Prevalence and patterns of gender-based violence across adolescent girls and young women in Mombasa, Kenya
Bibliographic record
Abstract
BACKGROUND: We sought to estimate the prevalence and describe heterogeneity in experiences of gender-based violence (GBV) across subgroups of adolescent girls and young women (AGYW). METHODS: We used data from a cross-sectional bio-behavioural survey among 1299 AGYW aged 14-24 in Mombasa, Kenya in 2015. Respondents were recruited from hotspots associated with sex work, and self-selected into one of three subgroups: young women engaged in casual sex (YCS), young women engaged in transactional sex (YTS), and young women engaged in sex work (YSW). We compared overall and across subgroups: prevalence of lifetime and recent (within previous year) self-reported experience of physical, sexual, and police violence; patterns and perpetrators of first and most recent episode of physical and sexual violence; and factors associated with physical and sexual violence. RESULTS: The prevalences of lifetime and recent physical violence were 18.0 and 10.7% respectively. Lifetime and recent sexual violence respectively were reported by 20.5 and 9.8% of respondents. Prevalence of lifetime and recent experience of police violence were 34.7 and 25.8% respectively. All forms of violence were most frequently reported by YSW, followed by YTS and then YCS. 62%/81% of respondents reported having sex during the first episode of physical/sexual violence, and 48%/62% of those sex acts at first episode of physical/sexual violence were condomless. In the most recent episode of violence when sex took place levels of condom use remained low at 53-61%. The main perpetrators of violence were intimate partners for YCS, and both intimate partners and regular non-client partners for YTS. For YSW, first-time and regular paying clients were the main perpetrators of physical and sexual violence. Alcohol use, ever being pregnant and regular source of income were associated with physical and sexual violence though it differed by subgroup and type of violence. CONCLUSIONS: AGYW in these settings experience high vulnerability to physical, sexual and police violence. However, AGYW are not a homogeneous group, and there are heterogeneities in prevalence and predictors of violence between subgroups of AGYW that need to be understood to design effective programmes to address violence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".