Translation of Violence in Children’s Literature: Violence in Translated <i>Peter Pan</i>
Bibliographic record
Abstract
This study explores how violence in children’s literature and translated children’s books is displayed for young readers, taking Peter Pan, written by Scottish dramatist James Matthew Barrie, as an example, and selecting two Chinese translations by Shiqiu Liang and Jingyuan Yang to conduct a comparative analysis of the texts. Violence in Peter Pan is represented by verbal violence, metaphorical violence and narrative violence. While anticipating that most elements of violence would be deleted or downplayed by the translators, this paper finds that violence is retained in the two translations based on textual analysis but with some different manifestations. In the translation of violence, Liang is more loyal to the source text and does not mark the special characteristics of figures due to any associated connotation of violence, while Yang’s translation makes the diction livelier in line with children’s language and renders the identities and behaviors of figures with more prominence. Their different interpretations of violence result from their different expectations for their readers.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".