Bibliographic record
Abstract
Thirty years ago I published in Medium Aevum a short article entitled "Words against Women." It was a brief edition and commentary on some anti-feminist lines found in the manuscript Vatican Reg. lat. 1659. The lines were used to fill up an empty column and seem to have been linked to a longer passage in the Vatican copy of a moralising debate poem, the Petit Plet by the Anglo-Norman poet Chardri. The Petit Plet lines are marked in this manuscript by drawings of hands with the index finger pointing to particular couplets that deal with the unflattering characteristics of women. If there are many medieval texts that clearly see women in an unfavourable light, there are, however, a few that speak out in praise of women; in this paper I present some aspects of one of those, an unpublished poem in defence of women that Professor Francoise Vielliard of the Ecole nationale des Chartes and I are in the process of editing. Though this paper may be intended primarily to remind us of that rather small literary current, it also underlines the value of hunting through manuscripts ostensibly devoted to one subject but where marginalia and fill-in material can reveal a few unknown gems which often pass unrecorded—or at least passed over in the standard catalogues.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".