An exploration of HIV related stigma within the context of Kerala, India
Bibliographic record
Abstract
Purpose: To understand through explorations of the experiences of HIV positive individuals whether these individuals experience stigma in relation to HIV/AIDS and how it has impacted their lives and that of their families. Design: Qualitative study used ethnographic techniques (interviews, questionnaires, informal conversations, observation, field notes) to collect data over a four-month period. Setting: Data was collected from nine districts in the northern, central, and southern regions of the state of Kerala, India. Participants: Shared their perspectives on HIV related stigma (n=49 total). Of the 38 participants interviewed, 12 were HIV positives, 19 were HIV positives who also worked or volunteered with HIV positive networks (known as positive speakers), 2 were caregivers of HIV positives, and 5 were key informants involved with community organizations providing services to HIV positives. Informal conversations with 11 unaffected were also utilized. Findings were organized into four themes. (1) Anti-stigma/prevention strategies such as positive living and positive speaking offered positive speakers unique challenges and opportunities as they were called upon to be the face and voice of HIV (2) Contrary to expectations that formal education which also included awareness about HIV could increase one’s knowledge and subsequently dispel ignorance and stigma, the findings pointed out how knowledge itself is a resource that allowed stigma to unfold along existing social hierarchies. (3) Unconscious prejudices about physical appearances influenced perceptions of HIV risk, and a stigmatized identity waxed and waned with a change in physical appearance as the HIV positive oscillated between illness and health. (4) “Immoral behaviour” as the cause of HIV infection entered into family/caregiver decisions regarding the use of family resources for the treatment and care of the HIV positive member. Gender and social class also impinged on family decisions in numerous ways. Conclusions: This research project has highlighted the need to develop a more nuanced understanding of HIV related stigma that extends beyond the current conceptualization of stigma as “ignorance” or lack of awareness about modes of HIV transmission. Refining current understandings of HIV related stigma could guide research, policy, and practice.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".