Bibliographic record
Abstract
The article examines the institution of exemption from criminal prosecution of legal entities in various legal systems, including the legislation of Armenia and foreign countries. It analyzes the balance between the principles of legality and expediency in decisions to forgo criminal prosecution, as well as the legal mechanisms that allow for the avoidance of judicial proceedings under certain conditions. Particular attention is given to international experience, including Deferred Prosecution Agreements (DPA) and Non-Prosecution Agreements (NPA) used in the United States, the United Kingdom, Canada, and France. The article explores the conditions under which legal entities may be exempt from liability, such as the implementation of anti-corruption measures, compensation for damages, and cooperation with law enforcement authorities. In conclusion, we substantiate the necessity of reforming Armenia's criminal procedural legislation to introduce procedural alternatives to criminal prosecution. The implementation of these mechanisms would enhance the flexibility of criminal proceedings, reduce reputational risks for businesses, encourage lawful behavior among legal entities, and establish an effective system for preventing corporate crimes. Furthermore, the application of these mechanisms could contribute to strengthening public trust in law enforcement and the judiciary by ensuring transparency and predictability in criminal prosecution decisions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; both teacher heads agree on what is shown here.
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".