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Record W2956156557 · doi:10.1017/9781108333603.028

Bilingual Education and Policy

2019· book-chapter· en· W2956156557 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCambridge University Press eBooks · 2019
Typebook-chapter
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsTransformative learningNeuroscience of multilingualismPhenomenonTranslanguagingMultilingualismGlobalizationField (mathematics)Bilingual educationSociologyPedagogyPolitical scienceLinguisticsEpistemologyLaw

Abstract

fetched live from OpenAlex

Bilingual education is a simple label for a complex phenomenon (Cazden & Snow, 1990). Implemented all over the world, bilingual education (BE) has been a cutting-edge field of research and practice for the past fifty years. Linked to research on bilingualism (and multilingualism) in its interdisciplinary dimensions, the field of BE continues to grow exponentially in the twenty-first century as globalization, migration, and hyperconnectivity among people mean that we use language(s) differently. When most people in the world today use more than one named language to communicate in their everyday life, when so many children come to school with so many different language practices, and when the past fifty years of research have shown the various benefits of BE, it is surprising that BE is not offered more widely. Where do the obstacles lie? Who does BE serve and to what purpose? Which languages are favoured and which are not? How have all the different frameworks and types of programmes been researched? How has the field moved forward to propose more dynamic and transformative pedagogies of BE?

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.989
Threshold uncertainty score0.904

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.020
GPT teacher head0.209
Teacher spread0.189 · 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