Influssi della lingua e della letteratura francesi medievali nellâItalia settentrionale e il Fondo Francese Antico della Biblioteca Nazionale Marciana di Venezia
Bibliographic record
Abstract
This dissertation regards the medieval French literary tradition’s presence in Northern Italy in the late Middle Ages. This phenomenon produced a corpus of texts copied or composed by Northern Italian scribes and authors in the French language. The Italian authors’ command of French verse was, in some cases, imperfect; in others, they consciously manipulated the French language for creative purposes. Whatever the case, what resulted was a body of work ostensibly written in French but with a distinctly Northern Italian flavour. Every work within this corpus presents unique linguistic features and a distinct blend of French and Northern Italian vernaculars. This cultural phenomenon, which is commonly referred to as “Franco-Italian,” was no doubt born from the linguistic proximity of the Northern Italian vernaculars to the languages of France in the late Middle Ages: absent an autochthonous Italian literary tradition, Northern Italian literati adapted the languages of France, which had already developed vernacular literary traditions, as a means for their own literary expression. Northern Italy constituted, in this sense, a peripheral region of a medieval “Francophonie.”\nThis dissertation first surveys the nature and function of the Franco-Italian “language” and then presents a critical historiography of the scholarship surrounding the most important manuscript collection of French and Franco-Italian works in Italy, that of the Biblioteca Marciana in Venice. This includes a discussion of all known catalogues and inventories of the corpus dating back to 1407 and an analysis of two others, until now largely unstudied, that shed new light on the history of the collection. What follows is an investigation into one little-known manuscript in the collection, Codex XIV, which recounts the adventures of Beuve de Hanstone. Codex XIV is unique in the collection insofar as it was not written in the hybrid Franco-Italian idiom, rather a pure Old French; consequently, it has received little attention from scholars. This dissertation revisits the text and its importance in the study of the influence of French literature in medieval Italy.\n\tThe dissertation concludes with a series of appendices that display and compare unpublished inventories of the collection that support the arguments advanced herein.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".