Intergenerational relationships and marriage in China: <scp>Within‐family</scp> longitudinal associations and <scp>between‐family</scp> differences
Bibliographic record
Abstract
Abstract Marriage is embedded in the web of spouses' broader social ties, and relationship quality with parents and parents‐in‐law is associated with marital quality. Guided by Family Systems theory and using three waves of dyadic data from 268 Chinese different‐sex couples across the first several years of marriage, we first conducted a Random‐Intercept Actor‐Partner Interdependence Cross‐lagged Panel Model (RI‐APIM‐CLPM) to examine the within‐family longitudinal associations among husbands' and wives' relationship quality with parents, parents‐in‐law, and spouse. Then, husbands' and wives' filial obligations were added as predictors of between‐family differences in their own and their partner's relationship quality in the three social ties. Among husbands, increased relationship quality in one social tie (e.g., with parents) predicted reductions in relationship quality in the other social ties (e.g., relationships with parents‐in‐law and marital quality). Our examination of between‐family differences demonstrated that high levels of filial obligations predicted higher intergenerational relationship quality and marital quality. By simultaneously considering the within‐family associations of multiple social ties and how filial obligations account for between‐family differences in relationship quality, we contribute to a nuanced understanding of how Chinese couples' romantic partnerships are embedded in their broader family system.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".