Raising Generation Z Children in China: Parenting Styles and Psychosocial Adjustment
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".