Equipping Public Health Professionals for Youth Engagement
Bibliographic record
Abstract
There is strong evidence of the positive role that youth engagement programs and policies play in creating resiliency and producing positive outcomes among youth populations, such as delaying or avoiding the onset of risk-taking behaviors. Research also suggests that achieving positive outcomes ideally includes influence from the individual, the family, the school, the community, and the field of public health (available in A Research Report and Recommendations for Ontario Public Health Association). The authors conducted a comprehensive evaluation of a 2-year pilot project designed to increase the application of engagement and resiliency theory, knowledge, and skills among public health professionals engaging students from Grades 6, 7, and 8 (11- to 14-year-olds). Qualitative methods assessed public health satisfaction with training, resources, and networking activities, whereas quantitative methods assessed changes in capacity with respect to youth engagement knowledge, awareness, confidence, and skills. The findings have helped shed light on public health professional needs concerning capacity and confidence to undertake youth engagement work. Key lessons learned about making youth engagement possible and effective for public health professionals are presented.
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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 | 0.020 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".