Understanding Public Perceptions of Chinese Law and the Legal System: Legal Experiences Matter
Bibliographic record
Abstract
Abstract: Over the past decade, Chinese law has undergone a considerable number of major reforms, ranging from the high-profile constitutional amendments to the implementation of multiple online platforms, which have significantly altered legal practice and the judicial process. While scholarly debate remains split over whether China is turning away from law or is becoming more legalistic, there is little empirical understanding of how Chinese law and the legal system are perceived by those most affected by it, namely the Chinese citizens. This article fills the critical gap by leveraging an original public opinion survey of more than 5,000 Chinese adults to examine their views on issues such as the importance of law and the status of legal development in relation to economic growth. The findings suggest that Chinese citizens with actual experience of the legal system—whether from study, practice or personal involvement in litigation—hold vastly different views on many of these issues from those without such experience. The findings also suggest that important policy initiatives introduced by the Chinese leadership and the judiciary, such as the emphasis on constructing a socialist rule of law and the potential introduction of some system of case law, may enjoy popular support.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".