Unsung Heroes: Gay Physicians’ Lived Journeys During the HIV/AIDS Pandemic
Bibliographic record
Abstract
The HIV/AIDS pandemic was a major crisis at the end of the 20th and beginning of the 21st century. Such a defining moment in the history of health-related infections led to transformations in its proponents, as well as their medical practice. This research article, using a study consisting of semi-structured interviews with six Canadian gay physicians from different Canadian HIV/AIDS treatment centers, aims to offer insights into their lived journeys, from 1981 to 2009, while they attempted to treat, care for, and cure/heal their gay HIV/AIDS patients. The results of the study, deduced from a qualitative and interpretative data analysis, suggest that through reflection on their experiences during the HIV/AIDS pandemic, they transformed their personal and professional identities, and rethought their relationship with their patients, as well as their professional, pharmaceutical, and community networks. These results are testimonies from Canadian gay physicians who fought against the HIV/AIDS pandemic and who advocated for their gay HIV/AIDS patients. In fact, these results are evidence of an untold and valuable period in medical history. For some, it will serve as a reminder. For others, it will be foreign. It was a time marked by a major crisis that mobilized gay militant physicians who were personally and professionally affected, and who were forever transformed by their response to the HIV/AIDS pandemic. This is their hereto untold lived journeys.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.042 | 0.034 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.007 |
| 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".