1. Short Definition

U4 Classification Scaling Rule means that classifications valid at one scale, load, or context cannot be assumed valid after scale changes.

U4 claims require U5/U6/U7 validation before being treated as structurally true.

2. Canonical Pattern

U4 claim ≠ U6 truth without U5/U7 validation

Expanded:

classification / metric / label / ranking / claim
+
scale change
⇒ validation required across timing, field coherence, and recurrence

Plain form:

Labels must be revalidated when scale changes.

3. Mechanic Description

SCALE-067 applies scaling directly to U4, the classification layer.

U4 includes:

• labels
• metrics
• categories
• rankings
• claims
• diagnoses
• dashboards
• benchmarks
• compliance classes
• risk classes
• safety labels
• legal categories
• identity-bound classifications
• institutional determinations
• AI outputs framed as truth

Classification is necessary for action.

But classifications can degrade under scale because scale changes the context in which the classification operates.

A category that worked at low load may fail at high load.

A metric that worked locally may fail globally.

A risk label that worked in one environment may misfire in another.

A benchmark that measured one capability may be gamed at deployment scale.

A diagnosis that names a symptom may not explain the system-level origin.

A legal category may fail under new technological or social conditions.

The core rule is that U4 classification is provisional until validated through:

• U5 timing and delay
• U6 whole-system coherence effects
• U7 recurrence behavior
• perturbation testing
• hidden debt tracking
• affected-node outcomes

U4 is powerful because classifications steer action.

Therefore scaled classification must remain auditable, reversible, contestable, and repairable.

4. UTS Variable Mapping

5. Diagnostic Questions

1. What classification is being scaled?
2. Was it validated only locally?
3. Does the classification still work under higher load?
4. Is the metric becoming the target?
5. Are edge cases increasing?
6. Is the classification auditable?
7. Can affected nodes appeal or correct it?
8. Does the label preserve or harm meaning integrity?
9. Does recurrence decrease after the classification is used?
10. Has the U4 claim been validated at U5/U6/U7?

6. Failure Signatures

1. U4 Overclaim

classification asserted as truth without U6/U7 validation

The system treats a label as reality before validation.

2. Metric Drift

metric validity↓ under scale while Φ_metric↑

The metric gains influence as it loses target fidelity.

3. Identity-Binding Misclassification

low-resolution label + identity consequence ⇒ H↑

A rough classification produces durable harm.

4. Recurrence After Classification

classification applied while τ_m↑

The classification does not reduce the repeating pattern.

5. Appeal Failure

classification consequence↑ + correction access↓

Affected nodes cannot repair wrong labels.

7. Related Failure Modes

• classification scaling failure
• misclassification
• metric drift
• U4 overclaim
• identity-binding error
• proxy capture
• appeal collapse
• bad routing
• AI classification failure
• legal category failure
• medical mismatch
• hidden debt accumulation

8. Related Diagnostics

9. Restoration Implications

If SCALE-067 is active, restoration requires classification revalidation and correction pathways.

Required actions:

1. Identify classifications operating at scale.
2. Revalidate metrics, labels, and categories under current conditions.
3. Check U5 timing effects, U6 field effects, and U7 recurrence.
4. Increase category resolution where consequences are high.
5. Preserve appeal and correction pathways.
6. Make classifications reversible where possible.
7. Audit identity-binding labels with higher rigor.
8. Reduce metric pressure where proxy capture appears.
9. Repair harms caused by wrong classifications.
10. Time-validate classification changes before canonizing them.

Core restoration rule:

No U4 classification becomes canon without U6/U7 validation.

10. Compact Registry Entry

id: SCALE-067
name: "U4 Classification Scaling Rule"
family: "SCALE-L — U-Layer Scaling Mechanics"
type: "classification-truth-validation-scaling-constraint"
status: "draft-ready"
short_definition: "Classifications valid at one scale, load, or context cannot be assumed valid after scale changes."
canonical_pattern: "U4 claim ≠ U6 truth without U5/U7 validation"
failure_signature: "classification/metric/label/ranking/claim + scale change ⇒ validation required across timing, field coherence, and recurrence"
primary_variables:
  - O
  - H
  - ε
  - ι
  - Au
  - µᵢ
  - BΣ
  - K
  - R
  - Φ
primary_diagnostics:
  - Γ_accuracy
  - Γ_resolution
  - U4_claim_strength
  - U6_validation_status
  - τ_m
  - appeal_access_ratio
  - edge_case_density
  - Au_classification
  - Φ_metric
  - affected_node_cost
related_failure_modes:
  - classification_scaling_failure
  - misclassification
  - metric_drift
  - U4_overclaim
  - identity_binding_error
  - proxy_capture
  - appeal_collapse
  - bad_routing
  - ai_classification_failure
  - hidden_debt_accumulation
restoration_implication: "Revalidate classifications under scale, test U5/U6/U7 effects, preserve appeal and reversibility, increase category resolution, and repair harms caused by wrong labels."

11. One-Line Canon

A label that worked at one scale must prove itself again when scale changes.