WEO Methodology Rationale: Empirical Derivation and Calibration Justification for AI Infrastructure Coordination Analysis
Engine Warmth · Zenodo (CERN European Organization for Nuclear Research) · 2026
Companion document to the WEO Methodology Manual providing empirical derivation, theoretical grounding, and calibration justification for all methodology components used in tracking AI infrastructure coordination dynamics. The methodology achieves approximately 70-75% empirical grounding with 25-30% category creator calibration. This document classifies each component across six categories: Empirically Grounded (direct external precedent), Adapted (modified from established methodology), WEO Synthesis (novel combination of precedents), WEO-Original (genuine novel contribution), Category Creator (novel calibration for new domain), and Standard Practice (industry convention). Key derivations documented include: source quality hierarchy from ICD 203/206, Reuters, and EFCSN precedent; claim verification tiers adapted from UK PHIA probability/confidence frameworks; Basel 5-Factor Assessment calibration including $500M and 5,000+ GPU thresholds; Keohane coordination criteria operationalisation; Finnemore & Sikkink 33% norm adoption threshold; PISA-5 framework design including J-Tier jurisdictional classification; three-tier architecture rationale; and the seven-type Coordination Connection taxonomy with novelty verification across 25+ platforms. All category creator components are flagged with validation commitments at designated milestones (100-event threshold). The methodology represents current best practice for this emerging domain, subject to refinement as empirical data accumulates. This document can be read independently but is designed as a companion to the Methodology Manual. January 2026