Bibliographic record
Abstract
Plans to prepare for a global pandemic have proliferated in recent years, and “legal preparedness” has emerged as a critical component of such plans. Commonly, the threat of disease is analogized to terrorism and recast as an issue of national security. In this framing, laws authorizing surveillance, containment, and forced treatment are understood as necessary. Law’s promise of protection against abuses in the exercise of such powers through procedural rights of review offers meagre comfort for critics concerned that individual liberties will readily yield to national security and public health in the context of an actual pandemic. An alternative framing shifts the focus to marginalized populations and existing disparities that account for the markedly disparate impacts of disasters. In shifting the frame, a broader conceptualization of law’s role emerges, one in which the redistribution of the burden of pandemics and access to the social determinants of health become central.
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 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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.024 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.017 | 0.011 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".