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Record W2791900348 · doi:10.1080/15381501.2017.1396519

Unwanted humans: Pathways to the street and risky behaviors for girls in Côte d’Ivoire

2018· article· en· W2791900348 on OpenAlexaff
Andrew M. Muriuki, Sithokozile Maposa, Denise Kpébo, Wendy Blanpied

Bibliographic record

VenueJournal of HIV/AIDS & Social Services · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSexual abuseRural areaWork (physics)Cote d ivoirePhysical abuseSex workEconomic growthNarrativeSocioeconomicsGeographySuicide preventionPoison controlGender studiesPolitical scienceSociologyMedicineEnvironmental healthHumanities

Abstract

fetched live from OpenAlex

A number of previous research and nongovernmental organization (NGO) reports have documented rural-to-urban migration trends of adolescent girls seeking work in sub-Saharan Africa. Unfortunately, many of these girls end up living on the street. This study examined factors that lead many of these girls in Côte d’Ivoire to become homeless and at risk for exploitation. We found that more than two thirds of those interviewed had been brought to the city by a relative or other significant adult to work as domestic workers, but many ended up on the street and exploited for commercial sex. The rural-born girls reported a higher level of abuse and risky sexual behavior than those raised in the city. Amidst broken promises for schooling support, narratives also uncovered a link between domestic work and abuse, and limited family support that marginalized girls and young women. More research is needed to understand the challenges and experiences of adolescents living on the street. Countries with high rural-to-urban migration must develop an alternative protection system that supports life-skill development to protect them from the risks of living on the street.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.420
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.016
GPT teacher head0.302
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 teacher head, not a consensus.

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

Citations3
Published2018
Admission routes1
Has abstractyes

Explore more

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