Multilateral Trade Measures in a Post-2012 Climate Change Regime
Bibliographic record
Abstract
The climate-trade nexus gains increasing attention as governments are taking great efforts to forge a post-2012 climate change regime to succeed the Kyoto Protocol. This raises the issues of the scope of trade-related measures and of when and how they could be used. This paper discusses how far trade-related measures should be incorporated in that context. Drawing on an analogy to the Montreal Protocol and comparing developing country’s climate mitigation and adaptation needs with the funding available, the paper argues that such measures should initially be applied only among Annex I or II countries. To discipline the use of unilateral trade measures at the international level, the paper emphasizes a need to define comparable climate efforts. Moreover, the Lieberman-Warner bill in the U.S. Senate- taken as a proxy for future U.S. climate legislation- is assessed, and found to be neither effective nor likely to be WTO-consistent. The paper is concluded by arguing that, in order to encourage developing countries to do more to combat climate change, developed countries should focus on carrots. Sticks can be incorporated, but only if they are credible and realistic and serve as a useful supplement
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 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".