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Record W2116869852 · doi:10.5539/gjhs.v4n3p1

Unravelling Barriers to Accessing HIV Prevention Services Experienced by African and Caribbean Communities in Canada: Lessons from Toronto

2012· article· en· W2116869852 on OpenAlexvenueaboutno aff
Paulson Amibor, Ayodeji Bayo Ogunrotifa

Bibliographic record

VenueGlobal Journal of Health Science · 2012
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsCultural competenceService providerPublic relationsQualitative researchGovernment (linguistics)ImmigrationStigma (botany)Health promotionSocial workPolitical scienceEconomic growthMedicineNursingService (business)BusinessSociologyPublic healthMarketing

Abstract

fetched live from OpenAlex

Barriers to accessing HIV-prevention services, experienced by African and Caribbean communities in Canada, is an issue warranting sustained research. This study seeks to achieve a better understanding of the nature of HIV-prevention services in Canada, and to explore the dynamics, which underpin barriers to accessing these services confronting African and Caribbean populations in Toronto (Canada). This study also endeavours to assess what is being done to reduce these barriers. Semi-structured qualitative interviews with 7 professionals and community workers who were involved in organizing, researching and delivering HIV-prevention services were conducted for this study. Four themes pertaining to barriers to accessing HIV-prevention services, including, levels of cultural competence and sensitivity among service providers; cultural and social stigma directed at persons living with HIV/AIDS; various social determinants of health, including gender, race and precarious immigration status'; as well as constrained funding resources that are available for service providers; were uncovered in the findings of the study. The paper concludes that several health promotion and health education initiatives exist, which can help reduce these barriers to HIV-prevention service access for these populations. However, in order to ensure their effectiveness there will be much needed involvement from community and other relevant government agencies, which will need to work separately and in conjunction with one another, in order to tackle some of the broader issues that affect these populations.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.229
Threshold uncertainty score0.533

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 studies0.0000.000
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 head0.036
GPT teacher head0.375
Teacher spread0.339 · 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

Citations18
Published2012
Admission routes2
Has abstractyes

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