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On the native/nonnative speaker notion and World Englishes: Debating with K. Rajagopalan

2016· article· en· W2520732594 on OpenAlexaboutno aff
John Robert Schmitz

Bibliographic record

VenueDELTA Documentação de Estudos em Lingüística Teórica e Aplicada · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsVarieties of EnglishPrestigeAmerican EnglishActive listeningLinguisticsSubject (documents)Power (physics)SociologyBritish EnglishWorld EnglishesHistoryMedia studiesComputer scienceCommunicationLibrary science

Abstract

fetched live from OpenAlex

ABSTRACT In a series of three articles published in the Journal of Pragmatics (1995, henceforth JP), the purpose of the papers is to question the division of English spoken in the world into, on one hand, "native" varieties (British English, American English. Australian English) and, on the other, "new/nonnative" varieties (Indian English, Singaporean English, Nigerian English). The JP articles are indeed groundbreaking for they mark one of the first interactions among scholars from the East with researchers in the West with regard to the growth and spread of the language as well as the roles English is made to play by its impressive number of users. The privileged position of prestige and power attributed to the inner circle varieties (USA, UK, Canada, Australia and New Zealand) is questioned. Rajagopalan (1997, motivated by his reading of the JP papers, adds another dimension to this questioning by pointing to the racial and discriminatory stance underlying the notions "native speaker" and "nonnative speaker" (henceforth, respectively NS and NNS). Rajagopalan has written extensively on the issue of nativity or "nativeness"; over the years, Schmitz has also written on the same topic. There appears, in some cases, to be a number of divergent views with regard to subject on hand on the part of both authors. The purpose of this article is to engage in a respectful debate to uncover misreading and possible misunderstanding on the part of Schmitz. Listening to one another and learning from each another are essential in all academic endeavors.

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 imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0170.034
Scholarly communication0.0130.021
Open science0.0020.011
Research integrity0.0040.013
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.035
GPT teacher head0.370
Teacher spread0.335 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2016
Admission routes1
Has abstractyes

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