‘Those MONUSCO agents left while we were still pregnant’: Accountability and support for peacekeeper-fathered children in the DRC
Bibliographic record
Abstract
The Democratic Republic of Congo hosts the longest-running and largest United Nations peacekeeping mission in history. The United Nations also has reckoned with sexual exploitation and abuse in its own ranks and, in 2003, recognized its importance with a Bulletin which became known as the 'zero tolerance policy'. Policymakers and researchers have paid little sustained attention, however, to children fathered by peacekeepers. In this article, we share the results of our mixed-methods SenseMaker® research with community members who interact with peacekeeping personnel and interviews with 58 women who are raising children fathered by peacekeepers. Despite the United Nations policies in place, most women did not report children fathered by peacekeepers and did not receive systematic support. The analysis reveals a large gap between the aspirations of the 'zero tolerance policy' and its operationalization in the Democratic Republic of Congo. We uncovered deep poverty and insecurity as both driving and resulting from women's sexual encounters with peacekeepers, with support needs largely unmet. We argue that there is a lack of enforcement of the United Nations policies, jurisdictional complexity and inaccessible justice, as well as significant gaps between the United Nations' approach to investigating and supporting children fathered by peacekeepers and the expectations of mothers, resulting in worsened life conditions for mothers and their children.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".