“How can we leave the traditions of our<i>Baab Daada</i>” socio‐cultural structures and values driving menstrual hygiene management challenges in schools in Pakistan
Bibliographic record
Abstract
INTRODUCTION: Despite the growing attention to the relationship between menstruation and girls schooling, there remain many challenges to addressing the issue. Current interventions, which mostly focus on developing WASH infrastructure and sanitary hygiene management products, while necessary, may not be sufficient. This paper aimed to identify the root causes of poorly maintained WASH infrastructure, and understand the deeply embedded socio-cultural values around menstrual hygiene management that need to be addressed in order to provide truly supportive school environments for menstruating girls. METHODS: Qualitative data were collected in rural and urban sites in three provinces in Pakistan using participatory activities with 312 girls aged 16-19 years, observations of 7 School WASH facilities, 42 key informant interviews and a document review. RESULTS: Three key themes emerged from our data: (1) a poorly maintained, girls-unfriendly School WASH infrastructure was a result of gender-insensitive design, a cultural devaluation of toilet cleaners and inadequate governing practices; (2) the design of WASH facilities did not align with traditionally-determined modes of disposal of rag-pads, the most common used absorbents; (3) traditional menstrual management practices situate girls in an 'alternate space' characterised by withdrawal from many daily routines. These three socio-culturally determined practices interacted in a complex manner, often leading to interrupted class engagement and attendance. CONCLUSIONS: To be truly effective, current menstrual hygiene management strategies need to address the root causes of poor WASH infrastructure and ensure facility design is sensitive to the gendered and deeply embedded local socio-cultural values and beliefs around menstrual hygiene management.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".