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Record W2531450668 · doi:10.5539/jel.v5n4p221

A Standalone but not Lonely Language: Chinese Linguistic Environment and Education in Singapore Context

2016· article· en· W2531450668 on OpenAlexvenueno aff
Huang Min, Cheng Kangdi

Bibliographic record

VenueJournal of Education and Learning · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
FundersSouthwest UniversityNanyang Technological University
KeywordsSyllabusBilingual educationContext (archaeology)Neuroscience of multilingualismSociologyLinguisticsPsychologyLanguage policyPedagogyHistory

Abstract

fetched live from OpenAlex

Bilingual education policy in Singapore permits the students learn both English as working language and mother tongues, such as Chinese, as L2 anchoring to culture heritage. Starting from historical and sociolinguistic reasons, this paper is intended to provide a panoramic view of Chinese education in Singapore, clarify and compare Chinese education syllabi on different levels from primary schools to pre-university schools, cover social movement support on promoting Chinese learning and use in this multilingual society. Meanwhile, Singapore’s success in bilingual education cannot hide its own problems. The status of Chinese dialects, the competitive role of English, the rational and practicality for proficient bilingual users, the choice of teaching methodologies between L1 and L2, are all remaining open to further discussing and probing for language policy making and modification in the future.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0040.002
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.021
GPT teacher head0.406
Teacher spread0.384 · 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 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

Citations0
Published2016
Admission routes1
Has abstractyes

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