Poetry Translation and Translation Criticism in Translation Journals of the Republican Period
Bibliographic record
Abstract
With a linguistic point of view, this article investigates the various aspects of poetry translation in Turkish Literature within the Republican Period. Our aim is to discuss the various manifestations of poetry translation in terms of the translation criticism and our discussion is based on the data taken from the three journals of translation published in the Republican era: Tercüme (1940-1966), Yazko Çeviri (1982-1984) and Metis Çeviri (1989-1992). Our findings indicate that literary clerk put a great emphasis on the poetry translation and express their views on translation via these journals. Accordingly, the poetry translation requires a distinct semiotic mechanism in order to transfer the linguistic material which is a combination of semantic, pragmatic, stylistic and rhetoric features from the source text into the target text. Our findings also show that the main point of discussion in the journals in terms of translation criticism is the (lack of) equivalence between the source text and target text, the specific linguistic devices to be used in the translation and the translation of stylistic features. It is evident from the discussions that the translation criticism in this period has limited contribution to the field due to fact that it approaches to the translation not as a linguistic process but an end product. Key words Translation, translation criticism, poetry translation, Tercüme, Yazko Çeviri, Metis Çeviri
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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 | 0.012 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".