Annie Duprat (dir.), Révolutions et Mythes identitaires. Mots, violence, mémoire
Bibliographic record
Abstract
Annie Duprat est bien connue de nos lecteurs.Membre du comité de rédaction de notre revue, historienne des représentations, elle publie régulièrement des livres dont l'importance et l'intérêt ont été à plusieurs reprises soulignés dans ces pages (cf.AHRF, n o 295, 324, 331, 347).Ici, elle propose un ouvrage collectif, dirigé par ses soins, et pour lequel elle a adapté ou traduit plusieurs contributions d'historiens étrangers.Il n'est donc pas étonnant d'y retrouver quelques-uns de ses thèmes de prédilection : la mémoire, les images et les mots.Notons toutefois que les bornes chronologiques envisagées par les seize auteurs s'étalent de la pré-Révolution jusqu'à la fin du XX e siècle.Nous n'évoquerons ici que les études portant sur la période 1780-1848, soit onze contributions au total.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.007 |
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".