Buard, Jean-Luc. Culture médiatique et presse numérisée. Médiasphère des feuilletons-nouvelles de Marie Aycard (1794-1859)
Bibliographic record
Abstract
De quoi parle-t-on quand on parle de littérature ? C’est la question qu’on pourrait se poser, en paraphrasant de manière guère originale (cela a été fait dix mille fois) le titre du célèbre recueil de nouvelles de Raymond Carver pour parler de ce livre de Jean-Luc Buard, rédacteur en chef de la revue Le Rocambole et explorateur passionné des bas-fonds de la production populaire. Dans ce cas particulier, la paraphrase usée peut toutefois paraître particulièrement appropriée, justement en raiso...
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".