Bibliographic record
Abstract
The choice of language to convey specific message with the intention of influencing people is vitally important. As we all know; human experience involves so much migration and blending of people with different ethnic and language groups over time. This is important because it reminds us that differences in treatment of ethnic and language groups are based on social distinctions, not innate biological distinctions. Thus, we specifically explore respondents’ tussle to secure public accommodation and the infringement of right on accommodation in Yoruba on language discriminations. The paper adopted interview as a means of data collection with 10 respondents that cut across different government parastatal, institution, self-employed and artisan within Ibadan. The respondents’ interactions that were recorded were subjected to transcriptions. It was observed that the non-native speakers of Yoruba in Ibadan were discriminated against based on their ethnicity or language affiliations. This has exceptionally creates gaps, propelled disunity and hatred between the native and non-native speakers of Yoruba in Ibadan. Hence, the non-native speakers of Yoruba in their views opined that, if they can be permitted to live in the environments surrounded by their ethnic or language affiliations, there will be mutual intelligibility and it will give them advantage to interact effectively and peradventure, if quarrels emanates, they will be able to know the possible means of settling them. The paper concludes that, public awareness and enlightenment should be organized constantly by the host community; and that government should re- visit the issue of national language.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".