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Record W4309495779 · doi:10.32920/21596487

Framing Deaf Children’s Right to Sign Language in the Canadian Charter of Rights and Freedoms

2022· preprint· en· W4309495779 on OpenAlexaffabout
Jennifer J. Paul, Kristin Snoddon

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsCarleton University
Fundersnot available
KeywordsLinguistic rightsSign languageManually coded languageFundamental rightsCharterHuman rightsLinguisticsFraming (construction)Political scienceSign (mathematics)Bill of rightsRight to propertyLawGeographyMathematics

Abstract

fetched live from OpenAlex

<p>Sign language rights for deaf children bring a unique perspective to bear in the fields of both disability rights and language planning. This is due to the lack of recognition in existing case law of the right to language in and of itself. Deaf children are frequently deprived of early exposure to a fully accessible language, and as a consequence may develop incomplete knowledge of any language. Thus, in the case of deaf children the concept of sign language rights encompasses rights that are ordinarily viewed as more fundamental to human equality. This paper will take as a starting point the historical treatment of the enumerated disability ground in the Canadian Charter of Rights and Freedoms’ section 15(1) guarantee of equality rights. We argue that in order to meet deaf children’s specific biological and linguistic needs, these children’s right to sign language also needs to be recognized as an analogous ground for protection from discrimination. Sign language rights are framed in terms of an immutable characteristic of all children, namely the biolingual process for language acquisition. The biolingual process is the experiential and innate ability to acquire language. </p>

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.760
Threshold uncertainty score0.997

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.303
Teacher spread0.286 · 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 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

Citations4
Published2022
Admission routes2
Has abstractyes

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