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Record W2898044683 · doi:10.20360/langandlit29443

Modeling the Relationships between Language Skills and Sentence Comprehension among Chinese Junior Elementary Graders

2020· article· en· W2898044683 on OpenAlexvenueno aff
Xiaoyun Xiao, Connie Suk‐Han Ho

Bibliographic record

VenueLanguage and Literacy · 2020
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsnot available
Fundersnot available
KeywordsVocabularySentenceReading comprehensionComprehensionLinguisticsReading (process)PsychologyComputer scienceLiteracyNarrativeNatural language processingPedagogy

Abstract

fetched live from OpenAlex

The present study examined the contributions of vocabulary knowledge, syntactic skills, and oral narrative skills to sentence reading comprehension among Chinese junior elementary school children. Various language and reading measures were administered to 85 Chinese normally-achieving children at Grades 2 and 3 in Hong Kong. Results showed that vocabulary knowledge and oral narrative skills contributed significantly to word order skills, an important syntactic skill in Chinese. Vocabulary knowledge contributed to word recognition directly and contributed to sentence comprehension indirectly through word recognition and syntactic skills; and syntactic skills contributed to sentence comprehension directly. These findings suggest that while vocabulary knowledge is important for Chinese word reading, syntactic word order plays a central role in Chinese sentence comprehension. The implications of these findings for our theoretical understanding of the Simple View of Reading, as well as reading instruction, will be discussed.

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)0.000
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 score0.428
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.020
GPT teacher head0.303
Teacher spread0.283 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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