The Translator’s New Clothes Translating the Dual Audience in Andersen’s “The Emperor’s New Clothes”
Bibliographic record
Abstract
‘The Emperor’s New Clothes’ is one of Hans Christian Andersen’s best known fairy tales. All over the world it appeals to children and adults alike. As such it belongs to what Zohar Shavit (1986) called ‘children’s literature with an ambivalent audience.’ This study addresses the question as to how translators deal with this dual audience. Do they stick to it or do they rather adapt the story more clearly to children? The corpus consists of the original Danish text and fourteen translations and adaptations in six languages. The research focuses on the implied dual audience as it is given shape in source and target texts on the phonological, lexical-semantic, syntactic and pragmatic levels. The first part of the article investigates how substitutions, omissions and rearrangements might change the dual orientation of the text. The second part deals with the additions and examines how they influence the divertive, creative, emotional and educative function of the text.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".