Economic Event Relational Ground (EERG): A Maximum-Expanded Complementary Research Architecture for Currency Expression, Multi-Fiber Monetary Qualification, Denomination Continuity, External Accounting Reference, and AI Economic Control-Latency

Economic Event Relational Ground (EERG) is a complementary academic architecture for the filed GCCMC technical system. It addresses research questions that benefit from fuller theoretical treatment than a patent specification normally provides: how economic meaning can remain relation-native without collapsing into issuance, ownership, payment, settlement, accounting effect, legal effect, or execution authority; how multiple bounded readings can coexist over a common economic source; and how those distinctions survive AI-speed processing. The related GCCMC architecture provides the technical anchor. EERG provides the complementary academic layer: formal relation grammar, non-equivalence laws, multi-fiber monetary qualification, denomination-definition continuity, bounded external accounting-reference theory, explicit bridges, lineage and requalification, conflict preservation, multi-source hyper-relational membership, resource/monetary dual-role analysis, implementation topology, threat analysis, worked examples, falsifiability criteria, and open research questions. Currency expression is modeled through four distinguishable relation positions, C_C = , corresponding to denomination or currency-unit frame, quantity, economic reference, and bounded monetary admissibility. EERG preserves the principle that relation existence does not automatically generate issuance, authority, ownership, payment, settlement, accounting effect, or legal effect. The paper further develops an AI Economic Control-Latency Problem. AI and agentic systems may generate and revise economic-relation candidates faster than legitimate human or institutional authority can review them. EERG therefore preserves candidate, validated relation, evidence, authority, execution, and effect as non-identical layers regardless of processing speed. Its central acceleration rule is: machine-speed relation generation does not imply machine-speed authority inheritance. EERG and GCCMC are complementary rather than competing disclosures. GCCMC remains the filed technical architecture; EERG expands the public academic theory, validation framework, interoperability analysis, AI-economic implications, and scientific research program around that architecture. EERG does not amend, backdate, or determine the legal scope of the filed GCCMC rights. Structural Paper Series — Paper 01.GCCMC Complementary MAX EXPANDED Final Publication Edition v2.1.