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Record W2050755588 · doi:10.1080/13557858.2010.523456

HIV-related stigma among South Asians in Toronto

2011· article· en· W2050755588 on OpenAlexaffabout
Carol Vlassoff, Firdaus Ali

Bibliographic record

VenueEthnicity and Health · 2011
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsStigma (botany)OutreachDisadvantagedHuman immunodeficiency virus (HIV)MainstreamFocus groupPovertySocial stigmaMedicineGerontologyFamily medicinePsychiatrySociologyPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVES: This paper explores the nature of HIV-related stigma among South Asians in Toronto, its consequences for people living with it and its role in determining access to HIV services. DESIGN: The study is based on data from four focus group discussions with members of an HIV outreach organization, HIV-positive men and women, and women of different ages from the mainstream South Asian community. The questions were adapted from the Explanatory Model Interview Catalog that has been widely used to assess health-related stigma. RESULTS: HIV-related stigma was found to be high in Toronto's South Asian community. Respondents perceived it to be greater among South Asians than in other Canadian communities. South Asian families were said to harbor the most stigma, often rejecting HIV-positive members. Differences were noted between first- and second-generation South Asian migrants in knowledge about, and stigma toward, HIV. Women living with HIV were found to be particularly disadvantaged and stigmatized. Because of stigma, many people living with HIV concealed their illness and avoided HIV-related services. CONCLUSION: Major gaps in knowledge about HIV among Canadian South Asians, and a considerable amount of stigma against people living with HIV, were found. The implications of stigma were highly problematic for people living with HIV, impeding access to services and social support. The paper concludes with recommendations to address stigma, based on suggestions from the study's participants.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.999

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.082
GPT teacher head0.385
Teacher spread0.303 · 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 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

Citations32
Published2011
Admission routes2
Has abstractyes

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