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Record W1981390370 · doi:10.7202/003624ar

Assessment In Translation Studies: Research Needs

2002· article· en· W1981390370 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueMeta Journal des traducteurs · 2002
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPresuppositionCompetence (human resources)Computer scienceTranslation (biology)Translation studiesField (mathematics)LinguisticsPsychologyMathematicsPhilosophySocial psychology

Abstract

fetched live from OpenAlex

On the whole, most research into assessment in translation only concentrates on one area — evaluation of translations of literary and sacred texts — and other areas are ignored. In fact, this field of research includes two other areas, each with its own characteristics: assessment of professionals at work and assessment of trainee translators.Starting with this presupposition, we describe the three areas and analyze the notion of translation assessment, so as to define the characteristics of each area: objects, types, functions, aims and means of assessment. Next, we discuss the question of translation competence, and the concepts of translation problems and translation errors, in order to reach a general principle that should be applied in all assessment. Finally, we suggest assessment instruments to be used in teaching translation and make suggestions for research in assessing translator training, an area that has long been neglected and deserves serious attention.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.448
GPT teacher head0.420
Teacher spread0.028 · 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