Organizing State Protection of the Personnel of Penal Institutions in Some Countries of Western Europe, North America and Asia
Bibliographic record
Abstract
Introduction: the paper investigates the experience of some countries of Western Europe (Italy, Germany, Austria and The Netherlands), North America (the U.S. and Canada) and Asia (Mongolia and Japan) in the field of state protection of penitentiary personnel. The aim of summarizing the experience of these countries is to identify relevant examples of legal regulation and organization of state protection of civil servants, including prison staff, for the purpose of implementation of this experience in Russian practice. Methods: we use general scientific (analysis, synthesis, induction, etc.) and specific sociological methods of cognition (comparative-legal, sociological, statistical, comparative). Results: having conducted the comparative study, we find that Mongolia and Japan do not have a separate unified legal framework for state protection of penitentiary personnel. The norms that establish the legal and social guarantees of employees are contained in several laws and by-laws that specify them. The experience of the countries of Western Europe and America indicates that the activities aimed at ensuring state protection are concentrated and implemented by a specially created body with a wide range of powers. In these countries, special attention is paid to the issue of separate funding of programs for the protection of state servant sand persons who assist justice. Discussion: we highlight the fact that the legal and organizational aspects of ensuring state protection of the personnel of penitentiary institutions in some foreign countries have positive aspects. Some examples of foreign experience can be used in law-making and law enforcement activities in the Russian Federation. Keywords: Penitentiary personnel; foreign experience; state protection; penal system; security measures; legal and social protection measures
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".