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Record W1977379117 · doi:10.1080/07434610601151803

The effects of phonological awareness instruction on beginning word recognition and spelling

2007· article· en· W1977379117 on OpenAlexaff
Joan E. Truxler, Bernard M. O'Keefe

Bibliographic record

VenueAugmentative and Alternative Communication · 2007
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of TorontoArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsSpellingPhonological awarenessWord (group theory)Word recognitionComputer scienceLinguisticsPhonemic awarenessPsychologySpeech recognitionNatural language processingReading (process)

Abstract

fetched live from OpenAlex

This investigation examined the effects of phonological awareness instruction on four children, aged 8-9 years, with complex communication needs (CCN) who used augmentative and alternative communication (AAC). During Experiment 1 all four children acquired letter/sound correspondence and phoneme awareness at varying levels. One child reached criterion. Three children maintained their skills and one child generalized to 10 untaught letters/sounds. During Experiment 2 one of four children reached criterion in beginning word recognition and improved her post-intervention word identification. Three children increased their spelling ability. The results are interpreted within the framework of current theory and are suggestive of the skills children with complex communication needs may need in order to acquire early decoding skills.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.062
GPT teacher head0.367
Teacher spread0.305 · 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

Citations35
Published2007
Admission routes1
Has abstractyes

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