Individual and collective exposure to political violence: Palestinian adolescents coping with conflict
Bibliographic record
Abstract
BACKGROUND: We conducted a survey of Palestinian adolescents in school. We hypothesized that collective and individual exposures to violence would both negatively affect adolescents' mental health. We also anticipated that the negative effect of collective exposures on mental health would be less than that of individual exposures. Our analysis was designed to test these hypotheses. METHODS: A representative sample of 3415 students of 10th and 11th grades from the Ramallah District of the West Bank participated in the survey. The primary independent variables were scales of individual and collective exposures to trauma/violence (ETV) by the Israeli military and settlers. Factor analysis revealed several sub-scales. Outcome measures were constructed and included: a binary measure of depressive-like states, and emotional, depressive-like state, and somatic scales. Several variables were identified as possible covariates: gender, age, school-type, residence, employment status of father, and identity documents held. RESULTS: Logistic and multiple regression analyses revealed a strong relationship between ETV and adolescents' mental health, with both individual and collective exposures having independent effects. There was a higher prevalence of depressive-like symptoms among girls compared with boys, and in adolescents living in Palestinian refugee camps compared with those living in cities, towns and villages. CONCLUSION: The findings confirmed our hypothesis that both individual and collective ETV independently affect the mental health of adolescents. Contrary to expectations, individual exposures did not consistently have a greater negative effect on health outcomes than collective exposures, although the sub-scale of direct personal exposures to violence consistently showed the strongest effect among sub-scales. The results emphasize the importance of going beyond individual experiences and including the health outcomes of collective violation when analyzing violent and traumatic contexts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".