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Record W4249952478 · doi:10.31038/awhc.2020353

Mapping Contextual Drivers of HIV Vulnerability: A Qualitative Study of African, Caribbean, Black Youth in Windsor, Canada

2020· article· en· W4249952478 on OpenAlexafffundabout
Francisca Omorodion, Eleanor Maticka‐Tyndale, Neema William Jangu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHIV/AIDS Impact and Responses
Canadian institutionsUniversity of Windsor
FundersCanadian Institutes of Health ResearchWilfrid Laurier UniversityUniversity of WindsorUniversity of Louisville
KeywordsWindsorVulnerability (computing)Qualitative researchBlack africanHuman immunodeficiency virus (HIV)Caribbean regionGender studiesGeographyPolitical scienceSociologyEthnologyMedicineComputer securityAnthropologyComputer scienceLatin AmericansVirologyEcology

Abstract

fetched live from OpenAlex

Background: Based on POWER study: Promoting and owning empowerment and resilience among African, Caribbean, and Black Canadian (ACB) youth, this paper explored the contextual factors that expose ACB youth to HIV infection. Method:We conducted six focused community-mapping sessions with 43 purposively drawn ACB youth living in Windsor, Canada.Based on socioenvironmental approach, we investigated a number of issues including, where to find ACB people, places afraid to go, places to find casual partners, where they spend leisure time, healthy and unhealthy places.Results: The findings showed that ACB population mainly resides in poor areas, with close proximity to bars, strip shops, recreational/sports places.And, multifaceted factors, such as economic deprivation, marginalization, discrimination, and substance use provided an enabling environment for ACB youth exposure to HIV/AIDS.Conclusion: Future HIV/AIDS prevention must be locality specific and culturally sensitive, by taking into account individual, structural, environmental and socio-cultural factors in future HIV prevention strategies.

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)0.005
metaresearch head score (Gemma)0.007
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 score0.044
Threshold uncertainty score0.319

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0310.007
Scholarly communication0.0060.002
Open science0.0030.006
Research integrity0.0010.003
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 head0.072
GPT teacher head0.268
Teacher spread0.197 · 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

Citations1
Published2020
Admission routes3
Has abstractyes

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