A Theoretical Inquiry of the Offset Mechanism in Mitigating Global Warming: Economic Welfare Implications of the Clean Development Mechanism Investment
Bibliographic record
Abstract
This study attentively examines the role of the offset mechanism like the Clean Develop Mechanism (CDM) in mitigating global warming problems and considers its economic welfare implications in a theoretical offset environment. The CDM is a kind of offset trading scheme of carbon dioxide (CO2) emissions between advanced and developing economies. Formulating the essence of the offset market into a simple model, we interpret the right to trade CO2 emissions at an ideal price as rewards to advanced economies for investing in more CO2 saving technologies and/or factories in developing economies. Our model shows that under some conditions the CDM can succeed in suppressing CO2 emissions and become a second-best measure to mitigate global warming. Nevertheless, we also clarify that the prices of carbon offset in advanced economies are not generally sustainable without the help of the outside agencies such as the governments. This fact suggests that offset mechanism like the CDM incurs an additional burden, such as taxes to advanced economies for preserving the scheme, although the resultant transfer evidently equalizes the international income distribution.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".