The impact of environmental factors on risk, harm, and health care access among people who inject drugs
Bibliographic record
Abstract
Background: Growing awareness of the role social, structural, and environmental factors in producing harm among people who inject drugs (IDU) has underscored the need for safer environment interventions. However, emerging evidence underscores how current interventions are insufficient to bring about more significant reductions in drug-related harm. To date, there have been few studies examining how contextual forces operating within the wider risk environment shape the socio-spatial relations of IDU in relation to safer environment interventions and health care settings. This dissertation seeks to address this gap by examining the socio-spatial dynamics within three settings in Vancouver, Canada: the street-based drug scene; an ‘unsanctioned’ supervised drug consumption room (DCR); and, hospitals. Methods: This dissertation used an ethno-epidemiological approach, and the individual studies were undertaken in connection with ongoing prospective cohort studies of current and former drug users. Ethnographic fieldwork, including participant-observation, in-depth interviews and qualitative mapping exercises, sought to characterize the socio-spatial relations of IDU in relation to the abovementioned settings. Results: Study findings underscored how contextual forces shaped the socio-spatial relations of IDU, and thus access to and engagement with safer environment interventions and hospital settings. First, findings highlighted the role of gendered power relations within the street-based drug scene in shaping the spatial practices of highly vulnerable IDU, and constraining their access to a supervised injection facility. Second, findings demonstrated how, by permitting assisted injections, the DCR created a ‘legitimate place’ for IDU who require help injecting, and enabled them to enact risk reduction. Finally, social (e.g., stigmatization) and structural (e.g., abstinence-based drug policies) factors within hospital settings were found to produce considerable suffering (e.g., inadequate pain management) and contribute to discharges from hospital against medical advice. Conclusions: The collective findings of this dissertation demonstrate how the socio-spatial relations of IDU, and the contextual forces that impact upon them, are key determinants of drug-related harm and access to interventions and hospital services. These findings point to the need to modify and scale up existing safer environment interventions, and expand these into hospital settings, to mitigate the impacts of contextual forces on IDU and better address their health needs.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".