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Record W4318953401 · doi:10.32920/22001720.v1

“I don’t want anyone to follow my path:” Commercial Sexual Exploitation of Children in the Dominican Republic

2023· preprint· en· W4318953401 on OpenAlexafffund
Veronica Escobar Olivo, Henry Parada, Fabiola Bravo

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsToronto Metropolitan University
FundersSocial Sciences and Humanities Research Council of CanadaGlobal Affairs Canada
KeywordsCompensation (psychology)Reproductive healthTollThe RepublicPsychologyGender studiesDevelopmental psychologyPolitical scienceEconomic growthSocial psychologySociologyMedicineDemographyEconomicsPopulation

Abstract

fetched live from OpenAlex

The commercial sexual exploitation of children (CSEC) involves children in any sexual exchange with an adult for compensation—monetary or non-monetary. This article explores the experiences of sexually exploited children in the Dominican Republic. This research seeks to understand the impact global economies have on local realities and how these complex systems impact the everyday realities of young, impoverished children in the Dominican Republic. This article's findings are based on 19 interviews with children who were sexually exploited for compensation and seven interviews with parents of children who had been sexually exploited. The findings indicate that children firmly believed that they decided to engage in sexually exploitative encounters; however, all participants expressed to some degree that they did not have a choice. Further, nearly all the participants advised other children from getting involved in sexual exchanges for compensation, given the emotional toll it would have.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.084
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.007
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.002
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 head0.060
GPT teacher head0.346
Teacher spread0.286 · 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 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
Published2023
Admission routes2
Has abstractyes

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