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Record W4403475098 · doi:10.1177/15248380241290245

Digital Traps: The Critical Role of Online Encounters in the Entrapment of Minors in Sex Trafficking

2024· article· en· W4403475098 on OpenAlexaff
Kyla Baird, Jennifer Connolly

Bibliographic record

VenueTrauma Violence & Abuse · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsYork University
Fundersnot available
KeywordsSex traffickingCriminologyThe InternetExploitPoison controlIntervention (counseling)Computer securityPsychologyInternet privacyMedicineComputer scienceMedical emergencyHuman traffickingPsychiatryWorld Wide Web

Abstract

fetched live from OpenAlex

We are grateful to the Editors of TVA for the opportunity to respond to the commentary on our systematic review of the sex trafficking of minors, specifically regarding the initial recruitment location. Upon revisiting the 7 out of 23 reviewed studies that address recruitment locations, we find that the discrepancy with the commentators' views stems from differing interpretations of the term "initial." We affirm that these seven studies, which include the internet as a prominent initial recruitment site, are valid and appropriate for inclusion. We also emphasize that, irrespective of recruitment location, we and the commentators share deep concerns about the severe impact of sex trafficking on minors, recognizing it as a heinous crime against vulnerable populations. Traffickers use both online and in-person methods to manipulate and exploit youth. Our review highlights the internet as a primary platform for traffickers to form relationships with minors, comparable in danger to in-person interactions. The 23 reviewed papers focus on documenting these predatory relationships and the critical role of supportive, healing relationships in prevention and intervention.

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 score0.258
Threshold uncertainty score0.242

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 studies0.0000.001
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 head0.013
GPT teacher head0.310
Teacher spread0.296 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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