Ethical Reflections on the Conduct of HIV Research with Community Members: A Case Study
Bibliographic record
Abstract
Some researchers continue to engage in "helicopter" or "parachute" research and do not ethically engage or collaborate with communities from which data are collected. This paper uses a case study to discuss the ethical issues arising from these research practices and the importance of increasing meaningful community involvement in research. Set in the context of research among older people living with HIV, the case study is followed by the perspectives of four research stakeholders. Through these perspectives, this paper demonstrates the ethical perils and harms that stem from research practices exemplified in the case. We argue instead for researchers to practice participatory research methods in line with community-based participatory research approaches (CBPR), good participatory practices (GPP), the Denver Principles, and CIOMS guidelines. Towards this end, we describe tools developed in collaboration with stakeholders in the research process to help researchers incorporate community participation and reduce unethical research conduct.
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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 | 0.103 | 0.121 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.060 | 0.039 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.006 | 0.021 |
| Research integrity | 0.016 | 0.017 |
| Insufficient payload (model declined to judge) | 0.003 | 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".