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Record W4407145825 · doi:10.13185/2799-015x.1039

The Recruitment of Female “Mules” by Transnational Criminal Organizations: Securitization of Drug Trafficking in the Philippines and Beyond

2013· article· en· W4407145825 on OpenAlexaff
Stéphanie Martel

Bibliographic record

VenueSocial Transformations Journal of the Global South · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsDrug traffickingSecuritizationOrganised crimeBusinessIllicit drugCriminologyPolitical scienceDrugMedicineFinancial systemSociologyPharmacology

Abstract

fetched live from OpenAlex

Southeast Asia has long been vulnerable to drug trafficking. Recently, intensified flows of persons, goods, and capital across borders have rendered it more fragmented and complex. The recruitment of female drug “mules” by transnational criminal organizations is a growing concern for both national and international counter-trafficking authorities in the region. This phenomenon has been the focus of a particular securitization process, emerging primarily in the Philippines but having regional implications, which has supported the implementation of counter-trafficking policy initiatives on both levels of state and region in Southeast Asia.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.782

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.018
GPT teacher head0.289
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2013
Admission routes1
Has abstractyes

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