Topiques de la saison inverse : hiver, désamour et pauvreté dans la littérature médiévale
Bibliographic record
Abstract
Yver, vous n'estes q'un villain ! 1 , s'exclame Charles d'Orlans, assimilant la saison froide l'un des personnages de la fiction mdivale qui s'oppose le plus aux codes littraires 2 . Les textes mdivaux ont souvent rinvesti la pense binaire des saisons en liant intimement l't plaisant et gentil 3 la littrature, tandis que l'hiver renvoyait l'obscurit et au silence. L'ouverture printanire, qui caractrise la plupart des textes des XII e et XIII e sicles, autant lyriques que narratifs, a cr dans l'esprit littraire une rciprocit topique entre renouveau de l'anne et commencement de l'oeuvre. L o la saison chaude servait de cadre la thmatique amoureuse et aventureuse, l'hiver a surtout fait l'objet de personnifications lies la bourgeoisie,
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".