A Hub intervention in Surrey, Canada: learning from people at risk
Bibliographic record
Abstract
Co-occurring health and public safety concerns involving mental illness, substance use, and homelessness are increasingly prevalent challenges for policymakers in cities worldwide. The Hub model is a roundtable process where the combined resources of diverse agencies are used to mitigate urgent risk of crime, victimization, illness and death, by establishing immediate connections with appropriate services and supports. Initiated in Scotland, the model has been replicated in more than 60 communities across Canada since 2012. In November 2105, the Surrey Mobilization and Resiliency Table (SMART) became the first Hub in British Columbia. Little peer-reviewed research has examined the impact of Hub inter-ventions from a client perspective. We conducted semi-structured interviews with 16 SMART clients and analyzed their responses thematically. We also examined demographic- and intervention-related characteristics reported in the SMART database. Participants described positive experiences with SMART service providers, and commented that the intervention was effective at meeting relatively circumscribed needs. However, most clients reported complex and mutually exacer-bating health and social conditions, and expressed the need for ongoing structured support (e.g., Assertive Community Treatment (ACT)). Our results emphasize the beneficial role played by SMART’s coordinated, real-time approach. They also indicate demand for social policies that include substantial and enduring forms of support to prevent crises and promote community safety.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".