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Record W1510217489 · doi:10.21810/sfuer.v5i.357

The absence of ESL students’ voices in education

2014· article· en· W1510217489 on OpenAlexvenueaboutno aff
Yeonjung Lee

Bibliographic record

VenueSFU Educational Review · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsPaceEllMainstreamCurriculumEnglish-language learnerMathematics educationPedagogyEnglish languageLanguage assessmentPopulationPsychologySociologyTeaching methodPolitical scienceGeography

Abstract

fetched live from OpenAlex

Canada’s classrooms are becoming increasingly diverse with a fast-growing school population of students whose first language is not English. They are English as Second Language (ESL) students; each pupil is an English Language Learner (ELL). Since 1990, the number of students identified as needing ESL services in British Columbia has more than tripled. These students face challenges in keeping pace academically and learning a new language. The challenge is especially great when students are placed in mainstream English-language classrooms before they develop their language proficiency. With its focus on the development of academic skills, the ESL curriculum may not be providing enough support to help ELLs fully participate in mainstream English classes. The lack of support will result in unequal access to high-quality learning opportunities and cultural gaps within schools. English language learners (often referred to as ESL students) may become marginalized and may prematurely reach a plateau in their English acquisition.

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)0.006
metaresearch head score (Gemma)0.009
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: none
Teacher disagreement score0.192
Threshold uncertainty score0.382

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0030.004
Scholarly communication0.0060.004
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.054
GPT teacher head0.540
Teacher spread0.486 · 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

Citations1
Published2014
Admission routes2
Has abstractyes

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