PUBLIC HEALTH, PUBLIC HEALTH ETHICS PRINCIPLISM, AND GOOD GOVERNANCE DURING THE COVID-19 PANDEMIC
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The COVID-19 pandemic brought about at least two normative challenges on unprecedented scale for liberal democracies. One concerned prioritization decisions when health care resources were constrained. The other, which arguably led to lasting damage to social cohesion and citizens’ trust in government and government public health institutions, concerned policies introduced with the aim of reducing the spread of SARS-CoV2, some of which turned out to be mistaken. I discuss in this essay a few examples of misguided, liberty-limiting public health policies and describe how public health and public health ethics principlism provided cover for such policies. Citizens had reasons to be concerned about the duration of such liberty-infringing policies, the absence of predictable government policies, and the absence of transparent justifications for the policies that were implemented.
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.
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 | 0.021 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.014 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.009 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it