A patient’s narrative of engaging HIV care: Lessons learned to harness resources and improve access to care
Bibliographic record
Abstract
In Canada and the USA, about 30% of people with HIV are uninsured or not covered by government-subsidized health insurance. This paper presents a patient’s narrative of his experience being diagnosed with HIV and accessing care in the midst of his process of immigrating to and studying in Canada. The narrative explores how Vincent Croft (pseudonym) has coped with the chronicity of the infection and its associated social stigma, and the temporary solutions he found to access treatment. Engaging with healthcare providers, researchers, and other people living with HIV has allowed Croft to share his experience, including the barriers he encountered and the solutions he envisioned or attempted, resulting in self-empowerment and reinterpretations of Croft’s own trajectory. Patrick Keeler, a community-based intervener, reflects on Croft’s narrative as symptomatic of systemic issues in access to care of people living with HIV in Canada. He also illustrates how the experiential knowledge of people with similar lived experiences can trigger simple, innovative, and cost-efficient initiatives with Le Cercle Orange, which connects and mobilizes existing resources for people with HIV with no or limited access to care and treatment. Experience Framework This article is associated with the Patient, Family & Community Engagement lens of The Beryl Institute Experience Framework (https://www.theberylinstitute.org/ExperienceFramework). Access other PXJ articles related to this lens. Access other resources related to this lens.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.024 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.005 | 0.018 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".