MétaCan
Menu
Back to cohort
Record W2335440160 · doi:10.5539/elt.v9n5p77

‘The Burden of Diversity’: The Sociolinguistic Problems of English in South Africa

2016· article· en· W2335440160 on OpenAlexvenueno aff
Berrington Ntombela

Bibliographic record

VenueEnglish Language Teaching · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsLanguages of AfricaIndigenousIndigenous languageMedium of instructionHegemonyFirst languageSociologyMindsetPopulationLanguage policyLinguisticsGender studiesPolitical sciencePedagogyLaw

Abstract

fetched live from OpenAlex

<p>At the emergence of democracy in South Africa the government corrected linguistic imbalances by officialising eleven languages. Prior to that only English and Afrikaans were the recognised official languages. The Black population had rejected the imposition of Afrikaans as the medium of instruction. However, such rejection did not mean the adoption of indigenous languages as media of instruction; instead English was supposedly adopted as a unifying language among linguistically diverse Africans. Such implicit adoption of the English language has created a stalemate situation in the development of African languages to the level of English and Afrikaans. Although there is a widespread desire to promote indigenous languages to the level of being media of instruction, the desire is peripheral and does not carry the urgency that characterised the deposition of Afrikaans in the 1976 uprisings. On the other hand this paper argues that the hegemony of English language as a colonial instrument carries ambivalence in the minds of Black South Africans. Through ethnographic thick description of two learners, this hegemony is illustrated by the ‘kind’ of English provided to most Black South African learners who do not have financial resources to access the English offered in former Model C schools. The paper concludes that Black South Africans do not only need urgency in the promotion and development of indigenous languages, but further need to problematize, in addition to the implicit adoption of English language, the quality of the language they have opted. The paper therefore suggests that this is possible through a decolonised mindset.</p>

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.038
GPT teacher head0.352
Teacher spread0.314 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations13
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueEnglish Language TeachingSame topicMultilingual Education and PolicyFrench-language works237,207