Throwing down the gauntlet : the challenge represented by current research in the fields of World Englishes and English as a Lingua Franca
Bibliographic record
Abstract
Throwing down the gauntlet: the challenge represented by current research in the fields of World Englishes and English as a Lingua Franca "Language is very powerful.Language does not just describe reality.Language creates the reality it describes.i " Desmond Tutu "An Englishman's way of talking absolutely classifies him.The moment he talks, he makes some other Englishman despise him!"My Fair Lady This paper is based on insights gained at the International Association of World Englishes (IAWE) conferences which I had the privilege of attending in Vancouver and Melbourne in 2010 and 2011 and on research that I have conducted since 2010 in what was then a new field of study for me.The expression "throwing down the gauntlet" takes us back to a time when a knight would challenge an opponent to a duel by tossing one of his gauntlets (armoured gloves) onto the ground.If the opponent picked up the gauntlet, it meant that the challenge had been accepted.This paper employs this central metaphorical image and argues research in World Englishes (WE) and English as a Lingua Franca (ELF) offer challenges to which practitioners in TESOL (Teaching of English to Students of Other Languages) should respond.Metaphorically speaking, a challenge has been issued and a response is required. World EnglishesAn essential starting point involves outlining the intellectual territory occupied by fields of World Englishes and English as a Lingua Franca.WE 'establishes a conceptual framework for investigating the spread and functions of English in global contexts' (Coetzee-Van Rooy 2010: 8) which includes research into the cultural, socio-linguistic and educational attributes of developing and established varieties of English.The use of the plural 'Englishes' indicates the inclusivity and pluricentricity at the heart of the discipline.WE contests the possibility of a monolithic English and acknowledges the linguistic rights of divergent and emerging varieties of the English language.It asserts that varieties of English cannot be viewed simply as deviations from an acknowledged standard from traditionally native-speaking countries, such as the United Kingdom and America.WE is multi-disciplinary in that it draws on theoretical perspectives from fields as divergent as Applied Language studies, Didactics, English studies, Literature, Cultural Studies and Identity Theory.Its underpinnings are deeply political, embedded in the
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".