Canonical Specification — Governance and Friction Enhancement
This specification operationalizes the CTM Model v1.0.
(FROZEN)

CTM – Process v1.1

PURPOSE AND SCOPE

CTM Process v1.1 introduces the governance and friction layer into the civic-stress pipeline established in v1.0.

Major additions in v1.1:

Formal governance-style modifiers
Four composite metrics capturing governance behavior
Friction metrics and oscillation modeling
Composite Friction Coefficient (CFC)
Updated Load Update step (still feed-forward)
Expanded JSON result schema

v1.1 remains strictly feed-forward with no recursive feedback loops.
All feedback dynamics appear in v1.2.

INHERITED STRUCTURE FROM v1.0

CTM Process v1.1 preserves:

The 8-step pipeline structure
All v1.0 formulas not explicitly modified
All domain definitions
Decay mechanics
Drift (early form)
ShockMemory (early form)
Classification logic
Smoothing
Threshold definitions

Where v1.1 introduces enhancements, they override or extend v1.0 behavior.

CTM consumes upstream signal metrics (e.g., persistence, diversity, load) that are defined and calculated by CT Monitor. CTM does not define or compute these metrics

GOVERNANCE STYLES (NEW)

Each event is interpreted under a governance style, representing systemic behavioral tendencies of the political environment.

Examples include:

Consolidated
Polarized
Fragmented
Bureaucratic
Extractive
Reformist

Each governance style influences stress processing through governance modifiers, described in the next section.

GovernanceStyle may be assigned:

per event
per period
per administration
manually by analyst

GOVERNANCE MODIFIERS (NEW)

Governance styles are operationalized through three direct modifiers applied to stress vectors:

For each stress component j in domain i:

Governance Severity Multiplier

Scales overall stress magnitude.

GovernanceSeverity_i = 1 + GovWeightSeverity * SeverityFactor

Typical range: 0.9 – 1.3

Governance Directional Multiplier

Influences how strongly polarity is expressed.

DirectionalFactor_j = 1 if Polarity_j positive
                     -1 if Polarity_j negative

GovernanceDirection_i =
    1 + GovWeightDirection * DirectionalFactor_j

Governance Volatility Multiplier

Models instability and irregularity.

GovernanceVolatility_i = 1 + GovWeightVolatility * RandomFactor(t)

Where RandomFactor(t) is bounded noise in [-0.1, +0.1].

Combined Governance Modifier

GovMod_i(t) =
    GovernanceSeverity_i
  * GovernanceDirection_i
  * GovernanceVolatility_i

This modifies EffectiveImpact_j(t) in Step 3.

COMPOSITE METRICS (NEW)

Four composites summarize systemic governance behavior.

Each is ∈ [0,1].

All composites are smoothed over time:

CompositeX(t) = λ * rawX(t) + (1 - λ) * CompositeX(t-1)

with λ = 0.5.

Composite Amplification

Measures how strongly governance amplifies existing stress.

Inputs:

Governance severity
Frequency of severe events
Magnitude of directional multipliers

rawAmplification(t) = normalize(Avg(GovernanceSeverity))

Composite Latency

Measures how governance delays or suppresses stress signals.

rawLatency(t) = normalize(Avg(ThresholdDelays))

Higher latency → lower stress responsiveness.

Composite Oscillation Probability

Probability that rapid swings in stress will occur.

Based on:

GovernanceVolatility
Frequency of polarity inversions
Threshold proximity shifts

rawOscProb(t) = normalize(Volatility + PolarityFlipRate)

Composite Stability

Inverse of systemic instability.

rawStability(t) = 1 - rawOscProb(t)

Then smoothed.

FRICTION METRICS AND CFC (NEW)

Friction represents the degree to which governance conflict or institutional contradiction dampens or distorts stress.

Friction Components

Examples:

Interbranch conflict
Administrative bottlenecks
Message contradictions
Policy paralysis
Judicial-legislative disputes

Each contributes a friction component FC_k(t) ∈ [0,1].

Composite Friction Coefficient (CFC)

CFC aggregates all friction components:

CFC_raw(t) = Σ_k w_k * FC_k(t)

Normalized:

CFC(t) = normalize(CFC_raw(t))

Then floored for numerical stability:

CFC(t) = max(CFC(t), ε)

where ε = 0.0001.

CFC is used in Step 4.

UPDATED LOAD UPDATE STEP (STEP 4 in v1.1)

This is the main change from v1.0.

Effective Impact with Governance Modifiers

In v1.1:

EffectiveImpact_j(t) = RawImpact_j
                     * Weight_j
                     * GovMod_i(t)

Load Update with Friction Effects

Load_i(t+1) = Load_i(t) * DecayRate_i(t)
            + StressTerm_i(t) * (1 + CFC(t))

Where:

StressTerm_i(t) = Σ_j EffectiveImpact_j(t)

Notes:

This is still feed-forward
No recursion
No cross-domain coupling
No dependency on future or accumulated feedback

v1.2 introduces feedback; v1.1 does not.

DRIFT, SHOCK MEMORY, CLASSIFICATION (UNCHANGED FROM v1.0)

v1.1 inherits the following unchanged:

Drift formula
ShockMemory formula
Threshold evaluation
System aggregation
Trajectory classification
Smoothing

These behave exactly as defined in v1.0.

JSON RESULT STRUCTURE (v1.1)

v1.1 expands the JSON schema to reflect new governance and friction metrics.

{
  "version": "1.1",
  "event_id": "string",
  "timestamp": "string",
  "governance_style": "string",
  "system": {
    "system_load": "number",
    "system_state": "string",
    "shock_memory": "number",
    "composites": {
      "composite_amplification": "number",
      "composite_latency": "number",
      "composite_osc_prob": "number",
      "composite_stability": "number",
      "cfc": "number"
    }
  },
  "domains": [
    {
      "name": "string",
      "load_t": "number",
      "load_t1": "number",
      "stress": "number",
      "effective_stress": "number",
      "decay_rate": "number",
      "threshold": "number",
      "drift": "number",
      "shock_memory": "number",
      "state": "string"
    }
  ]
}