Nigerian English Usage in Literature: A Sociolinguistic Study of Wole Soyinka’s The Beatification of Area Boy
Bibliographic record
Abstract
This paper examined the imbalances created by social situations and captured in the English language usage by the characters in Wole Soyinka’s The beatification of area boy. The play, set in the busy city of Lagos, is a theatrical typification of the Nigerian society that creates variety differentiation in language use. The sociolinguistic data for the analysis were extracted from the primary text. The findings indicate that, in the play, Soyinka succinctly displays characters as linguistic pointers to showcase the peculiarities in Nigerian English usage that differentiate the linguistic behaviours of Nigerians from other Englishes. The study reveals the categorisation of the ‘spoken’ varieties into Nigerian Pidgin, Incipient bilingual, Local colour variety and the Nigerian literary variety. These features which manifest at the phonological, semantic, lexical, syntactic and pragmatic levels altogether combine to represent the typical linguistic situation in a non-native speaker environment. The linguistic variations, when juxtaposed with sociolinguistic variables, explicitly express the domestic adaptations and modifications in English language usage suggestive of the playwright’s representation of the Nigerian multilingual society.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".