Discovering a Preacher and his Work. First Approaches to Petrus Hispanus' Sermon Collections
Bibliographic record
Abstract
The name Petrus Hispanus covers a range of authors on different topics, such as medicine or philosophy. The less studied part of the “corpus petrinicum” concerns a group of three sermon collections discovered in the 1970s by Schneyer and Cruz Pontes. This article investigates, for the first time, two of these three sermon collections, \ninquiring into their authorship, their environment of composition and the purpose for \nwhich they were written down. In doing so, the figure of a Dominican Preacher, active in \nLangue d’Oc in the third quarter of the 13th century, emerges. In the second part of the paper two sermons of each Sunday collection are compared \nso as to discover not only the main interests of the preacher, but also the different uses for which these collections were written. A kaleidoscopic range of possibilities comes to light, enriching the perspective in which to approach this new material.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.017 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".