Translator’s Creativity found in the Process of Japanese-Korean Translation*
Bibliographic record
Abstract
It has been commonly understood (in Korea) that Japanese and Korean’s linguistic similarities make Japanese-Korean translation easier than translations from other languages into Korean. However, this does not concur with the fact that Japanese-Korean translations are not better compared to other language combinations from the readers’ point of view. This might be due to the problem of translationese caused by language interference, but the present research zooms in on translator’s ‘creativity’ and observes the effects of translator’s creativity on translation quality. The method of research involves analyzing transcriptions gathered through Think Aloud Protocol (TAP) from thirteen professional translators for the purpose of evaluating the strategies used by the translators and examining the occurrence of shift. The research confirms that Japanese-Korean translator creativity is restricted, and such result demonstrates the need for scholars and educators in translation education to recognize and appreciate the concept of creativity and to devise new educational approaches for nurturing creativity.
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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 | 0.001 |
| 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) | 0.001 | 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".