Male Students Are More Stressed than Female Due to Social Class Differences in Peshawar (Pakistan)
Bibliographic record
Abstract
This article comprises of questionnaire / interview survey of 212 students to study the association between the socio economic status of the students and their standard of living. The social classes are divided into three main groups Upper, Middle and Working social classes on the basis of education, occupation, income, and place of residence. On the self assessment basis majority of the students put themselves in the middle socioeconomic class. Test was carried out for the association between gender of the respondents and the satisfaction with the standard of living, mental stress and social status, gender and social status causes mental stress, social classes and sufficient education facilities are available for poor people. Analysis showed that the gender of the respondent and all the two factor interaction were insignificant but profession and monthly income of the respondent play a vital role in discriminating the people in different social classes. This discrimination causes a mental stress. Work also revealed that in Peshawar region the mental stress phenomenon is more common in male than females in various fields of life. This may be due to the fact that males have more responsibilities. In most cases they have to earn to support their families. Hard government policies are also considered as the major factor which causes mental stress among the students.
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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 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".