Coping Strategies of Economically Destitute Women Who Acquired HIV Through Paid Blood and Plasma Collections in Rural China
Bibliographic record
Abstract
Little is known about the lives and hardships of socially marginalized and economically destitute women in rural Central China living with human immunodeficiency virus (HIV), who acquired the virus through commercial blood and plasma donations in the mid-1990s. Women living with HIV and acquired immune deficiency syndrome (AIDS) experience significant economic hardships and social exclusion in a male dominated, traditional, rural Chinese society, including the loss of labor power, financial burdens, and HIV-related stigma. This qualitative study examined strategies used by these marginalized women to cope with these hardships. Thematic analysis was used to analyze data from 15 interviews from women in Fuyang City, Anhui. Findings reveal that women undertook a variety of coping strategies: migrating to smaller towns, reducing labor intensity, reallocating labor within households, supplementing incomes by taking on additional jobs, borrowing money from relatives, reducing food consumption, lowering standards of living, withdrawing children from school, strategically disclosing HIV status and background information to employers, as well as avoiding weddings or funerals. This study identifies policy implications that can be used by social workers to mitigate the deleterious social and economic impacts of HIV and AIDS on the lives of women in vulnerable rural households in central China.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".