Ekarach Chandon English Foundational Corpus Charter

Version 3.1 of the Ekarach Chandon English Foundational Corpus Charter provides a governance and version-control framework for the Ekarach Chandon Corpus. It separates provenance class, claim form, assertion status, authorship and contribution, stop and resume conditions, open-term and relationship controls, active non-claim boundaries, question dependencies, and version-specific approval and release criteria. The Charter does not certify the truth of every Corpus proposition and does not present the three-role protocol as an empirically validated or demonstrated method. Publication, DOI assignment, citation, AI agreement, expert approval, institutional language, or repository status are not treated as sufficient sources of truth by themselves. Open concepts, questions, dependencies, and DNC boundaries remain visible according to their recorded status. AI disclosure: Version 3.1 release engineering, AI Scholar audit work, and the 13 August 2026 release-metadata synchronization used OpenAI GPT-5.6 Sol. The same AI system has operated under separately governed AI Scholar and Corpus Interpreter roles in recorded parts of the workflow. Role separation does not constitute independent review. Ekarach Chandon is the appointed Record-Integrity Reviewer and is assisted by OpenAI GPT-5.6 Sol; that assistance is not independent review. Rights boundary: CC BY-NC-SA 4.0 applies only to released material that Ekarach Chandon owns, controls, or is authorized to license. Uncleared third-party materials, private family records, personal images, sensitive materials, unmapped source records, and materials involving children or other persons are withheld unless separately cleared.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-14
DOI
https://doi.org/10.5281/zenodo.21845465
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Ekarach Chandon English Foundational Corpus Charter

Ekarach Chandon
Zenodo (CERN European Organization for Nuclear Research)
Scientific Computing and Data Management
article

Ekarach Chandon English Foundational Corpus Charter

Ekarach Chandon
article en

Abstract

Version 3.1 of the Ekarach Chandon English Foundational Corpus Charter provides a governance and version-control framework for the Ekarach Chandon Corpus. It separates provenance class, claim form, assertion status, authorship and contribution, stop and resume conditions, open-term and relationship controls, active non-claim boundaries, question dependencies, and version-specific approval and release criteria. The Charter does not certify the truth of every Corpus proposition and does not present the three-role protocol as an empirically validated or demonstrated method. Publication, DOI assignment, citation, AI agreement, expert approval, institutional language, or repository status are not treated as sufficient sources of truth by themselves. Open concepts, questions, dependencies, and DNC boundaries remain visible according to their recorded status. AI disclosure: Version 3.1 release engineering, AI Scholar audit work, and the 13 August 2026 release-metadata synchronization used OpenAI GPT-5.6 Sol. The same AI system has operated under separately governed AI Scholar and Corpus Interpreter roles in recorded parts of the workflow. Role separation does not constitute independent review. Ekarach Chandon is the appointed Record-Integrity Reviewer and is assisted by OpenAI GPT-5.6 Sol; that assistance is not independent review. Rights boundary: CC BY-NC-SA 4.0 applies only to released material that Ekarach Chandon owns, controls, or is authorized to license. Uncleared third-party materials, private family records, personal images, sensitive materials, unmapped source records, and materials involving children or other persons are withheld unless separately cleared.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Openalex Percentile: Top 4%
Scientific Computing and Data Management
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