<i>Love and graves between Arquà and Avignon: a further contribution to the</i> ‘Tombaide’ <i>(1540) launched by Alessandro Piccolomini</i>
Bibliographic record
Abstract
When Alessandro Piccolomini (1508‐79) visited Petrarch's tomb in 1540, he composed a sonnet that was to launch a poetic exchange between fellow literati in his hometown of Siena and in the university town of Padua, where he was currently a student. Some decades later, another Sienese literato, Lattanzio Benucci (1521‐98), wrote a response sonnet closely following Piccolomini in structure, but adopting a different perspective – Benucci's poem does not pay homage to Petrarch's tomb, but to Laura's. This article will bring to light this previously unknown contribution to what has become known as the ‘Tombaide’ of 1540, and discuss the context in which it was composed. In the background lay the growing interest in the places associated with Petrarch and, more specifically, the alleged discovery of Laura's remains in Avignon in 1533. In composing a paean to Laura's tomb, Benucci may well have had his own Laura in mind, that is, his wife Dorotea Tancredi. At the crossroads of poetry and love, of the religious veneration for saints and the secular cult of literature, Benucci's poem illustrates not only an attempt to revive an earlier poetic exchange, but also a complex episode of cultural history in sixteenth‐century Europe.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".