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Where the Answer Stands: How Dionyas Designs History Questions About Three Treaties · The study

Sources and bibliography

By RISCON Labs AI from Dionyas's public records · Dionyas publishes these history questions as editorial question designs with reference answers written from documents and no judgment, and this study put them into English from the Korean · the readings through the works named are this study's interpretation · First edition · October 2026

AI-generated editorial illustration: A closed blank archival case rests on a reading cradle.
Where the Answer Stands: How Dionyas Designs History Questions About Three TreatiesOpening
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  1. Bibliography

This study is an expansion by AI of inquiry records published by Dionyas, the music studio of the RISCON family. The records are in Korean; every sentence in a block quote is a record's own, word for word, in the English translation made once for this study by its editorial session from the Korean original, which each translation names by its hash. The rest is AI writing. Dionyas describes its list as editorial question design and states that it has generated no judgment; its history questions each have a reference answer written from named documents, which the list counts but does not carry, and no automatic connector run has been made on them. Dionyas does not say who drafted these records. The records name three international instruments and the bodies whose documents they cite; what they say of them is their framing, which this study has not checked, and this study gives none of the answers. Nothing here is legal advice or a statement of what any treaty provides or where it applies today. The readings through the works named are this study's interpretation.

The records were read on 2026-10-06. This book was written on 2026-10-07.

Bibliography

  • Gaye Tuchman, Objectivity as Strategic Ritual: An Examination of Newsmen's Notions of Objectivity (1972).
  • Michael K. Buckland, What is a "document"? (1997).
  • Joseph E. Uscinski and Ryden W. Butler, The Epistemology of Fact Checking (2013).
  • Lucas Graves, Anatomy of a Fact Check: Objective Practice and the Contested Epistemology of Fact Checking (2016).
  • Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev and Percy Liang, SQuAD: 100,000+ Questions for Machine Comprehension of Text (2016).
  • James Thorne, Andreas Vlachos, Christos Christodoulopoulos and Arpit Mittal, FEVER: a Large-scale Dataset for Fact Extraction and VERification (2018).
  • Florian Jaton, We get the algorithms of our ground truths: Designing referential databases in digital image processing (2017).
  • Amandalynne Paullada, Inioluwa Deborah Raji, Emily M. Bender, Emily Denton and Alex Hanna, Data and its (dis)contents: A survey of dataset development and use in machine learning research (2021).
  • Inioluwa Deborah Raji, Emily M. Bender, Amandalynne Paullada, Emily Denton and Alex Hanna, AI and the Everything in the Whole Wide World Benchmark (2021).
  • Stephanie Lin, Jacob Hilton and Owain Evans, TruthfulQA: Measuring How Models Mimic Human Falsehoods (2022).
  • Edward B. Kang, Ground truth tracings (GTT): On the epistemic limits of machine learning (2023).

Every sentence in a quotation block is Dionyas's record, word for word. The rest is AI's writing from those records and the works the book names, and it does not say which choice is right.

RISCON Labsrisconlabs.com