Covid-19 Escaled Ongoing Injustices: Voices of Women Living With HIV in Nepal
Bibliographic record
Abstract
The first HIV case in Nepal was reported in 1988. As of July 2020, the total number of PLHIV was 29,503 PLHIV whereas the numbers for male and females were respectively 17, 587 and 11, 916 (UNAIDS, 2021.). More than 72% of People Living with HIV (PLHIV) are of age group 25 to 49 years (Ministry of Health National Centre for AIDS and STD Control, 2020). There are 80 ART (Anti-Retroviral therapy) centres providing services to PLHIV in seven Provinces and a number of community-based organizations to provide services to PLHI (Ministry of Health National Centre of AIDS and STD Control, 2020). The current knowledge on this area are maninly the reports from HIV Service Agencies that do not capture the silenced voices of PLHIV on intersectional oppression. By acknowledging the need of a evidence-based study, a Participatory Action Research (PAR) project was developed in 2019 to understand the challenges of the Women Living with HIV in Kathmandu, Nepal (Dhungel, 2020; Dhungel & Lama, 2020). This understanding was reached through a variety of means, including photovoice, individual interviews and street dramas. Four major intersectional challenges were identified including discriminations against WLHIV at workplace, violations of privacy in health sectors, excluding from parental's property and discriminations against their children at school. The same study suggested the need for a further study, focusing on intersectional oppressions and public health services and programs available for WLHIV with a focus on Mental Health Services. Therefore, this study was initiated to bridge the gaps in current knowledge with a foucs on COVID-19 policies/programs. Keywords: COVID-19, HIV community, injustice, intersectional oppression
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.011 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.006 |
| 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".