A Rare Moment of Cross-Partisan Consensus: Elite and Public Response to the COVID-19 Pandemic in Canada
Bibliographic record
Abstract
The COVID-19 pandemic requires an effort to coordinate the actions of government and society in a way unmatched in recent history. Individual citizens need to voluntarily sacrifice economic and social activity for an indefinite period of time to protect others. At the same time, we know that public opinion tends to become polarized on highly salient issues, except when political elites are in consensus (Berinsky, 2009; Zaller, 1992). Avoiding elite and public polarization is thus essential for an effective societal response to the pandemic. In the United States, there appears to be elite and public polarization on the severity of the pandemic (Gadarian et al., 2020). Other evidence suggests that polarization is undermining compliance with social distancing (Cornelson and Miloucheva, 2020). Using a multimethod approach, we show that Canadian political elites and the public are in a unique period of cross-partisan consensus on important questions related to the COVID-19 pandemic, such as its seriousness and the necessity of social distancing.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.019 | 0.005 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".