The Community Alliance: A community-school-university partnership to explore mental health and addiction services to support youth and young adults.
Bibliographic record
Abstract
Memorial University of Newfoundland and a small urban community are collaborating on a community-based research project to study mental health and addictions (MH&A) in youth and young adults. Clinicians at the health centre noticed an increased prevalence of more severe cases of MH&A amongst youth and young adults in the community. For example, this included young people with undiagnosed mental health problems, youth facing problems with the law, and families overwhelmed by narcotic addictions. The clinicians then engaged the community board to collaborate on a strategy to help identify the extent of the problem and to foster community attention around this matter. In this process, a Community Alliance of the three organizations within the community emerged which included the community board, the local school and the university supported health centre. This demonstrates a true community-university partnership and transition to action. The Community Alliance chose a variety of methods to gather information and understand the problem. This included community information sessions, posters, and a needs assessment which included a survey of the youth, and focus groups of community members. The panel discussion will share the development of the Community Alliance from the perspectives of the partners and describe the methods used to conduct a needs assessment in the community. As part of our knowledge translation efforts, there will discussion about the continued collaboration between the community, school and university, and engagement of various stakeholders. The ultimate goal of this project is to develop a tailored MH&A program for this community using a coordinated community-based strategy to achieve long-term benefits on population health and well-being.
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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 | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.029 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".