ETHICS BEYOND BORDERS: HOW HEALTH PROFESSIONALS EXPERIENCE ETHICS IN HUMANITARIAN ASSISTANCE AND DEVELOPMENT WORK
Bibliographic record
Abstract
Health professionals are involved in humanitarian assistance and development work in many regions of the world. They participate in primary health care, immunization campaigns, clinic- and hospital-based care, rehabilitation and feeding programs. In the course of this work, clinicians are frequently exposed to complex ethical issues. This paper examines how health workers experience ethics in the course of humanitarian assistance and development work. A qualitative study was conducted to consider this question. Five core themes emerged from the data, including: tension between respecting local customs and imposing values; obstacles to providing adequate care; differing understandings of health and illness; questions of identity for health workers; and issues of trust and distrust. Recommendations are made for organizational strategies that could help aid agencies support and equip their staff as they respond to ethical issues.
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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 | 0.049 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.027 | 0.063 |
| Scholarly communication | 0.020 | 0.012 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.008 | 0.013 |
| 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".