What determines violence among female sex workers in an intimate partner relationship? Findings from North Karnataka, south India
Bibliographic record
Abstract
BACKGROUND: Like other women in India, female sex workers (FSWs) frequently experience violence from their intimate partners (IPs)-a reality that increases their risk of acquiring HIV or other sexually transmitted infections. Less is known about the nature of these intimate relationships or what aspect of the relationship increases the risk of IP violence (IPV). We measured the prevalence and determinants of IPV on FSWs in the context of north Karnataka, India, characterized by high HIV-prevalence and extreme poverty. METHODS: Overall 620 FSWs with an IP participated in a baseline survey conducted for an on-going cluster-randomised controlled trial aiming to evaluate the impact of a multi-level intervention on IPV reduction. We characterize the nature of intimate relationships and explored determinants of severe physical and/or sexual IP violence using univariable and multivariable analyses. RESULTS: The median age of participants was 35 years with 10 years of duration in an intimate relationship. Though most relationships originated from a sex work encounter, 84% stated that IPs did not know they were currently practicing sex work. In past 6 months, the experience of emotional violence was 49% (95%CI:45.2-53.2), physical 33% (95%CI:29.5-37.1) and sexual violence 7% (95%CI:4.8-8.9), while 24% (95%CI:21.0-27.9) FSWs experienced recent severe physical and/or sexual violence from IPs. Factors associated with recent IPV included experience of physical and/or sexual violence from their clients in last 6 months (AOR 2.20; 95%CI: 1.29-3.75), sexual intercourse in the past 1 month when their IP was under the influence of alcohol (AOR 2.30; 95%CI: 1.47-3.59) and providing financial support to their IP (AOR 2.07; 95%CI: 1.28-3.34). CONCLUSIONS: The association between increased risk of violence and provision of financial support to an IP is indicative of gendered power dynamics as men remain dominant irrespective of their financial dependency on FSWs. Interventions are needed that address inequitable gender norms which makes FSWs tolerate violence even though she is not financially dependent on IP. Higher likelihood of violence in presence of alcohol use and FSWs' previous experience of workplace violence linked to IPV call for strengthening the crisis management systems within community-based organisations that can address all forms of violence and associated risk factors. TRIAL REGISTRATION: Clinical Trials NCT02807259.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| 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".