Demedicalizing the Ethics of PrEP as HIV Prevention: The Social Effects on MSM
Bibliographic record
Abstract
Abstract In order to demedicalize the ethics of pre-exposure prophylaxis (PrEP) as HIV prevention, I consider the social effects on men who have sex with men (MSM). The Centers for Disease Control and Prevention (CDC) considers MSM to be the highest risk group for contracting HIV in the USA. The ethics of using PrEP as HIV prevention among MSM, however, has both a medical dimension and a social dimension. While the medical dimension of the ethics of PrEP includes concerns about side effects, drug resistance and distribution, the social dimension of the ethics of PrEP includes concerns about stigmatization, sexual and romantic relationships and sexual freedom. The medical concerns of the ethics of PrEP may take precedence over the social concerns, but there is a growing body of literature that already addresses the medical concerns. Much less attention has been given to the social concerns of the ethics of PrEP, and in this article, I aim to fill this gap in the literature. Therefore, I focus on the often-overlooked social dimension of the ethics of PrEP to help understand the connection between the risks, relationships and communities of MSM using PrEP as HIV prevention.
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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 | 0.020 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.036 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.006 |
| 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".