How useful is the concept of polycrisis? Lessons from the Development of the Canada Emergency Response Benefit during the COVID-19 pandemic
Bibliographic record
Abstract
the empirical basis for the concept of polycrisis has only been articulated at a high level of abstraction, typically dealing with global issues like climate change or migration.Because of that, its relevance and utility at the domestic level vis-à-vis adding value to existing studies of crisis management are unclear.as a set of events lasting over two years involving a pandemic with multiple simultaneous and interconnected economic and public health implications, the cOViD-19 pandemic provides both scholars and practitioners with a rare opportunity to look in more detail into how domestic policy design actually occurred during this global event.in this article, we investigate the creation of the canada emergency Response Benefit (ceRB) program during the cOViD-19 crisis.the ceRB case illustrates the importance of three factors that together form a trifecta of best practices for national-level policy design in a crisis-policy integration, learning, and agility-and shows how these elements evade capture by the polycrisis concept, thereby limiting its usefulness.
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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 | 0.023 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.063 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".