Individual agency under systemic constraints : dynamics of health and social service access among people who use drugs receiving income assistance
Bibliographic record
Abstract
Prior research shows that people who use drugs and receive income assistance experience unique difficulties accessing and engaging with health and social services, contributing to unmet population health needs. While these findings are important, a deeper understanding of the factors shaping barriers is necessary so that effective strategies to facilitate access can be implemented. Drawing on 121 interviews conducted in a Canadian inner-city, this study analyzes the health and social service experiences of people who use drugs and receive income assistance during the ongoing opioid overdose crisis. Through an application of Coleman’s framework for linking macro social outcomes and micro-level behaviour, this research examines the institutional, operational and interactional dynamics impacting client experiences with service access. The findings show that institutional frameworks influence the decisions and actions of individuals when engaging with providers by structuring and constraining their available choices. Operational challenges and stigmatization during encounters with providers leads to disengagement, which limits the utilization and positive effects of services. Despite these obstacles, individuals exercise agency in navigating, adapting to and pushing back against these constraints in order to meet their service needs. Efforts to reform social policies and service delivery must be informed by a patient-focused perspective that considers the inter-related institutional, operational and interactional dimensions of this complex service landscape.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".