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Early Child Language Mediates the Relation Between Home Environment and School Readiness

2009· article· en· W2111964905 on OpenAlexaff
Nadine Forget‐Dubois, Ginette Dionne, Jean‐Pascal Lemelin, Daniel Pérusse, Richard E. Tremblay, Michel Boivin

Bibliographic record

VenueChild Development · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversité de MontréalUniversité de SherbrookeUniversité Laval
Fundersnot available
KeywordsPsychologySocioeconomic statusDevelopmental psychologyAffect (linguistics)Reading (process)Association (psychology)Language developmentLanguage acquisitionRelation (database)Early childhoodDemographyLinguisticsMathematics educationCommunication

Abstract

fetched live from OpenAlex

Home environment quality is a well-known predictor of school readiness (SR), although the underlying processes are little known. This study tested two hypotheses: (a) child language mediates the association between home characteristics (socioeconomic status and exposure to reading) and SR, and (b) genetic factors partly explain the association between language and SR. Data were collected between 6 and 63 months in a large sample of twins. Results showed that home characteristics had direct effects on SR and indirect effects through child language. No genetic correlation was found between language and SR. These results suggest that home characteristics affect SR in part through their effect on early language skills, and show that this process is mainly environmental rather than genetic in nature.

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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.245
Teacher spread0.236 · 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

Citations173
Published2009
Admission routes1
Has abstractyes

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