ROLLING OUT SNAP® AN EVIDENCE-BASED INTERVENTION: A SUMMARY OF IMPLEMENTATION, EVALUATION, AND RESEARCH
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p>This article describes the evolutionary process of developing, disseminating, and implementing an evidence-based intervention model for children in conflict with the law. Stop Now And Plan (SNAP<sup>®</sup>), a Canadian, evidence-based gender sensitive model for young children in conflict with the law, was initiated in 1985 in response to the de-criminalization of children under 12 in Canada. This community-based model is well validated for its efficacious outcomes on reducing problem behaviours in this high-risk population, helping to shift the trajectory of criminal outcome. The article describes the lessons learned during the evaluation, implementation, and replication of SNAP<sup>®</sup> and the resulting creation of a stringent implementation approach. Currently under the management of the Centre for Children Committing Offences (CCCO), replication sites known as SNAP<sup>® </sup>Affiliates, enter into a formalized licensing agreement that includes assessing site readiness and theoretical philosophy, ongoing training and consultation, and an accreditation quality assurance process. This formalized approach has been adopted to ensure sites are able to deliver the highest quality of service and to replicate successful outcomes, changing life course trajectories of these high-risk children and families.</p>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it