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Record W2951938450 · doi:10.82308/6785

An exploration of heritage language maintenance among Arabic speakers in Montreal, Quebec

2018· article· en· W2951938450 on OpenAlexfundaboutno aff
Ruqayyah Shalaby

Bibliographic record

VenueeScholarship@McGill (McGill) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
FundersUniversity of TorontoMcGill University
KeywordsArabicHumanitiesHeritage languageSociologyVernacularEthnologyPsychologyArtPedagogyLinguisticsLiterature

Abstract

fetched live from OpenAlex

This research is an exploration of the experiences of six Arab-Canadians learning LA (Literary Arabic) as a heritage language in Montreal. Four of the six participants are Canadian born and two were born in France. All six participants are undergraduate university students, aged 21 to 24. Two semi-structured interviews were conducted with each of the participants. Results of the study indicate that the participants who were able to maintain their spoken vernacular of Arabic in addition to developing literacy in the language are those who had their parents' support as well as themselves making efforts to keep both forms of the language. Factors contributing to heritage language maintenance and loss are discussed with reference to the findings of this study.

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)0.002
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 score0.035
Threshold uncertainty score0.241

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0220.006
Scholarly communication0.0030.001
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.045
GPT teacher head0.361
Teacher spread0.316 · 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

Citations2
Published2018
Admission routes2
Has abstractyes

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