Harm Reduction in Canadian Health Care: A Qualitative Study of Caring and Compassion in a Supervised Consumption Clinic
Bibliographic record
Abstract
This autoethnographic research explores my lived experiences within Calgary’s only supervised consumption site, Safeworks, and those of program, staff and clients. In this thesis I am attentive to the everyday, the minute, and the details of lives lived within real time, in specific moments, and in actual situations. Drawing on several months of participatory observations within the supervised consumption site and 21 in-depth interviews with program staff and clients, I discuss how supervised consumption services offer more than a reduction in drug related harms; rather, these services fulfill an essential social void in the lives of people who use drugs – that of interpersonal recognition and respect. I offer consideration into caring relationships as they are cultivated at Safeworks – exploring the difficulties and tensions of caring for a population that is regularly publicly denounced and denied. Further, I offer a reflection of the ethical dilemmas present in the course of providing care; what may be felt to be intuitively just by some staff is seldom shared by all those involved in the delivery of supervised consumption services. What moral predicaments arise when clients present at Safeworks with more needs than staff can ever hope to meet? The burdens borne by staff, I argue, exist because they are not shared. In the absence of a collective vision of mutual recognition and resemblance with persons who use substances, care providers at Safeworks must work overtime: supporting clients to feel less stigmatized and less isolated, above attending to their daily needs in states of dependency, despair, and overdose, while simultaneously extending their reach to cover gaps in service delivery that manifest in societies indifferent to the plight of those overwhelmed by addictions.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.050 | 0.022 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".