COVID-19 and Support for Executive Aggrandizement
Bibliographic record
Abstract
Abstract The COVID-19 pandemic offers a critical opportunity to assess the extent to which Canadians can be considered reliable defenders of democratic norms and institutions. In the face of such a serious threat to their physical and economic well-being, how willing are Canadians to condone the loosening of restraints on the power of the executive? This article addresses this question by drawing on the terror management and threat literatures. Combining a cross-sectional regression analysis with a vignette experiment and a candidate-choice conjoint experiment, it tests two hypotheses: that people experiencing debilitating anxiety about COVID-19 are more likely to favour weakening checks on the executive and that people will be willing to trade off legislative checks for the sake of their preferred lockdown policy. Both hypotheses are confirmed. In the face of an unprecedented health crisis, COVID-related anxiety and a desire for protective policies may trump respect for democratic norms.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".