Financial Support or Emotional Companion: Childbearing Motivations on Children’s Development in China
Bibliographic record
Abstract
A preference for having a son has existed among Chinese parents for centuries due to, in part, sons having to provide financial support to elderly parents, while married daughters do not have this responsibility under Confucianism. Thus, this study examined the influence of parents’ childbearing motivation (financial support or emotional companion) on children’s development (academic performance and well-being) utilizing empirical data from the 2012 China Family Panel Studies. This study included 1,541 children (aged 10–15 years) and their parents who were surveyed via a questionnaire. Using exploratory factor analysis, two dimensions of parents’ childbearing motivation were identified namely, utilitarian and psychological motivation. Furthermore, the invariance of the measurement model across the female and male group was tested. Then, results from structural equation modeling showed that parents’ childbearing motivation, particularly expected utilitarian benefits, decreased children’s expectation of the highest education, thus, worsening children’s academic performance. Alternatively, emotional/psychological motivation appeared to increase children’s self-esteem, thus, improving children’s well-being. Furthermore, gender differences were also observed. These findings have provided important insights into how childbearing motivations influence children’s development, thus, can be utilized to ensure positive development of future children in China.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".