A Qualitative Study of Paramedic Duty to Treat During Disaster Response
Bibliographic record
Abstract
OBJECTIVES: Disasters place unprecedented demands on emergency medical services and can test paramedics personal commitment as health care professionals. Despite this challenge, guidelines and codes of ethics are largely silent on the issue, providing little to no guidance on what is expected of paramedics or how they ought to approach their duty to treat in the face of risk. The objective of this research is to explore how paramedics view their duty to treat during disasters. METHODS: The authors employed qualitative methods to gather Australian paramedic perspectives. RESULTS: Our findings suggest that paramedic decisions around duty to treat will largely depend on individual perception of risk and competing obligations. A code of ethics for paramedics would be useful, but ultimately each paramedic will interpret these suggested guidelines based on individual values and the situational context. CONCLUSIONS: Coming to an understanding of the legal issues involved and the ethical-social expectations in advance of a disaster may assist paramedics to respond willingly and appropriately. (Disaster Med Public Health Preparedness. 2019;13:191-196).
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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 | 0.021 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.012 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".