Transitioning to a circular economy in a mid-sized city: takeaways from the Circular and Sustainable Innovation District project of Victoriaville, Canada
Bibliographic record
Abstract
This chapter presents how Victoriaville, a mid-sized city in Canada, plans to become a sustainability leader through the Circular and Sustainable Innovation District (CSID) project, with a particular focus on mutualization initiatives. It underscores Victoriaville’s long-standing commitment to environmental sustainability and innovative recycling practices. This case study shows how a city of modest size (48 461 inhabitants) can significantly contribute to sustainable development through focused initiatives. The chapter’s approach includes an analysis of key planning documents and interviews with stakeholders, offering diverse insights into the development and impact of the CSID project. The chapter highlights the importance of municipal leadership, an integrated approach, adaptability, community engagement, and strategic resource management. A key takeaway for mid-sized cities is that implementing mutualization projects, in addition to the typical focus on resource reduction or recycling can be an effective circular economy strategy.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".