Intralingual translation, cultural accessibility and the ethics of translation: The <i>Volxbibel</i> as a case study
Bibliographic record
Abstract
This article deals with the ethics of intralingual translation and cultural accessibility. Based on the analysis of five characteristic text examples of the Volxbibel, a German intralingual translation of the Bible which makes excessive use of local adaptive strategies and whose central aim is to make the Scriptures accessible to youngsters, it will be shown that cultural accessibility can only be achieved if the ethical dimension of semiotic translational transfer is taken duly into account. Methodologically, the analysis will be based on a contrastive pragmatic analysis of the Volxbibel and its canonical counterpart, the Lutherbibel. The results of the analysis reveal that ethically grounded intralingual translation can only be achieved when transfer actions are oriented, not only towards the translational skopos and the target-text, but, at the same time, respect the source-text author’s intention(s) and the source-text’s ideological and socio-cultural background. Finally, on the grounds of these results, a slight adjustment of Zethsen’s and Hill-Madsen’s criterial definition of translation is proposed, by explicitly integrating therein the ethical dimension. This would contribute to a more precise delineation of both intralingual and interlingual translation.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.017 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".