drift
A relation becomes problematic when it is:
- detached from its date;
- generalized to all audiences;
- turned into a permanent property;
- used as proof of global superiority;
- retained after its condition expires;
- reconstructed by plausibility when data is missing.
The clarification intrinsic attribute vs contextual relation protects this boundary. In interpretive conditioning, the relation supplies the material for variation but does not by itself authorize recommendation. A governed relation must remain inspectable as a relation: its endpoints, scope, source, date and reversal conditions should survive downstream reformulation.