WHAT IS SUCCESS? HOW PEER SUPPORT WORKERS IN ONTARIO SEE ADDICTION & RECOVERY
Bibliographic record
Abstract
The drug crisis in Canada has high mortality rates, especially in remote and rural communities, but there are significant barriers to accessing healthcare to which peer support may represent a partial solution, (Eddie et al., 2019; Englander et al., 2020; The Government of Canada, 2023; Kourgiantakis et al., 2023; Lavalley et al., 2020; Lennox et al., 202; Russell et al., 2021). Research how peer support workers define success in their work with adults experiencing addiction in Ontario, Canada is lacking, but important to understanding the crisis and implementing peer programs. Grounded in Marxist theory, the following exploratory research investigated the outcomes of interest to peer support workers, using data from 9 peer workers across rural, urban and remote Ontario. Thematic analysis produced 5 themes: i) “the professional is personal & the personal is professional”, “ii) Success is a blurry concept”, “iii) Recovery is more than abstinence”, iv) “Some barriers to peer work & recovery are institutional”, and v) “Some barriers to peer work & recovery are socially systemic”. The nature of peer work as the provision of unconditional support, not based on clinical outcomes, reveals a conflict between the peer workers and the larger healthcare system. The findings reflect both the psychological and material nature of addiction and the barriers to recovery, and are explained with concepts of alienation, reification, and capitalist oppression (Martin-Baro, 1994). Analyses of the addiction crisis in Ontario should take into account the historical and material sources of addiction. Social workers and clinicians should consider alternative models of support.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.011 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".