Quebec’s Cap-and-Trade System for Greenhouse Gas Emission Allowances: Insights for Vietnam’s Upcoming Carbon Market Initiative
Bibliographic record
Abstract
Abstract Quebec inaugurated its Cap-and-Trade System for greenhouse gas emission allowances in 2013, and in 2014 linked with California’s program to create the largest North American carbon market and the first cross-border subnational trading system. Despite over a decade of trading and nearly ten years since the Paris Agreement, global warming remains off track. Emerging economies are acting, notably Vietnam, which is establishing a carbon market to support sustainable development and achieve Net Zero by 2050. The present article thus retraces the evolution of Quebec’s Cap-and-Trade system from its beginnings until today, highlighting some of its successes, challenges, before underlining some key insights for Viet Nam. This is done with the goal to provide Vietnamese officials and experts with valuable tools and insights at an important moment in the development of Viet Nam’s carbon market initiative.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".