La mer pourpre : façons grecques de voir en couleurs. Représentations littéraires du chromatisme marin à l’époque archaïque
Bibliographic record
Abstract
Pourquoi, chez Homère et dans le reste de la littérature préclassique, la mer arbore-t-elle de multiples couleurs (noir, blanc, gris, violet, pourpre,..), sans être jamais bleue ? La réponse à cette question n’est pas à chercher dans un quelconque problème de déficience visuelle, mais bien plutôt dans la nature du regard que les Grecs de l’époque archaïque portaient sur l’étendue marine. En abordant la question philologique par le biais de l’anthropologie historique, on découvre alors que les incohérences et étrangetés apparentes du lexique chromatique grec s’évanouissent. L’article cherche ainsi à montrer que l’analyse des représentations du chromatisme marin dans la littérature archaïque permet de décentrer notre regard et de mettre en lumière la nature des sentiments suscités par la toute puissance de la mer dans l’imaginaire collectif grec.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".