Coherence Regulators (γ₆)

1. Canonical Definition

Coherence Regulators (γ₆) are structural conditions and corrective practices that sustain proportional stability by reducing drift rate pressure and supporting the operational use of stabilizers. In Meaning System Science, γ₆ names the stabilizing forces that strengthen truth fidelity (T), signal alignment (P), and structural coherence (C) as a system operates under load, including enforceable constraints, transferable closure routines, and interface governance that prevents drift import.

2. Featured Lineage

Amy Edmondson — The Fearless Organization (2019)
Showed that correction depends on the ability to surface error and contradiction without penalty. MSS incorporates this as a regulator condition that increases correction throughput and reduces inconsistency accumulation.

Chris Argyris — Organizational Learning (1978)
Showed how reflective practices detect and resolve underlying inconsistencies. MSS extends this by treating double loop learning as a regulator that sustains alignment and coherence under change.

3. Plainly

Coherence Regulators are the conditions that help a system correct itself in time. When regulators are strong, contradictions are surfaced, tested, and resolved before they become durable.

4. Scientific Role in Meaning System Science

γ₆ provides a named class for analyzing why some systems maintain stable interpretation under variation while others accumulate unresolved inconsistency. It supports diagnosis by identifying which stabilizing routines and boundary controls preserve comparability and correction throughput across roles and interfaces.

5. Relationship to the Variables (T, P, C, D, A)

• T: Verification routines and evidence discipline keep reference conditions reconstructable.

• P: Signal governance reduces competing interpretations of authority and action weight.

• C: Stable pathways and ownership rules support consistent routing and integration.

• D: Correction and closure throughput slows inconsistency accumulation.

• A: Regulation conditions preserve evaluative bandwidth and reduce correction avoidance.

6. Relationship to the Physics of Becoming

L = (T × P × C) / D

γ₆ supports the law by reducing D pressure and sustaining the operational strength of T, P, and C. Strong regulators keep proportional relationships viable under demand.

7. Application in Transformation Science

Transformation Science uses γ₆ to model resilience, to explain why certain system designs stabilize after change, and to identify regulator patterns that preserve proportional stability across time and varying conditions.

8. Application in Transformation Management

Practitioners strengthen γ₆ by stabilizing definitions, standardizing evidence thresholds, clarifying decision rights, enforcing constraints, naming closure points, and governing interfaces so resolution outcomes remain transferable across systems.

9. Example Failure Modes

• Governance cadence is irregular, so contradictions remain unadjudicated.

• Key terms vary by team, reducing comparability of reports and decisions.

• Decision rights are ambiguous, producing inconsistent routing and ownership.

• Closure routines are missing or not transferable across interfaces, enabling recurrence.

10. Canonical Cross References

Meaning-System • Interpretation • Meaning System Science • Physics of Becoming • First Law of Moral Proportion • Legitimacy (L) • Truth Fidelity (T) • Signal Alignment (P) • Structural Coherence (C) • Drift (D) • Affective Regulation (A) • Interface • Coupling • Meaning Topology • Drift Catalysts (β₆) • Constraint Failure • Closure Failure • Meaning-System Governance • Transformation Science • Transformation Management • LDP-1.0 • 3E Standard™