Clinical ethics issues in HIV care in Canada: an institutional ethnographic study
Bibliographic record
Abstract
BACKGROUND: This is a study involving three HIV clinics in the Canadian provinces of Newfoundland and Labrador, and Manitoba. We sought to identify ethical issues involving health care providers and clinic clients in these settings, and to gain an understanding of how different ethical issues are managed by these groups. METHODS: We used an institutional ethnographic method to investigate ethical issues in HIV clinics. Our researcher conducted in-depth semi-structured interviews, compiled participant observation notes, and studied health records in order to document ethical issues in the clinics, and to understand how health care providers and clinic clients manage and resolve these issues. RESULTS: We found that health care providers and clinic clients have developed work processes for managing ethical issues of various types: conflicts between client-autonomy and public health priorities ("treatment as prevention"), difficulties associated with the criminalization of nondisclosure of HIV positive status, challenges with non-adherence to HIV treatment, the protection of confidentiality, barriers to treatment access, and negative social determinants of health and well-being. CONCLUSIONS: Some ethical issues resulted from structural disadvantages experienced by clinic clients. The most striking findings in our study were the negative social determinants of health and well-being experienced by some clinic clients - such as experiences of violence and trauma, poverty, racism, colonization, homelessness, and other factors affecting well-being such as problematic substance use. These negative determinants were at the root of other ethical issues, and are themselves of ethical concern.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.026 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 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".