Translating for Children: Using Alfredo Gómez Cerdá’s 'El árbol solitario' as a case study
Bibliographic record
Abstract
The study of translation of children’s literature is a recent phenomenon. The goal of this study is to explore the extent to which a translator needs to accommodate a child reader by making the text conform to the target culture. I examine two mainstream dual theories: “domestication”, which gives preference to the cultural and linguistic values of the target culture and “foreignization”, which leaves traces of the source culture and takes the readers out of their “comfort zone”. As a case study, I translated Alfredo Gómez Cerdá’s book, El árbol solitario from Spanish to English and compared my strategies with another translation of the book done in French. Following a panoramic overview of the history and translation of children’s literature in Spain as well as in Quebec, I introduce the translation theories which I have explored during the translation process and compare them to the French translation of the text.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".