Incorporation of peer support in a novel community-based mobile withdrawal management program
Bibliographic record
Abstract
Despite the sweeping and deep-rooted impacts of problematic substance use throughout Canada, services remain under-resourced and overwhelmed. Innovative approaches are required if meaningful change is to occur. In this paper, we examine the incorporation of peer support into a novel, community-based outreach withdrawal program which engages with participants where they are situated. Peer support is an evidence-based intervention utilized in a wide range of health care arenas. It employs lived experience as a skillset to address health care needs to complement other components in the therapeutic journey. In the context of an outreach withdrawal service, peer support holds potential to deconstruct the power dynamic that acts as a barrier in conventional withdrawal programs. Peer support promotes the concept of interdisciplinary care, while actively dismantling stigma. More research is required to evaluate outcomes, client satisfaction, and cost-effectiveness with regards to peer support interventions in community-based outreach detoxification programming.
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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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".