Farming, Good Neighbours, and Protecting the General Interest in Water Resources: How Effective is the Promise of Sustainable Watershed Management in Quebec?
Bibliographic record
Abstract
The framework for implementation of sustainable watershed management in Quebec comprises a mix of statutory accountability, compliance with plans, and civil liability. At the centre of this framework is the goal of realizing collective responsibility for the protection and preservation of water now and for future generations. Implementation of this framework to achieve that goal, and the extent to which it enables farmers to deliver sustainable watershed management practices, is a case study in natural resource governance arrangements and sustainable resource management behaviour change. This article reviews governance arrangements for sustainable watershed management in Quebec and presents research on farmer accountability within sustainable watershed systems. The analysis considers the extent to which farmer accountability for protection of water is defined by sustainable watershed management planning processes. Such processes are focussed on strategic imperatives that are not effectively connected with the practice of private rights and interests. With this in mind, I question how effectively accountability for sustainable watershed management translates into practical guidance that enables farmers to manage resources as good neighbours and meet their duty of water protection. Obstacles identified include: a tendency for the National Assembly, regulators, and courts to absolve farmers from liability for environmental harm; the lack of sanctions for non-compliance with a plan; a lack of financial incentives to modify farm practices; and the fact that watershed organizations lack powers to compel participation in the adoption of a plan.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.016 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".