Bibliographic record
Abstract
Nowadays, climate change is an overwhelming threat to many people who live in the planet. As a result, countries signed the United Nations Framework Convention on Climate Change (UNFCCC) and held rounds of negotiations to curb the increasing temperature. Under the principle of ‘common but differentiated responsibility’ in Kyoto Protocol, the responsibilities of developed countries were emphasized. This situation changed in 2007, when China overtook the United States to become the largest emitter of carbon dioxide in the world. China is criticized for being the culprit of the over-emitting carbon dioxide in the atmosphere and is required to shoulder the main responsibility of cutting emissions in post-Kyoto era. However, these blames and requirements are unfair to china and hamper the economic justice of china. This paper is intended to analyze the impact of climate negotiations on economic justice of china from three different aspects: The right to development of China, Emission transfer and China’s export-oriented industry and Injustice China encounters under Clean Development Mechanism (CDM). Key words : Climate negotiation; Economic justice; China; United Nations Framework Convention on Climate Change; Developed countries; Greenhouse gas emission; Right to development; Export-oriented industry; Clean development mechanism
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.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".