Signal Alignment (P)

1. Canonical Definition

Signal Alignment (P) is the degree to which actions, communications, cues, and decisions consistently correspond to verified information. It measures whether signals preserve truth fidelity (T) as they move through roles, channels, and structures. Within Meaning System Science, P is the behavioral variable that determines whether meaning transitions reliably from accuracy into coordinated action.

2. Featured Lineage: Foundational Thinkers

Herbert Simon — Administrative Behavior (1947)
Showed that decisions depend on how information is signaled and filtered through organizational structures; MSS extends this by treating signal alignment as the structural link between verified information and operational behavior.

Erving Goffman — Frame Analysis (1974)
Demonstrated that people act based on the interpretive frames indicated by signals, not raw information alone; MSS incorporates this by defining P as the variable governing whether signals produce consistent interpretation across contexts.

3. Plainly

Signal Alignment means that messages, cues, and behaviors match what is actually true.

• High P = all channels reinforce the same verified conditions.

• Low P = different signals indicate different conditions, producing inconsistent interpretation.

4. Scientific Role in Meaning System Science

P connects truth fidelity (T) to operational behavior. It determines:

• whether accurate information becomes accurate action,

• whether signals distort as they move through the system, and

• whether interpretation remains consistent across roles and contexts.

Signal alignment is essential because it links the semantic and structural dimensions of meaning.

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

• T — Truth Fidelity: Signals must reflect verified truth to maintain accuracy.

• P — Signal Alignment: Defines consistency across channels and roles.

• C — Structural Coherence: Structure influences whether signals propagate predictably.

• D — Drift: Misaligned signals increase contradiction and raise the drift rate.

• A — Affective Regulation: Regulation affects how signals are interpreted or prioritized.

6. Relationship to the First Law of Moral Proportion

L = (T × P × C) / D

P is one of the system’s stabilizing forces.

• High P increases legitimacy when aligned with T and C.

• Low P reduces legitimacy by increasing contradiction relative to verified information.

Signal misalignment reduces proportional stability even when T or C remain strong.

7. Application in Transformation Science

Transformation Science uses P to analyze:

• how inconsistencies propagate across systems,

• why identical information leads to divergent interpretations across roles,

• how policies or strategies become non-coherent when signals vary by context, and

• how small signal deviations accelerate drift (D).

P is an early indicator of system-wide interpretive inconsistency.

8. Application in Transformation Management

Practitioners assess P through:

• decision consistency,

• communication pathways,

• leadership signals, and

• role and authority cues.

High P is required for coordinated action, stable expectations, and reliable execution during transformation.

9. Example Failure Modes

• Formal communication and actual behavior signal different priorities, lowering P.

• Teams receive inconsistent cues across channels, increasing D.

• Signals reference outdated or incorrect truth conditions.

• Structural pathways amplify or filter signals unevenly, creating divergent interpretations.

10. Canonical Cross-References

Meaning System Science • Physics of Becoming • First Law of Moral Proportion • Truth Fidelity (T) • Structural Coherence (C) • Drift (D) • Affective Regulation (A) • Semantics • Semeiology • 3E Standard™ • LDP-1.0 • Transformation Management