Out‐of‐school time use in Pakistan: A qualitative study featuring youth's voices
Bibliographic record
Abstract
The current study addresses the lack of out-of-school time (OST) research in low- and middle-income countries by exploring OST use in the context of Pakistan and incorporating youth's voices. Using a qualitative descriptive design with focus-group discussions, we conducted a study in three middle schools set in low- to middle-income neighborhoods in urban and rural areas of Karachi, Pakistan. We engaged 86 youth (50% girls; aged 10-15 years) that were purposefully selected from grade six (31.4%), seven (44.2%) and eight (24.4%) classrooms, balancing gender and locality. In each focus group, we asked participants to describe their afterschool activity routine on a typical weekday afternoon until bedtime. Digital recordings of discussions were transcribed verbatim and analyzed using content analysis. Based on sixteen focus groups with five to six participants in each group, we identified eight distinct categories: religious activities, schoolwork, screentime, helping adult family members, family time, outdoor play, indoor leisure activities, and hanging out with friends. We found that structured activities (e.g., religious activities and schoolwork supervised by an adult) were reported more frequently than unstructured activities (e.g., outdoor play and family time). Participation in activities varied by gender and location (i.e., urban vs. rural), highlighting disparities associated with the sociocultural context that marginalized youth face. Our findings provide a glimpse into the everyday lives of Pakistani youth outside of school. Additionally, they elucidate how economic resources, sociocultural norms regarding gender, and community safety shape youth's time use and socialization patterns. Findings from this study can inform the development of OST activities and initiatives aimed at promoting the positive development of Pakistani youth.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".