Skip to content

Clarification

Semantic proximity vs causal relevance

Clarification separating resemblance in meaning from need-based relation in interpretive governance.

CollectionClarification
TypeClarification
Version0.1-proposed
Stabilization2026-07-06
Published2026-07-06
Updated2026-07-06

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.

  1. 01
    Canon and scopeDefinitions canon
  2. 02
    Response authorizationQ-Layer: response legitimacy
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.

Clarification

Semantic proximity answers a neighborhood question: do two elements resemble each other in meaning-space?

Causal relevance answers a need question: does one explain why the other becomes useful, required or prioritary in a given situation?

These two relations may coexist, but they do not replace one another.

Typical wrong inference

A system may bring “website redesign” and “SEO audit” close together because both notions appear in the same lexical field. That proximity does not yet authorize saying that an audit is required, sold, guaranteed or sufficient.

The admissible causal relation must be declared more precisely: a redesign may create organic-loss risk, that risk may reveal a diagnostic need, and that diagnostic may make an audit relevant. The chain remains conditional and non-promissory.

CCL rule

CCL does not measure proximity. It governs declared causality. A future proximity layer may help detect dangerous neighbors, but it must not absorb CCL.