Testing the Limits of Oral Narration: A Case Study of the Armenian Genocide
Bibliographic record
Abstract
This paper incorporates mnemonic, oral-formulaic, and semantic theory to identify a clear, replicable pattern of tropes, memes, and 'phraseological units' in Armenian Genocide oral narratives. The paper is part of a larger project that aims to propose a new theory on the efficacy and structural value of memory-based storytelling and oral transmission.Cette communication incorpore des théories de la mnémonique, de l’oralité et de la sémantique afin d’identifier un ensemble de tropes, de mèmes et d’unités phraséologiques clairs et reproductibles dans le discours narratif oral relatif au génocide arménien. La communication s’inscrit dans un projet plus vaste qui cherche à proposer une nouvelle théorie sur l’efficacité et la valeur structurelle de l’histoire basée sur la mémoire et la transmission orale.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".