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Record W2019626760 · doi:10.1353/sls.2012.0013

Recognition of Langue des Signes Québécoise in Eastern Canada

2012· article· en· W2019626760 on OpenAlexfundaboutno aff
Anne-Marie Parisot, Julie Rinfret

Bibliographic record

VenueSign language studies · 2012
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsnot available
FundersGovernment of OntarioLouisiana Board of RegentsU.S. Department of Health and Human Services
KeywordsLegislationGovernment (linguistics)Sign (mathematics)Sign languageBilingual educationNeuroscience of multilingualismPolitical scienceSociologyLinguisticsPublic administrationPedagogyLaw

Abstract

fetched live from OpenAlex

This contribution addresses language policy and planning (LPP) for sign languages (SL) in Canada, focusing on the situation of Langue des signes québécoise (LSQ) in the east, particularly in Quebec and Ontario. Drawing on papers from the deaf press, government and scientific reports, legislation, experiments, surveys, social services, and official educational programs, we present an overview of the distribution of SLs across Canada, which has two legitimate SLs: American Sign Language (ASL) and LSQ. This characterization includes a description of educational policies and focuses on the provinces of Ontario and Quebec. We also describe the actions undertaken by Canadian Deaf communities and their arguments in support of the official recognition of SL, with an emphasis on education. We provide a detailed account of what has been achieved in terms of the government's response to these efforts (e.g., implementation of an LSQ-French bilingual program in Ottawa and Montreal deaf schools). Finally, we offer a critical look at SL policies and discuss issues surrounding the (non)recognition of SL in deaf education.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.761

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0120.004
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.077
GPT teacher head0.352
Teacher spread0.275 · 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 designObservational
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

Citations40
Published2012
Admission routes2
Has abstractyes

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