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Record W2169874440 · doi:10.1093/deafed/enm020

What Really Matters in the Early Literacy Development of Deaf Children

2007· review· en· W2169874440 on OpenAlexaff
Charles Mayer

Bibliographic record

VenueThe Journal of Deaf Studies and Deaf Education · 2007
Typereview
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsYork University
Fundersnot available
KeywordsPsychologyLiteracyReading (process)Hearing lossDevelopmental psychologyLanguage developmentDeaf educationEarly literacySign languageLinguisticsPedagogy

Abstract

fetched live from OpenAlex

With much earlier identification of hearing loss come expectations that increasing numbers of deaf children will develop literacy abilities comparable to their hearing age peers. To date, despite claims in the literature for parallel development between hearing and deaf learners with respect to early literacy learning, it remains the case that many deaf children do not go on to develop age-appropriate reading and writing abilities. Using written language examples from both deaf and hearing children and drawing on the developmental models of E. Ferreiro (1990) and D. Olson (1994), the discussion focuses on the ways in which deaf children draw apart from hearing children in the third stage of early literacy development, in the critical move from emergent to conventional literacy. Reasons for, and the significance of, this deviation are explored, with an eye to proposing implications for pedagogy and research, as we reconsider what really matters in the early literacy development of 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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.104
GPT teacher head0.465
Teacher spread0.361 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations218
Published2007
Admission routes1
Has abstractyes

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