Effects of Specific Training on the Ability to Deal with Cultural References in Translation*
Bibliographic record
Abstract
The aim of this empirical study (carried out as part of a wider research project – see “Credits” below) was to discover the effects of specifically designed pre-service translator training on the trainees’ ability to deal with cultural references, a text segment type which is widely considered as potentially problematic for the translator. 1 Specifically, we set out to discover any significant differences, as a result of said training, in trainees’ ability to: (a) detect cultural references within a text, (b) provide multiple feasible options (variants) to translate them, (c) evaluate those potential options, and (d) apply reasoning in making a final choice from the options. The rationale and nature of the specific training involved has already been extensively reported in González Davies and Scott-Tennent (2005). In the present article, we focus our attention on reporting and discussing its observed effects. The design of the specific training drew heavily on a previous study on specific translator training in problem-solving, reported in Scott-Tennent et al. (2000) and González Davies et al. (2001).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".