Illiteracy: The Cause of Poor Maternal Health among Ever-Married Women in Malakand, Pakistan
Bibliographic record
Abstract
Education is the basic source to empower women in all spheres of life. Among the various socio-cultural factors, family restriction on women to access and getting formal education and preference to religious education within the family is contributing to poor maternal health care access and utilization in the study area. The major objective of the study was to analyze the association between education and maternal health condition among ever-married women. In the present study researchers used the quantitative research design and household data were collected through interview schedule from (n=503) ever-married women having reproductive age (15-49 years). The data was analyzed through SPSS and binary logistic regression is applied to draw the association between illiteracy and poor maternal health care. The statistical results show the majority ever-married women are illiterate (53.0%). The OR is 14.85 times higher among illiterate ever-married women toward inappropriate maternal health care as compare to literate women with C.I (9.504-23.228) P-Value 0.001. In order to achieve Sustainable Development Goal No. 3, 4 & 5 the study recommends women should be provided equal educational opportunities, empowering women in the decision making and gender equality in all social services to them.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".