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Record W2100516357 · doi:10.1177/1049732308319924

Endangered Womanhood: Women's Experiences With HIV/AIDS in China

2008· article· en· W2100516357 on OpenAlexaff
Yanqiu Zhou

Bibliographic record

VenueQualitative Health Research · 2008
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsMcMaster University
Fundersnot available
KeywordsContext (archaeology)Socioeconomic statusQualitative researchChinaHuman immunodeficiency virus (HIV)DiseaseDeveloping countryMedicineGender studiesGerontologyPsychologyEconomic growthPopulationSociologyPolitical scienceFamily medicineEnvironmental healthSocial science

Abstract

fetched live from OpenAlex

Women in China are increasingly affected by HIV/AIDS. Current AIDS studies have examined the HIV risks faced by this gender group, paying inadequate attention to women's actual experiences with the disease. This oversight has inhibited our ability to understand the impact of gender on women's capacity to respond to HIV/AIDS in their postinfection lives. Based on a qualitative study on illness experiences of HIV-infected people, this article examines the interactions between HIV/AIDS and gender roles in the Chinese context. It was found that traditional gender norms have played a key role for HIV-infected women in their efforts to tackle this disease and to make sense of their daily lives. HIV infection has created a conflict between women's intention to fulfill their conception of "womanhood" and a decreased ability to do so, which, in turn, has adversely affected their self-perceptions and well-being. To avoid worsening the inequality women experience, therefore, we must also work on the socioeconomic conditions, for example, through delivering comprehensive care to affected families and developing a gender-sensitive welfare policy, so that the gender imparity that permeates this epidemic can be challenged and transformed.

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)0.004
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 score0.103
Threshold uncertainty score0.205

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0190.007
Scholarly communication0.0030.003
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.229
GPT teacher head0.538
Teacher spread0.308 · 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

Citations30
Published2008
Admission routes1
Has abstractyes

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