Pidgin Englishes, marginality and fragility in Nollywood cinema: Exploring language, culture and storytelling
Bibliographic record
Abstract
Nigerian Pidgin English serves as a means of communication and cultural expression in Nollywood films. Its usage is often stigmatized and marginalized, relegating Nigerian Pidgin English to inferior status compared to standard English. This article explores the sociocultural dynamics surrounding language ideologies and the tensions between monolingual and multilingual language enterprises. It analyses the cultural significance of storytelling in Nollywood, where language plays a crucial role in conveying community values and preserving knowledge systems. By examining the work of Nollywood director Ema Edosio, who focuses on authentic Nigerian narratives, the article underscores the power of Pidgin English as a tool for agency, cultural mediation and for challenging dominant linguistic paradigms. Perhaps it is not Nigerian Pidgin English that is fragile or marginalized.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".