Growing Apart: China and India at the Kigali Amendment to the Montreal Protocol
Bibliographic record
Abstract
Abstract Developing countries are growing apart on environmental issues. International environmental negotiations are no longer characterized merely by the North–South conflict. Rising powers have come to divide the Global South and redefine the Common-But-Differentiated Responsibilities principle. This article explains the divergence of China and India at the Kigali Amendment to the Montreal Protocol, one of the first global environmental agreements to differentiate obligations between developing countries. China and India, the world’s two largest hydrofluorocarbon producers, ended decades of collaboration and split the rest of the developing world behind them. I argue that developmental strategy and political institutions shape the preferences and influences of industrial, governmental, and social stakeholders, thereby explaining their negotiation behavior and outcome. This article explains why China moved faster and further than India on negotiations for hydrofluorocarbon regulation. It has important implications for the two rising powers’ implementation of the Kigali Amendment and for their position formulations on other environmental issues.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".