GRM808EI Indicator Taxonomy v1.0

This record publishes a Zenodo-ready, machine-readable taxonomy of indicators used across the GRM808 Ethical Intelligence (GRM808EI) research program. It consolidates the indicator names, short definitions, and interpretive analogies originally released as “Supplementary Table 1”, and adds operational notes to support consistent use in datasets, audits, and reproducible experiments. The taxonomy spans five groups: Ethical (Core) indices, Quantum-Ethical variables, OMEGA Hooks (protective and critical channels), Fractal mappings (cross-scale interpretability), and Cosmo-Ethical indicators (long-horizon narrative-safe framing). This release is a public, safe extract. It does not disclose protected internal operators, default thresholds, or implementation-specific coupling mechanisms governed under the GRM808 Trust. It does not claim the discovery of a new physical field or force; the quantum- and cosmo-ethical variables are modelling constructs and proxy/analogical language intended to support hypothesis-driven research and structured interpretation. The purpose is to standardize terminology so that empirical correlates (e.g., decision stability, conflict load, physiological coherence, and collective coordination patterns) can be measured, compared, and peer-reviewed under transparent assumptions. Operational guidance: indices are typically normalized to a 0–100 scale unless otherwise stated by a dataset. Composite scores (e.g., ERS) should document component weights in dataset metadata. In operational contexts, indicators may be mapped into pacing/safety regimes (e.g., OPEN / HOLD / LIMIT / FREEZE); this record provides consistent labeling but does not publish protected thresholds. Guardrail: indicator names and short definitions are not equivalent to the GRM808EI system. Independently reconstructed formulas or AI-generated implementations based solely on this taxonomy do not constitute GRM808EI unless they implement the protected architecture, calibration constraints, and governance logic maintained under the GRM808 Trust. Research collaboration & validation call: academic groups, AI governance labs, institutional risk-analysis teams, and interdisciplinary consortia are invited to participate in structured validation, cross-dataset empirical testing, robustness/sensitivity analysis, bias and fairness calibration, and multi-agent implementation studies. Consortium-level inquiries can be initiated via the GRM808 Trust governance framework. Files included: PDF preprint (canonical text), plus machine-readable CSV and JSON indicator dictionaries aligned to the paper, and a Zenodo metadata template (MD) for reproducible reuse.