“Quella importanza di materia”: Women and saints in Francesco Pona’s Galeria delle Donne Celebri Magdalena Maria Kubas
Bibliographic record
Abstract
In his Galeria delle Donne Celebri, a collection of twelve short stories about famous female figures, Francesco Pona “depicts” four lascivious women and four chaste women from classical antiquity, and four saints from the early and medieval Christian era. Pona, a writer and medical doctor, rationally studied the Other, that is, women; his narrator in Galeria analyzes the characters’ bodies and behaviours, but almost never their psychology. In this essay, I examine the “portraits” of saints in Pona’s Galeria (Magdalene, Barbara, Monica, and Elisabeth of Hungary) and the observation of otherness by a collector who studied both the natural and miraculous aspects of female sanctity. As interest in the ancient and medieval saints was typical of the period following the Council of Trent, I investigate Pona’s short stories within the framework of the decree on saints and relics issued in 1563. I also consider the misogynistic controversy that took place in Italy between the sixteenth and seventeenth centuries, as well as Pona’s treatise Della Eccellenza et Perfettione ammirabile della Donna.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.016 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".