Standardization and Development: Brief Discussion on Chinese Quick Transaction Mechanism of Minor Criminal Case
Bibliographic record
Abstract
At present, establishment of diversified Chinese quick transaction mechanism of minor criminal case has become an important project that the judicial organ have to confront due to the reason that the simple procedure set up by Criminal Law of our country is not efficient for transacting the increasing minor criminal cases. Since 2014, Standing Committee of the National People's Congress has authorized the Supreme People's Court and the Supreme People's Procuratorate to launch reform of quick transaction mechanism of minor criminal case in 14 cities like Beijing according to the overall scheme of Central judicial system reform. Since the reform, Courts around have begun to focus on protecting the lawful rights and interests of the criminal suspect and the defendant when they are establishing quick verdict program of minor criminal cases so as to ensure the justice of the case, of which useful experience has been taken. But from the perspective of judicial practice, judicial process of places is not unified because more principled rules of quick transaction mechanism of minor criminal case are launched only by the Supreme People's Court and the Supreme People's Procuratorate. Many problems occur in practice: application and scope are not inconsistent; time is too long in handle procedures before trial, which will influence efficiency; cooperation of public security unit, the inspecting authorities, and courts are not efficient; evidence system of minor criminal cases is not perfect…… These problems have restricted the function of quick transaction mechanism. Therefore, quick transaction mechanism of minor criminal case is to be standardized.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".