Broken lives, resilient souls: The cost of conflict for Sudanese women
Bibliographic record
Abstract
"The report, published by the U.N. Human Rights Council on Oct. 23, states that more than 10.7 million people have been displaced and 25.6 million Sudanese are at risk of starvation as a result of the conflict in Sudan between the Sudanese Armed Forces (SAF) and the Rapid Response Forces (RSF). Another issue highlighted by the report is the devastating impact of the conflict in Sudan on women. As both the report and many journalists have recently pointed out, the conflict in Sudan is also being waged through the bodies of women. Sudanese women are subjected to severe sexual violence by both SAF and RSF forces and even by some nongovernmental organization (NGO) workers who go to the region to provide aid. In particular, many women who are displaced, forced to leave their families behind and seek refuge in refugee camps, are subjected to sexual assault and harassment. As a result, it has recently been reported in the press that many women have committed suicide in the conflict in Sudan. Sudanese women are not only at risk of rape and harassment in conflict. Women who are raped are usually killed by male family members to "cleanse the dishonor." Those who are not killed face intense psychological and sociological pressure. Many women who are raped as a "war tactic" and become pregnant as a result are trying to survive for themselves and their children in challenging circumstances. The United Nations Population Fund (UNFPA) is currently supporting 49 centers across the country to intervene and prevent the increasing sexual violence against women in Sudan. On the other hand, more than 1,200 women have received sexual health consultations at health centers in the region, with the help of the U.N. and countries such as Canada, Sweden, the U.K. and the U.S. However, despite all these efforts, Sudanese women continue to be wounded by the spiral of violence into which the country has fallen."
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.068 | 0.007 |
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".