The Consequences of Country’s Withdrawal from Climate Change Agreements: Implications for Carbon Emissions Reduction
Bibliographic record
Abstract
At the end of the recently held UN climate change conference in Durban, South Africa in 2011, a number of key and important issues on global warming were discussed including an agreement to negotiate a new and more inclusive legally binding treaty and the establishment of a Green Climate Fund. Suprisingly, with regard to the existing agreements, some countries have pulled out and also decided not to be bound by subsequent agreements. It is against this backdrop that this article examines the consequences of some countries pulling out of the existing agreements aimed at protecting the environment and reducing the countries’ carbon footprints. The article looks at the existing international legal framework mainly the Kyoto Protocol which has been ratified by about 192 countries and the legal regimes of the countries that have pulled out or refused to be legally bound by any agreement pertaining to reduction of carbon footprints. It examines the consequences such withdrawal will have on the set targets of reducing the global emissions by half in 2050.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".