The Effects of Translation Shifts on The Readability in Translation of Children’s Literature
Bibliographic record
Abstract
This study examines the effects of translation shifts on the level of readability in translating children’s literature. It conducts this study on three Persian translations of “Alice’s Adventures in the Wonderland” to rank Catford’s shifts based on their effects on the readability of translation. To do that, in this study, the typology of Catford’s shifts will be extended, and the way to measure text readability will be modulated to include the effects of these shifts on the translation readability. Thus, Ranking 14 types of shifts, the study reveals that complex shifts (represented as clauses and groups in the texts) are more effective than simple shifts (which are symbolized as single word -nouns and adjective, determiners- in the text) on the readability of translations. This means the complex shifts are more recognizable for children. Of course, verbs, although are mostly the representatives of simple shifts, are very effective on readability of text. Since, they, along with clause and group segments, are will recognizable for them. Therefore children cannot determine the place of single words in the text, but are expert in realizing word clusters in form of clauses and groups.
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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 | 0.003 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".