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Record W4300003684 · doi:10.1177/2212585x221124155

Family socioeconomic status and young children’s learning behaviors: The mediational role of parental expectation, home environment, and parental involvement

2022· article· en· W4300003684 on OpenAlexaff
Wei Mao

Bibliographic record

VenueInternational Journal of Chinese Education · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsConcordia University
Fundersnot available
KeywordsSocioeconomic statusDevelopmental psychologyPsychologyMediationDemographyPopulation

Abstract

fetched live from OpenAlex

Utilizing a national longitudinal sample from China Family Panel Studies (2018), this study examined how family socioeconomic status (SES) is related to young children’s learning behaviors through parental expectation, parental involvement and home learning environment. A total of 1348 children aged 3–5 years were included. Mediation analysis was conducted to test the hypotheses. The results identified a significant relationship between family SES and home learning environment and parental involvement, whereas family SES was only partially related to parental academic expectations. There were no statistically significant relationships between SES and children’s learning behaviors. Moreover, no indirect effects were found between parental expectation, home learning environment, and children’s learning behaviors. However, parental involvement had an indirect effect on children’s learning behaviors. The present study highlights the need to consider the role of parental involvement in supporting the development of young children’s learning behaviors. The findings and discussions raise implications for researchers and practitioners to provide parental involvement support programs for Chinese families from diverse SES backgrounds.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.031
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

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

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 head0.293
Teacher spread0.285 · 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 teacher head, 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

Citations14
Published2022
Admission routes1
Has abstractyes

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