Childhood and adolescent factors shaping vulnerability to underage entry into sex work: a quantitative hierarchical analysis of female sex workers in Nairobi, Kenya
Bibliographic record
Abstract
OBJECTIVE: To explore factors associated with early age at entry into sex work, among a cohort of female sex workers (FSWs) in Nairobi, Kenya. BACKGROUND: Younger age at sex work initiation increases the risk of HIV acquisition, condom non-use, violence victimisation and alcohol and/or substance use problems. This study aimed to understand factors in childhood and adolescence that shape the vulnerability to underage sex work initiation. DESIGN: Building on previous qualitative research with this cohort, analysis of behavioural-biological cross-sectional data using hierarchical logistic regression. PARTICIPANTS AND MEASURES: FSWs aged 18-45 years were randomly selected from seven Sex Workers Outreach Programme clinics in Nairobi, and between June and December 2019, completed a baseline behavioural-biological survey. Measurement tools included WHO Adverse Childhood Experiences, Alcohol, Smoking and Substance Involvement Screening Test and questionnaires on sociodemographic information, sexual risk behaviours and gender-based violence. Descriptive statistics and logistic regression were conducted using hierarchical modelling. RESULTS: Of the 1003 FSWs who participated in the baseline survey (response rate 96%), 176 (17.5%) initiated sex work while underage (<18 years). In the multivariable analysis, factors associated with entering sex work while underage included incomplete secondary school education (aOR=2.82; 95% CI=1.69 to 4.73), experiencing homelessness as a child (aOR=2.20; 95% CI=1.39 to 3.48), experiencing childhood physical or sexual violence (aOR=1.85; 95% CI=1.09 to 3.15), young age of sexual debut (≤15 years) (aOR=5.03; 95% CI=1.83 to 13.79) and being childless at time of sex work initiation (aOR=9.80; 95% CI=3.60 to 26.66). CONCLUSIONS: Lower education level and childhood homelessness, combined with sexual violence and sexual risk behaviours in childhood, create pathways to underage initiation into sex work. Interventions designed for girls and young women at these pivotal points in their lives could help prevent underage sex work initiation and their associated health, social and economic consequences.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".