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Record W4410282865 · doi:10.5093/pi2025a9

Raising Generation Z Children in China: Parenting Styles and Psychosocial Adjustment

2025· article· en· W4410282865 on OpenAlexfundno aff
Marta Alcaide, Óscar F. García, Fangzhou Chen

Bibliographic record

VenuePsychosocial Intervention · 2025
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsnot available
FundersGeneralitat ValencianaTrent UniversityNottingham Trent University
KeywordsRaising (metalworking)PsychosocialPsychologyChinaParenting stylesDevelopmental psychologyPolitical sciencePsychotherapistMathematics

Abstract

fetched live from OpenAlex

Objective: This study aims to analyze the relationship between parenting styles, i.e., authoritative, indulgent, authoritarian, and neglectful, and psychosocial adjustment, i.e., aggression, self-concept, and emotional-social competence, among Generation Z (Gen Z) individuals. Method: The participants were 1,417 Chinese individuals, 736 young adults (born between 2003-2005) and 681 adolescents (born between 2006-2008). A multivariate multifactorial design 4 × 2 × 2 × 2 was applied. Dependent variables were various components of child psychosocial adjustment (aggression, five dimensions of self-concept and emotional-social competence). Independent variables were parenting styles, children antisocial tendency during adolescence, sex, and age (adolescent vs. young adult cohorts). Results: Children from authoritarian homes reported higher levels of aggression, and the worst scores in self-concept and emotional-social competence. By contrast, the optimal results were consistently associated with warm parenting (i.e., authoritative and indulgent). Conclusions: Parental warmth was beneficial for Gen Z, including both adolescent and young adult cohorts. The present findings seriously questioned that the Chinese authoritarian parenting, which has often been related to positive outcomes—particularly for educational success—is beneficial for child psychosocial adjustment.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.649
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.027
GPT teacher head0.336
Teacher spread0.309 · 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.

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

Citations11
Published2025
Admission routes1
Has abstractyes

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