Bibliographic record
Abstract
Disasters that produce an overwhelming number of casualties demand that healthcare resources be rationed. Given the gravity of these decisions, it is imperative that they be guided by acceptable principles of distributive justice. Utilitarianism governs current disaster triage protocols because the efficient use of resources prevents the greatest amount of disability and mortality in the population. However, this conflicts with maximin egalitarianism, which demands that the most severely injured patients be prioritized even if it is not an efficient use of resources. Utilitarian triage also conflicts with the egalitarian principle of equal chances, which states that all people should be given an opportunity to be given treatment since all persons value their lives equally. Utilitarianism protects the needs of the entire population, and so demands that an individual patient’s right to autonomy and a fiduciary relationship with their physician must be sacrificed. Like other policies in a democratic society, the legitimacy of disaster triage protocols comes from support by the majority. For this reason, choosing the values that guide disaster triage requires open and transparent communal disaster planning that reflects the values of all members of society. Rather than prioritizing one principle over another, it is likely that the most just approach to allocating resources in disaster triage may be to apply a mixture of distributive justice principles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".