Can a national government implement a violence prevention and response strategy for key populations in a criminalized setting? A case study from Kenya
Bibliographic record
Abstract
INTRODUCTION: Key population (KP) members frequently experience violence that violates their human rights, increases their risk of HIV, and acts as a barrier to access and uptake of HIV services. To be effective, HIV programmes for members of KPs need to prevent and respond to violence against them. We describe a violence prevention and response strategy led by the national KP programme in Kenya and examine trends in reports of and responses to violence (provision of support to an individual who reports violence within 24 hours of receiving the report). METHODS: Quarterly programme monitoring data on the number of reports of violence and the number of responses to violence from 81 implementing partners between October 2013 and September 2017 were aggregated annually and analysed using simple trend analysis. Reports of violence relative to KP members reached, expressed as a percentage, and the percentage of reports of violence that received a response were also examined. RESULTS AND DISCUSSION: Between 2013 and 2017, annual reports of violence increased from 4171 to 13,496 cases among female sex workers (FSWs), 910 to 1122 cases among men who have sex with men (MSM) and 121 to 873 cases among people who inject drugs (PWID). Reports of violence relative to KP members reached increased among FSWs (6.2% to 9.7%; p < 0.001) and PWID (2.1% to 6.0%; p < 0.001) and decreased among MSM (10.0% to 4.2%; p < 0.001). During the same period, timely responses to reports of violence increased from 53% to 84% (p < 0.001) among FSWs, 44% to 80% (p < 0.001) among MSM and 37% to 97% (p < 0.001) among PWID. CONCLUSIONS: Over the past four years in Kenya, there has been an increase in violence reporting among FSWs and PWID and an increase in violence response among all KPs. This case study demonstrates that violence against KP members can be effectively addressed under the leadership of the national government, even in an environment where KP members' behaviours are criminalized. Creating an enabling environment to promote wellbeing and safety for KP members is a critical enabler for HIV prevention programmes to achieve 95-95-95 goals.
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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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".