DOSSIERSSYSTEMIC-ALIGNMENT-SCORING
github.com/glassmetric-public

Multidimensional Alignment & Divergence Model

mathematical divergence modeling of behavioral coherence

Published: 2026-06-20  |  Project: Glassmetric  |  Discipline: Sovereign Architecture & Systems Design

Author: Nicholas Alexander MacAskill — Founder & CTO, Flocano Labs  |  Canonical: https://www.nicholasmacaskill.com/dossier/systemic-alignment-scoring

divergence penalty threshold
15.0 std_dev
Verified Invariant
alignment score refresh rate
realtime
Verified Invariant
domain dimension weight
nervous_system: 0.40 // others: 0.20
Verified Invariant

Systemic Coherence Math

Traditional analytics evaluate software metrics and human execution in silos. Glassmetric models the human operator as the Biological CPU coupled with autonomous execution machines. The engine calculates an overall alignment index that measures systemic coherence across domains relative to their variance. High execution volume paired with elevated operator nervous system congestion triggers a "Misalignment" penalty, enforcing automated cooldowns on trading fleets.

Scoring Algorithm Implementation

The four core pillars (Nervous System, Quant Fleets, Prediction CLOB, Sovereign Truth) calculate normalized scores scaled to [0, 100]. The overall System Score is weighted toward the Biological CPU:

$System Score = 0.40 · N + 0.20 · Q + 0.20 · P + 0.20 · S$

The Glass Alignment score calculates the standard deviation across these domains, applying an exponential penalty multiplier if divergence spikes:

TYPESCRIPTPRODUCTION RUNTIME
export function calculateGlassAlignment(
    scores: DomainScores
): { score: number; label: string; divergence: number } {
    const values = [scores.nervous_system, scores.quant_fleets, scores.prediction_clob, scores.sovereign_truth];
    const mean = values.reduce((a, b) => a + b, 0) / values.length;

    // Standard Deviation as proxy for "Misalignment"
    const variance = values.reduce((a, b) => a + Math.pow(b - mean, 2), 0) / values.length;
    const stdDev = Math.sqrt(variance);

    // Alignment Penalty: penalize divergence > 15
    const penalty = Math.min(1, stdDev / 30);

    // Glass Metric = Pure Average * (1 - Penalty)
    const glassScore = Math.round(Math.max(0, mean * (1 - penalty * 0.5)));

    let label = "CALIBRATING";
    if (stdDev < 5) label = "PERFECTLY ALIGNED";
    else if (stdDev < 10) label = "HIGH COHERENCE";
    else if (stdDev < 15) label = "STABLE";
    else if (stdDev < 25) label = "MISALIGNED";
    else label = "FRACTURED";

    return { score: glassScore, label, divergence: Math.round(stdDev) };
}
SIGNAL_DETECTED:"system online // first dossier lesson logged"//TARGET:sovereign layer////////////////////////
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