Transboundary Policy Challenges in the Pacific Border Regions of North America
Bibliographic record
Abstract
Transboundary Policy Challenges in the Pacific Border Regions of North America responds to a growing interest in borderlands environmental policy by highlighting significant transboundary research and practices being undertaken within and across the Pacific border regions of North America. The issues explored here reveal how intricate and interrelated social, economic, and environmental concerns have become, particularly along borders, as Canada, Mexico, and the United States collectively search for sustainable solutions. Growing concern about the seriousness of environmental problems, particularly in high-growth border areas, coupled with the rising awareness of the complexities entailed in wise development decisions, has spurred recognition that new realities require new responses. Critical for effective environmental protection, restoration, and education is a sharing of understanding and effort across borders. Transboundary Policy Challenges in the Pacific Border Regions of North America highlights advances in transborder environmental research and discusses sensible policy directions with particular focus on critical areas of international concern and engagement: land and water use planning; regional growth management; trade and transportation corridors; environmental education; and travel and tourism. With Contributions By: J.C. Day Donald K. Alper K.S. Calbick Jose Luis Castru-Ruiz Alejandro Diaz-Bautista David A. Fraser Salvador Garcia-Martinez Warren G. Gill Duncan Knowler James Louckey Krista Martinez Martin Medina Jean O. Melious Cristobal Mendoza John C. Miles John M. Munroe Emma Spencer Norman Hugh O'Reilly Vicente Sanchez-Munguia Preston L. Schiller Tina Symko Peter Williams
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".