Bibliographic record
Abstract
The ethical implications of research into HIV infection and AIDS merit attention in their own right, but of related concern are the ethical implications of HlV infection and AIDS research that investigators in sponsoring international agencies and countries, principally in the developed world, plan and execute in host countries that are principally in the developing world. HlV/AIDS is now a universal phenomenon, but its burden, until recently most profoundly felt in countries of sub-Saharan Africa, especially East Africa, is spreading to countries of Asia that, like those of Africa, are ill-equipped to cope with its personal and economic effects. Within the general area of research with human subjects, concerns arise about how research on HlV infection and AIDS in particular, has affected popular understanding of the character of medical and wider health research. Trans-national research raises questions about the ethical sensitivities that have to be applied when investigators propose research studies on human subjects to be conducted in cultures with which they are unfamiliar, and when investigators from countries with relatively affluent economies intend to develop and implement. research among relatively resource-poor populations, in other countries. Countries with relative wealth often contain impoverished populations, among which HlV infection and AIDS may have an above-average incidence, but the focus of this paper will be on low-income populations in countries other than the investigators' own.
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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 | 0.186 | 0.190 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.084 |
| Scholarly communication | 0.016 | 0.009 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.017 | 0.018 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".