Perspectives on non-clinical health care workers’ moral obligation to report for work during virulent epidemics: an exploration in Guinea
Bibliographic record
Abstract
Objectives To examine the views of non-clinical health care workers (NCHW) and lay people in Guinea on NCHWs’ moral obligation to work during epidemics. Methods NCHWs ( N = 227) and lay people ( N = 253) were presented with theoretical vignettes of NCHWs who refused to work during a virulent epidemic and invited to rate the extent to which such decision was acceptable. Vignettes varied in four factors: level of risk of getting infected; the nature of the infection (Ebola, influenza, tuberculosis); working conditions and the NCHW’s family status. Results Three general qualitatively different positions were identified: (a) NCHWs have an unlimited moral obligation to work, irrespective of circumstances (10% of study participants); (b) NCHWs do not have a moral obligation to work (12%), and (c) the moral obligation to work depends entirely on circumstances (58%), while 19% of participants did not express any position. Conclusions Only a small proportion of NCHWs and lay people in Guinea considered that NCHWs’ refusal to work during an epidemic is always unacceptable. Policy makers planning for future epidemics need to take account of NCHWs’ moral dilemmas in deciding whether to report to work during epidemics and provide appropriate working conditions.
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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 | 0.025 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.020 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| 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".