CLIMATE CLUBS WITH TAX REVENUE RECYCLING, TARIFFS, AND TRANSFERS
Bibliographic record
Abstract
The E3ME-FTT model is applied to assess the impacts of alternative climate club structures. We consider two kinds of climate club memberships: the World Climate Club (WCC), where every country in the world joins the club, and the Core Climate Club (CCC), with seven likely club members: EU+5, Japan, South Korea, Canada, Brazil, Mexico, and Australia. First, we find that both the WCC and domestic revenue-neutral recycling matter a lot. The global CO2 emissions in 2050 could be reduced by 50% from BAU under the WCC. With domestic revenue-neutral recycling, there will be large positive impacts on GDP under both the WCC and the CCC. Secondly, the negative effects of trade sanctions on cumulative global GDP and global CO2 emissions make it unwelcome to be used as part of the club design. Lastly, the introduction of international transfers will result in a win—win solution that will not only increase the cumulative global GDP and reduce global CO2 emissions but also enhance the equality among club members and induce more likely participation in the climate club.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 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".