Post-Paris Climate Agreement UNFCCC COP-21: Perspectives on International Environmental Governance
Bibliographic record
Abstract
This contribution presents a number of key assets on the road to a renewable energy global economy. Among these are science, technology innovation and green investment. The Paris Climate Agreement is also presented as a normative framework asset but the deal failed to establish measureable targets to follow up progress throughout its implementation process. This research points out the fact that such a failure is common to most environmental international instruments. The UNFCCC 21st COP which adopted the Paris Climate Agreement is indeed a demonstration once again of the incapacity of the COP mechanism to adopt suitable institutional arrangements to build up sustainability and resilience. It is suggested, however, that this very fact should raise among nations a collective conscience regarding the inadequacies of the current environmental institutions and forums. The international community is invited to seek a strong specialised institution with organisational status within the United Nations system to adopt decisions, environmental standards and sustainability indicators and to implement these autonomously for the sake of the preservation of life on earth for generations to come. To this end, this article shares the solution of resuming and concluding previous consultations and negotiations on reform of the international environmental governance within the United Nations system aiming at the creation of a World Environmental Organisation (WEO).
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".