Language management, discursive power, and English as lingua franca in island countries and territories
Bibliographic record
Abstract
Both geographical factors and colonial histories have contributed to the marginalization of many islands. In the context of globalization, European colonial languages often dominate, and the Standard English ideology has been gradually internalized alongside the spread of English worldwide. Islands face an apparent tension between promoting local languages for the purpose of strengthening social and cultural cohesion and maintaining the favored status of European colonial languages in order to facilitate integration into global markets. Languages are, however, ideologically constructed, and the dominant status of English and other European languages on islands has created a cultural system of ideas, norms, and values originating from the West. This turns islands into norm followers, creating difficulties for the construction of island identities and making it impossible to act from a position of discursive power on the international plane. This paper argues that island governments should carry out language management in such a way as to promote the idea of English as a lingua franca for use in global intercultural communications and thereby enhance the island’s discursive power while strengthening social and cultural cohesion.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| 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".