Period Poverty and Its Consequences among Secondary School Students in Perak, Malaysia
Bibliographic record
Abstract
Period poverty refers to the lack of access to menstrual products. More than a billion women currently lack access to even the most basic supplies during their period, which can be linked to the inconveniences faced by women during their menstruation. The aim of this study was to evaluate period poverty issues among secondary school girls aged 15 to 17 in Ipoh, Malaysia. A cross-sectional questionnaire-based study was conducted among female secondary school students in Ipoh, Perak in order to determine the prevalence of period poverty and its consequences among adolescent girls. The study type was a convenient study, which involved distribution of questionnaires to the secondary school girls. Based on attitude adequacy on menstrual health practices, results showed students had good practices in maintaining menstrual hygiene and only 8.57% had an inadequate level of menstrual practices. Besides, period poverty is not prevalent among secondary school girls in Ipoh, Perak. This was due to that only 16.67% of students experienced period poverty. Moreover, previous study on period poverty showed how it affecting the students lifestyle. Results showed that 20.95% skipped the attendance in school, 37.62% experienced emotional stress and anxiety and 39.05% did not change their menstrual products due to unclean washing facilities and 54.76% experienced lack of participation in school activities.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".