Research on entrapment in China--with reference to the experience in Canada
Bibliographic record
Abstract
Entrapment, as a behavior of abusing of the power by the police, should be prohibited by the law. However, in China, entrapment is read as legal and appropriate detective measure and the police or agent use it universally while recent legal regulation has begun to restrict its application. There are three reasons which contribute to its existence: firstly, insufficient understanding of the relationship between the human nature and entrapment; secondly, lacking the awareness of protecting the human rights and lastly overemphasizing on national accusatorial function. In terms of legal system, there is defectiveness in it. Specifically speaking, the defectiveness includes the law acquiesces in using entrapment by the police or agent; there is no regulations about whether the Judge could exclude the evidence that obtained because of entrapment and other procedural remedies for the accused are incomplete and ineffective. By comparing with the Canadian theory and legal system, the Chinese legal system in regulating entrapment might be improved to an extent.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.020 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".