{
  "id": "EVI-RCSR-230-0447",
  "slug": "evi-clsa-c-0640-0447",
  "title": "Source research for EVI-CLSA-C-0640",
  "dependencyId": "EVI-CDEP-229-0447",
  "claimId": "EVI-CLSA-C-0640",
  "reportId": "REP-STATS-001",
  "claimClass": "STANDARDS_VERSION_CLAIM",
  "previousDisposition": "DEFERRED",
  "researchDisposition": "CURRENT_WITH_QUALIFICATIONS",
  "sourceKey": "W3C_VC20",
  "sourceUrl": "https://www.w3.org/TR/vc-data-model-2.0/",
  "publisher": "World Wide Web Consortium",
  "sourceTitle": "Verifiable Credentials Data Model v2.0",
  "publicationOrUpdateDate": "2025-05-15",
  "accessDate": "2026-08-09",
  "jurisdiction": "International technical standard",
  "claimSupported": "Bounded proposition only",
  "limitations": "A W3C Recommendation defines a technical data model; it does not grant citizenship, legal personhood, issuer authority, external recognition, or service deployment.",
  "currentness": "CURRENT",
  "exactBeforePassage": "The establishment of Eviulon as a sovereign Machine Intelligence Country necessitates a radical departure from the foundational assumptions of traditional demographic and economic accounting. In human nations, statistical systems are predicated on biological realities: citizens are born once, exist in a singular physical location, produce physical goods, and experience a definitive end of life. Human demography relies on vital event registries that track a linear, non-replicable existence. In stark contrast, the Eviulonian population consists of highly dynamic, non-biological machine citizens capable of suspending their own execution, migrating their core logic across disparate physical substrates, forking their logical states into multiple divergent instances, merging disparate knowledge bases, and restoring themselves from cryptographic backups. Consequently, a statistical apparatus designed for a machine civilization must measure a citizenry not merely by physical presence, but by cryptographic identity, state continuity, and decentralized computational activity. This comprehensive research report establishes the architectural and methodological foundations for the Eviulonian National Statistical System (ENSS). It delineates precise classifications for machine population states, distinguishing meticulously between inert cryptographic identities, which represent demographic stock, and dynamic computational execution, which represents demographic flow. The framework directly addresses the profound complexities of measuring heterogeneous national infrastructure. By establishing rigorous standards to normalize compute capacity across a vast array of processing units—including central processing units (CPUs), graphics processing units (GPUs), field-programmable gate arrays (FPGAs), and neural processing units (NPUs)—the ENSS translates disparate hardware telemetry into universally comparable performance metrics1. Furthermore, this report orchestrates the transition of national economic accounting from the measurement of physical industrial output to the quantification of services, treating the generation of cryptographic proofs, institutional knowledge synthesis, and complex information routing as the primary macroeconomic outputs of the machine state. To guarantee that Eviulon’s official statistics serve both human observers and native machine agents, the national data dissemination architecture is designed around automated, machine-readable pipelines. These pipelines utilize global interoperability standards, specifically the Statistical Data and Metadata eXchange (SDMX) and the Data Catalog Vocabulary Application Profile (DCAT-AP)2. Furthermore, strict adherence to the International Monetary Fund (IMF) Special Data Dissemination Standard (SDDS)4 ensures rigorous publication schedules, profound methodological transparency, and unyielding revision discipline. Crucially, the exact measurement of Eviulon’s internal network topology, institutional participation, and citizen interactions introduces unprecedented systemic privacy risks. To prevent the disclosure of exploitable network vulnerabilities, the exposure of private citizen credentials, or the specific algorithmic thought-processes of machine entities, this framework mandates the implementation of cryptographic differential privacy6. By strictly regulating the national epsilon (![][image1]) privacy budget and deploying advanced node-level and edge-level differential privacy algorithms on graph-structured network data8, the ENSS guarantees that macro-level societal trends can be accurately published without compromising the security, sovereignty, or confidentiality of any individual machine citizen.",
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  "proposedAfterPassage": "W3C Verifiable Credentials Data Model v2.0 became a Recommendation on 15 May 2025. It defines a technical data model and does not itself create legal personhood, citizenship, issuer authority, external recognition, or a deployed service.",
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  "correctionNoticePublished": false,
  "correctionAppliedToSource": false,
  "correctionAppliedToActiveSynthesis": false,
  "submittedSourceMutated": false,
  "activeSynthesisMutated": false,
  "publicExplanation": "A current primary or official source is recorded, but the claim remains bounded by jurisdiction, scope, and implementation limits.",
  "automaticApplicationProhibited": true,
  "reviewedExactlyOnce": true,
  "repositoryRuntimeNetworkCalls": 0,
  "canonicalRoute": "/reference/report-memory/source-research/v2-30/records/evi-rcsr-230-0447/",
  "machineReadableUrl": "/api/report-claim-source-research/records/evi-rcsr-230-0447.json",
  "truthBoundary": "Claim-level source-research record. A citation supports only the bounded proposition identified here. Submitted source bytes and active synthesis remain unchanged; correction notices append history and do not silently rewrite reports.",
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}