Meaning System Science

1. Canonical Definition

Meaning System Science (MSS) is the scientific study of the conditions under which binding meaning production remains reliable within and across meaning systems.

MSS does not define the content of meaning. It defines the variable architecture of Truth Fidelity (T), Signal Alignment (P), Structural Coherence (C), Drift (D), and Affective Regulation (A), and specifies how proportional relationships among these variables condition whether meaning remains interpretable, correctable, and action-relevant across interpreters, environments, and time.

Meaning, in MSS, is treated as an event-level outcome produced through interpretation when an interpretation becomes binding for action. MSS governs the reliability of that production, not the semantic or moral content of meanings themselves.

2. Featured Lineage

Claude Shannon — A Mathematical Theory of Communication (1948)
Formalized information transmission under noise and constraint. MSS extends this work by treating interpretive instability as a structural and rate-based phenomenon rather than a transmission error alone, and by defining drift as a measurable accumulation condition.

Niklas Luhmann — Social Systems (1984)
Modeled communication as a system governed by internal constraints and complexity reduction. MSS builds on this foundation by specifying a variable architecture that conditions whether communication remains interpretable and coordinative across roles, contexts, and time.

3. Plainly

Meaning System Science explains why meaning remains compatible in some systems and incompatible in others.

It identifies the measurable conditions that determine whether interpretation can remain reliable under uncertainty, scale, and change.

4. Scientific Role in Meaning System Science

MSS establishes:

• the five governing variables (T, P, C, D, A)

• proportional conditions required for interpretive stability

• drift as a rate condition and the dynamics that increase or reduce it

When binding meaning persists after closure, its authorization status and re-activation thresholds are treated under post-closure meaning regimes (PCMR/DMR) and Action Determinacy Loss (ADL), not within MSS itself. Together, these provide the basis for diagnosis, modeling, and governance of meaning systems under constraint.

MSS treats meaning systems as analyzable objects whose interpretive reliability can be compared across domains, scales, and transformation sequences.

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

Interpretive reliability within a meaning system is conditioned by the proportional interaction of five variables:

• (T) Truth Fidelity: correspondence and verification discipline relative to declared reference conditions

• (P) Signal Alignment: convergence of signals across roles, authorities, and channels

• (C) Structural Coherence: availability of usable pathways that distribute meaning consistently

• (D) Drift: rate of accumulated unresolved inconsistency under load

• (A)Affective Regulation: regulation conditions determining update capacity and correction throughput under pressure

No single variable determines reliability in isolation. MSS evaluates proportional stability, not individual factor strength.

6. Relationship to the General Theory of Interpretation

Meaning System Science operates within the General Theory of Interpretation (GTOI).

GTOI establishes interpretation as a law-governed, system-level process and specifies the invariants required for interpretive stability across interpreters, environments, and time. MSS provides the formal operational layer that makes those invariants measurable, diagnosable, and governable in practice.

Within this relationship:

• GTOI defines the scope and constraints of interpretation as a general phenomenon.

• MSS specifies the variable architecture through which interpretive reliability is conditioned inside meaning systems.

• GTOI states what must hold for interpretation to remain stable at scale.

• MSS explains how those conditions vary, interact, and fail under load.

MSS does not compete with or revise GTOI. It implements the theory by translating general interpretive constraints into a proportional science suitable for empirical analysis and institutional governance.

7. Relationship to the Physics of Becoming

L = (T × P × C) ÷ D

MSS supplies the variables used in the First Law of Moral Proportion and defines drift as a rate condition. The Physics of Becoming formalizes how proportional instability accumulates over time and how legitimacy emerges or degrades as a function of system dynamics.

Legitimacy (L) is treated as a system-level output, not a psychological or moral attribute.

8. Application in Transformation Science

Transformation Science uses MSS to model variable movement over time, identify proportional imbalance, quantify rising drift rates, and locate where topology and coupling concentrate instability during change attempts.

MSS provides the analytic substrate that allows transformation claims to be evaluated for structural admissibility rather than narrative coherence.

9. Application in Transformation Management

Practitioners apply MSS to design decision environments and governance controls that preserve interpretive stability, particularly across interfaces and AI-mediated workflows where drift accelerates and correction pathways are fragile.

Intervention targets system conditions, not interpretive content or individual behavior.

10. Example Failure Modes

• roles interpret the same conditions differently because stabilizers are not proportionate

• binding outcomes diverge across roles or channels, producing incompatible routed actions from the same declared reference conditions

• drift rate rises faster than correction capacity

• pathways cannot distribute meaning consistently under current load

• verification and traceability are insufficient for declared baselines

11. Canonical Cross References

General Theory of Interpretation • Interpretation • Meaning • Meaning System • Interpretive Event • Physics of Becoming • First Law of Moral Proportion • Proportionism • Legitimacy (L) • Truth Fidelity (T) • Signal Alignment (P) • Structural Coherence (C) • Drift (D) • Affective Regulation (A) • Semantics • Semeiology • Systems Theory • Thermodynamics (Meaning System) • Affective Science • Interface • Transformation Science • Transformation Management • Meaning System Governance