Bibliographic record
Abstract
The recent COVID-19 pandemic has brought a broad range of ethical problems to the forefront, raising fundamental questions about the role of government in response to such outbreaks, the scarcity and allocation of health care resources, the unequal distribution of health risks and economic impacts, and the extent to which individual freedom can be restricted. In this clear introduction to the topic Iwao Hirose explores these ethical questions and analyzes the central issues in the ethics of pandemic response and preparedness such as: The general nature of pandemics and the ethics of preparedness Ethical questions about general goals of pandemic response and preparedness The distribution of scarce resources, for example, ventilators, hospital beds, antiviral drugs, and vaccines Restrictions on individual freedom Ethical questions in the wake of pandemics, including contact tracing, vaccine passports, and socioeconomic inequalities. With the use of real-life examples and a clear philosophical approach, The Ethics of Pandemics is a much-needed introduction to some of the most important ethical issues surrounding pandemics. It is essential reading for students of ethics, bioethics, and political philosophy and will also be of interest to those working in related areas such as public policy, public health, health law, nursing, and life sciences.
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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 | 0.002 | 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 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".