Bibliographic record
Abstract
Recensioni and in the further investigation of the motivations behind self-censorship.Pugliese recognizes the potential that the early drafts of the Cortegiano hold for illuminating Castiglione's questione della donna., and she dedicates the entire final chapter of her study to it.Readers may in fact find that "censored statements both against and for women may arouse potentially stronger reactions than the vulgate text" (361).Readers will also be pleased to learn that Pugliese is in the process of creating a public electronic archive of the transcriptions and digitized manuscripts of at least the first four manuscripts that she used in her study (mentioned on pages 6-7, 37, and elsewhere), a resource that she hopes will be available in the coming year.In short, Pugliese has demonstrated her own mastery of sprez- zatura in the way that she has made the extremely daunting task of collating and interpreting the labyrinth of Castiglione's drafts seem so accessible, and in the way that she has made A Classic in the Makings classic of indispensable scholarship for future Castiglione studies.
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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 | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".