Female Marginalization by Male Head of the Household and Mental Health Concomitants amongst Educated Women of Urban Lahore, Pakistan
Bibliographic record
Abstract
Aim of the Study: The aim of the study was to investigate marginalization from male head of the household and mental health concomitants in a sample of educated women in Pakistan. Methodology: The study is quantitative in nature and a questionnaire was completed by (n=200) women using purposive sampling. The mean age was 25.03 years (SD 5.76). The questionnaire included two scales for measuring marginalization and mental health concomitants. Findings: The sample revealed significant levels of marginalization, with patriarchy and customs/traditions exerting greater influence than religious indoctrination or economic dependence. The most frequent patriarchal act was making unpleasant remarks, while traditional marginalization often involved restricting women from pursuing business studies. Women experiencing higher marginalization reported significantly greater anxiety, depression, obsessive-compulsive, and somatization symptoms. Patriarchal marginalization predicted anxiety, obsessive compulsive, and somatization symptoms, whereas traditional marginalization predicted depressive symptoms. Overall, marginalization by male household heads through patriarchy and tradition was strongly linked to adverse mental health outcomes. Conclusion: This study concludes that there is significant female marginalization in elite households of Pakistan. Pakistani women are subject to mental health issues and psychological disorders due to patriarchal systems within their households regardless of socio-economic status. There is a need for the government to take strict actions against female marginalization and involve NGOs and international organizations to facilitate gender equality and security for women in their households. More importantly, similar studies on other South Asian countries can help in highlighting the severity of the issue internationally and collectively looking for solutions for coming generations.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".