The Legitimacy Diagnostic Protocol (LDP-1.0)

A Structural Diagnostic for Meaning-System Stability

Authors: Jordan Vallejo and the Transformation Management Institute™ Research Group

Status: Technical Monograph D1 | October 2025

Overview

The Legitimacy Diagnostic Protocol (LDP-1.0) measures the interpretive stability of an organizational meaning-system through the four structural variables defined by Meaning System Science:

• T — Truth Fidelity

• P — Signal Alignment

• C — Structural Coherence

• D — Drift (Thermodynamic Misalignment Rate)

Legitimacy (L) is computed using the First Law of Moral Proportion:

L = (T × P × C) ÷ D

All variables are normalized to a 0–1 scale.

L is a stability function.
It indicates how reliably an organization can construct and maintain shared interpretation under real operational load.

LDP evaluates structural proportionality, not sentiment, opinion, personality, or perceived effectiveness.

1. Variable Definitions

Each variable is defined operationally and grounded in observable behavior.
Together, T, P, C, and D represent the structural forces that determine the reliability of interpretation within a meaning-system.

1.1 Truth Fidelity (T)

Definition

Truth Fidelity measures the accuracy, verifiability, and preservation of information as it is encoded, transmitted, and referenced within the organization.

Components

• Accuracy: Information corresponds to observable or validated reality.

• Auditability: Claims and decisions can be traced to verifiable sources.

• Fidelity: Meaning remains consistent as information moves across levels, roles, and contexts.

Measurement

Indicators normalized to 0–1 and combined using a geometric mean.

1.2 Signal Alignment (P)

Definition

Signal Alignment measures the degree to which authority, incentives, and action reinforce verified information as they propagate across environments.

Components

• Alignment: Decisions reflect validated truth.

• Responsiveness: Corrections follow evidence in a timely, complete manner.

• Proportionality: Actions match the scale of evidence, risk, and context.

Measurement

Indicators normalized to 0–1 and combined using a geometric mean.

1.3 Structural Coherence (C)

Definition

Structural Coherence assesses how effectively the organization conducts information, decisions, and corrections without distortion or contradiction.

Components

• Transparency: Information and rationales are accessible and traceable including the visibility of decision rationales and the traceability of interpretive changes.

• Accountability: Roles, boundaries, and correction pathways are understood.

• Trust Conductivity: Upward and lateral information moves without suppression.

• Memory Continuity: Decisions and knowledge persist across turnover and time.

Meaning Topology (Analytical Lens)

Topology describes patterns of information concentration and flow within the structure.
It supplements interpretation of C; it does not introduce a fifth variable.

Measurement

Indicators normalized to 0–1 and combined using a geometric mean.

1.4 Drift (D)

Thermodynamic Misalignment Rate

Definition

Drift (D) is the rate at which stabilizing variables lose proportionality, even in low-pressure conditions. Load accelerates it, but proportional imbalance generates it. Drift originates as an emergent rate: the speed at which the system accumulates unresolved contradictions and inconsistencies. Once present, Drift behaves as a thermodynamic variable of the meaning-system, accelerating destabilization over time.

Drift is a rate, not an event. D = 0 is thermodynamically impossible in active meaning-systems. LDP sets minimal drift at 0.05 for model stability.

Inputs to Drift

LDP assesses Drift through two behavioral sets:

• β₆ — Drift Catalysts (accelerators)

• γ₆ — Coherence Regulators (decelerators)

These do not replace Drift, they quantify observable forces that influence the rate at which drift emerges and grows.

Drift Catalysts (β₆)

Increase the rate of inconsistency accumulation:

1. Overstated Certainty

2. Decision Latency

3. Status-Protective Filtering

4. Incentive Distortion

5. Interpretive Withdrawal

6. Engagement Collapse

Coherence Regulators (γ₆)

Reduce the drift rate:

1. Evidence Responsiveness

2. Corrective Willingness

3. Feedback Quality

4. Safety for Dissent

5. Repair Cadence

6. Participation Renewal

Computation

• Compute β = mean of β₆ indicators

• Compute γ = mean of γ₆ indicators

Operational Drift Index:

D = β ÷ γ
Capped to 0.05 ≤ D ≤ 1.00

This index captures the effective drift rate: how quickly inconsistency accumulates relative to the system’s capacity to correct it.

Affective Regulation (A) — Clarification

A is intentionally excluded from LDP-1.0 to preserve the proportional structure of the First Law. Future versions may integrate affective volatility into correction coefficients.

2. Data Requirements

LDP only uses observable data. All data must reflect system conditions rather than sentiment or preference.

Eligible data sources include:

• audit trails

• decision logs

• correction cycle duration

• process usage patterns

• semantic alignment in documents

• structured interviews

• behaviorally anchored survey items

• participation and escalation metrics

• memory continuity measures

• dissent tracking and follow-up

All indicators are normalized to a 0–1 scale.

3. Normalization Rules

• Percentages → value ÷ 100

• Latency → (Target ÷ Actual), capped at 1 and floored at 0.1 to preserve geometric mean stability.

• Survey items → response ÷ max scale

• Text similarity → semantic similarity (0–1)

• Frequency → Observed ÷ Expected

Composite variables (T, P, C) use geometric means so one strong dimension cannot compensate for a weak one.
Drift uses β and γ as defined above.

4. Legitimacy Computation

Legitimacy (L) is computed as:

L = (T × P × C) ÷ D

L quantifies the proportional balance between stabilizing conditions (T/P/C) and the destabilizing rate (D).
Values are rescaled to 0–10 for interpretation.

5. Interpretation Framework

LDP produces ranges describing interpretive stability:

• 0–3.9 → Critical instability

• 4.0–5.9 → Low stability

• 6.0–7.9 → Functional but strained

• 8.0–10 → High stability

ΔL (shift in legitimacy) and ΔD (shift in drift rate) provide stability trendlines. An L value below 4.0 indicates that drift is accumulating faster than stabilizing variables can compensate.

6. Measurement Cadence

• Quarterly (enterprise-level)

• Pre/mid/post for transformation initiatives

• Annual longitudinal analysis

Typical samples: 30–200 people depending on system size.

7. Data Ethics and Standards

LDP requires:

• transparent methodology

• anonymous, aggregated reporting

• purpose limitation to system improvement

• correction of measurement errors

• peer review of indicator selection

• non-retaliation protections

LDP cannot be used to evaluate individual employees.

8. Output Profile

Each LDP assessment yields:

• T value

• P value

• C value

• D value

• L score

• ΔL and ΔD trends

• Coherence topology summary

• Proportionality matrix (T:P:C:D)

9. Instrument Limitations

LDP measures system proportionality.
It does not:

• predict individual performance

• assess psychological states

• measure moral virtue

• prescribe interventions

It describes the condition of the meaning-system.
Interpretation of results requires the Proportionist stance.

10. Purpose of the Protocol

LDP-1.0 provides a structural diagnostic aligned with:

• Meaning System Science

• The Physics of Becoming

• Transformation Science

• The First Law of Moral Proportion

Its purpose is to quantify interpretive stability using structural data rather than subjective perception, enabling leaders to identify early drift, strengthen coherence, and maintain meaningful execution under complexity.

Citation

Vallejo, J. (2025). Monograph D1: The Legitimacy Diagnostic Protocol (LDP-1.0). TMI Technical Monograph Series. Transformation Management Institute.