Varieties of Crises: Comparing the Politics of COVID-19 and Climate Change
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
The COVID-19 pandemic is the largest public health crisis in recent history. Many states have taken unprecedented action in responding to the pandemic by restricting international and domestic travel, limiting economic activity, and passing massive social welfare bills. This begs the question, why have states taken extreme measures for COVID-19 but not the climate crisis? By comparing state responses to COVID-19 with those to the climate crisis, we identify the crisis characteristics that drive quick and far-reaching reactions to some global crises but not others. We inductively develop a conceptual framework that identifies eight crisis characteristics with observable variation between COVID-19 and climate change. This framework draws attention to under-considered areas of variance, such as the perceived differences in the universality of impacts, the legibility of policy responses, and the different sites of expertise for both crises. We use this structured comparison to identify areas of leverage for obtaining quicker and broader climate action.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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