Bibliographic record
Abstract
The article examines the role of resocialization as a key tool of modern criminological policy aimed at reducing recidivism and ensuring public safety of the state. Punishment, in addition to its punitive function, should protect society by reintegrating offenders through socio-legal, economic and psychological mechanisms. However, social stigmatization and the lack of effectiveness of programs complicate this process, increasing the risk of recidivism. The purpose of the study is to analyze international legislation on the application of resocialization to offenders and its implementation in Ukrainian legislation. The author emphasizes the need for cooperation between government agencies, civil society, business and the media in creating conditions for the effective reintegration of persons released from prison. The study summarizes international experience of resocialization in such countries as: Germany, Lithuania, the Netherlands, the United Kingdom, Canada, etc. Successful practices of implementing social adaptation infrastructure, including reintegration centers, training programs, employment support, overcoming addictions and developing life skills are considered. The author draws attention to the peculiarities of applying the stages of resocialization during the serving of sentence and after release. The author analyzes the legal framework for resocialization in Ukraine, in particular, the role of the Criminal Executive Code, the Law “On Probation” and legislation in the field of employment. The author states that despite the existing guarantees, the practical implementation of resocialization programs in Ukraine faces a number of difficulties, including limited funding and the lack of effective special programs. However, in order to develop resocialization programs adapted to today’s realities, as well as to increase the role of probation authorities and social adaptation centers in accompanying offenders (released from prison), there is a need to implement international experience (international practices).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".