A Study of Chadian Learners/ Speakers of English’s Pronunciation
Bibliographic record
Abstract
With the development of English as the world’s lingua franca, there is a serious rush for the language by many countries, which have no past history with Britain, the US or any other country of the Inner Circle (Kachru 1988). Chad, which was colonized by France is one of those countries (Anderson 2008). In those countries, where English is generally learnt as a foreign language by an elitist group, the language progressively develops and has local stable features among it speakers. With the increasing number of Chadian learners of English in Nigerian, Sudanese and Cameroonian universities, as well as in other English-speaking countries, it is interesting to look at the way they pronounce English words. From the interlanguage framework, this study analyses some speech produced by postgraduate Chadian learners of English (N=20). The focus is on some difficult consonants, consonant clusters, vowels and word stress.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".