Retrospection of the Rationality and the Feasibility of the Criminal Reconciliation System
Bibliographic record
Abstract
In a criminal procedure,if the offender and the victim negotiate to solve the criminal case in the way of confession,compensation and apology,the specialized agency terminate the criminal responsibility investigation of the offender or give lighter punishment to the offender.This form of case treatment method is defined as criminal reconciliation.[1](P191)The system dated from 70s of last century when a reconciliation experiment of‘Victim-Offender’appeared in Ontario,Canada.After that,the method was introduced to America and some European countries.The practice of the method in western countries attached the attention of Chinese law society,and some regions has made legal attempts.However the author hold the view that the criminal reconciliation lacks enough rationality and feasibility,so that it shocks the basic principle of the existing criminal law,corrodes the social psychological basis of the law,and aggravates the judicial corruption.The method has theoretic defects,and it should not be promoted in current judicial practice.
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 | 0.031 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.059 |
| Scholarly communication | 0.006 | 0.014 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.015 |
| Insufficient payload (model declined to judge) | 0.003 | 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".