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Record W4200119055 · doi:10.1111/famp.12735

The longitudinal links between marital conflict and Chinese children’s internalizing problems in mainland China: Mediating role of maternal parenting styles

2021· article· en· W4200119055 on OpenAlexaff
Bowen Xiao, Amanda Bullock, Junsheng Liu, Robert J. Coplan

Bibliographic record

VenueFamily Process · 2021
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsCarleton University
FundersNational Natural Science Foundation of China
KeywordsPsychologyAuthoritarianismMainland ChinaDevelopmental psychologyParenting stylesChinaCoparentingPartner effectsSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

The present study explored the role of parenting styles as mediating mechanisms in the link between marital conflict and Chinese children's internalizing problems. Participants were N = 1269 families (mothers, fathers, and children) from Shanghai, P. R. China. Multisource assessments were employed at three time points. Mothers and fathers reported their marital conflict and parenting styles (authoritative, authoritarian) and teachers and children reported on children's internalizing problems. Results from the Actor-Partner Interdependence Model (APIM) showed significant actor and partner effects for associations between marital conflict and parenting styles. After controlling for internalizing problems at Time 1, only maternal authoritarian parenting continued to mediate the relations between mothers' reported marital conflict and change in children's internalizing problems over time. This research provides valuable information about how important aspects of parenting influence the relations between marital conflict and internalizing problems among Chinese children.

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)0.001
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 score0.079
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.018
GPT teacher head0.343
Teacher spread0.325 · 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

Citations19
Published2021
Admission routes1
Has abstractyes

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