Contagious Elections: The Influence of COVID-19 on Comfort in Voting in Canadian Provincial Elections
Bibliographic record
Abstract
Did the COVID-19 pandemic impact citizens' comfort voting in-person? Did it influence their decision to vote, and if so, which method they used to cast their ballot? This article presents public opinion data from the first five Canadian provinces to hold elections during the COVID-19 pandemic: New Brunswick, Saskatchewan, British Columbia, Newfoundland and Labrador, and Nova Scotia. We find that comfort voting in person can be predicted by a person's assessment of their own and their families' COVID risk, as well as their interest in, and the importance that they place on, the act of voting. Those with higher risk, and the psychological engagement with politics that likely led to great awareness of some of the risks the pandemic posed to society, were less comfortable with in person voting. Additionally, we find that those uncomfortable voting in person were more likely to not vote at all, or when they did vote, to use the mail-in voting option. Although advance in-person voting was recommended to avoid election day crowds, comfort voting in-person could not predict in-person advance voting when compared to election day voting.
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".