Ethics issues for HIV/AIDS researchers in international settings — perspectives from the Canadian experience
Bibliographic record
Abstract
In recognition of the level of international HIV/AIDS research being conducted by Canadians, the Canadian Association for HIV Research (CAHR), along with its partners, has developed a resource document to assist researchers in identifying and preparing for the unique ethics issues and challenges that may arise during international HIV/AIDS research. Between 2004 and 2007, face-to-face consultations were undertaken with community and government stakeholders, and interviews were conducted with eight prominent HIV/AIDS researchers with international experience to identify key research ethics challenges and structural, cultural, political, social, and economic factors that may impact HIV/AIDS research ethics in resource-limited settings. These challenges and factors served as the basis for the hypothetical ethics issues case scenarios developed for each of the four research tracks. Ethics issues were identified at every stage of the research process. Key contextual issues included: (1) stigma and culturally-embedded conceptualizations of HIV; (2) local and global politics and economics; (3) gender inequities, power dynamics, and sexual roles; and (4) allocation and availability of resources for research and health services. The final document resulting from the consultation process provides a framework for open dialogue on the complex and interconnected ethics issues researchers may experience in the field of international HIV/AIDS research, and contributes to the HIV/AIDS research field by reinforcing the need for high quality and ethically sound research. This document can be found at http://ethics.cahr-acrv.ca/.
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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 | 0.033 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.077 | 0.037 |
| Scholarly communication | 0.022 | 0.006 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.007 | 0.014 |
| Insufficient payload (model declined to judge) | 0.005 | 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".