Penser et représenter un troisième genre dans les Amériques (xvie-xviiie s.). Le massacre des « hommes-femmes », entre images et littérature
Bibliographic record
Abstract
Cette enquête a pour point de départ le motif iconographique et littéraire de la mise à mort de centaines d’Autochtones ordonnée en 1513 par l’Espagnol Núñez de Balboa, dans la région de l’actuel Panama. À travers l’étude de livres illustrés entre les xvie et xviiie siècles, nous constatons que le concept d’« homme-femme » fut déplacé, puis transféré de « l’antique vers l’exotique », pour permettre d’appréhender une réalité méconnue des colons. Après une analyse de la mise en image du massacre par Théodore de Bry au xvie siècle, nous traitons des considérations critiques et de l’analyse comparatiste de Joseph-François Lafitau, qui, au xviiie siècle, fait entrer les hommes-femmes dans le domaine de la religion.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".