Conflict in the Indian Kashmir Valley I: exposure to violence
Bibliographic record
Abstract
BACKGROUND: India and Pakistan have disputed ownership of the Kashmir Valley region for many years, resulting in several conflicts since the end of partition in 1947. Very little is known about the prevalence of violence and insecurity in this population. METHODS: We undertook a two-stage cluster household survey in two districts (30 villages) of the Indian part of Kashmir to assess experiences with violence and mental health status among the conflict-affected Kashmiri population. The article presents our findings for confrontations with violence. Data were collected for recent events (last 3 months) and those occurring since the start of the conflict. Informed consent was obtained for all interviews. RESULTS: 510 interviews were completed. Respondents reported frequent direct confrontations with violence since the start of conflict, including exposure to crossfire (85.7%), round up raids (82.7%), the witnessing of torture (66.9%), rape (13.3%), and self-experience of forced labour (33.7%), arrests/kidnapping (16.9%), torture (12.9%), and sexual violence (11.6%). Males reported more confrontations with violence than females, and had an increased likelihood of having directly experienced physical/mental maltreatment (OR 3.9, CI: 2.7-5.7), violation of their modesty (OR 3.6, CI: 1.9-6.8) and injury (OR 3.5, CI: 1.4-8.7). Males also had high odds of self-being arrested/kidnapped (OR 8.0, CI: 4.1-15.5). CONCLUSION: The civilian population in Kashmir is exposed to high levels of violence, as demonstrated by the high frequency of deliberate events as detention, hostage, and torture. The reported violence may result in substantial health, including mental health problems. Males reported significantly more confrontations with almost all violent events; this can be explained by higher participation in outdoor activities.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".