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The role of phoneme and onset‐rime awareness in second language reading acquisition

2011· article· en· W2170101179 on OpenAlexafffund
Corinne A. Haigh, Robert Savage, Caroline Erdos, Fred Genesee

Bibliographic record

VenueJournal of Research in Reading · 2011
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsMcGill University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsHard rimePhonological awarenessPsychologyReading (process)LinguisticsPsycholinguisticsRhymePhonemic awarenessFrench immersionLearning to readPhonologyLanguage acquisitionDevelopmental psychologyCognitionMathematics educationPoetry

Abstract

fetched live from OpenAlex

This study investigated the link between phoneme and onset‐rime awareness and reading outcomes in children learning to read in a second language (L2). Closely matched phoneme and onset‐rime awareness tasks were administered in English and French in the spring of kindergarten to English‐dominant children in French immersion programmes (n=98). Regression analyses indicated that English phoneme manipulation was a significant predictor of both English and French reading outcomes after controlling for kindergarten knowledge of letter names and word identification. French onset‐rime knowledge measured in kindergarten accounted for significant variance for French reading outcome measures. Results support the existence of a link between English phoneme manipulation in kindergarten and both English and French reading outcomes in Grade 2. Practically, these results provide information about what phonological awareness measures can be used in kindergarten to predict later reading outcomes for children learning to read in an L2.

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)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.063
GPT teacher head0.409
Teacher spread0.346 · 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

Citations30
Published2011
Admission routes2
Has abstractyes

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