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Record W4309505052 · doi:10.32920/21596736

Supporting families and young deaf children with a bimodal bilingual approach

2022· preprint· en· W4309505052 on OpenAlexaboutno aff
Katherine Rowley, Kristin Snoddon, Rachel O’Neill

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsnot available
FundersEconomic and Social Research Council
KeywordsSign languageNeuroscience of multilingualismSociolinguistics of sign languagesManually coded languageSign (mathematics)LinguisticsGrammarLiteracyLanguage interpretationAmerican Sign LanguageVocabularyPsychologyPedagogy

Abstract

fetched live from OpenAlex

<p>This article reviews research and presents recommendations concerning bimodal bilingualism for families with young deaf and hard of hearing children. Bimodal bilingualism means deaf children and their families have access to a national sign language in addition to other spoken/written languages. National sign languages are one or more of the sign languages that make up the linguistic ecology of a country, including but not limited to British Sign Language (BSL) in the UK and American Sign Language (ASL) in Canada. National sign languages have their own vocabulary, grammar, and social rules of use, and many sign languages are used by deaf communities around the world. Bimodal bilingualism and enhanced family communication have long-lasting benefits for deaf children’s development and wellbeing. We look at how to support early bimodal bilingual communication and literacy, and the role of practitioners in guiding families.</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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.819

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 science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.339
Teacher spread0.309 · 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.

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

Citations3
Published2022
Admission routes1
Has abstractyes

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