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Record W2167036132 · doi:10.1017/s0142716407080125

Common and distinct cognitive bases for reading in English–Cantonese bilinguals

2008· article· en· W2167036132 on OpenAlexaff
Gigi Luk, Ellen Bialystok

Bibliographic record

VenueApplied Psycholinguistics · 2008
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsYork University
Fundersnot available
KeywordsPsychologyPhonological awarenessReading (process)CognitionLearning to readSet (abstract data type)Cognitive psychologyLinguisticsPhonologyIdentification (biology)Computer science

Abstract

fetched live from OpenAlex

ABSTRACT The study explores the relationship between phonological awareness and early reading for bilingual children learning to read in two languages that use different writing systems. Participants were 57 Cantonese–English bilingual 6-year-olds who were learning to read in both languages. The children completed cognitive measures, phonological awareness tasks, and word identification tests in both languages. Once cognitive abilities had been controlled, there was no correlation in word identification ability performance across languages, but the correspondence in phonological awareness measures remained strong. This pattern was confirmed by a principal components analysis and hierarchical regression that demonstrated a different role for each phonological awareness factor in reading performance in each language. The results indicate that phonological awareness depends on a set of cognitive abilities that is applied generally across languages and that early reading depends on a common set of cognitive abilities in conjunction with skills specific to different writing systems.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.038
GPT teacher head0.349
Teacher spread0.311 · 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.

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

Citations42
Published2008
Admission routes1
Has abstractyes

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