Cross-border Great Lakes Fishery Management: Achieving Transboundary Governance Capacity Through a Non-binding Agreement
Bibliographic record
Abstract
Fishery management authority on the Great Lakes is spread amongst eight states, the Province of Ontario, and Native American tribes. These jurisdictions are inherently in conflict over their fishery management, as they have differing management philosophies, needs, constituent pressures, and political dynamics. To avoid a tragedy of the commons, some degree of transboundary governance must occur. To work within this paradigm, the jurisdictions cooperate through “lake committees,” which are action arms of A Joint Strategic Plan for Management of Great Lakes Fisheries, a non-binding, consensus-based agreement. This paper presents the lake committees and the Joint Strategic Plan as a set of institutional arrangements for transboundary governance; it analyzes the plan according to the four indicators presented in the framework paper in this special issue: functional intensity, stability and resilience, legitimacy, and compliance. The plan’s transboundary governance capacity ranks high on all four institutional indicators: it fosters deep ongoing interactions, it is robust, it is legitimate in the eyes of a strong “epistemic community” of fishery management professionals, and it contains effective compliance mechanisms. The plan fares less well in terms of coordinating fishery management with other Great Lakes policy goals (such as water quality improvement and habitat protection), though integration is improving.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".