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Record W4391301083 · doi:10.18192/olbij.v13i1.6618

Overcoming barriers to access in French immersion: Special education needs and socioeconomic status

2024· article· en· W4391301083 on OpenAlexaffvenueabout
Diana Burchell, Roksana Dobrin-De Grace, Elizabeth Kay‐Raining Bird, Xi Chen

Bibliographic record

VenueOLBI Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsDalhousie UniversityToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsSocioeconomic statusImmersion (mathematics)PsychologyEnvironmental healthMedicineMathematics

Abstract

fetched live from OpenAlex

Canadian French immersion (FI) programs have increased in popularity due to the social and developmental benefits of English–French bilingualism. However, several studies have shown that FI programs do not provide equitable access to diverse students, nor do they provide adequate support to these students once they gain access to the program. To examine these issues in finer detail, the current study interviewed eight parents on their child(ren)’s enrollment and participation in FI programs. We specifically queried the impact of special education needs (SEN) and socioeconomic status (SES) on these families’ experiences. Results showed that parents encountered barriers on multiple levels while supporting their children in the FI program. These barriers increased significantly for children who had SEN, and/or for children and families from low SES communities.

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 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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.030
GPT teacher head0.364
Teacher spread0.334 · 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 teacher head, not a consensus.

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
Published2024
Admission routes3
Has abstractyes

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