Bibliographic record
Abstract
In his 2000 book, From Chaos to Coercion: Detention and the Control of Tuberculosis, Richard Coker makes a number of important observations and arguments regarding the use of coercive public health measures in response to infectious disease threats. In particular, Coker argues that we have a tendency to neglect public health threats and then demand immediate action, which can leave policymakers with fewer effective options and may require (or may be perceived as requiring) more aggressive, coercive measures to achieve public health goals. While Coker makes a convincing case as to why we should find it ethically problematic when governments find themselves in this position and resort to coercion, left outstanding is the question of whether this should preclude governments and health authorities from using coercion if and when they do find themselves in this position. In this paper, I argue that, while we should consider it ethically objectionable when governments resort to coercion because they have neglected a public health threat, its causes, and other possible responses to that threat, this should not then necessarily rule out the use of coercion in such circumstances; that there are ethically objectionable antecedents for why coercion is being considered should not necessarily or automatically cause us to think coercion in such cases cannot be justified. I address an objection to this argument and draw several conclusions about how governments' use of coercion in public health should be evaluated.
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 | 0.002 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".