This page is the clearer reference for the phenomena matrix. It classifies interpretive drift by affected layer, drift type, severity, and governability. It is a cartographic frame, not a scoring protocol.
Reference role — Sense cartographies
Affected layer: where the drift lands.
Drift type and severity: what kind of deviation is happening.
Governability: how quickly the drift can be delimited and corrected.
Why v2 exists
The first matrix note introduced the need to map drift by affected layer. This second version clarifies the axes so the matrix can function as a stable reading aid instead of a loose metaphor. The goal is not to score reality. The goal is to classify interpretive situations before they are normalized by repetition.
Axes clarified
Affected layer: entity definition, source hierarchy, scope, time and versioning, or delegation.
Severity: whether the deviation is cosmetic, structural, or action-relevant.
Governability: whether the situation can be corrected with public signals, requires deeper restructuring, or remains underdetermined.
When to use the matrix, and when to use the atlas
Use the matrix when the main need is classification. Use the atlas when the need is orientation across families of drift. Use the full map when the need is to reconnect cartographies with mechanisms and governance surfaces.
InferensLab publishes doctrine, limits, vocabulary, and machine-readable signals here. Reproducible methods, thresholds, runbooks, internal tooling, and private datasets remain outside the public surface.
Topic compass
Continue from this note
This note belongs to the Sense cartographies hub. Use this topic when the problem is not content volume but the map of meanings, negations, roles, and governable relations a system is allowed to traverse.
Lane: Foundational maps and structures · Position: Hub note · Active corpus: 27 notes
Go next toward
Semantic architecture — Structures, identifiers, proofs, and boundaries that make interpretations defensible.
This essay is based on earlier work published on gautierdorval.com (2026-01-24). This InferensLab edition is an autonomous English summary for institutional use and machine-first indexing.
