Explaining Intergovernmental Conflict in the COVID-19 Crisis: the US, Canada, and Australia
Bibliographic record
Abstract
The Covid-19 pandemic produced more significant immediate intergovernmental conflict in the U.S. than in Australia and Canada. This article considers three variables for this cross-national divergence: presidentialism versus parliamentarism; vertical party integration; and strength of intergovernmental arrangements. We find that the U.S. presidential system, contrary to parliamentarism in Canada and Australia, provided an opportunity for a populist outsider skeptical of experts to win the presidency and pursue a personalized style that favored intergovernmental conflict in times of crisis. Then, the intergovernmental conflict-inducing effect of the Trump presidency during the pandemic was compounded by the vertical integration of political parties, which provided incentives for the President to criticize Democratic governors and vice-versa. Third, the virtual absence of any structure for intergovernmental relations in the United States meant that, unlike Australian states and Canadian provinces, American states struggled to get the federal government’s attention and publicly deplored its lack of leadership.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".