MétaCan
Menu
Back to cohort
Record W4414137947 · doi:10.1080/10409289.2025.2559338

Cumulative Family Sociodemographic Risk and Preschoolers’ Language Skills Development: The Mediating Role of the Home Literacy Environment

2025· article· en· W4414137947 on OpenAlexaff
Angélique Laurent, Marie‐Josée Letarte, Jean‐Pascal Lemelin

Bibliographic record

VenueEarly Education and Development · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsLiteracyFamily literacySocioeconomic statusHome languageLanguage developmentLanguage proficiencyFamily incomeStatistical analysis

Abstract

fetched live from OpenAlex

Research Findings: This longitudinal study examined the mediating role of home literacy environment (HLE) in the relationship between family sociodemographic risk factors and preschoolers’ language skills during their transition to kindergarten. A sample of 142 children showing vulnerability regarding school readiness were assessed three times. Eight months before kindergarten, family sociodemographic information was collected, and a cumulative family sociodemographic risk score was calculated. Children’s language skills (i.e. receptive and expressive vocabulary and sentence recall) were also collected at this timepoint. Four months later, three components of HLE (i.e. frequency of parents’ involvement in literacy activities, quality of parents’ involvement in literacy activities, and availability of learning materials at home) were measured. At the end of kindergarten, 1 year later, children’s language skills were reassessed. One main indirect association was found: cumulative risk was related to expressive vocabulary through the availability of learning materials. Practice or Policy: These findings highlight that interventions with parents of preschoolers showing vulnerability regarding school readiness should focus on supporting parental practices and helping parents gain access to learning materials through school, social services, and other community resources.

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 score0.017
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.004
GPT teacher head0.251
Teacher spread0.246 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueEarly Education and DevelopmentSame topicChild Development and Digital TechnologyFrench-language works237,207