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Record W1517168247 · doi:10.1515/9782763721859

Les traducteurs dans l'histoire

2014· book· fr· W1517168247 on OpenAlexaboutno aff
Jean Delisle, Judith Woodsworth

Bibliographic record

Venuenot available
Typebook
Languagefr
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsGeography

Abstract

fetched live from OpenAlex

Les traducteurs dans l’histoire a été accueilli dès sa première édition comme un ouvrage incontournable. Cette nouvelle édition, revue et enrichie, comporte d’importantes mises à jour et des sections inédites. Elle tient compte aussi des orientations de la recherche contemporaine et offre une interprétation plus nuancée de certains faits historiques. La bibliographie renferme plus de cent nouveaux titres. Cet ouvrage, indispensable pour les étudiants, les chercheurs et les professionnels de la traduction, intéressera tout autant les chercheurs d’autres disciplines et le grand public, car l’histoire de la traduction recoupe celle des cultures et des civilisations. « Un livre stimulant ! Une pierre magnifique pour étayer les travaux d’historiographie à venir. Ce livre sera apprécié pour toute sa valeur, pour les chemins qu’il défriche, pour les horizons qu’il trace. » – Yves Gambier, Université de Turku, Finlande « La traductologie et les traductologues découvrent enfin l’importance des traducteurs. Les traducteurs dans l’histoire est une contribution inestimable aux efforts pour leur rendre leur juste place. » – John Milton, Université de São Paulo « Le livre est sans conteste un ouvrage de vulgarisation, destiné aux lecteurs du monde entier. » – André Clas, Université de Montréal « C’est le caractère central du rôle des traducteurs qui donne son unité à l’ouvrage de J. Delisle et J. Woodsworth. L’ensemble des portraits qu’il renferme forme une fresque historique. » – Mirella Agorni, Università degli Studi, Bologue

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.024
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0080.017
Scholarly communication0.0140.007
Open science0.0010.003
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0110.004

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.

Opus teacher head0.067
GPT teacher head0.259
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations46
Published2014
Admission routes1
Has abstractyes

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Same topicTranslation Studies and PracticesFrench-language works237,207