MétaCan
Menu
Back to cohort
Record W1561705310 · doi:10.4324/9781315843575

English as a Second Language in the Mainstream

2014· book· en· W1561705310 on OpenAlexaboutno aff
Constant Leung, Chris Davison, Bernard Mohan

Bibliographic record

Venuenot available
Typebook
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsMainstreamLinguisticsComputer sciencePolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Introduction PART 1: AUSTRALIA1. ESL in Australisn schools: from the margins to the mainstreamChris Davison 2. Current policies, programs and practices in school ESLChris Davison 3. Integrating language and content: unresolved issuesChris Davison and Alan Williams 4. Identity and Ideology: the problem of defining and defending ESL-nessChris Davison PART 2: CANADA5. ESL in British ColumbiaMary Ashworth 6. The second language as a medium of learningBernard Mohan 7. Knowledge framework and classroom actionGloria Tang 8. Implementation of the Vancouver School Board's ESL initiativesMargaret Early and Hugh Hooper PART 3: ENGLAND9. England: ESL in the early daysConstant Leung and Charlotte Franson 10. Mainstreaming: ESL as a diffused curriculum concernConstant Leung and Charlotte Franson 11.Evaluation of content-language learning in the mainstream classroomConstant Leung 12. Curriculum identity and professional development: system-wide questionsConstant Leung and Charlotte Franson Conclusion

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)0.000
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.033
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0330.004

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 head0.011
GPT teacher head0.212
Teacher spread0.201 · 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
GenreOther

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

Citations167
Published2014
Admission routes1
Has abstractyes

Explore more

Same topicSecond Language Learning and TeachingFrench-language works237,207