A national population-based assessment of 2007–2008 election-related violence in Kenya
Bibliographic record
Abstract
Following the contested national elections in 2007, violence occurred throughout Kenya. The objective of this study was to assess the prevalence, characteristics, and health consequences of the 2007-2008 election-related violence.A cross-sectional, national, population-based cluster survey of 956 Kenyan adults aged ≥ 18 years was conducted in Kenya in September 2011 utilizing a two-stage 90 x 10 cluster sample design and structured interviews and questionnaires. Prevalence of all forms of violence surrounding the 2007 election period, symptoms of major depressive disorder (MDD) and posttraumatic stress disorder (PTSD), and morbidity related to sexual and physical violence were assessed.Of 956 households surveyed, 916 households participated (response rate 95.8%). Compared to pre-election, election-related sexual violence incidents/1000 persons/year increased over 60-fold (39.1-2370.1; p < .001) with a concurrent 37-fold increase in opportunistic sexual violence (5.2-183.1; p < .001). Physical and other human rights violations increased 80-fold (25.0-1987.1; p < .001) compared to pre-election. Overall, 50% of households reported at least one physical or sexual violation. Households reporting violence were more likely to report violence among female household members (66.6% vs. 58.1%; p = .04) or among the Luhya ethnic group (17.0% vs. 13.8%; p = 0.03). The most common perpetrators of election-related sexual violence were reported to be affiliated with government or political groups (1670.5 incidents/1000 persons per year); the Kalenjin ethnic group for physical violations (54.6%). Over thirty percent of respondents met MDD and PTSD symptom criteria; however, symptoms of MDD (females, 63.3%; males, 36.7%; p = .01) and suicidal ideation (females, 68.5%; males, 31.5%; p = .04) were more common among females. Substance abuse was more common among males (males, 71.2%; females, 28.8%; p < .001).On a national level in Kenya, politically-motivated and opportunistic sexual and physical violations were commonly reported among sampled adults with associated health and mental health outcomes.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".