‘Where am I in all of this?’ Impact of a morally injurious mission on the home front of Dutchbat III military Veterans
Bibliographic record
Abstract
Introduction: In 1995, the United Nations (UN) peacekeeping mission involving the Dutch battalion, Dutchbat III, in the former country of Yugoslavia ended in the killing of 8,000 Bosniak Muslim boys and men by the Bosnian-Serbian army. The mission and its aftermath may be considered potentially morally injurious events that had a long-term impact on the Bosnian people and Dutch Veterans. A study was conducted 25 years after the mission to examine its impact on home front members (i.e., Veterans' partners and close family members). Methods: Qualitative data were obtained through interviews with five female partners and two parents of Dutchbat III Veterans, as well as from a focus group with four female partners. Topics included the mission, experience of appreciation and support, health, daily functioning, resilience, meaning-making, and possible solutions. Thematic analysis was conducted using open, axial, and selective coding. Results: Findings were interpreted using a model of morally injurious impacts of war on military family members. Family members reported a generally good quality of life and no need for care for themselves but a unanimous perceived lack of support by the government and need for more recognition and appreciation of the Veterans. Discussion: Home front members of Dutchbat III Veterans seemed to suffer mainly from indirect mission impact that led to continued feelings of betrayal. Recognition and appreciation of military Veterans by the government and media may prevent or mitigate such feelings. Involving home front members in Veteran care and long-term follow-up is important.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".