Curbing Dependence on Coal in China and India to Attain Global Carbon Neutrality: Challenges and Options
Bibliographic record
Abstract
While many developed countries have announced policies for energy transitions, particularly in regard to greenhouse gas emissions, some emerging nations do not appear to be positioned to achieve the goal of net zero carbon. This policy paper focuses on two countries, China and India, which derive the bulk of their energy from coal, and are key to a net zero carbon world. Both countries have prioritized energy security and view all climate initiatives through this prism. They also distinguish between the early industrializers responsible for the bulk of the stock of GHGs, and emerging nations accountable for part of the current flow of emissions. Numerous initiatives have already been undertaken, and policies announced, for cutting carbon emissions in both China and India. However, both countries face major impediments to undertake the measures needed to curb their dependence on coal. Employing a qualitative interpretive methodology rooted in grounded theory, the paper examines the complex energy dynamics facing these two nations, the actions adopted, and policies formulated to limit emissions. The technological, social, political, and financial challenges they face are developed in some detail. Unless mechanisms are devised to support appropriate climate policies, and reduce coal-dependency in China and India, the successful implementation of climate policies in developed nations will not be sufficient to achieve a carbon neutral world.
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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) | 0.000 | 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".