A Contrastive Study on Translations of Li Qingzhao’s Ru Meng Ling: From the Perspective of Subjectivity and Subjectification
Bibliographic record
Abstract
Poetry is quite personal in the sense that it is mainly written for the expression of the poets’ personal emotions, feelings, attitudes, point of views, etc. Therefore, it is endowed with strong subjectivity. Poets resort to different linguistic devices to realize their subjectivity in their poetry, which is termed as subjectification. Consequently, poets’ subjectivity constitutes an essential part of the meaning of their poetry. Thus, in the translation of poetry, it is vital for the translator to reconstruct the poets’ subjectivity. This paper attempts to conduct a contrast of thirteen English versions of Ru Meng Ling by Li Qingzhao from the perspective of subjectivity and subjectification. It will first make an analysis of Li Qingzhao’s subjectivity and subjectification in her Ru Meng Ling from the three dimensions, perspective, affect and epistemic modality. Then, a contrast is provided among the thirteen English versions. It is found that it is difficult to achieve a complete equivalence of subjectification due to the translators’ subjectivity in their translation. However, a good translator attempts to eschew his/her own subjectivity and reconstruct the poet’s subjectivity as much as possible.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".