Examining the Cultivating Effect of Social Issue Based Dramas on Women of Pakistan
Bibliographic record
Abstract
This study examined the cultivating effect of social issue-based dramas on women of Pakistan. N=100 women were surveyed on convenient sampling. These samples included working women who were lecturers (PhD) and assistant professors (PhD) at universities. The second sample compromises housewives living in G8, G9 sector of Islamabad and Satellite Town in Rawalpindi. The questionnaire comprised of twenty questions, furnished among working women and housewives in person. The sample was collected from the three mainstream channels of Pakistan i.e., Ruswai (aired from ARY Digital between the last quarter of 2019 and first quarter of 2020) Dar Khuda Say (aired from Geo TV between the second quarter of 2019 and the first quarter of 2020) and Inkaar (aired from Hum TV between the first and second quarter of 2019). The results showed that dramas cultivate an effect in women and the hypothesis was supported.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".