Assessing Adaptive Transboundary Governance Capacity in the Great Lakes Basin: The Role of Institutions and Networks
Bibliographic record
Abstract
Introduction The Great Lakes St. Lawrence River Basin is the largest freshwater basin on earth, containing roughly 20 percent of the world’s surface freshwater. The Great Lakes is a highly complex ecosystem, composed of interrelated open water, shoreline and upper watershed systems, which support a high level of biological diversity. Collectively, the five lakes and their draining river systems span two provinces, eight states, more than forty ‘First Nations/Tribes’ and hundreds of municipalities. The Basin has played a major role in the economic development of the United States and Canada. It continues to provide water for domestic consumption, industry, transportation, power, recreation, and a host of other uses. However, the Great Lakes Basin is under siege. Invasive species, climate change, economic decline, urban sprawl, and chemical and biological contaminants threaten the health and vitality of this ecosystem. Despite numerous initiatives to remedy these varying threats, the environmental sustainability of the basin remains an important public policy and transboundary governance challenge. ...
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".