Data on the Bologna anti-inquisition tumult, 13 May 1299: Defendants, their transgressions, and inquisitorial decisions
Bibliographic record
Abstract
This dataset maps the individual transgressions of defendants recorded in the Bologna inquisition register, 1291-1310, who were involved in the 13 May 1299 civic tumult against inquisitors and their burning of Bompietro, Giuliano, and Rosafiore. It records those defendants' IDs and names, the document number in the edition by L. Paolini and R. Orioli, a matrix of several tens of transgression types (1 = present, 0 = not present) and their evaluation into broader categories: (1) criticism of specific inquisitorial decisions, (2) claiming that inquisitors act in their own interest, (3) criticizing inquisitors or inquisition in general (not just specific decisions), (4) wishing bodily harm to inquisitors, (5) anti-friar sentiments (beyond anti-inquisitorial expressions only) and (6) legalistic criticism. Then it records the financial guarantees, fines, and obligations, and records the inquisitor and notary involved, as well as the date(s) of hearing. As defendants' demographics, it records sex, occupational group, parish and quarter of residence, and for some, their net property worth from the tax declarations (estimo) from 1296-7.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.029 |
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".