Towards Cross-Border Environmental Policy Spaces in North America: Province-State Linkages on the Canada-U.S. Border
Bibliographic record
Abstract
A growing number of case studies have painted a picture of a burgeoning network of subnational and cross-border regional environmental linkages along the Canada-United States border, a development which may indicate an evolution in governance arrangements such that cross-border environmental policy spaces are being created. In addition to increasing in number, this literature suggests that cross-border interactions have become more formalized, more functionally intense and increasingly multilateral, or regional, in orientation. This paper explores in a comprehensive, cross-regional manner the finding of these case studies with regard to the extent and intensity of subnational activity by examining the findings of a 2005 survey of environmental linkages between states and provinces along the Canada-U.S. border. The survey findings indicate that subnational and regional interactions have been institutionally and functionally ‘intact’ for longer than most observers of Canada-U.S. environmental relations might expect. One of the most interesting findings is that subnational and regional cross-border environmental linkages, contrary to conventional wisdom, have become more numerous over time but not necessarily more intense in functional terms. Moreover, as expected, environmental linkages are clearly regionally concentrated; clusters of highly linked states and provinces can be found along the Canada-U.S. border, particularly in New England, the Great Lakes and the Pacific Northwest. Each of the clusters – or environmental regions – exhibits unique characteristics in terms of the extent and intensity of cross-border linkages.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".