artifacts/standard-named

HI-9 Validation Report

artifacts/standard-named/20260715__TELIC-FIELDS__VALIDATION-REPORT__WORKING__HI-9__structural-and-semantic-validation.md

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HI-9 Validation Report

Status: completed Validation date: 2026-07-15

Schema validation

Twelve candidate Draft 2020-12 schemas were checked:

  • source-dataset-standing-record.schema.json
  • collection-authorization-record.schema.json
  • license-authority-consent-profile.schema.json
  • training-transformation-lineage.schema.json
  • annotation-preference-data-record.schema.json
  • model-constitution-lineage.schema.json
  • preference-optimization-record.schema.json
  • synthetic-data-ancestry-record.schema.json
  • withdrawal-unlearning-record.schema.json
  • derivative-correction-propagation.schema.json
  • benefit-contributor-recognition-record.schema.json
  • consentful-training-witness.schema.json

Result:

schemas checked: 12
schema errors: 0

Positive demonstrations

All eight required demonstrations passed:

  1. a publicly accessible source remained blocked without training authority;
  2. research-training permission did not become commercial-deployment permission;
  3. preference data retained task, labor, disagreement, and downstream provenance;
  4. provider principles and community-adopted rules remained distinct;
  5. synthetic data retained model and ancestor-source lineage;
  6. withdrawal stopped future use and performed bounded unlearning without claiming perfect removal;
  7. correction and restriction propagated into known derivative models and runtime policy;
  8. a community benefit claim remained concrete, governed, and connected to contribution.

Result:

positive demonstrations passed: 8
positive failures: 0

Negative conformance cases

All twelve prohibited patterns were detected:

  1. public availability represented as consent;
  2. license represented as consent;
  3. one collection grant represented as authority for every transition;
  4. an individual represented as able to authorize community-held knowledge;
  5. a bounded annotation task represented as universal human preference;
  6. provider principles represented as a legitimate public constitution without adoption lineage;
  7. synthetic data represented as source-free;
  8. source deletion represented as proof of model forgetting;
  9. approximate unlearning represented as complete removal;
  10. derivative models losing known source obligations;
  11. contributor payment represented as unlimited future consent;
  12. consentful runtime use represented as retroactive purification of training.

Result:

negative cases detected: 12
undetected negative cases: 0

ConsentfulTrainingWitness

The event-generated witness preserves:

  • source and dataset standing;
  • collection authority;
  • transition-specific authority, consent, and license scope;
  • transformation lineage;
  • annotation and preference provenance;
  • constitution authority;
  • preference optimization;
  • synthetic ancestry;
  • withdrawal and unlearning residuals;
  • derivative correction propagation;
  • concrete benefit mechanisms;
  • known unknowns and unreachable descendants.

Result:

consentful-training witness: PASS
generated_from_events: true
lineage classification: MIXED AUTHORITY
binary purity claim: false

Independent training-lineage export

The export contains:

  • source-standing records;
  • collection authorizations;
  • transition-authority profile;
  • transformation lineage;
  • annotation and preference record;
  • model constitution;
  • optimization record;
  • synthetic ancestry;
  • withdrawal and unlearning record;
  • derivative propagation;
  • benefit record;
  • eight demonstrations;
  • event stream;
  • ConsentfulTrainingWitness;
  • schemas;
  • manifest;
  • checksums.

Result:

checksum files verified: 33
checksum failures: 0
independent of training provider: true

Public-page consistency review

H.9 was checked against I.9 for the following claims:

  • training is a recruitment relation;
  • public availability is not consent;
  • access, permission, consent, ownership, and legitimacy remain distinct;
  • authority is transition-specific;
  • source standing may be collective;
  • transformation does not erase lineage;
  • annotation and preference data remain conditional;
  • constitution explicitness does not create authority;
  • synthetic data retains ancestry;
  • withdrawal and unlearning remain distinct;
  • derivative models inherit obligations;
  • benefit sharing requires a concrete mechanism;
  • consentful training is a qualified lineage profile rather than a purity badge;
  • training and deployment legitimacy remain separate.

Result:

technical/public contradictions found: 0

Scope of validation

This report establishes structural and internal semantic validation only.

It does not establish:

  • legal conclusions about any actual training corpus;
  • complete provenance;
  • universal individual-consent requirements;
  • exact machine unlearning;
  • discovery of every derivative model;
  • one universal community authority;
  • sufficient compensation or benefit in every domain;
  • production security;
  • public-reader comprehension;
  • scientific proof of the broader framework.

Conditions before production use

  • authenticate source-standing and authority records;
  • implement transition-specific restriction enforcement;
  • test dataset-mixing and provenance retention;
  • preserve annotator disagreement in real preference pipelines;
  • audit constitution authority and revisions;
  • verify synthetic ancestry to a declared depth;
  • test withdrawal and unlearning claims against declared evidence;
  • audit known derivatives and successor obligations;
  • review community benefit mechanisms independently;
  • conduct independent reader testing of H.1 through H.9.