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Record W2106150714 · doi:10.1080/016502500383557

Maternal authoritative and authoritarian attitudes and mother–child interactions and relationships in urban China

2000· article· en· W2106150714 on OpenAlexaff
Xinyin Chen, Mowei Liu, Boshu Li, Guozhen Cen, Huichang Chen, Li Wang

Bibliographic record

VenueInternational Journal of Behavioral Development · 2000
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsWestern University
Fundersnot available
KeywordsAuthoritarianismPsychologyDevelopmental psychologyChinaMediationChild rearingParenting stylesBeijingSocial psychologyDemocracyPoliticsPolitical science

Abstract

fetched live from OpenAlex

The purpose of the study was to examine how maternal authoritative and authoritarian attitudes were manifested in mother–child interactions and relationships in Chinese culture. A sample of 2-year-old children and their mothers ( N= 166) in Beijing and Shanghai, People’s Republic of China, participated in the study. Information on maternal child-rearing attitudes and mother–child attachment relationships was obtained from mothers’ reports. Data concerning maternal parenting strategies, child behaviours, and child reactions to maternal reunion were collected from observations. The results indicated that maternal authoritative attitudes were associated with low power parenting strategies, whereas maternal authoritarian attitudes were associated with enforcement and prohibitory strategies. It was also found that maternal attitudes were associated with child behaviours through the mediation of parenting strategies. However, maternal attitudes might contribute uniquely to mother–child relationships, over and above maternal behaviours. The study provided evidence on the internal coherence of authoritative and authoritarian patterns and their differential significance for child development in urban China.

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 score0.029
Threshold uncertainty score0.057

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.033
GPT teacher head0.340
Teacher spread0.306 · 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

Citations119
Published2000
Admission routes1
Has abstractyes

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