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Record W3200457826 · doi:10.1080/07399332.2021.1959589

Enduring stigma and precarity: A review of qualitative research examining the experiences of women living with HIV in high income countries over two decades

2021· review· en· W3200457826 on OpenAlexaboutno aff
Lisa‐Maree Herron, Allyson Mutch, Chi‐Wai Lui, Lara Kruizinga, Chris Howard, Lisa Fitzgerald

Bibliographic record

VenueHealth Care For Women International · 2021
Typereview
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)Qualitative researchGerontologyStigma (botany)Coping (psychology)Social supportSocial stigmaMedicinePsychologySociologySocial psychologyClinical psychologyPsychiatryFamily medicine

Abstract

fetched live from OpenAlex

The lived experience of HIV for women remains poorly understood. In particular, there has been little attention to the consequences for women living with HIV (WLHIV) of changing social, epidemiological, biomedical and policy contexts, or to the implications of long-term treatment and aging for the current generation of HIV-positive women. We reviewed qualitative research with WLHIV in selected high-income countries (Australia, Canada, New Zealand, the UK and the USA) to identify the most prevalent experiences of HIV for women and trends over time. Our synthesis highlights the relative consistency of experiences of a diverse sample of WLHIV, particularly the enduring prevalence of gendered HIV-related stigma, sociostructural barriers to healthcare and support, and negative encounters with health professionals. We also identified gaps in knowledge. Understanding women's experiences, particularly their changing needs and strategies for coping as they live long-term with HIV, is key to effective support and services for WLHIV.

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)0.015
metaresearch head score (Gemma)0.025
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.010
Science and technology studies0.0020.002
Scholarly communication0.0030.004
Open science0.0010.003
Research integrity0.0020.002
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 head0.144
GPT teacher head0.551
Teacher spread0.407 · 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
GenreReview

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

Citations15
Published2021
Admission routes1
Has abstractyes

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