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Record W2134393291 · doi:10.5539/ijel.v2n2p21

Code-switching in Botswana’s ESL Classrooms: A Paradox of Linguistic Policy in Education

2012· article· en· W2134393291 on OpenAlexvenueno aff
Ambrose B. Chimbganda, Tsaona Mokgwathi

Bibliographic record

VenueInternational Journal of English Linguistics · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsCode-switchingPrideContext (archaeology)EthnographyIdentity (music)Code (set theory)SociologyPedagogyResource (disambiguation)PsychologyLinguisticsMathematics educationPolitical scienceGeographyComputer scienceLaw

Abstract

fetched live from OpenAlex

Code-switching in the classroom is known to take place across a wide range of subjects in multilingual settings in Africa and, indeed, throughout the world; yet it is often regarded pejoratively by some educational policy makers. This article looks at code-switching (CS) in Botswana’s senior secondary schools within the context of the country’s language-in-education policy, which states that English is the official language of learning and teaching while Setswana is the national language used for identity, unity and national pride. The data are derived from an ethnographic study conducted at four high schools in the north-eastern part of the country, which is uniquely multilingual. The findings indicate that code-switching from English to Setswana is quite prevalent in content subjects, and is used as a pedagogic resource to clarify the knowledge of the subject matter and to reduce the social distance between the teacher and learners. From the findings, it is suggested that code-switching in ESL classrooms in Botswana should be recognized not only as a communicative strategy for instruction, but also as a way of creating classroom warmth and friendliness.

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)0.287
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.952
Threshold uncertainty score0.719

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.287
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.041
GPT teacher head0.450
Teacher spread0.410 · 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 designNot applicable
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

Citations14
Published2012
Admission routes1
Has abstractyes

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Same venueInternational Journal of English LinguisticsSame topicMultilingual Education and PolicyFrench-language works237,207