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Record W4416341774 · doi:10.1186/s12982-025-01076-6

Perceptions about the use of direct cash-transfers to increase housing stability and HIV services utilization among street-connected young women in Western Kenya

2025· article· en· W4416341774 on OpenAlexfundno aff
Ashley Chory, Reuben Kiptui, Sheila Kirwa, Becky L. Genberg, Lonnie Embleton

Bibliographic record

VenueDiscover Public Health · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchUniversity of Toronto
KeywordsBeneficiarySustainabilityStakeholderPerceptionDisbursementHuman immunodeficiency virus (HIV)Focus groupHealth care

Abstract

fetched live from OpenAlex

Addressing homelessness is a critical component of HIV prevention; in high income countries, unconditional cash-transfer (CT) programs have been implemented for housing support with youth populations. Here we describe a pilot unconditional CT program for street-connected young women in western Kenya and stakeholder and beneficiary perceptions of its feasibility, acceptability, appropriateness, implementation and sustainabilit. Interviews were conducted with 17 participants, of which 9 were street-connected young women (median age 22 years) and 8 were key informants (policymakers, healthcare workers and community organization workers in two counties). Almost all street-connected young women were strongly in support of the CT program, citing numerous potential benefits, including general wellbeing and safety, improved community perceptions secondary to housing related cleanliness, the potential to create businesses and generate independent income, and finally HIV-related adherence benefits. In general, stakeholders were also supportive, with some indicating additional programmatic considerations were necessary related to the CT monetary amount, disbursement procedures, and sustainability and expansion. The CT program was found to be highly feasible, appropriate and acceptable; participants provided additional input on implementation and sustainability approaches.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.880

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.098
GPT teacher head0.393
Teacher spread0.295 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes

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