“To be remedied of any vendetta” : Petitions and the Avoidance of Violence in early modern Parma
Bibliographic record
Abstract
The Farnese dukes dominated the province of Parma, north Italy, from the period 1548 to 1731. An important characteristic of their rule was their receptiveness to petitions and supplications from their subjects. Petitions from subjects of varying social positions to absolutist rulers provide a wealth of information pertaining to the relationships between dukes or princes and the populations they ruled. This article argues that the subjects of the Farnese duchy of Parma relied on the relationships of channels of communication provided by a well-entrenched system of petitions and appeals as a way to relieve themselves of the obligation to resolve quarrels and social conflicts through violence. Importantly, malefactors also seem to have calculated their crimes in accordance with the likelihood of receiving a ducal pardon, tending to threaten rather than wound, or insult rather than attack. The system of petitioning was operated by the Council of Sentencing (Consiglio della Dettatura), a tribunal that developed as an integral part of the Farnese judiciary system. By the waning of the Farnese dynasty, petitioning allowed a broad swath of Farnese subjects to protect their own interests while submitting to the authority of the ducal regime.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".