Thermodynamics (Meaning-System)

1. Canonical Definition

Thermodynamics (Meaning-System) is the scientific domain that studies load, dissipation, and capacity in meaning-systems. Within Meaning System Science, it defines drift (D) as a rate condition by specifying when inconsistency accumulates faster than verification, alignment, and structural pathways can integrate correction.

2. Featured Lineage

Claude Shannon — A Mathematical Theory of Communication (1948)
Modeled reliability under noise and load; MSS extends this by treating drift as the rate of inconsistency accumulation under constrained correction throughput.

Ilya Prigogine — Order Out of Chaos (1984)
Showed how systems reorganize under sustained disequilibrium; MSS adapts this by modeling non-stable interpretive states when inconsistency accumulation exceeds correction capacity.

3. Plainly

Thermodynamics explains why interpretation becomes more difficult as volume, variability, or pace increases. When correction cannot keep pace with accumulating inconsistency, drift (D) rises.

4. Scientific Role in Meaning System Science

Thermodynamics provides the load–capacity basis for Drift (D). It specifies:

• how inconsistency accumulates under constraint

• how correction throughput limits stability

• how sustained load changes drift-rate behavior

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

• T — Truth Fidelity: High load reduces verification throughput and update consistency.

• P — Signal Alignment: Channel volume and variability increase misalignment risk.

• C — Structural Coherence: Throughput limits and routing inconsistency increase cross-zone mismatch.

• D — Drift: Thermodynamics defines D as the rate of accumulated inconsistency under constraint.

• A — Affective Regulation: Regulatory limits constrain correction capacity and influence drift-rate acceleration.

6. Relationship to the Physics of Becoming

L = (T × P × C) / D

Thermodynamics specifies the denominator behavior. As drift rate (D) increases, legitimacy (L) decreases when stabilizers cannot scale proportionately with load.

7. Application in Transformation Science

Transformation Science uses meaning-system thermodynamics to model drift-rate changes, identify when correction throughput is insufficient, and anticipate when structural reconfiguration is required for stability.

8. Application in Transformation Management

Practitioners use thermodynamic analysis to:

• evaluate interpretive load relative to capacity

• identify where inconsistency enters and accumulates

• design pacing and sequencing that preserves correction throughput

• adjust workload, governance cadence, and update routines

9. Example Failure Modes

• Volume increases faster than verification throughput, reducing T and increasing D.

• Signals multiply across channels without equivalence rules, reducing P.

• Routing sequences vary under time pressure, reducing C.

• Correction and closure cadence does not match accumulation rate, raising D.

10. Canonical Cross-References

Meaning System Science • Physics of Becoming • First Law of Moral Proportion • Drift (D) • Truth Fidelity (T) • Signal Alignment (P) • Structural Coherence (C) • Affective Regulation (A) • Constraint Failure • Closure Failure • Drift Catalysts (β₆) • Coherence Regulators (γ₆) • Interface • LDP-1.0 • 3E Standard™ • Transformation Management