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Record W4417432095 · doi:10.1177/00222194251399192

Comparing Children With and Without Learning Disabilities on Their Home Literacy Environment and Its Association With Pre-Reading Skills

2025· article· en· W4417432095 on OpenAlexafffund
Rachelle Margaret Johnson, Sara A. Hart, Richard K. Wagner

Bibliographic record

VenueJournal of Learning Disabilities · 2025
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Waterloo
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Child Health and Human DevelopmentInstitute of Education SciencesNational Institutes of HealthCanada Excellence Research Chairs, Government of Canada
KeywordsSocioeconomic statusAssociation (psychology)Learning disabilityLiteracyReading (process)CohortDyslexiaEarly childhood

Abstract

fetched live from OpenAlex

Despite children with learning disabilities (LDs) being at high risk for reading delays, how the informal home literacy environment (HLE) of LD children compares to that of their non-LD peers has not previously been investigated. Neither has the extent to which informal HLE is associated with pre-reading skills been compared for these two groups. To address these questions, we analyzed the data of 2,090 U.S. children with and without LDs from the nationally representative Early Childhood Longitudinal Study-Kindergarten Cohort of 2010-2011 (ECLS-K:2011). Children with LDs had a lower informal HLE the summer before kindergarten than those without LDs, although this difference was not independent of group differences in socioeconomic status (SES). Next, informal HLE was associated with pre-reading skills at the start of kindergarten comparably for children with and without LDs, and this remained true after accounting for SES. In conclusion, LD children experience lower informal HLE than their non-LD peers.

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)0.003
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 score0.023
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.008
GPT teacher head0.265
Teacher spread0.257 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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