Measures to strengthen the identity and professionalism of social workers in correctional welfare practice
Bibliographic record
Abstract
The purpose of this study is to diagnose the identity and professionalism of social workers working in Korean correctional settings and to suggest comprehensive measures for institutionalizing correctional social workers and strengthening their capabilities. Through literature review and comparison of domestic and foreign systems, it was confirmed that the participation of Korean social workers in correctional welfare is very limited due to legal and structural limitations. On the other hand, in the United States, the United Kingdom, Canada, and Japan, correctional social workers are leading the prevention of recidivism and social reintegration as core members of multidisciplinary teams. As a result of the study, it was suggested that the following measures are essential for Korean social workers to strengthen their identity and professionalism as correctional social workers: first, improvement of policies and systems; second, establishment of education, training, and supervision systems; third, strengthening of multidisciplinary and community-based platforms; fourth, establishment of evidence-based practices and performance evaluation indicators; and fifth, establishment of a professional culture based on ethics and values.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| 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".