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Record W2010751907 · doi:10.1177/0022219414522706

A Longitudinal Examination of the Persistence of Late Emerging Reading Disabilities

2014· article· en· W2010751907 on OpenAlexaff
Jill M. Etmanskie, Marita Partanen, Linda S. Siegel

Bibliographic record

VenueJournal of Learning Disabilities · 2014
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPseudowordPsychologyReading (process)Reading comprehensionSpellingDevelopmental psychologyReading disabilityLearning disabilityDyslexiaPhonemic awarenessComprehensionCognitive psychologyLinguistics

Abstract

fetched live from OpenAlex

There are some children who encounter unexpected reading difficulties in the fourth grade. This phenomenon has been described as late emerging reading disabilities (LERD). Using Grade 4 as a starting point, this study examined the reading development of 964 children between kindergarten and Grade 7. The results showed that 72.0% of children had typical reading performance in Grade 4, whereas there was 0.7% with poor word reading, 12.6% with poor reading comprehension, 2.5% with poor word reading and comprehension, and 12.2% with borderline performance. We also showed that there were similar proportions of children who had early versus late emerging reading difficulties; however, most of the late emerging poor readers recovered by Grade 7. Furthermore, our study showed that poor comprehenders showed poorer performance than typical readers on word reading, pseudoword decoding, and spelling between Grade 1 and Grade 7 and poorer performance on a working memory task in kindergarten. Overall, this study showed that most children recover from late emerging reading problems and that working memory may be an early indicator for reading comprehension difficulties.

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)0.005
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 score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.294
Teacher spread0.262 · 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

Citations43
Published2014
Admission routes1
Has abstractyes

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