Community managed alcohol programs in Canada: Overview of key dimensions and implementation
Bibliographic record
Abstract
INTRODUCTION AND AIMS: People with severe alcohol dependence and unstable housing are vulnerable to multiple harms related to drinking and homelessness. Managed Alcohol Programs (MAP) aim to reduce harms of severe alcohol use without expecting cessation of use. There is promising evidence that MAPs reduce acute and social harms associated with alcohol dependence. The aim of this paper is to describe MAPs in Canada including key dimensions and implementation issues. DESIGN AND METHODS: Thirteen Canadian MAPs were identified through the Canadian Managed Alcohol Program Study. Nine key informant interviews were conducted and analysed alongside program documents and reports to create individual case reports. Inductive content analysis and cross case comparisons were employed to identify six key dimensions of MAPs. RESULTS: Community based MAPs have a common goal of preserving dignity and reducing harms of drinking while increasing access to housing, health and social services. MAPs are offered as both residential and day programs with differences in six key dimensions including program goals and eligibility, food and accomodation, alcohol dispensing and administration, funding and money management, primary care services and clinical monitoring, and social and cultural connections. DISCUSSION AND CONCLUSIONS: MAPs consist of four pillars with the alcohol intervention provided alongside housing interventions, primary care services, social and cultural interventions. Availability of permanent housing and re-establishing social and cultural connections are central to recovery and healing goals of MAPs. Additional research regarding Indigenous and gendered approaches to program development as well as outcomes related to chronic harms and differences in alcohol management are needed.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".