Tri Community Watershed Initiative: Towns of Black Diamond, Turner Valley and Okotoks, Alberta, Canada Promoting Sustainable Behaviour in Watersheds and Communities
Bibliographic record
Abstract
For the past two years, three rural municipalities in the foothills of the Canadian Rockies have been working together to promote sustainability in their communities. The towns share the belief that water is an integral part of the community; they have formed a Tri Community Watershed Initiative to help manage their shared resource. Activities of the Initiative include changing municipal policies, writing municipal water, and river valley management plans, working with partners, hosting community events and engaging local media in community success stories. The towns are also assisting residents in outdoor water conservation efforts. To date, 100 percent of the households -- more than 15,000 residents in approximately 6,000 households -- have participated in community-wide water conservation campaigns that protect the local watershed. The Initiative has improved local policy and decision-making through a collaborative, multi-stakeholder approach that delivers ecological monitoring science in a manner that improves knowledge in the decision-making process. Involvement of town councilors in this ecological monitoring initiative has allowed local decision makers to gain awareness and knowledge that has led to action on community environmental watershed issues and increased community capacity. Decisions made at local and landscape scales have a direct impact on sustainability. This Initiative has succeeded in ensuring that choices are informed and reflect the collective values of the community. By identifying values and defining sustainability, the communities have been empowered to monitor progress and feed into adaptive decision- making processes. The framework and best practices the towns have developed for engaging communities will be discussed as well as lessons learned.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.002 |
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".