Training in the Application of Translation Strategies for Undergraduate Scientific Translation Students
Bibliographic record
Abstract
A research project2 was recently carried out consisting of the following stages: 1. Finding out what was previously known or hypothesised about the role of strategies in the translation process by reviewing the relevant literature. 2. Deciding on an operative definition of translation strategies. 3. Selecting 3 types of problems to give experimental training in the application of strategies to solve them. 4. Designing a theoretically optimal course, by considering relevant pedagogical literature, to give pre-service training in the application of these strategies. 5. Carrying out an empirical study to observe, measure and analyse the effects of such a course. A full report on this study is to be found in Investigating Translation (John Benjamins, 1999). On conclusion of the study, it was found that the experimental course had been perceived as satisfactory by all the participants, and clearly increased the frequency and effectiveness of trainees' application of target strategies. It was also found that this had significantly improved the quality of target texts, according to external raters. Subsequently, the teacher of this experimental course has spontaneously continued to include this type of training in her regular work. Other colleagues have also undertaken similar experiences and expressed their positive evaluation of them. The aim of this present article is to report more fully on the methodology which was followed in the experimental course. This could provide a useful starting point for discussion for those teachers who would like to experiment with this type of training in their own classes.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".