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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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