Narratology meets Translation Studies, or, The Voice of the Translator in Children’s Literature
Bibliographic record
Abstract
When critics identify ‘manipulations’ in translations, these are often described and analysed in terms of the differing norms governing the source and the target languages, cultures and literatures. This article focuses on the agent of the translation, the translator, and her/his presence in the translated text. It presents a theoretical and analytical tool, a communicative model of translation, using the category of the implied translator, the creator of a new text for readers of the target text. This model links the theoretical fields of narratology and translation studies and helps to identify the agent of ‘change’ and the level of communication in which the most significant modifications take place. It is a model applicable to all translated narrated literature but, as examples illustrate, due to the asymmetrical communication in and around children’s literature, the implied translator as he/she becomes visible or audible as the narrator of the translation, is particularly tangible in translated children’s literature.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.047 |
| Scholarly communication | 0.010 | 0.016 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".