An Investigation on the Legislative Tradition of Should Be Rough Rather Than Detailed in China's Marriage Law—Also on the Early Practice of Chinese Feminist Movement
Bibliographic record
Abstract
The Civil Code of the People's Republic of China, which was reviewed and passed in May 2020, continues the tradition of should be rough rather than detailed in China's marriage and family legislation since the promulgation of the Marriage Law of 1950. The embodiment of this tradition in the marriage law text is fewer legal provisions, more general provisions, and more moral norms. This legislative tradition did not come from the Soviet Union but was mainly due to the unique legal nature of the Marriage Law of 1950. This law is the product of the victory of the Chinese feminist movement since the Revolution of 1911. Its legislative tradition of should be rough rather than detailed is determined by the legislative purpose of this law to break the feudal marriage system and protect the rights of women and children, and its unique legal attributes. The formulation of this law was subject to the legislative difficulties and the social reality faced by the marriage law drafting group centered on women leaders. It was a helpless choice in a particular period. In the modern society where China's economy, society, and marriage and family relations have undergone significant changes, it is crucial to improve marriage legislation and reverse the legislation tradition of should be rough rather than detailed, so that the improvement of legislative techniques and legislative goals meet the needs of economic and social development.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| 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".