Annie Duprat, Marie-Antoinette, 1755-1793 Images et visages d’une reine
Bibliographic record
Abstract
1Les représentations de Marie-Antoinette ont déjà fait couler beaucoup d'encre, si l'on pense aux travaux dirigés par Deena Goodman, de Jean-Clément Martin et Cécile Berly ou les études de Lynn Hunt sur les caricatures.Le livre d'Annie Duprat apporte néanmoins une réflexion intéressante sur la profusion des imaginaires qui se sont construits depuis plus de deux siècles et ont, de diverses manières et pour différentes raisons, totalement déformé l'image de celle qui fut la reine du plus puissant État européen à la fin du XVIII e siècle.En introduction, le projet annonce son originalité : Annie Duprat entend se « placer au niveau du regard et des affects du spectateur, au niveau de cet observateur qui, des années 1770 aux premières décennies du XXI e siècle, voit changer les images et les visages d'une reine […] ».
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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 | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".