Kachru’s Three Concentric Circles Model of English Language: An Overview of Criticism & the Place of Kuwait in it
Bibliographic record
Abstract
This paper attempts to examine in a descriptive way the pioneering model of “World Englishes” proposed by Kachru in the mid-1980s that allocates the presence of English into three concentric circles: The Inner Circle, the Outer Circle, and the Expanding Circle. The Inner Circle presents the countries where English is used as a native language and as a first language among people. These countries include the USA, the UK, Canada, Australia, and New Zealand. The Outer Circle includes countries that have old historical British colonial relations and where English is commonly used in social life or the government sectors. Most of the countries that belong to this circle are former colonies of the British Empire, such as India, Malaysia, Singapore, Ghana, Kenya, and others. The usage of English in these countries is similar to what is known as English as a second language. The third circle, The Expanding Circle, includes countries that introduce English as a foreign language in schools and universities, mostly for communicating in English with the Inner and Outer Circles. Such countries include Turkey, Saudi Arabia, The Emirates, Japan, China, Korea, and others. Since its first introduction in 1985, Kachru's Three Concentric Circles Model of English Language has occasioned a great debate. Many linguists considered it one of the most influential models for understanding the use of English in different countries. Some, on the other hand, including Kachru himself, criticized the model for its oversimplification and the unclear membership to the circles. In addition to an overview of criticism on Kachru's model based on different studies, this paper tries to locate the place of ELT in Kuwait among the three circles.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.007 | 0.023 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| 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".