Translators’ subversion of gender-biased expressions: a study of the English translation of <i>The Three-Body Problem</i> trilogy
Bibliographic record
Abstract
The Three-Body Problem trilogy, a work by Cixin Liu, won the Hugo Award, making it the first Asian science fiction work to achieve this. The English translation of this trilogy has garnered significant attention from academics, emphasizing its literary significance. However, the androcentric and gender-biased expressions in the original text, as well as the subversive translation used to mitigate them, have received little attention. This mixed methods study, based on Theo Hermans’ concept ‘modalities of normative force’ (1996), aims to examine the translation norms in this regard and discuss how these norms define the relation between source and target texts. The findings indicate that translators Ken Liu and Joel Martinsen were required to employ subversive translation norms to eliminate gender-biased content that might cause discomfort and aversion among the target audience. This highlights the importance of translators’ subjectivity in balancing divergent social and cultural contexts during the translation process.
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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 | 0.020 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".