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Record W2265521349 · doi:10.5539/res.v8n1p35

The Prostitution Business of Greater Mekong Subregion Women in Bangkok and the Adjacent Areas

2016· article· en· W2265521349 on OpenAlexvenueno aff
Jomdet Trimek, Kittisak Jermsittiparsert, Noppon Akahat, Sarunyaphat Sieangsung, Sunisa Ratchaphan

Bibliographic record

VenueReview of European Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSoutheast Asian Sociopolitical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMekong deltaBusinessGeographyMekong riverSocioeconomicsEconomicsWater resource managementEnvironmental scienceGeology

Abstract

fetched live from OpenAlex

<p>This paper is a qualitative based research, conducting in-depth interviews with 18 subjects consisting of GMS prostitutes working in Bangkok and other relevant informants. The objectives of this research are to study characteristics of the prostitution business in Bangkok and the adjacent areas and to study dynamics of causes, motivation, and the processes of how GMS women entering the prostitution business in Bangkok. The research results show that the entertainment places secretly provide prostitution services in Bangkok and the adjacent areas run the business openly. GMS women and Thai women providing prostitution services is illegal in Thailand. GMS women travelling to Bangkok to provide the prostitution services come from Laos, Myanmar, Vietnam, China, and Cambodia, respectively. Although the government takes strict action, the prostitution business cannot be completely eradicated. The most important problem is corruption of government officials in various areas. As for the recommendations, it is advised that there should be a study of international practices consisting of crime control models, especially elimination of corruption of government officials in various areas, legalization model, or decriminalization model in the offence of the prostitution service to study the models suitable for the current situations.</p>

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.562
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.039
GPT teacher head0.318
Teacher spread0.278 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreReview

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

Citations1
Published2016
Admission routes1
Has abstractyes

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