La poesie en question dans la premiere et la cinquieme elegie de George Buchanan
Bibliographic record
Abstract
From the first verse of the first Elegy (entitled “Quam misera sit conditio docentium literas humaniores Lutetiae...”) written by Buchanan while he was a young teacher in Paris, the Scottish scholar depicts himself as an unlucky lover of poetry whose passion is impeded by his educational job. Through his fifth Elegy, “Ad Franciscum Oliuarius, Franciae Cancellarium, nomine Scholae Burdigalensis”, the Scottish scholar, then teaching Latin in Bordeaux, becomes the advocate of the Muses in order to obtain from the French Chancellor François Olivier the financial and moral help that classical studies need at the moment. In the first Elegy which testifies a personal experience as well as in the second one which is an “event poem” written for the defense of the Collège de Guyenne, Buchanan adopts the position of the poet complaining that too many difficulties prevent him from living completely and with dignity from his art whereas he embodies a sophisticated way of life, civilization in short. In both elegies, the status of the poet is seen as problematical: George Buchanan uses the topoi of the poet’s representation and of the current situation that is sometimes personal, sometimes shared by his fellow teachers in Bordeaux. Such a situation casts doubt on the poetical vocation of the “Prince of Poets of his time”, so called a little later by the French publisher Robert Estienne.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".