Climate Change Policy in North America
Bibliographic record
Abstract
Illustrations Tables Acronyms Chapter 1: Designing Integration: The System of Climate Change Governance in North America Debora VanNijnatten (Wilfrid Laurier University, Political Science) and Neil Craik (University of Waterloo, director of the School of Environment, Enterprise and Development) Chapter 2: Supply and Demand for a North American Climate Regime Isabel Studer (Tecnologico de Monterrey, director of the Global Institute for Sustainability) Chapter 3: Building on Sub-Federal Climate Strategies: The Challenges of Regionalism Barry G. Rabe (Gerald Ford School of Public Policy) Chapter 4: Standards Diffusion: The Quieter Side of North American Climate Policy Cooperation Debora VanNijnatten (Wilfrid Laurier University, Political Science) Chapter 5: Deploying the Smart Grid Across Borders in North America Ian H. Rowlands (University of Waterloo, Environment and Resource Studies) Chapter 6: New Approaches to Climate Mitigation: Collaborative Strategies for Developing Renewable Energy in North America Jose Etcheverry (York University, Environmental Studies) Chapter 7: Climate Financing in a North American Context Clare Demerse (Pembina Institute, Director of Federal Policy) and Sandra Guzman (Director of the Air and Energy program of the Mexican Center of Environmental Law) Chapter 8: Regional Climate Policy Facilitation: The Role of the North American Commission on Environmental Cooperation Neil Craik (University of Waterloo, director of the School of Environment, Enterprise, and Development) Chapter 9: Design Issues for Linking Carbon Markets Brian C. Murray (Duke University, Nicholas School of the Environment), Peter T. Maniloff (Duke University, Nicholas School of the Environment) and Jonas Monast (Duke University, School of Law) Chapter 10: Developing Integrated Carbon Accounting Systems Steven B. Young (University of Waterloo, School of Environment, Enterprise and Development) and Clint L. Abbott (University of Victoria, Centre for Global Studies) Chapter 11: Trade Rules, Dispute Settlement, and Barriers to Regional Climate Cooperation Andrew Green (University of Toronto, Faculty of Law) Chapter 12: Conclusion Neil Craik (University of Waterloo, director of the School of Environment, Enterprise, and Development) and Debora VanNijnatten (Wilfrid Laurier University) Appendix A List of Contributors
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.049 | 0.003 |
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".