The Roles of Local Rules of Criminal Procedure in the Process of Rule by Law in China
Bibliographic record
Abstract
Although China has a unitary tradition, there exist a large number of local rules in criminal procedure. Based on more than one thousands of copies of local rules of criminal procedure and relevant investigations, the article analysis the important functions of local rules of criminal procedure in the process of rule of law in China. In order to refine laws and regulations and guide pilot reforms, judicial offices draw up local rules of criminal procedure.These local rules also build mechanisms of coordinations between judicial offices and judicial internal offices and government departments,and local rules regulate the administration of justice system of judicial personals and business.In the aspect of protection of rights, local rules of criminal in China succeed in strengthen the rights of defendant and counsel and victim and prisoners.In addition, some controversies against local rules of criminal procedure in China are discussed. Finally,the article offer some suggestions to improve the justify of local rules in criminal procedure in China,such as admitting the power of local judicial offices to make rules and standardizing the procedure of formulating rules,and it’s necessary to set a bottom line and effective relieving courses.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| 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".