Bibliographic record
Abstract
Joachim Du Bellay, a poet of contradiction, is known in his later verse for mastering a sculpted and “cold” style of writing. This article proposes that in conjunction with a unique typography and formatting of the poems in their first editions, catchwords (or réclames), seemingly isolated and fragmentary marks at the end of gatherings of signatures, punctuate the verse and, now and again, become a function of its force. Appearing as they do and where they do, catchwords invoke what poet René Char called a parole en archipel (words comprising an archipelago and of an originary calling), and what Maurice Blanchot referred to as a parole de fragment (speech of fragment) or a parole morcelée (shattered speech). Of uncommonly modern appeal, catchwords—intermediaries, unique spatial signs—are vital elements in the design, impact, and consequence of collections that run from L’Olive and the Recueil de poesie (1549) to Fédéric Morel’s handsome and carefully formatted editions of Le Premier livre des Antiquitez de Rome and Les Regrets (1558).
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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 | 0.007 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".