Crisis standards of care in a pandemic: navigating the ethical, clinical, psychological and policy-making maelstrom
Bibliographic record
Abstract
The COVID-19 pandemic has caused clinicians at the frontlines to confront difficult decisions regarding resource allocation, treatment options and ultimately the life-saving measures that must be taken at the point of care. This article addresses the importance of enacting crisis standards of care (CSC) as a policy mechanism to facilitate the shift to population-based medicine. In times of emergencies and crises such as this pandemic, the enactment of CSC enables concrete decisions to be made by governments relating to supply chains, resource allocation and provision of care to maximize societal benefit. This shift from an individual to a population-based societal focus has profound consequences on how clinical decisions are made at the point of care. Failing to enact CSC may have psychological impacts for healthcare providers particularly related to moral distress, through an inability to fully enact individual beliefs (individually focused clinical decisions) which form their moral compass.
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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 | 0.039 | 0.063 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.034 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.015 | 0.025 |
| 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".