COVID-19 Vaccination Mandates and Vaccine Uptake
Bibliographic record
Abstract
We evaluate the impact of government mandated proof of vaccination requirements for access to public venues and non-essential businesses on COVID-19 vaccine uptake.We find that the announcement of a mandate is associated with a rapid and significant surge in new vaccinations (more than 60\%increase in weekly first doses) using the variation in the timing of these measures across Canadian provinces in a difference-in-differences approach.Time-series analysis for each province and for France, Italy and Germany corroborates this finding, and we estimate cumulative gains of up to 5 percentage points in provincial vaccination rates and 790,000 or more first doses for Canada as a whole as of October 31, 2021 (5 to 13 weeks after the provincial mandate announcements).We also find large vaccination gains in France (3 to 5 mln first doses), Italy (around 6 mln) and Germany (around 3.5 mln) 11 to 16 weeks after the proof of vaccination mandate announcements.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".