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Record W1967195936 · doi:10.7202/008034ar

Translator Training: What Translation Students Have to Say

2004· article· en· W1967195936 on OpenAlexvenueno aff
Defeng Li

Bibliographic record

VenueMeta Journal des traducteurs · 2004
Typearticle
Languageen
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsInterpreterTraining (meteorology)Relation (database)Computer scienceOrder (exchange)Mathematics educationPsychologyPedagogyMedical educationMedicineProgramming language

Abstract

fetched live from OpenAlex

Following an earlier study by the same author on professional translators which appeared in Target 2000 (12:1 127-149), this article reports on an empirical study, based on both quantitative and qualitative data, on the learning needs of translation students, another major stakeholder in translator training. This study shows that contrary to a widely held assumption, the great majority of students taking translation did not and do not intend to be professional translators/interpreters. It is found that translation students prized training of both L1 and L2 before or during translation training, and that they preferred practice-oriented courses to theoretical courses. Also revealed in this study is that many students believe the current translation program does not reflect the market needs very well and that measures such as offering more practical courses, strengthening language training, teachers’ providing more detailed comments on assignments, etc., must be taken in order to improve the program. Based on such findings, a comparison with the earlier study on professional translators is made and pedagogical implications are also drawn in relation to some of the focal issues in translator training.

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 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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.615
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.214
GPT teacher head0.466
Teacher spread0.253 · 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 teacher head, not a consensus.

Study designOther design
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

Citations76
Published2004
Admission routes1
Has abstractyes

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