Phenomena should not only be observed; they must be classified. Classification is what turns a corpus of drift into a governable taxonomy.
Operational definition
This second phenomena matrix classifies interpretive drifts by dominant layer. Unlike a simple symptom inventory, it assigns each phenomenon to the structural layer where it primarily operates, even when secondary effects appear elsewhere.
Why dominant-layer classification matters
Many phenomena spill across several surfaces at once. Yet operational action requires a dominant entry point. A layer-based taxonomy keeps diagnosis tractable, reduces overlap between categories, and clarifies which map or doctrinal principle should take priority.
Layers used for classification
- Structural layer: page architecture, entity modeling, and internal coherence.
- Offer layer: services, capabilities, variants, and perimeter.
- Identity layer: person, organization, role, and relationship boundaries.
- Authority layer: source hierarchy, reputation, and arbitration.
- Temporal layer: validity, obsolescence, transition, and versioning.
Classification rules
- Assign one dominant layer even when a phenomenon has several consequences.
- Use secondary tags only after the primary layer has been established.
- Prioritize the layer that changes the corrective logic most strongly.
- Keep classification stable across examples and sectors.
- Revise the taxonomy only when a phenomenon truly escapes the existing layers.
What this matrix prevents
- Taxonomies that grow by accumulation without internal discipline.
- Multiple categories claiming the same phenomenon for different reasons.
- Corrective ambiguity caused by weak classification.
- Diagnostic inflation driven by semantic overlap rather than real novelty.
