Stigma and unmet sexual and reproductive health needs among international migrant sex workers at the Mexico–Guatemala border
Bibliographic record
Abstract
OBJECTIVE: To explore international migrant sex workers' experiences and narratives pertaining to the unmet need for and access to sexual and reproductive health (SRH) at the Mexico-Guatemala border. METHODS: An inductive qualitative analysis was conducted based on ethnographic fieldwork (2012-2015) including participant observation and audio-recorded in-depth interviews. The participants were female sex workers aged 18 years or older and international migrants working at the Mexico-Guatemala border. RESULTS: In total, 31 women were included. The greatest areas of unmet need included accessible, affordable, and nonstigmatizing access to contraception and treatment of sexually transmitted infections. On both sides of the border, poor information about the health systems, services affordability, and perceived stigma resulted in barriers to access SRH services, with women preferring to access private doctors in their destination country or delaying uptake of until their next trip home. Financial barriers prevented women from accessing needed services, with most only receiving SRH services in their destination country through public health regulations surrounding sex work or as urgent care. CONCLUSIONS: There is a crucial need to avoid prioritizing vertical disease-specific services and to promote access to rights-based SRH services for migrant sex workers in both home and destination settings.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".