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Record W2587138196 · doi:10.7202/1038689ar

La traduction des connaissances scientifiques en arabe : état des lieux, défis et perspectives

2017· article· fr· W2587138196 on OpenAlexvenueno aff
Akram Odeh

Bibliographic record

VenueMeta Journal des traducteurs · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicAfrican history and culture analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Comme ce fut le cas dans le passé, la traduction est, pour le monde arabe, la voie royale pour accéder aux connaissances modernes. Aussi l’état de la traduction de et vers l’arabe est-il d’actualité depuis deux décennies. Cette contribution confronte diachroniquement les différents états des lieux de ce transfert. Elle cherche à mettre au jour les obstacles qui entravent son épanouissement tout en plaçant sa problématique dans un contexte socioéconomique et politique. L’héritage culturel arabe de jadis étant inadéquat pour le XXIe siècle, cette étude souligne l’importance /de s’inspirer des expériences réussies des autres nations modernes pour traduire les savoirs actuels.

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)0.024
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.008
Science and technology studies0.0080.022
Scholarly communication0.0150.008
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.068
GPT teacher head0.335
Teacher spread0.268 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations0
Published2017
Admission routes1
Has abstractyes

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