Уголовно-правовая характеристика соучастия по уголовному законодательству зарубежных государств
Bibliographic record
Abstract
It is considered that for a more complete study of the problems of the Institute of participation in the domestic criminal law it is advisable to analyze the bulk of foreign legislation, establishing responsibility for crimes committed in complicity. In modern scientific studies the different legal systems are highlighted. Romano-German (continental) legal system, Anglo-American (common law) and Islamic system of law are considered the most common in the world. Roman-Germanic legal system includes Germany, France, Spain, Poland, Switzerland and other European countries, common law countries make up England, the USA, Canada, Australia and some other, which were colonies of Great Britain. The specific provisions of criminal codes and standards, as well as other foreign laws Anglo-American and Roman-Germanic legal systems governing liability for complicity in crimes are considered. The Criminal Codes of most foreign countries do not contain a general definition of complicity in the crime, but the signs of complicity disclosed under the regulation of its individual species and forms. The author analyzed the differences of species of partners, forms of participation, as well as showing the sanctions of criminal laws of foreign countries for crimes of complicity. Some provisions of the foreign criminal laws are compared with similar Russian standards institute complicity that allowed the author to give suggestions about the feasibility of changes and additions to the rules of the Criminal Code of Russian Federation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".