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Record W2040360702 · doi:10.1093/wsr/wsr010

The role of tone awareness and pinyin knowledge in Chinese reading

2011· article· en· W2040360702 on OpenAlexaff
Li Yin, Wenling Li, Xi Chen, Richard C. Anderson, Jie Zhang, Hua Shu, Wei Jiang

Bibliographic record

VenueWriting Systems Research · 2011
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPinyinPsychologyTone (literature)Phonological awarenessReading (process)SentenceLiteracyLinguisticsDevelopmental psychologyChinese charactersPedagogy

Abstract

fetched live from OpenAlex

Previous literature has established that tone awareness is significantly related to reading development in young children (age 3–6 years) across Chinese-speaking societies. To date, no study has been conducted to explicitly examine how tone awareness contributes to reading at the intermediate level of primary schooling, or the relationship between tone awareness and pinyin instruction, a demonstrated booster for phonological awareness in Chinese children. The present study aimed to fill this gap by investigating the relationship between tone awareness and pinyin proficiency, and the contribution of each construct to Chinese reading among 8- to 9-year-old children in Mainland China. Experiment 1 compared the relative contribution of tone awareness and pinyin proficiency to Chinese reading, and Experiment 2 explored the contribution of tone sensitivity to Chinese reading after controlling for rapid naming. Results showed that tone awareness was the only significant predictor of Chinese sentence reading when entered with onset awareness and pinyin proficiency measures (Experiment 1); and that tone awareness continued to be a unique contributor to Chinese sentence reading after controlling for speed naming measures (Experiment 2). This study provides important empirical evidence for the critical role of tone awareness in Chinese reading in intermediate-level primary school 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 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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.140
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.091
GPT teacher head0.445
Teacher spread0.354 · 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.

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

Citations79
Published2011
Admission routes1
Has abstractyes

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