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 artifactinterpretive-integrity.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.
interpretive-integrity.json
/interpretive-integrity.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.
Interpretive conditioning
Interpretive conditioning is the operation through which an entity representation is adapted to explicit context without allowing that context to rewrite material facts about the entity, erase exclusions or extend a conclusion beyond available evidence.
Its minimal form is:
R(E | C)E is the entity, C is the context and R(E | C) is the representation produced under that context.
Interpretive conditioning does not require every answer to be identical. It requires differences to be attributable to real context dimensions while the invariant core remains compatible across outputs.
Constituent elements
A complete operation should identify:
- the correctly resolved entity;
- entity invariants;
- the context profile being used;
- the contextual relations being mobilized;
- the source and freshness of every material relation;
- conditions that could reverse the conclusion;
- the authorized output mode;
- uncertainties or missing data.
Context may include intent, place, date, audience, constraint, use mode or a set of criteria. It must remain explicit enough for the resulting variation to be explained, contested and re-observed.
Example
A hotel may be represented as practical for a car-free stay when planned destinations are reachable by public transit at the declared times. The same hotel may be less practical for travel requiring long-term parking.
The conclusions differ, but hotel identity, address, amenities and policies must not change. Variation concerns fit between entity and context, not the entity itself.
Boundaries
Interpretive conditioning is not:
- permission to personalize facts;
- proof that one option is better than all others;
- recommendation without a comparison set;
- self-certification by an official source;
- a pretext for inventing missing data;
- authorization for dynamic composition in the current runtime.
When context is insufficient, a legitimate output may be clarification, a weaker formulation or abstention.
Relation to existing layers
The Causal Context Layer explains why a situation creates a need. The Situational Applicability Layer declares when a capability may become mobilizable. Interpretive conditioning then governs how facts and relations are transformed into a situated representation.
The Interpretive Conditioning Layer publishes the doctrinal rule. The interpretive conditioning matrix prepares variables and the contextual fidelity protocol measures outputs.