FC27-01 - Youth matters in London: Mental health, addiction and homelessness
Bibliographic record
Abstract
This project will work closely with existing service partners involved in street level services and focus on testing and evaluating three approaches for street level interventions for youth who are homeless and who have severe or moderate mentally illness. Youth will be asked to choose their preferred service approach: Housing First related initiatives focused on interventions designed to move youth to appropriate and available housing and ongoing housing supports. Treatment First initiatives to provide Mental Health/Addiction supports and treatment solutions, and; Simultaneous attention to both Housing and Treatment Together Our primary objective is to understand the service delivery preferences of homeless youth and understand the outcomes of these choices. Our research questions include: 1. Which approaches to service are chosen by youth? 2. What are the differences and similarities between groups choosing each approach? 3. What are the critical ingredients needed to effectively implement services for homeless youth from the perspectives of youth, families and service providers? Focus groups with staff and family members will occur to assist in understanding the nature of each of service approach, changes that evolve within services, & facilitators and barriers to service delivery. This work will be important in determining which approach is chosen by youth and why. Evaluating the outcomes with each choice will provide valuable information about outcomes for the service options chosen by youth. This assist in better identifying weaknesses in the services offered and inform further development of treatment options that youth will accept.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 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".