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Record W2096833589 · doi:10.1177/1363461507081635

Women Trafficked Into Prostitution: Determinants, Human Rights and Health Needs

2007· article· en· W2096833589 on OpenAlexaff
Olga Gajic‐Veljanoski, Donna E. Stewart

Bibliographic record

VenueTranscultural Psychiatry · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHuman rightsHuman traffickingMental healthCriminologyMultidisciplinary approachHealth careDeveloping countryPoison controlPolitical scienceFreedom of movementSuicide preventionEconomic growthPsychologyMedicineEnvironmental healthPsychiatryLawEconomics

Abstract

fetched live from OpenAlex

Human trafficking is an international challenge that increasingly affects industrialized countries. It represents a gross violation of a person's right to liberty and freedom of movement, and is often accompanied by violence and degrading treatment which can have detrimental effects on health. In this article, we review the definition and extent of human trafficking, and focus on the human rights abuses and determinants of trafficking in women. Mental health and other health outcomes are reviewed, and differences between countries in organized activities for victim assistance and protection are assessed. Finally, we discuss the roles of mental health and other healthcare providers in identifying and helping trafficked women, and recommend a tailored multidisciplinary approach for victim assistance.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.021
GPT teacher head0.340
Teacher spread0.319 · 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

Citations100
Published2007
Admission routes1
Has abstractyes

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