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Record W2597688312 · doi:10.3138/jcfs.39.3.413

HIV and AIDS: Are All Women Equally at Risk? Afrikaans Speaking Married Women’s Perceptions of Self-Risk

2008· article· en· W2597688312 on OpenAlexvenueno aff
Ria Smit

Bibliographic record

VenueJournal of Comparative Family Studies · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Development and Education Research
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)DemographyFocus groupRisk perceptionMarital statusHuman immunodeficiency virus (HIV)PerceptionPopulationMedicinePsychologyFamily medicineSociologyGeography

Abstract

fetched live from OpenAlex

The ever-growing concern about AIDS worldwide has increased the importance of understanding the disproportionate way in which the epidemic affects the lives of women. A cause for concern is the findings of a number of studies which indicate that the level of HIV infection among married women in sub-Saharan Africa has increased dramatically in comparison to the infection rate of those who are single. This article focuses on findings from a qualitative study done in South Africa during 2005/2006, which aimed to shed light on the perceptions and experiences of Afrikaans-speaking married women with regard to living in a society characterized by a high HIV prevalence rate. The main focus of the study fell on the women’s perceptions of self-risk of becoming HIV infected. It was found that, although the respondents in the study saw themselves to be at some risk of contracting the virus through unforeseen circumstances, such as receiving contaminated blood through blood transfusions, they viewed themselves as having no susceptibility to HIV within the context of their marital relationships. The rationale for having this view is the fact that they consider their marriages to be characterized by trust and fidelity, and therefore free from any form of unsafe sexual practices.

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)0.003
metaresearch head score (Gemma)0.008
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 score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.005
Scholarly communication0.0030.003
Open science0.0000.002
Research integrity0.0010.002
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 head0.138
GPT teacher head0.406
Teacher spread0.268 · 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

Citations4
Published2008
Admission routes1
Has abstractyes

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