‘Trying to Fix What is Broken’: Experiences of Encountering Children in Armed Conflict During Military Service
Bibliographic record
Abstract
Canadian Armed Forces Veterans, clinicians, and researchers (n = 39) engaged in Participatory Action Research to enhance understanding of the mental health impacts of deployment-related encounters with children and to identify recommendations to better prevent, mitigate, and address the mental health effects of these encounters. Four key findings emerged: (1) the variation and gendered experiences and impacts of encounters with children; (2) the need for pre-deployment education around concepts of moral injury, military culture and childhood; (3) the role of military institutional readiness and proactive leadership support in mitigating the impacts of potentially morally injurious encounters with children; and (4) a requirement for long-term, comprehensive and integrated services, spanning formal and informal networks, to support personnel impacted by encounters with children. This research reveals that centreing shared experiences through participatory and trauma-informed approaches in military mental health research offer meaningful insights on addressing moral injuries related to encounters with 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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.028 | 0.027 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.004 | 0.010 |
| 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".