Translation as Culture Transfer: Evidence from African Creative Writing
Bibliographic record
Abstract
Translation as Culture Transfer: Evidence from African Creative Writing — Due to the impact of African oral tradition the language of African creative writing in European languages (French and English) poses specific translation problems. We wish to illustrate the various processes and techniques used to cope with these translation problems. The different translation techniques discussed will throw some light on well-known concepts in translation theory such as Newmark's semantic vs communicative translation, House's overt vs covert translation, Diller and Kornelius' primary vs secondary translation and Berman's "traduction ethnocentrique" vs "traduction hypertextuelle." Translation as culture transfer, particularly regarding non-related language cultures, has been discussed by translation theorists such as Mounin, Nida, Lefevere, and Snell-Hornby. Translating African creative works is a double "transposition" process: (1) primary level of translation i.e., the expression of African thought in a European language by an African writer; (2) the "transfer" of African thought from one European language to another by the translator. The primary level of translation results in an African variety of European languages, and the translator's task is to deal with the unique problems posed by this so-called non-standard language. This paper is focussed on the various translation techniques used by translators of African works. These translators show a clear preference for semantic, overt and "literal" translation, in which, in Nida's terms, formal equivalence is given priority over dynamic equivalence. Such an approach is judged by the translators to be the most reliable for an effective representation of African sociocultural and sociolinguistic reality in European languages.
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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 | 0.026 | 0.129 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".