Getting hotter : how could China’s climate change policy trajectory impact a Post-Kyoto accord?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
China’s unprecedented economic growth has given rise to equally rapid increases in greenhouse gas emissions. China has already ratified the Kyoto and Montreal Protocols, yet as the international community looks beyond Kyoto, China’s willingness to adhere to binding emissions standards remains a critical question. This study describes and analyzes the factors that influence China’s possible participation in a binding greenhouse gas emissions treaty. Existing international treaty compliance models often overlook China’s own official policies and stances toward such treaties. This study examines China’s current climate change policy, historical adjustments of that policy, and potential future trajectory to determine the factors that would most impact China’s willingness to sign a post-Kyoto climate change. This study utilizes both English and Chinese-language documents to analyze current Chinese climate change policies. It describes the historical trajectory of Chinese environmental policy since 1972, tracing the evolution of the “common but differentiated responsibilities” principle and of the demand for technology transfers and access to international funds. This study also examines reports from the World Bank, China Council for International Cooperation on Environment and Development (CCICED) and the Organisation for Economic Co-operation and Development (OECD), explicating how recommendations from influential organizations may impact China’s future policy trajectory. Most surprisingly, the conclusion of this study is that China, while retaining much of its former stance on climate change, is also increasingly warming to taking bold actions to reduce greenhouse gas emissions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it