The Implementation of Wraparound Model in Israel - An Alternative to Out-of-Home Placement of Delinquent Juveniles
Bibliographic record
Abstract
Wraparound model refers to community-based programs designed to rehabilitate youth; characterized by multiple risk factors, through "wrapping" them with a variety of assistance agencies, first and foremost their families. The purpose of the current paper was to describe the way of implementation of the Wraparound model in Israel, named the Ma'atefet1, which is operated by the Juvenile Probation Service (JPS), as an alternative to out-of-home placement of convicted juvenile offenders. The paper presents an overview of the program's background, objectives and goals, as well as findings of evaluation studies designed to examine the program effectiveness, and case studies of convicted minors that participated in the program in Israel. In consistent with previous studies from different countries in the world, it was found that the program in Israel achieves its main goals, reflected in improvements in the educational, familial and mental condition of the treated youth; reducing recidivism; and preventing out-of-home placement. In light of these many advantages, we recommend policy-makers to expand the program, for the benefit of young offenders, their families and the community as a whole.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".