Knowledge and Perceptions on Menstrual Hygiene Management Among School-Going Adolescent Girls in South Sudan
Bibliographic record
Abstract
This article draws on grounded theory and ethnographic fieldwork approaches and applies a political ecology of adolescent health (PEAH) framework to examine how school-going adolescent girls and their communities perceive sexual and reproductive health education (SRHE) and menstrual hygiene management (MHM) in the region. Three young girls were purposefully selected from each of 10 government-run mixed primary schools in Juba, South Sudan, as peer research evaluators (PREs) and key informants ( N = 30). Each PRE interviewed and reported on three of their peers about how they talk about and manage menstruation. The findings show that political, socioeconomic, and cultural factors do influence adolescent girls’ and their communities’ perceptions about puberty and menstruation. In general, MHM was culturally constructed, but the results show a disproportionate emphasis on social norms rather than on SRHE, which could have long-lasting health implications for adolescent girls. There is a need for all stakeholders in education to come together to better grasp and address the obstacles young girls face in their communities and school environments. There is also a need to develop relevant training materials to assist care providers and adolescent girls to openly talk about and address sexual and reproductive health issues.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".