La pandémie immunise-t-elle les\nQuébécois 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. Abstract: La pandémie de COVID-19 a forcé les gouvernements de partout dans le monde à mettre en place très rapidement un nombre important de nouvelles politiques non seulement en matière de santé, mais également dans le domaine sociofiscal. Plusieurs se questionnent ouvertement à savoir si ces nouvelles mesures sont là pour de bon et si la crise et la réponse qui y est apportée marquent un changement de direction quant à la taille des États occidentaux et l'ampleur de leur intervention. Cette étude vise, à l'aide de données de sondage, à observer si des changements sont à l'œuvre quant à ces questions au sein du public. Les données ont été colligées au Québec au plus fort de la crise sanitaire. Les Québécois se montrent en général plus tolérants face au niveau des impôts par rapport aux données d'enquêtes précédentes. Nous observons également que les Québécois qui ont directement bénéficié des mesures de soutien comme la Prestation canadienne d'urgence ne diffèrent pas des autres Québécois quant à leur opinion sur le poids des impôts. La plus grande ouverture à des impôts plus élevés à l'avenir semble donc généralisée et ne s'explique pas par les bénéfices individuels tirés des programmes inédits liés à la pandémie. D'autres enquêtes seront nécessaires pour mesurer si ces changements sont durables.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".