A public health ethics analysis of Doxy-PEP: arguments for and against – the ‘no’ case
Bibliographic record
Abstract
In September 2023, the Australasian Society for HIV, Viral Hepatitis and Sexual Health Medicine recommended doxycycline pre-exposure prophylaxis to prevent STIs in gay, bisexual and other men who have sex with men. However, expanding antibiotic use carries the risk of propagating antimicrobial resistance among target STIs and non-target pathogens, prompting some experts to advocate withholding doxycycline pre-exposure prophylaxis until further research is done. Thus, the use of doxycycline pre-exposure prophylaxis is a question of whether the risk of antimicrobial resistance to the population is justified by the health benefits to gay, bisexual and other men who have sex with men. Here, we outline the public health ethics cases for and against this strategy.
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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 | 0.104 | 0.141 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.052 |
| Scholarly communication | 0.018 | 0.020 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.035 | 0.035 |
| Insufficient payload (model declined to judge) | 0.006 | 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".