Bibliographic record
Abstract
Étude systématique des stratégies de persuasion qu’emploie Euripide dans Hippolyte mises en paralléle avec les témoignages des tribunaux d’Athènes et les atechnoi pisteis d’Aristote. On peut déceler deux sources d’influence sur Euripide: d’abord, la continuité de la tradition à Athènes, qui indique une cohèrence des idées au sujet du témoignage légal pendant les V c et IV c siècles; puis, le fait que les rhétoriciens aient continué à concentrer leur attention sur les applications légales. De toutes les tragédies athéniennes, l’ Hippolyte permet d’établir la meilleure comparaison avec les traitements techniques, avec les règles de procédure légale à Athènes et avec les pratiques oratoires attiques par rapport aux lois, aux dépositions des témoins, au témoignages des esclaves soumis a la question, et enfin aux serments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".