Vaccinate-or-mask: Ethical duties and rights of health care providers in obtaining or refusing the influenza vaccination
Bibliographic record
Abstract
There is much controversy over the effectiveness of the influenza vaccination; yet, globally, many health institutions are implementing policies that require health providers to either receive the influenza vaccination or wear a surgical mask. This vaccinate-or-mask policy has caused great hullabaloo among health care providers and the institutions wherein they work. In light of the limitations to best practice evidence, we conducted an analysis of the policy and its implications based first on the bioethical principles of beneficence, nonmaleficience, respect for autonomy, and justice and then on the ethical theories of Immanuel Kant and John Stuart Mill. The most important ethical issue was threat to patient safety and welfare in the event of receiving care from a health provider who chose to forego the influenza vaccination and surgical mask requirement. We concluded that policies requiring health care providers to receive the influenza vaccination or wear a surgical mask are only partially supported by the bioethical principle approach; however, they are clearly justified from a deontological standpoint. That is, Kant would argue the rightness of the policy as a moral imperative for health care providers to not impose a health risk to those they serve and for health care institutions to ensure professional care giver vaccination. In further considering the vaccinate-or-mask policy in terms of the utilitarian “greatest good for the greatest number”, we determined that Mill would argue that this type of policy is ethically right and just, but also that policies solely requiring immunization would be ethical as public well-being is promoted.
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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 | 0.065 | 0.096 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.047 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.010 | 0.010 |
| 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".