Awareness of HIV among Bangladeshi women: evidence from the MICS dataset
Bibliographic record
Abstract
Bangladesh exhibits a low prevalence of HIV; however, socioeconomic and gender disparities contribute to an increased vulnerability among women, primarily due to limited awareness of transmission methods, preventive measures, and testing services. This study employs data from the Multiple Indicators Cluster Survey (MICS) 2019, utilizing descriptive statistics, Chi-square tests, and logistic regression analyses to examine the influence of socio-demographic factors, educational attainment, and media exposure on HIV awareness. The findings indicate a moderate level of awareness, albeit accompanied by widespread misconceptions; only 27.5% of women knew where to access testing services. Women residing in urban areas, possessing higher education levels, belonging to wealthier households, and with media exposure demonstrated significantly higher awareness levels. Disparities are evident across different regions, notably in Barishal and Mymensingh. Futhermore, women with higher secondary education exhibited a 17.5-fold increase in HIV knowledge compared to those with primary education. The study underscores the importance of targeted educational initiatives, media campaigns, and enhanced testing acessibility, particularly in underserved regions, to improve awareness and mitigate stigma.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".