English as an Agent of ‘Lingua-Cide’ and ‘Native Tonglocaust’ in Adekunle Ajasin University, Nigeria
Bibliographic record
Abstract
This study examines the role of English as an agent of lingua-cide, more specifically the case study of native tonglocaust among undergraduates in Adekunle Ajasin University, Akungba-Akoko, Ondo State. This work evolved out of the sociolinguistic consciousness that the entire populace needed to be re-orientated about the impending sociolinguistic effect and danger their indifferent language attitude posed towards native tonglocaust in term of national under-development, cultural alienation, individuals’ loss of ‘native’ identity, educational and mental incapacitation and social disintegration. Through re-orientation and affinity with one’s cultural value, the linguistic badge would be preserved; national vis-a-vis educational development would be enhanced; and most importantly, efficiency and effective development of mental ability and capacity in individuals would be encouraged. The study employed the descriptive research design. The data was collected using a self-designed questionnaire as the research instrument with a reliability coefficient of 0.73. Simple random sampling technique was adopted in the selection of the respondents for this research work. One hundred and eighty (180) students were randomly selected from the six faculties in the institution. Simple percentage was used in analyzing the data generated. The results revealed that many Nigerian native languages are beginning to experience a gradual ‘self-actualized’ crime of ‘native tonglocaust’ and ‘lingua-cide’ based on the ‘status’ prestige granted to English in its sociolinguistic usage. It is recommended that much more than ‘little love’ be shown towards the use of native languages while the ‘vernacular syndrome/consciousness’ be eradicated among the populace in order to encourage individuals to ‘develop mentally’, the nation to fully get ‘developed’, and affinity with the cultural vis-a-vis linguistic identity be restored so as to avoid native languages from moving into a state of being ‘loss’, ‘dead’, or ‘extinct’.
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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 | 0.001 |
| 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 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 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".