Mitigation of punishment and criminal defenses in criminal legislation of Canada and Republic of Uzbekistan (comparative analysis)
Bibliographic record
Abstract
The existing paper provides a comparative analysis of the criminal legislation of Canada and Uzbekistan in terms of consideration of the mitigation of punishment and criminal defenses. In detail, the present research provides an overall overview of the mitigation of sentence institute in accordance with the existing editions of the Criminal Code of Canada and the Criminal Code of the Republic of Uzbekistan, including the issues of determining the punishment for the criminal offences committed in a state of mental disorder, as well as insanity and diminished responsibility for incomplete offences and criminal complicity, including criminal defenses, institutions on the withdrawal (voluntary refusal) from the commission of an offence and innocent harm, etc. Pursuant to the results of the conducted analysis, similar and different sides of current criminal laws have been clarified. Decisions on the performed analysis and a final conclusion on the implementation of Canada's some criminal law norms to the criminal law of the Republic of Uzbekistan have been provided
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".