Addressing sustainability challenges in micro‐municipalities: Insights from the study of Quebec's smallest municipalities
Bibliographic record
Abstract
Abstract Many empirical studies on large municipalities, ranging from thousands to millions of inhabitants, have helped shape the knowledge of sustainability management in developed countries. However, issues and approaches specific to micro‐municipalities with fewer than 1,000 inhabitants have been relatively less covered. In this context, this study presents an empirical content analysis of sustainability‐related instruments used in the 487 smallest municipalities of Quebec. A total of 1,962 instrumental documents were identified, and their characteristics (e.g., accountability‐based vs. informative‐based approach) and scope (e.g., land‐use planning and pollution reduction) were assessed. The results are threefold. First, informative‐based instruments (e.g., flyers and project presentations) are generally preferred to those with accountability mechanisms (e.g., policies and plans). Second, 90% of the municipalities address sustainability issues, but in pieces and parsimoniously rather than comprehensively; hence, initiatives vary significantly from one municipality to another. Third, because of their mandatory nature, initiatives such as sorted waste collection and pro‐environmental zoning are common among municipalities. In contrast, non‐mandatory services such as transportation planning have only a few adopters. These findings have policy implications for urban sustainability management in micro‐municipal organizations .
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".