Cross-sectoral integration in youth-focused health and social services in Canada: a social network analysis
Bibliographic record
Abstract
BACKGROUND: Youth with concurrent substance use and mental health concerns have diverse psychosocial needs and may present to a multitude of clinical and social service sectors. By integrating service sectors at a system level, the diversity of needs of youth with concurrent disorders can be addressed in a more holistic way. The objective of the present study was to quantify the level of cross-sectoral integration in youth-focused services in Canada. METHODS: Social network analysis (SNA) was used to examine the relationships between eight sectors: addictions, child welfare, education, physical health, housing, mental health, youth justice, and other social services. A total of 597 participants representing twelve networks of youth-serving agencies across Canada provided information on their cross-sectoral contacts and referrals. RESULTS: Overall, results suggested a moderate level of integration between sectors. The mental health and the addictions sectors demonstrated only moderate integration, while the addictions sector was strongly connected with the youth justice sector. CONCLUSIONS: Despite evidence of moderate integration, increased integration is called for to better meet the needs of youth with concurrent mental health and substance use concerns across youth-serving sectors. Ongoing efforts to enhance the integration between youth-serving sectors should be a primary focus in organizing networks serving youth with concurrent mental health and substance use needs.
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How this classification was reachedexpand
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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".