WEO Methodology Manual: Systematic Tracking of AI Infrastructure Coordination Dynamics Across Geopolitical Blocs

Read full text
Authors: Engine Warmth
Cited by: 4

Abstract

Complete operational methodology for the Warmth Engine Observatory, enabling systematic tracking of AI infrastructure coordination dynamics across geopolitical blocs through verified events and mapped coordination connections. No existing framework systematically documents coordination dynamics at the intersection of technology deployment, geopolitical alignment, and institutional governance. This manual addresses that gap by adapting proven frameworks: Basel Committee G-SIB Methodology (2018) for systemic importance assessment, ICD 203/206 and wire service standards for event verification, Keohane (1984) for coordination definition, and Finnemore & Sikkink (1998) for norm adoption thresholds. The methodology specifies a five-stage processing sequence: (1) Event Verification with gold-standard evidentiary requirements, (2) Significance Assessment via Keohane Pre-Filter, Basel 5-Factor, Route-Based, and PISA-5 frameworks, (3) Tier Classification across coordination scale (T1 Cross-Bloc, T2 Between-Bloc, T3 Intra-Bloc), (4) Domain Classification across Energy/Infrastructure, Security, Technology, and Trade, and (5) Coordination Connection Mapping using a novel seven-type taxonomy with three confidence levels (CC-V, CC-E, CC-A). Original contributions include the seven-type Coordination Connection taxonomy (verified novel via research across 25+ platforms), the PISA-5 significance assessment framework, and the Route-Based qualification structure. The methodology achieves approximately 70-75% empirical grounding with 25-30% category creator calibration. This document can be read independently. Readers seeking calibration justifications may consult the companion Methodology Rationale. January 2026

Fields of Study & Subjects

Infrastructure Resilience and Vulnerability Analysis Big Data and Digital Economy Sustainability and Climate Change Governance

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
31 January 2026
Language
EN