MétaCan
Menu
Back to cohort
Record W2070205616 · doi:10.1080/02702711.2010.495605

Orthographic Knowledge Important in Comprehending Elementary Chinese Text by Users of Alphasyllabaries

2011· article· en· W2070205616 on OpenAlexaff
Che Kan Leong, SK Tse, Elizabeth Ka Yee Loh, Wing Wah Ki

Bibliographic record

VenueReading Psychology · 2011
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPsychologyReading comprehensionOrthographic projectionCognitionLinguisticsWorking memoryComprehensionCognitive psychologyReading (process)Confirmatory factor analysisComputer scienceArtificial intelligenceStructural equation modeling

Abstract

fetched live from OpenAlex

Orthographic knowledge in Chinese was hypothesized to affect elementary Chinese text comprehension (four essays) by 80 twelve-year-old ethnic alphasyllabary language users compared with 74 native Chinese speakers at similar reading level. This was tested with two rapid automatized naming tasks; two working memory tasks; three orthographic knowledge tasks in Chinese; and equivalent tasks in English. Multivariate analyses of covariance showed that the two groups were differentiated on most of the linguistic and cognitive tasks. Confirmatory factor analyses found four factors as hypothesized: text comprehension, verbal working memory, orthographic knowledge in Chinese, and orthographic knowledge in English. Hierarchical multiple regression analyses showed that orthographic knowledge in Chinese explained a considerable amount of individual variation in elementary Chinese text comprehension.

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)0.004
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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.350
Teacher spread0.318 · 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

Citations49
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueReading PsychologySame topicReading and Literacy DevelopmentFrench-language works237,207