Quels sont les freins des villes à recourir aux mesures d'écofiscalité?
Bibliographic record
Abstract
As they are affected by climate change, municipalities must prepare and adapt their territories and infrastructure to increase their resilience. This work will require billions of dollars. In a context where cities are struggling to provide services to their populations, the question of where to find the necessary resources to finance new projects arises. Eco-taxation is one of the solutions that has been suggested. In 2017, the Quebec Government expanded the taxation and pricing powers of municipalities, enabling them to implement eco-tax measures to address environmental issues. However, few municipalities have used these tools. How can this be explained? This study has two objectives. The first is to identify the barriers preventing municipalities with populations between 10,000 and 50,000 from using eco-taxation tools to address environmental issues in their areas, particularly climate change. The second is to identify solutions to encourage cities to implement eco-taxation measures. Based on thirteen interviews with municipal elected officials and senior civil servants, as well as the responses of 52 elected officials and civil servants to an online questionnaire, seven barriers to the use of eco-taxation in municipalities were identified: the complexity and time required for implementation; the administrative burden of application and management; the lack of knowledge and human resources within municipalities to design eco-taxation measures; opposition from citizens and elected officials; legal challenges; the difficulty of analysing costs and benefits; and the organisational culture of municipal administrations. Solutions to overcome these barriers do exist. Those interviewed and surveyed suggested four solutions: - The Ministry of Municipal Affairs should propose tools that have been tried and tested for implementing eco-taxation measures. - The same ministry should give municipalities access to eco-taxation experts. - Regional county municipalities should be granted taxation and pricing powers similar to those of municipalities. - Government land use planning objectives should be improved by incorporating environmental objectives.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".