Integrated watershed management in Quebec (Canada): a participatory approach centred on local solidarity
Bibliographic record
Abstract
The Quebec Water Policy was launched in November 2002 in support of reform of the water governance. One of the government commitments is to gradually implement watershed-based management for 33 major watercourses located primarily in the St. Lawrence plain. At the local and regional levels, watershed organizations are responsible for implementing integrated management, from a sustainable-development perspective, by preparing a master plan for water (MPW), which will include watercourses, lakes, wetlands and aquifers. These watershed organizations rely on public consultation, as well as local and regional expertise, on the responsibilities for water of the municipalities and regional county municipalities of the territory, as well as those of the ministries and other government agencies. They are also required to observe national priorities regarding protection, restoration, and development of water resources and to comply with relevant guidelines, directives, standards, regulations, and legislation. The role of watershed organizations is to act as planning and consultation tables. Government representatives are present, on the initial process, as the facilitator and for scientific and technical support. They do not have, at this moment, any voting or decisional rights. After two years, integrated water management mobilized water stakeholders on watersheds and they are on their way to initiating their first MPW.
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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 | 0.009 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".