The Conflicts and Coordination in Transfer Rules for Climate-friendly Technology
Bibliographic record
Abstract
The transfer rules for climate-friendly technology are the key elements to settle down disputes between developed countries and most developing countries.Current international law on intellectual property has severely hindered the transfers and dissemination of climate-friendly technologies.This problem is not only due to the over-rigid principles and rules of UNFCCC and TRIPS,but also the deep-rooted conflicts between UNFCCC,which highly values public rights and the TRIPS rules that serve the protection of private rights as the supreme purpose.The future development of the UNFCCC has to seek a breakthrough over capital and technology,which needs great importance attached to coordinate between these two systems.The Doha Declaration has set an example to recognize the public interest to deal with climate change and the Montreal Protocol also has established a case of independent financial support and technology transfer mechanism.
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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 | 0.045 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.023 | 0.018 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 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".