Translation as editorial mediation: <scp>C</scp>harles <scp>E</scp>stienne's experiments with the dissemination of knowledge
Bibliographic record
Abstract
Charles Estienne is the most versatile member of the French humanist dynasty of printers, the Estiennes, yet he has suffered from an unfavourable comparison with his father and brothers. This article accords him, at last, the respect he deserves. He authored a series of short compilations for young students between 1536 and 1540, printed in Paris and Lyon. These booklets, organized like beginners' dictionaries, propose a system of bridges between languages: Greek, Latin, and French. Presented as summaries, they can be read as attempts to structure and circulate knowledge according to a new ‘printed’ model, and they were reprinted and rearranged by Estienne in the 1550s, after he himself became a printer. His anatomical treatise, first published in Latin (1545) then in French (1546), also appears like a system of names and languages. As the translator of texts representing a wide variety of genres, Estienne plays on the different registers of the annotated edition, summary, compilation, and translation to effectuate the same trope: vulgarization, meaning accessibility for a great number of readers as well as translation into the vernacular. Similarly, the printing press addresses a great number of potential readers. The study enquires whether the technology of this first form of vulgarization calls for a second one, a ‘vernacularization’, whether printing also implies editing, and whether annotations and editions turn into translations. Taking Charles Estienne, the one‐man printer, editor, translator and annotator as a case study, I explore the meaning of ‘vulgarization’ in the typographical workshop.
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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 | 0.003 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.194 | 0.089 |
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".