Too Much . . . Too Little . . . Just Right: Adjustments of Dionysus’ Heroism in Nonnus’ Dionysiaca
Bibliographic record
Abstract
Abstract: A heroic outlook is a necessity for the laudandi of late antique panegyrics and poems. Authors like Nonnus evoke the Homeric heroes and construct new heroic identities adapted to their own times. Nonnus’ Dionysiaca pays attention to the importance of intelligence and shedding of blood for the heroic masculinity of Dionysus. Il est indispensable pour les laudandi des panégyriques et des poèmes de l’Antiquité tardive d’apparaître comme des héros. Des auteurs tels que Nonnos évoquent les héros homériques et construisent de nouvelles identités héroïques adaptées à leur temps. Les Dionysiaques de Nonnos accordent beaucoup d’importance à l’intelligence et au sang versé dans leur construction de la masculinit é héroïque de Dionysos.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".