A SWOT Analysis of the Great Lakes Water Quality Protocol 2012: The Good, the Bad and the Opportunity
Bibliographic record
Abstract
Since the signing of the Great Lakes Water Quality Protocol by Canada and the United States on September 7, 2012, there has been no review of it in the literature. This paper aims to fill that gap by conducting a Strength, Weakness, Opportunity and Threats (SWOT) analysis that will aid in deducing strategies to maximize the strengths and opportunities and minimize the weaknesses and threats to achieving the purpose of the Protocol. The review found that the Protocol has maintained the basic visionary infrastructure retaining the purpose and main objectives while broadening the scope to include three new Annexes; Aquatic Invasive Species, Habitat and Species and Climate change. Weaknesses include instances of ambiguous language, the separate treatment of groundwater, lack of Annex on Indigenous engagement and discrepancies between the principles and the Annexes. A key threat remains the lack of resources for the implementation of the Protocol.
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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 | 0.155 | 0.183 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".