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Record W3034361108 · doi:10.1080/23322705.2020.1777382

Survivor’s Perceptions of Human Trafficking Rehabilitation Programs in Nigeria: Empowerment or Disempowerment?

2020· article· en· W3034361108 on OpenAlexaff
Nnenna Okoli, Uwafiokun Idemudia

Bibliographic record

VenueJournal of Human Trafficking · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsYork University
Fundersnot available
KeywordsEmpowermentConceptualizationRehabilitationContext (archaeology)Government (linguistics)Public relationsPolitical sciencePsychologyNursingEconomic growthMedicineGeographyLaw

Abstract

fetched live from OpenAlex

While disagreements about the value of rehabilitation programs persist, these programs are still largely seen as essential for the protection of the human rights of survivors of human trafficking, and the facilitation of their recovery and empowerment after trafficking. Consequently, it is not surprising that rehabilitation programs are a core component of the Nigerian government’s anti-trafficking policies. However, only limited efforts have so far been directed at ascertaining the extent to which these rehabilitation programs result in the empowerment of survivors in Nigeria. To address this gap, this paper explores the extent to which survivors’ perceptions and experiences in the rehabilitation programs reflect the ideals of empowerment. Drawing on qualitative data, we show that the government’s conceptualization of human trafficking influences their collaborative rehabilitation efforts, and that such efforts seem to simultaneously empower and disempower survivors.The paper concludes by considering the policy implications in the African context.

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 score0.006
Threshold uncertainty score0.635

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.039
GPT teacher head0.340
Teacher spread0.301 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

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