Bibliographic record
Abstract
Darfur is Sudan’s western region, and the site of one of the major crises of the early 21st Century that dominated world affairs from 2003 to 2009. The Darfur Crisis competed for world attention with major contemporary issues such as the US invasion of Iraq, the War on Terror, the US presence in Afghanistan, the Arab-Israeli Conflict, the Kosovo crisis and the civil war in Democratic Republic of Congo. China was largely held responsible for the overwhelming level of force utilized by the Sudanese Government in quelling peaceful protests in the region in spring and summer of 2003. Its oil interests in the Sudan were identified as the main catalyst for its siding with the Sudanese government and shielding it from punitive measures by the international community. Other catalysts include trade relations and arms sales to Sudan. The objective of this article is to examine China’s policy and role in the management of the Darfur Crisis over the past ten years. It’s based on the thesis that, China’s lenient policy toward the Sudanese government, driven by its oil interests has encouraged the Sudanese government to utilize overwhelming force against Darfur’s legitimate protest with impunity.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".