Transgressing Scales: Water Governance Across the Canada–U.S. Borderland
Bibliographic record
Abstract
This article examines the rescaling of transboundary water governance along the Canada–U.S. border. We draw on recent research in geography on rescaling and borderlands to query two assumptions prevalent in the water governance literature: that a shift in scale downward to the subnational or “local” scale implies greater empowerment for local actors, and that rescaling implies that higher orders of government become less important in water management. The case study presents an analysis of qualitative and quantitative data drawn from a comprehensive database of transboundary water governance instruments compiled by the authors, interviews with water managers on both sides of the border, and participant observation in transboundary water governance activities. Our analysis indicates that although a significant increase in local water governance activities has occurred since the 1980s, this has not resulted in a significant increase in decision-making power at the local scale, nor has it been accompanied by a “hollowing out” of the nation-state. This suggests the need to question some of the assumptions widespread in the water management literature, such as the putative primacy of the local scale, and highlights the utility of bringing current geographical debates over scale and borderlands to bear on questions of environmental governance.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".