Back to Translation as Language
Bibliographic record
Abstract
In this article, the six authors discuss the question of whether Translation Studies should devote more attention to the linguistic aspect of translation, in view of the tendency in recent years to focus on its social functioning. In the first part, each author tackles one or more aspects of this issue; in the second part, the authors respond to each other's views. Topics covered include what kind of language production translation is, whether translational language arises out of a particular form of communication or is itself a linguistic system, the relationship of Translation Studies to linguistics and other disciplines, the behaviour of particular language pairs when they clash during translation, translational language from the producer's as opposed to the receiver's viewpoint, and the relation of the linguistic to the social and to the cognitive. Reference is made to methodologies such as keystroke logging and the use of corpora, and also to a range of past and present linguistic approaches to translation, from comparative stylistics to relevance theory. Suggestions are offered regarding the directions to be taken by linguistically oriented studies of translation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.052 |
| Scholarly communication | 0.012 | 0.021 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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 source (direct Gemma or distilled Codex), 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".