Emissions trading outside the European Union
Bibliographic record
Abstract
The global market for greenhouse gas emission allowances and emission reductions has grown fast since the beginning of 2005. In the beginning of 2005 the European Union Emissions Trading Scheme (EU ETS) started, setting a GHG emission cap for installations in certain sectors, and allowing these companies to trade among themselves with emission allowances. Other countries are also implementing or planning to implement greenhouse gas emissions trading schemes. The most notable plans are currently in Canada, Japan, the RGGI initiative in the Northeast and Mid-Atlantic States of the USA and in the State of California and four other western states. The underlying asset in the carbon markets is greenhouse emissions and trading schemes can be linked directly or indirectly to each other. The objective of this report is to explore the current state of selected operational and planned greenhouse gas emissions trading schemes globally, to evaluate the compatibility with the EU ETS, and to assess preconditions for linking the schemes. Previous studies on linking are reviewed from the Nordic perspective. In addition the impact of linking state level greenhouse gas emissions trading schemes in the USA on the international carbon markets is discussed.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".