Bibliographic record
Abstract
Abstract French translations of Nigerian literature have evolved since its introduction in France in 1953. Previous research documented periodic gaps and accounted for an ongoing translation of Nigerian literary texts in France. Since Nigerian literature has emerged as one of France’s most translated Anglophone African works, this study pursues this field by investigating how the French target culture receives and legitimizes this new literature. Consequently, it discusses several zones for the reception of Nigerian literature translated in France. Through a case study of the translation of a Nigerian writer, a general analysis of a mainstream French magazine and review platforms, and information garnered from interviews and fieldwork in France, this study shows that the prestige of a publisher, an author’s literary status, and thematic and political leanings contribute to successful reception and visibility in the target literary system. Critical and popular reception analyses from this study indicate progress in the domain of translated Nigerian literature, such as that translated Nigerian literature is featured in a mainstream French magazine. However, they show a lack of more comprehensive and systematic representation crucial for literary legitimization and visibility of translated Nigerian literature.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".