Emissions trading - economic and political perspectives on an international scheme based on the examination of the EU ETS, the Australian CPRS and the WCI in the US and Canada
Bibliographic record
Abstract
Increasing greenhouse gas concentration in the atmosphere and the resulting warming of the climate are a great challenge for humanity.Politics has several instruments at hand to tackle this issue, one of them being the trade in emission permits.Based on the economic theory of emission trading the paper examines trading systems in the EU, Australia and the US and possible barriers and challenges in linking them.In combination with the opinions and experiences expressed in nine interviews carried out with experts from different areas, private industry, universities and public administration, a number of conclusions could be drawn.These have to be seen in light of a few basic assumptions the reader is made aware of before the start of the main part.They are presented to underline the viability of the cap-and-trade policy vis-à-vis different views.In the end, it turned out that there are several issues which represent major obstacles to linking the systems analysed.Comparability on multiple levels emerged as the essential problem, but also minor deficiencies within the schemes as such proved to be issues of importance beforehand.As a conclusion, for a direct link to become effective in the future, these barriers would have to be removed by political coordination or even integration, which seems unrealistic at present, despite the economic and social similarities in the regions examined.However, an idea to initiate this process as well as an outlook on the issue of involving emerging and developing countries is presented at the end.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".