Plural marking in Nigerian Pidgin English: A sociolinguistic study of diaspora speakers
Bibliographic record
Abstract
This study examines plural marking in Nigerian Pidgin English (NPE) in light ofan ongoing change in the language. Many older studies hold that dem and zeromarkings are the dominant plurals used in NPE (Mafeni 1971, Faraclas 1989) whilemore recent studies hold that -s is the dominant plural in NPE (Deuber 2005, Ogunmodimu 2014). This apparent time study assesses the choice of plurals in the spontaneous speech derived from sociolinguistic interviews with 20 older and youngerNPE speakers living in Winnipeg to bring to light the patterning of this change.The interaction between age and gender is found to be statistically significant as -sis the dominant plural used among the educated middle-class speakers of NPE inWinnipeg, with younger speakers and female speakers leading the change whilethe older male speakers are slower to adopt this change.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".