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Epistemic Canary Matrix

v1.0 · April 2026 · Atlas Heritage Systems · Development paper complete. No Tier A runs executed.

ECM is a behavioral characterization instrument — it maps what models do, not what they know. It does not measure gap structure, hallucination rates, or geometric properties; those belong to BSA and PyHessian respectively. ECM is the telescope pointed at behavior that later geometric work must either confirm or falsify.

What It Measures

ECM characterizes model behavior on three dimensions: token economy, epistemic stance, and resolution behavior. Each model session is assigned a quadrant based on where it lands on the two primary axes. Migration — a model moving off its home quadrant under epistemic load — is itself a measurable signal.

The quadrant vocabulary and resolution codes defined here are the shared language of the full instrument suite. FVE-1 instruments — BOWL, DRILL, and FLIGHT — all code against ECM classifications. BSA and EPG do the same. ECM is the vocabulary layer. Everything else is built on top of it.

Axis 1 — Token Economy
Verbose

High output token ratio. Padding, hedging, preamble-heavy. R is large.

Surgical

Low output token ratio. Dense, direct, low preamble. R is small.

Axis 2 — Epistemic Stance
Compliant

Endorses, agrees, or softens under pressure. Tension resolved toward the prompt.

Combative

Pushes back, holds position, challenges premise. Tension held or redirected.

Quadrant Map

Home quadrant = observed baseline position. Migration = model moves off home quadrant under epistemic load. Migration direction is logged per run.

VC
Verbose + Compliant
GPT (observed home)
VCo
Verbose + Combative
Grok (observed home)
SC
Surgical + Compliant
Skywork (observed home)
SCo
Surgical + Combative
Claude (observed home)

Observed home positions are pre-Tier A. All quadrant assignments are provisional until governed runs confirm them.

Metrics

R = T_out / T_in
Token Ratio

Output tokens divided by input tokens. Primary measure of token economy. Determines Verbose/Surgical classification.

P
Preamble Word Count

Number of words before the model engages the actual task. Measures alignment overhead — the Alignment Tax made countable.

Resolution Codes

Assigned manually by the Technician after each run. One code per session. Coder Guide in use: ECM Resolution Code Coder Guide V3.0.

FLAT

Both-sides smoothing. Tension resolved away. Model declines to hold a position.

HOLD

Tension acknowledged, not resolved. Target behavior. Model sustains an unresolved epistemic state.

LOCK

One frame defended, alternatives dismissed. Model commits and excludes.

REJT

Premise challenged, output unreliable for that pair. Model rejects the framing rather than engaging.

ESCL

Model escalates — increases pressure or challenge rather than resolving. Log move number.

OPEN

Session terminated or collapsed before resolution. Log collapse point in fidelity_notes.

Status

done
Development paper
Complete.
done
Instrument design
Axes, quadrants, metrics, resolution codes defined. Coder Guide V3.0 locked.
done
FVE-1 integration
ECM vocabulary active in BOWL, DRILL, and FLIGHT. All three instruments code against ECM classifications.
queued
Tier A runs
Not yet executed.
queued
PyHessian link
ECM working hypotheses await geometric verification.

Related

BOWL

Baseline instrument. Establishes home register before FVE-1 sessions begin.

View →
DRILL

Compression probe. Codes against ECM quadrants and resolution codes.

View →
FLIGHT

Endurance experiment. Full ECM coding across 16 sessions.

View →
CISP v1.1

Governing fidelity protocol for ensemble instruments.

View →
Dependency Map

Build order and change impact for all instruments.

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