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Record W2063577574 · doi:10.7202/001878ar

Translation Quality Assessment. Strategies, Parametres and Procedures

2002· article· fr· W2063577574 on OpenAlexvenueno aff
Jamal al-Qinai

Bibliographic record

VenueMeta Journal des traducteurs · 2002
Typearticle
Languagefr
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesMathematicsPhilosophy

Abstract

fetched live from OpenAlex

L'évaluation de la qualité de la traduction a souvent fait les frais de jugements impressionnistes et souvent paradoxaux s'appuyant sur une esthétique bien vague. Cette étude cherche à construire un modèle empirique d'évaluation de la qualité qui s'appuie sur des paramètres objectifs de typologie textuelle, de correspondance formelle, de cohérence thématique, de cohésion référentielle, d'équivalence pragmatique et de propriétés lexicosyntactiques. La vérification de la viabilité de ce modèle éclectique passe par son application à l'analyse textuelle d'un texte évocateur (une publicité) avec pour but de faire ressortir les points convergents et divergents.

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)0.113
metaresearch head score (Gemma)0.339
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: Methods · Consensus signal: Methods
Teacher disagreement score0.113
Threshold uncertainty score0.599

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1130.339
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0160.014
Science and technology studies0.0020.005
Scholarly communication0.0120.006
Open science0.0020.005
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0080.003

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 head0.195
GPT teacher head0.354
Teacher spread0.159 · 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
GenreMethods

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

Citations51
Published2002
Admission routes1
Has abstractyes

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