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Record W3153786462 · doi:10.1075/jicb.20015.dav

“More languages means more lights in your house”

2021· article· en· W3153786462 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Immersion and Content-Based Language Education · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsMcGill UniversityUniversity of Regina
Fundersnot available
KeywordsImmigrationNeuroscience of multilingualismRefugeeFrench immersionMathematics educationPedagogyLinguisticsSociologyPsychologyPolitical science

Abstract

fetched live from OpenAlex

Abstract French immersion programs throughout Canada have historically consisted of predominantly Anglophone populations pursuing bilingualism in the country’s two official languages, English and French. Nevertheless, recent developments in immigration and refugee resettlement have contributed to increasingly diverse student backgrounds nationwide (Statistics Canada, 2014). Researchers have explored the motivation for Allophone families to pursue FSL in Canada ( Dagenais & Berron, 2001 ; Dagenais & Jacquet, 2000 ; Mady, 2010 ); the language proficiency of Allophone learners in FSL programs ( Bérubé & Marinova-Todd, 2012 ; Carr, 2007 ; Mady, 2015 ); and the perspectives of FSL educators with respect to such learners ( Mady, 2016 ; Mady & Masson, 2018 ; Roy, 2015 ). The present study draws from interview data to explore and compare the experiences and perspectives of seven Allophone parents and 43 FI educators in Saskatchewan. In the present article, we examine the perspectives of FI educators, the experiences of Allophone families, and the implications for immersion programs worldwide.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.806
Threshold uncertainty score1.000

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)0.0010.000

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 head0.029
GPT teacher head0.284
Teacher spread0.254 · 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