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
health: 0.40 // others: 0.20
Verified Invariant

Systemic Coherence Math

Traditional trackers analyze metrics in silos (e.g., viewing trading drawdowns independently of sleep metrics). Glassmetric treats the user as a coupled dynamical system. The engine calculates an overall alignment index that measures performance across domains relative to their variance. High execution metrics (e.g., trading success) paired with low biometrics (e.g., poor sleep and low HRV) trigger a "Misalignment" or "Fractured" state penalty, warning of potential performance crashes.

Scoring Algorithm Implementation

Individual domains (Health, Trading, Betting, Social) calculate normalized scores scaled to [0, 100]. The overall System Score is weighted in favor of Health as the underlying biological state layer:

$System Score = 0.40 · H + 0.20 · T + 0.20 · B + 0.20 · S$

The Glass Alignment score then computes the standard deviation of these domains, applying a penalty multiplier if the deviation is large:

TYPESCRIPTPRODUCTION RUNTIME
export function calculateGlassAlignment(
    scores: DomainScores
): { score: number; label: string; divergence: number } {
    const values = [scores.health, scores.trading, scores.betting, scores.social];
    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: heavily penalize divergence > 15
    const penalty = Math.min(1, stdDev / 30);

    // Glass Metric = Pure Average * (1 - Penalty)
    // If you are high performing (90) but erratic (stdDev 20), score drops to ~65
    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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