Gender Violence Suffered by the Daughter-In-Law in the Changing Chinese Family — A Case Study from the Perspective of Family Power Structure
Bibliographic record
Abstract
With the development of society, the structure and function of the Chinese family have undergone great changes but gender violence still exists. Through in-depth interviews with two in-laws families, the article describes the gender violence suffered by three daughters-in-law (DILs) within two generations from the 1970s to the 2000s, discovering that despite the nuanced differences in the forms and frequencies of gender violence, three DILs were all at the inferior status in the stem family and were victims of family power inequality. It was revealed that the family power inequality gave rise to gender violence toward the DIL, inducing severe physical or mental injury to the DIL. However, family power inequality was rooted in the traditional gender ideology. The traditional gender ideology originated from the feudal society of China and still pervaded modern society. Consequently, the traditional gender ideology was the rooted cause of the occurrence of gender violence. The article concludes with a reminder of reflecting upon the impacts of the traditional gender ideology on our lives and promoting a new gender consciousness.
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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 | 0.012 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".