Article use in Cameroon English and in non‐standard British English
Bibliographic record
Abstract
ABSTRACT: This study is concerned with the various uses of articles in certain non‐standard dialects of British English and in Cameroon English (CamE). Variations in the use of definite and indefinite articles are dealt with. More specifically, the paper examines various contexts in which definite and indefinite articles are used in Cameroon: specific and non‐specific reference, institutional and non‐institutional meaning, count and noncount uses, among others. This paper is based on the observation that the influence of the British colonists, especially missionaries (many of whom were not always speakers of Standardized varieties of British English), on various CamE grammatical usages in general and article use in particular has so far been grossly under‐researched. In fact, in some contexts, a sizable portion of educated CamE speakers use the articles in much the same way as speakers of certain non‐standard dialects of the British Isles. One of the conclusions this paper arrives at is that the history of colonization and evangelization through mission schools might have played a major role in the transportation to, and transplantation into, the colonies (Cameroon in this case), of British non‐standard dialects, many features of which eventually took root.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".