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Record W2128331005 · doi:10.1177/0022219411402693

Cognitive Processing Skills and Developmental Dyslexia in Chinese

2011· article· en· W2128331005 on OpenAlexaff
Xiaochen Wang, George K. Georgiou, J. P. Das, Qing Li

Bibliographic record

VenueJournal of Learning Disabilities · 2011
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDyslexiaPsychologyFluencyPhonological awarenessReading (process)CognitionDevelopmental psychologyAudiologyCognitive psychologyReading disabilityRapid automatized namingPhonologyLinguisticsLiteracyNeuroscienceMedicine

Abstract

fetched live from OpenAlex

The purpose of the present study was twofold: (a) to examine the extent to which Chinese dyslexic children experience deficits in phonological and orthographic processing skills and (b) to examine if Chinese dyslexia is associated with deficits in Planning, Attention, Simultaneous, and Successive (PASS) processing. A total of 27 Grade 4 children with dyslexia (DYS), 27 Grade 4 chronological age (CA) controls, and 27 Grade 2 reading age (RA) controls were tested on measures of phonological awareness, rapid naming, phonological memory, PASS, reading accuracy, and reading fluency. The results indicated that the DYS group performed significantly poorer than the CA and RA groups on both measures of phonological awareness and on a measure of orthographic processing but comparably to the RA group on a measure of rapid naming and both measures of phonological memory. In regard to the PASS processing skills, the DYS group performed worse than the CA controls on Successive and Simultaneous processing but comparably to the RA group on all PASS processing skills. Implications of these findings for early identification and intervention of reading difficulties are 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 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)0.000
metaresearch head score (Gemma)0.002
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 score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
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 head0.023
GPT teacher head0.315
Teacher spread0.291 · 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

Citations77
Published2011
Admission routes1
Has abstractyes

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