Parental education and child labour: evidence from Pakistan
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Child labour deprives children of their right to education, resulting in a lack of skills, human capital, and a reduction in future earnings. This study provides a better understanding of child labour by examining its relationship with socio-economic factors. Using PSLM 2019-2020 data, logit estimates show that an increase in the parental level of education reduces the chance of child labour. The well-being measured by the wealth index shows that children from wealthy households are less likely to work. Furthermore, the fathers' employment substitutes, while mothers' employment complements children's work. Girls are less likely to involve in child labour than boys. However, this may be interpreted carefully as girls are primarily engaged in household chores that are not reported. Finally, children from rural areas are more likely to do work than children from urban areas. Similarly, children from Balochistan have a greater chance of child labour than Sindh, Punjab, and KPK.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it