Great Lakes Governance Reform for Place-based Regeneration of the Natural and Built Environment
Bibliographic record
Abstract
Canadian municipalities are confronted by challenges related to continued growth, climate change and aging infrastructure, and the increasingly limited ability of receiving waterways to absorb the impact of stormwater runoff and pollution. There is increased recognition that integrated water, wastewater and stormwater management is required to ensure cost-effective water services as well as sustainable water resources to support public health, economy and environment now and in the future. In particular, this is a defining moment for the Great Lakes St. Lawrence region, with the opportunity to update the approaches taken for ecosystem improvement and protection in the region. The outcome of a 2007 review of the binational Great Lakes Water Quality Agreement resulted in a broad call for revisions to the Agreement, so that it can once again serve as a visionary document driving binational cooperation to address both long-standing and emerging Great Lakes environmental issues in the 21st century. The focus of the new agreement emphasizes the creation of a nearshore framework. While this term is still undefined, it reflects a policy need for a framework for scientific cooperation in the nearshore zone. In parallel, there is a need for a governance framework that enables place-based decision making for appropriate interventions, in order to promote resilience at the land-water interface. Governance frameworks for integrated water management are limited in Canada, and this research seeks to identify the most promising models.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".