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Record W2772098882 · doi:10.22459/mr.12.2017.07

Adding insult to injury: Experiences of mobile HIV‑positive women who return home for treatment in Tanah Papua, Indonesia

2017· book-chapter· en· W2772098882 on OpenAlexfundno aff
Leslie Butt, Jenny Munro, Gerdha Numbery

Bibliographic record

VenueANU Press eBooks · 2017
Typebook-chapter
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health Research
KeywordsInsultHuman immunodeficiency virus (HIV)MedicineFamily medicinePolitical science

Abstract

fetched live from OpenAlex

This chapter explores the personal experiences of mobile HIV-positive indigenous women from Tanah Papua, Indonesia who returned to their home communities in need of social support and treatment.Little is known about the experiences of HIV-positive women returnees in general, and the contours and effects of the moral expectations and boundaries within home communities in particular.This paper draws on close-grained analysis of in-depth interviews and fieldwork conducted between 2009 and 2013 to suggest Papuan women returnees suffer a reduced quality of local network relations, and sustained stigma and gender-based discrimination.We illustrate how the inevitable struggles over belonging that returning young adults face are intensified by the intersection of seropositivity, shifts in the quality of social networks and gendered judgements about mobility.Women returnees are unable to rely on affective networks, and Papua's poorly developed HIV treatment programs magnify these challenges.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0090.005
Scholarly communication0.0030.003
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.340
Teacher spread0.304 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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