Grammatical Features in Language Contact Setting: The Case of 3è and 1ère students of GBHS Koza and GHS Mozogo
Bibliographic record
Abstract
The most common way that languages influence each other is in the exchange of words. The present study deals with grammatical features in essays written by students of GBHS Koza and BHS Mozogo and their natural occurring interactions which are the empirical foundations of primary data source. The research adopted the qualitative and quantitative approaches. The corpus comprises 250 essay writing scripts collected in February 2024. The data were processed and analysed using Kachru (1983a) theory on postcolonial and/or world Englishes. Results showed a new stream of CamFE in the grammatical features found in students’ essays and interactions which include haphazard relative pronouns, articles omission, object omission in nominal phrase, lack of subject-verb agreement, possessive adjectives, misplacement of adjectives, non-standard construction of interrogative sentences and adjectival reduplication.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.142 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".