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Record W2103249044 · doi:10.1177/1077801214528582

Prevalence and Correlates of Client-Perpetrated Abuse Among Female Sex Workers in Two Mexico–U.S. Border Cities

2014· article· en· W2103249044 on OpenAlexaff
Monica D. Ulibarri, Steffanie A. Strathdee, Remedios Lozada, Carlos Magis‐Rodríguez, Hortensia Amaro, Patricia O’Campo, Thomas L. Patterson

Bibliographic record

VenueViolence Against Women · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of Toronto
FundersNational Institute on Drug AbuseNational Institute of Mental HealthUniversity of California, DavisNational Institutes of HealthUniversidad Autónoma de Baja California
KeywordsDomestic violenceMedicinePoison controlSuicide preventionSexual abuseLogistic regressionPsychiatryMental healthOccupational safety and healthInjury preventionDemographyDistressEnvironmental healthClinical psychology

Abstract

fetched live from OpenAlex

History of abuse has been associated with greater HIV risk among women. This study examined client-perpetrated abuse among female sex workers (FSWs) in two Mexico-U.S. border cities where HIV prevalence is rising. Among 924 FSWs, prevalence of client-perpetrated abuse was 31%. In multivariate logistic regression models, intimate partner violence (IPV), psychological distress, and having drug-using clients were associated with experiencing client-perpetrated abuse. FSWs along the Mexico-U.S. border report frequently experiencing abuse from both clients and intimate partners, which may have serious mental health consequences. Our findings suggest the need for screening and gender-based violence prevention services for Mexican FSWs.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.164

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.007
GPT teacher head0.278
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations24
Published2014
Admission routes1
Has abstractyes

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