Understanding the International Joint Commission: a comparative case study approach
Bibliographic record
Abstract
Why the interest in the Commission? Internationally, its reputation is one of the most successful among conflict management agencies. Using a case study approach, this research aims to understand and account for the Commission's effective performance in two policy areas. The cases are chosen to capture a range of variation. In 1977, the governments of Canada and the United States asked the IJC to investigate controlling extreme water levels in the case on Great Lakes Diversions and Consumptive Uses. With the high water levels of the Great Lakes during the 1970's, there was interest in diverting water out of the Basin for western economic development. In 1985, the IJC finally made its recommendations on the issues. In 1975, the governments referred questions concerning the transboundary implications of the Garrison Diversion Unit project to the Commission. This public works project was designed to divert water from the Missouri River Basin to the Souris and Red River Valleys in North Dakota for irrigation; however, interests in Manitoba were concerned about the harmful implications of inter-basin water transfers. This represented a classic western water project that benefitted farmers in North Dakota. In comparison with the Garrison Diversion case, the Great Lakes reference demonstrates the technical and political complexities generated by regulatory issues in managing boundary problems. The Garrison case shows the influence that domestic politics can have on binational relations. We find that issue areas do matter in the Commission's ability to bring the governments to the table. We find that studying the domestic setting in which the Commission operates reinforces our argument about the influence policy arenas have on binational policy processes and outcomes. We find that the Commission's study boards became arenas of policy conflict, and in the case of the Great Lakes, were unable to generate consensus on regulatory norms. In comparison, the IJC was more successful in building a clear domestic constituency with the Garrison case. Its lack of a clear political constituency in the Great Lakes case was a handicap in building public and governmental support for a more independent role in that issue area.
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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 | 0.026 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.025 |
| Science and technology studies | 0.016 | 0.018 |
| Scholarly communication | 0.023 | 0.026 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".