Designing an International Greenhouse Gas Emissions Trading System
Bibliographic record
Abstract
gas (GHG) emissions trading will expand enormously with the development of GHG regulatory schemes internationally and domestically. Emissions trading offers significant cost savings for nations and firms addressing climate change and provides important risk management tools and profit opportunities for businesses. These include use of trading-based instruments and investments to reduce regulatory compliance costs and risks; and enhanced opportunities for sales, including exports to developed and developing countries, of technologies and products that reduce GHG emissions or sequester GHG. Taking advantage of these opportunities requires an understanding of the basic legal and institutional structures for GHG emissions trading systems. The Kyoto Protocol to the United Nations Framework Convention on Climate Change (FCCC) authorizes several GHG emissions trading systems (flexibility mechanisms) to combat global warming in an efficient, costeffective manner. See Michael Grubb, Kyoto Protocol: A Guide and Assessment (1999). First, Article 17 authorizes emissions trading among industrialized countries listed in Annex I to the FCCC, consisting of the Organization for Economic Cooperation and Development (OECD), Eastern, Central European, and former Soviet Union countries, in order to fulfill their Protocol emissions limitation obligations. This system likely will not become operative until between 2008 and 2112, when the Protocol limits Annex I country GHG emissions by fixed amounts (about 6 percent in the aggregate) below 1990 levels. Second, Article 12 authorizes emissions trading between developing countries, which currently do not have emissions limitation obligations, and Annex I countries and private entities. This system, referred to as the Clean Development Mechanism (CDM), provides certified emission reduction credits to Annex I countries and
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".