Fazioni e popolo in una provincia del dominio pontificio fra XIII e XIV secolo
Bibliographic record
Abstract
Between the 13th and 14th centuries, a number of cities in the inchoative papal state experimented a system of self-government that allowed the Guelph and Ghibelline factions, formally represented in those same bodies on an equal footing, to work alongside the more strictly communal magistracies. The case of Todi is rather well known, given the role that Bartolo da Sassoferrato assigns to it in his Tractatus de guelphis et gebellinis (ca. 1350), but current research has already ascertained that this political tradition appeared at least around 1260. Some evidence can suggest, however, that some form of integration of factions into the local institutional framework was possible elsewhere, and not far away, at Amelia for example. Here, in the new statute of the people (1343), we find a distribution of the roles of the priorato based on factions. At Todi, in 1337, something similar had happened: the statute issued that year followed the establishment of an explicitly popular regime which, in continuity with local tradition, integrated Guelphs and Ghibellines within it. The examples of these, and perhaps other, communities in the province of the Patrimonio di San Pietro in Tuscia can thus add some useful elements to the discussion of the problem of factions and their role in the communal and post-communal political order, and in particular the relationship between the people (popolo) as an institutional system and the parties.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".