Family Structural Norms Leading to Gender Disparity in Pakistan
Bibliographic record
Abstract
The major purpose of this study was to explore the, “Family Structural Norms Leading to Gender Disparity in Pakistan”. It was concluded that Females are not consulted regarding their higher education, proper transport facilities are not managed by universities for female students, females have less access to higher education, There are inadequate and a very small number of women’s universities, family structural norms found not supportive for female education, females located in either urban or rural areas are facing the same problem of gender disparity regarding their education, and they have the same views that family structural norms are not supporting for their education. On the basis of these conclusions it is recommended that females should have the freedom to make their own decisions, especially regarding their education, proper transportation facilities should be arranged or managed them, it is necessary to enhance females’ enrolment in each and every tier and streamline of education to bring equity in gender, more women s’ universities should be established, Legislation should be done at central level as well as at provincial level to enhance the females’ enrolment in all tiers of education and all streamlines, and 50% seats should be reserved for female students in every discipline in the universities.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".