Psychopathology of children of genocide survivors: a systematic review on the impact of genocide on their children's psychopathology from five countries
Bibliographic record
Abstract
Background: : The health consequences of genocides on children of survivors are increasingly discussed but conclusions have been conflicting. Methods: We systematically reviewed studies from five electronic databases (EMBASE, PILOTS, PUBMED, PsycINFO, Web of Science), which used a quantitative study design and included: (i) exposure to the genocides of Armenians in Nazi Germany, Cambodia, Rwanda and Bosnia; (ii) mental health outcomes; (iii) validated instruments; (iv) statistical tests of associations. Study quality was appraised using a quality assessment tool for genocide studies. PRISMA reporting guidelines were followed. Results: From 3352 retrieved records, 20 studies with a total of 4793 participants involving 2431 children of survivors and 2362 controls met the eligibility criteria. Studies were conducted in seven countries: Australia, Canada, Italy, Israel, Norway, Rwanda and the USAs over the past seven decades, using the Genocide Studies Quality Assessment Tool. Data from the high quality studies provide no consistent evidence that children of genocide survivors are more likely to have mental health problems than comparators who were not children of genocide survivors. Conclusions: Methodological characteristics were associated with findings: studies investigating random samples of genocide survivors did not find an impact of genocides on health of children of survivors. Potential confounders (e.g. recent life events, poverty) need further investigation. Future studies of the impact of genocides on mental health should report using a standardized structure, such as the quality tool used here.
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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 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".