Bibliographic record
Abstract
The objective of this study is to analyze the needs of inmates incarcerated for long period of time, as well as those of officers working in this environment for prolonged periods of time. Based on the research of the real conditions of long-term incarceration, and foreign cases. The study suggests the following new treatments for them. The study was performed by the following method; 1) Review the studies on long-term inmates of Korea, USA, Canada and the United Kingdom 2) Questionaire survey and analysis of 384 long-term inmates and 103 correctional officers in 9 correctional institutions 〈Results〉 1) The number of long-term inmates is continually increasing. The proportion of long-term inmates out of the total population is also on the rise and grows more rapidly compared to the number of general inmate population. There, however, have not been special regulations or various treatment programs. 2) Foreign cases a) The U.S.A. has long-term treatment by career planning model. b) Canada presents life-line program provided by Task Force on Long-Term Sentences c) The United Kingdom has treatment programs, based on career planning and end-to-end management 3) The analysis of the needs of long-term inmates and correctional officers, shows that inmates are primarily interested in family reunions and conjugal visitation. Correctional officers consider vocational training and self-development programs to be most important.. 〈Suggestions〉 5 Levels of treatment are suggested from the result of this study. These levels consist of the plan and preparation, the beginning-term, the mid-term, the later-term, and the preparation to return to society. Each level has a procedure goal, long-term inmates characteristics and treatment strategy respectably. 1) Level 1; The plan and preparation Assessment by counselling individually, helping long-term inmates emotionally and psychologically 2) Level 2; The beginning-term Providing long-term inmates with various programs to manage their career and give them opportunities to choose the most proper type for their career. 3) Level 3; The mid-term Providing them programs to specialize vocational training. 4) Level 4; The later-term Providing the opportunities to practice and self-control for reintegrating society. 5) Level 5; The preparation to return to society Providing necessities for re-integrating into society, such as community related activities, society adaptation, work release.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".