The Influence of Milan on the Development of the Lombard Koiné in Fifteenth-Century Italy: the Letters of Elisabetta of Pavia
Bibliographic record
Abstract
The main tendency characterizing the development of language in Lombardy in the fourteenth and fifteenth centuries is the formation of a koiné. The extent to which Milan influenced the Lombard koiné is the subject of ongoing debate. On the one hand, scholars suggest that Milan provided a centralizing force for the “Milanization” of other Lombard vernaculars, similar to what occurred for Piedmont and the Veneto. On the other hand, studies have pointed out that Milan was not a centralizing force for the Lombard koiné and that it remains to be verified whether the prestige of Milanese influenced non-Milanese vernaculars. This paper looks at the extent to which Milan influenced the koiné in fifteenth-century Lombardy. I consider eight linguistic items, previously described as unique to the vernacular of Pavia, to verify their presence or absence in a corpus of religious writings from the fifteenth-century nun Elisabetta of Pavia and whether Milanese items can be identified. I consider aspects of phonology and morphology in Elisabetta’s letters and conclude that her language is best characterized as a pre-koiné. The article concludes by arguing for less emphasis on the role of Milan in histories of the vernacular in Lombardy. This finding has implications for the history of non-literary writing in northern Italy and the importance attributed to capital cities in processes of koineization.
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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 | 0.002 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".