Helping behaviour among people who use drugs: Altruism and mutual aid in a harm reduction program
Bibliographic record
Abstract
Abstract People who use drugs, and particularly people experiencing addiction, are rarely afforded the opportunity to have their voices heard when it comes to drug treatment or drug policy or even when attempting to define themselves and their life experiences. Of course, there is much more to a person than one area of their behaviour. The current study seeks to capture and understand the lived experiences of people who use drugs, with a focus on their relationships and helping behaviour. We interviewed 32 participants in a harm reduction program seeking to provide understanding beyond stigmatizing and criminalizing drug narratives, by exploring their motivation and context for helping behaviours. Grounded theory methodology was used to understand the patterns of helping behaviour, along with the contexts in which help is or is not given. We particularly focus on participants' distribution of syringes and carrying medicine to reverse overdose (naloxone). Participants shared stories of altruism and mutual aid, along with barriers and disincentives to helping others. We situate these behaviours within contrasting environments of a free harm reduction program and the competitive market system of the U.S. society. Implications for practice and public policy are discussed.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".