Marital Power Structure in Two Chinese Societies: Measurement and Mechanisms
Bibliographic record
Abstract
The changing nature of conjugal relationships has become a focal issue in family research in East Asia. The rapid social changes in the region have imposed serious challenges to patriarchal dominance as well as to the cultural value of the father-son lineage. Patterns of conjugal relationships thus represent significant family dynamics in response to external changes in the region. A lack of conjugal data and the use of single weight measurement are two conventional drawbacks in studying marital power structures. Hence, this study aims to construct a better marital power index and to apply it in analyzing mechanisms accounting for wives’ marital status by using two corresponding couple datasets from Taiwan and Shanghai. Data are taken from “The Economic Development and Women’s Family Status in Different Chinese Societies”. Using the Analytic Hierarchy Process analysis, three sets of weights are derived for the marital power structure in Taiwan and in Shanghai. After taking into account both family decisions and household labor division, our results indicate that the marital power structure in Taiwan and in Shanghai tends to be male dominant. Taiwanese women’s family status score is approximately 39, in contrast with men’s score of 61. Shanghai women’s marital power score is about 43, higher than their Taiwanese counterparts, but remains lower than husbands’ score of 57. With regard to mechanisms explaining various marital power patterns, the Actor-Partner Interdependence Model reveals slightly different patterns for Taiwanese and Shanghai couples. While individual and relative conjugal resources account for wives’ domestic status in both Taiwan and Shanghai, normative effects such as co-residence with paternal parents, Hakka ethnic background and the immediate constraint of children produce salient negative effect on having egalitarian marital relations among Taiwanese couples. Our findings show that Shanghai couples lean toward the Western recourse model, while Taiwan couples are affected by the interaction between norm and resource. We conclude that it is essential to consider both family decision-making and household division of labor in the construction of a multi-dimensional marital power score. Use of the “dyad” as the unit of analysis, instead of using the “individual” unit, in studying conjugal relations is strongly suggested. Furthermore, our study points out the importance of examining the interplay of norms and resources in studying conjugal relations in a changing context such as the Chinese family.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".