MétaCan
Menu
Back to cohort
Record W2043731507 · doi:10.3138/cmlr.66.4.525

A Tale of Two Montréal Communities: Parents’ Perspectives on Their Children's Language and Literacy Development in a Multilingual Context

2010· article· en· W2043731507 on OpenAlexvenueaboutno aff
Caroline Riches, Xiao Lan Curdt‐Christiansen

Bibliographic record

VenueCanadian Modern Language Review/ La Revue canadienne des langues vivantes · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsLiteracyEthnic groupContext (archaeology)SociologyPerspective (graphical)MultilingualismFirst languageIdentity (music)Diversity (politics)Focus (optics)Cultural capitalLinguisticsMinority languageNeuroscience of multilingualismPedagogyGender studiesSocial scienceAnthropologyGeography

Abstract

fetched live from OpenAlex

This comparative inquiry examines the multi-/bilingual nature and cultural diversity of two distinctly different linguistic and ethnic communities in Montréal – English speakers and Chinese speakers – with a focus on the multi/bilingual and multi/biliterate development of children from these two communities who attend French-language schools, by choice in one case and by law in the other. In both of these communities, children traditionally achieve academic success. The authors approach this investigation from the perspective of the parents’ aspirations and expectations for, and their support of and involvement in, their children's education. These two communities share key similarities and differences that, when considered together, help to clarify a number of issues involving multi/biliteracy development, socio-economic and linguistic capital, minority/majority language status, mother-tongue support, home–school continuities, and linguistic identity.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.187

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0120.004
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.020
GPT teacher head0.331
Teacher spread0.311 · 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 designQualitative
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

Citations54
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Modern Language Review/ La Revue canadienne des langues vivantesSame topicMultilingual Education and PolicyFrench-language works237,207