Greening NAFTA: The North American Commission for Environmental Co-operation
Bibliographic record
Abstract
Greening NAFTA: The North American Commission for Environmental Co-operation, David L. Markell & John H. Knox, eds., Stanford Law & Politics Series; Stanford University Press, 2003, pp. xv, 324. At first blush, the title of this book, Greening NAFTA , would likely be viewed as an oxymoron by most environmentalists. After all, the environmental critiques of free trade including the massive use of fossil fuels in transporting goods around the globe and a “race to the bottom” as it relates to environmental standards, among others, continue to resonate among North American environmentalists. However, once one has tucked into this volume, it becomes clear that the intent of this edited collection is to examine how effective the North American Commission for Environmental Cooperation (the NACEC or CEC) has been in its (now) ten years of existence. Its genesis was largely the result of widespread objections made by North American environmental groups and, at the time it was created (1994), it was the first international organization created to address the environmental aspects and issues associated with economic integration. In some respects, a more appropriate title for this edition would have included a question mark after the word NAFTA, because the contributors to this book have very mixed assessments as to whether the CEC has fulfilled its early promise of having a greening effect on NAFTA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".