PII S0145-2134(99)00080-0 FORMATIVE EVALUATION OF A COLLABORATIVE COMMUNITY-BASED CHILD ABUSE PREVENTION
Bibliographic record
Abstract
Objective: Together for Kids is a child abuse prevention project that serves children and families in two neighboring communities in a mid-sized Canadian city. The project, a collaborative endeavor of various agencies in the health, social services, and law enforcement sectors, focuses on preventing child abuse and neglect through family support and programming. This article presents the results of a formative evaluation of the project focusing on client and team member views on project implementation. Method: The evaluation strategy was primarily qualitative. In-person interviews following a semi-structured format were conducted with 17 clients and 10 team members by an external evaluator. In addition, a review of all client records was conducted. Results: The community-based approach, the multidisciplinary composition of the team, the ability to seek services when needed, the immediacy of the response time and the availability of support during stressful times were all aspects of the project that clients found beneficial. The most beneficial aspect of the project, however, was the informal support received from team members who were accepting, non-threatening, and non-judgmental. Team members found the collaborative approach made access to services easier for clients, particularly for those who were more socially isolated. Conclusions: Multidisciplinary, community-based models of service delivery contribute to a more effective and compas-
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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 | 0.025 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.085 | 0.013 |
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".