Translators’ subversion of gender-biased expressions: a study of the English translation of <i>The Three-Body Problem</i> trilogy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it