Is Achieving a Scientific and Coherent Account of Translation an Illusion? - Looking into the Traditional Approaches to Translation Studies
Bibliographic record
Abstract
In the past several decades, translation studies have been developing quickly, lots of theoretical fruits have been achieved. Nevertheless, up to now, few theoretical fruits can be said to form a scientific and coherent account for translation studies, with Gutt’s theory as expounded in Translation and Relevance (2004) being one of some brilliant exceptions in this regard. Through unveiling the methodological advantages that underlie the success of the Gutt’s theory, the present paper purports to provide a reference for future translation scholars in forming a scientific and coherent account for translation studies.
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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 | 0.061 | 0.077 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.009 | 0.079 |
| Scholarly communication | 0.024 | 0.050 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".