Water quality protection of the Canada-US Great Lakes: examining the emerging state/nonstate governance approach
Bibliographic record
Abstract
This paper explores the growing contribution of nonstate actors (private sector and civil society) in the environmental regulatory governance of the North American Great Lakes. The paper maps the various state and nonstate rule-instruments, institutions, processes and actors (governance arrangements), focusing on arrangements in Ontario, Canada, one Great Lakes jurisdiction. At times, the private sector and nongovernmental organisation (NGO)-initiated governance contributions are collaborative in nature, but in other situations, a rivalrous dynamic is evident. The resultant combination of state and nonstate regulatory arrangements, operating at times in a collaborative manner, and in other cases, in more of an adversarial manner, aligns well with Webb's (2005) concept of sustainable governance. The issue of microbeads pollution in the Great Lakes is highlighted as an illustration of how state and nonstate actors are variously responding to an environmental issue, and provides evidence of how the norm of water quality protection is increasingly addressed and embedded through both state and nonstate mechanisms in the larger social environment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".