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Record W2070452678 · doi:10.3138/cmlr.64.4.581

American Sign Language and Early Intervention

2008· article· en· W2070452678 on OpenAlexvenueaboutno aff
Kristin Snoddon

Bibliographic record

VenueCanadian Modern Language Review/ La Revue canadienne des langues vivantes · 2008
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsAmerican Sign LanguageSign languageIntervention (counseling)Hearing lossPsychologyPerspective (graphical)Spoken languageSign (mathematics)Language acquisitionLanguage developmentDeaf educationLinguisticsDevelopmental psychologyMedicineAudiologyMathematics educationComputer science

Abstract

fetched live from OpenAlex

Abstract: Since the beginning of the twenty-first century, the introduction in several countries of universal neonatal hearing screening programs has changed the landscape of education for deaf children. Due to the increasing provision of early intervention services for children identified with hearing loss, public education for deaf children often starts in infancy. While infant hearing screening and intervention programs hold promise for enhancing deaf children's language development, concerns have been raised that these programs may not provide a well-informed or adequate range of options for families with deaf children. In particular, Ontario children who receive cochlear implants have frequently not been provided with support for learning American Sign Language (ASL), despite evidence for the benefits that learning ASL confers on spoken and written English language development in deaf children. This paper presents an applied linguistics perspective on early intervention policies and programs for deaf children.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.629
Threshold uncertainty score0.737

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.001

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 head0.022
GPT teacher head0.280
Teacher spread0.258 · 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

Citations50
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Modern Language Review/ La Revue canadienne des langues vivantesSame topicHearing Impairment and CommunicationFrench-language works237,207