MétaCan
Menu
Back to cohort
Record W1984162668 · doi:10.1044/1058-0360(2004/026)

Effect of Phonemic Perception Training on the Speech Production and Phonological Awareness Skills of Children With Expressive Phonological Delay

2004· article· en· W1984162668 on OpenAlexaff
Susan Rvachew, Michele Nowak, Geneviève Cloutier

Bibliographic record

VenueAmerican Journal of Speech-Language Pathology · 2004
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsAlberta Children's HospitalMcGill University
Fundersnot available
KeywordsPhonological awarenessPerceptionPsychologyPhonological DisorderPhonologyAudiologyPhonemic awarenessSpeech productionControl (management)RhymeSpeech perceptionSpeech soundCognitive psychologySpeech recognitionLinguisticsComputer scienceMedicineArtificial intelligenceLiteracy

Abstract

fetched live from OpenAlex

Children with expressive phonological delays often possess poor underlying perceptual knowledge of the sound system and show delayed development of segmental organization of that system. The purpose of this study was to investigate the benefits of a perceptual approach to the treatment of expressive phonological delay. Thirty-four preschoolers with moderate or severe expressive phonological delays received 16 treatment sessions in addition to their regular speech-language therapy. The experimental group received training in phonemic perception, letter recognition, letter-sound association, and onset-rime matching. The control group listened to computerized books. The experimental group showed greater improvements in phonemic perception and articulatory accuracy but not in phonological awareness in comparison with the control group.

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)0.001
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.288
Teacher spread0.278 · 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

Citations127
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Speech-Language PathologySame topicReading and Literacy DevelopmentFrench-language works237,207