Health implications of small arms and light weapons in eastern Uganda
Bibliographic record
Abstract
Injuries due to small arms and light weapons (SALW) are common in developing countries with ongoing collective violence, or those that exist in a post-conflict state. Uganda has a long history of armed conflict, but little quantitative evidence is available about the extent of the problem of SALW. We performed a review of all injuries due to SALW at Mbale Regional Hospital in eastern Uganda for the six-year period 1998-2003. Using a standardised questionnaire, we recorded information from over 200 cases concerning the characteristics of the victim, the incident, the weapon used and the care received. The majority involved males and occurred in the context of conflict within tribal communities, or armed robberies throughout the region. Each injury is of significant cost to the healthcare system and to the victim. Prevention, through limiting the availability of the 'vector' of disease (SALW), is a key part of the solution to this problem.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".