Born between war and peace: Situating peacekeeper-fathered children in research on children born of war
Bibliographic record
Abstract
In the last two decades, academic research has made significant progress exploring the life courses of so-called “children born of war” (CBOW). Similarly, the unintended consequences of peacekeeping operations, including the experiences of victims of sexual exploitation and abuse, and children born of these interactions, have received preliminary academic attention. This paper compares peacekeeper-fathered children (PKFC) to other CBOW to determine how these two groups relate to one another. We draw on research conducted in two peacekeeping contexts where personnel have been accused of fathering and abandoning children (Haiti and the Democratic Republic of Congo) to empirically situate PKFC within the category of CBOW. We introduce 5,388 micro-narratives from Haitian and Congolese community members (Haiti n = 2,541, DRC = 2,858) and 113 qualitative interviews with mothers/grandmothers of PKFC (Haiti n = 18, DRC n = 60) and PKFC (DRC n = 35) to investigate how PKFC fit in the CBOW paradigm. Our findings demonstrate that many of the multi-level adversities faced by PKFC resemble those of the broader reference group. Given their shared developmental needs and experiences of exclusion, we conclude that PKFC constitute CBOW and ought to be included in conceptualisations pertaining to them. Acknowledging PKFC as CBOW offers new opportunities for policy development to (a) enhance protection and support of all CBOW and (b) remind states of their commitments to uphold the rights of all 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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.015 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".