La pandémie immunise-t-elle les Québécois contre l’impôt ?
Bibliographic record
Abstract
The COVID-19 pandemic has forced governments to create and quickly implement new policies and programs to both mitigate the health effects of the virus and support the income of individuals. Many are wondering whether these income support programs are there to stay or if the current crisis marks a turning point in the debate about the adequate level of intervention by the State. This article tries to establish if public opinion about this issue is affected by current circumstances. Survey data was collected in Quebec at the height of the pandemic. It shows that, compared to earlier surveys, Quebecers are much more tolerant of the level of general taxation that applies to them. It also shows that opinions about the level of taxation are not influenced by having individually benefited from an income support program such as the Canada Emergency Response Benefit. This new openness to possibly higher taxes in the future does not seem to depend on exposure to the current crop of emergency support programs. Other surveys will be required to assess whether these changes are permanent or if they will recede after the crisis is over.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 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".