To the Problem of Linguistic and Cultural Cooperation in the Process of Language Contacts
Bibliographic record
Abstract
The spread of English across the Globe and its status as an official language in many countries, such as the Gambia, India, Cameroon, Canada, Kenya, Malta, Nigeria, the United States, South Africa, has determined its role and impact on a huge number of language versions of modern English variations. Due to the dominant influence of English on the spread of language diversity and the consolidation of its official status, the language policy of many countries, such as India, Pakistan, Nigeria, is carried out in line with the provision of education in English. The role of the English language in the development of the language policy in many countries is activated by both domestic and foreign policy of the state. The aim of domestic policy includes the solution of problems such as the preservation of the status of indigenous languages and strengthening their role in all spheres of society, the promotion of educational programs. However, in practice, this role is played by the English language, as a universal means of academic communication in schools and universities. Foreign language policy is aimed at preserving the status of the English language and is a set of language measures aimed at maintaining the structure of the language and its various forms of existence (Baghana et al., 2014). In our study, we analyze the linguistic, cultural features of such English language variation as the Nigerian English language. Nigeria is one of the largest countries in West Africa today, presenting the mixture of up to 250 language ethnic groups, where English, having the official status, has the role of uniting all ethnic variations as the means of communication. The official language policy of Nigeria is implemented in the promotion of English in all social spheres, such as education, politics, economics, diplomacy, jurisprudence, media. English is the main languages used in modern media and communications in Nigeria, namely television, Internet, etc. Each of the 36 States of Nigeria has its own radio station, which informs residents about the latest development in the country and in each state in English (Cruse, 1998). The English language has exerted a great influence on Nigerian culture, the results of which are the processes connected with losing a part of Nigerian cultural identity.
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 | 0.022 | 0.081 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".