La pratica medievale della 'mise en recueil': considerazioni sulla trasmissione manoscritta del fabliau «La dame escoillee» (NRCF, 83)
Bibliographic record
Abstract
Il contributo è un’indagine preliminare all’edizione critica della Dame escoillee, un fabliau composto intorno alla metà del Duecento che presenta alcuni tratti peculiari rispetto al corpus di appartenenza. L’intento è quello di analizzare i sei testimoni che tramandano il racconto in un’ottica non esclusivamente rivolta all’analisi singolare del testo oggetto d’esame; si intende piuttosto ricavare dalle piú recenti indagini sui recueils di fabliaux alcuni strumenti utili alla comprensione del testo e a una sua piú precisa collocazione nel panorama letterario coevo; di fatto questo panorama era costituito – agli occhi dei suoi primi lettori – dalle sillogi manoscritte: sono queste ultime perciò ad avere fornito il contesto in cui i primi fruitori del racconto l’hanno letto e interpretato. Coniugare l’approccio tradizionale della classificazione dei testimoni nell’edizione di singoli testi a un inquadramento di quegli stessi testi nel complesso dei recueils che li tramandano (con un’attenzione specifica al contesto e alle modalità di fabbricazione dei codici) è forse il metodo piú idoneo a chiarire meglio le dinamiche interne al corpus dei fabliaux, a superare l’errore «di volere a tutti i costi raccogliere in un corpus indifferenziato una congerie di testi» estremamente variegata e sfuggente alle categorie critiche consuete (Tavani 1997: 10).The contribution proposes an examination of the six manuscripts containing La Dame escoillee, a fabliau probably composed halfway through the 13th century, which is characterized by some peculiarities in comparison with the other texts belonging to the same corpus. The author intends to examine the recueils containing La Dame escoillee to find out some elements useful to the interpretation of the text and to its placing in the contemporary literary and cultural context. This research is based on the method recently applied to the study of fabliaux and their manuscript tradition by an international group of researchers (Universities of Geneva, Montreal, and Zurich): it is preliminary to the critical edition of this specific text, but is also intended to propose a reflection about the modern notion of fabliau and about its applicability and pertinence to the study of the varied and unsettled group of texts which are traditionally grouped together in the same corpus.
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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 | 0.018 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.030 |
| Scholarly communication | 0.019 | 0.013 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.013 | 0.015 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".