Ferrer, Véronique et Catherine Ramond, éds. La langue des émotions. XVIe–XVIIIe siècle
Bibliographic record
Abstract
The two remaining sections treat their topics somewhat more briefly.Stefano Carrai opens the section on Petrarchism and "Cultura classica" with an authoritative survey of variations upon classical forms such as elegy, ode, and pastoral eclogue by Petrarch, his contemporaries, and later advocates.Stefano Jossa pursues a deeply illuminating comparison between the attitudes of Annibal Caro and Ludovico Castelvetro toward Petrarchan style.While Caro advocated for an eclectic sort of imitation with greater mythological and metaphoric density, Castelvetro argued for a closer adherence to Petrarch's use of classical models.The results clarify two entirely opposing concepts of Petrarchism rooted in humanist debates about the nature of imitatio.Massimo Danzi extends this argument by focusing on the debt of Petrarch's Bucolicum carmen to Virgil's eclogues and the subsequent "grammatica" of vernacular pastoral from Sannazaro's Arcadia to Tasso's Aminta.In the concluding section on "Musica e teatro, " Franz Pensenstadler extrapolates affinities between the congruent forms of classical epigram and Petrarchan madrigal, and traces their musical evolution from Girolamo Parabosco to Claudio Monteverdi, culminating in the literary texts of Giovanni Battista Marino.Florian Mehltretter closes the section with a study of Petrarchan elements in the Mozartian libretti of Lorenzo Da Ponte.The contributors to this volume provide valuable insights into Italian Petrarchism, and their collective work affords a helpful guide to interdisciplinary Renaissance studies.Inspired by Italian and German scholarship, this project deserves emulation in Europe, North America, and elsewhere.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".