Developmental health and vulnerability among young children in Pakistan: Findings from a large-scale early childhood development assessment in Karachi
Bibliographic record
Abstract
Assessing and supporting early childhood development is a global priority—however, our understanding of the developmental health of young children from Lower and Middle-Income Countries (LMICs), including Pakistan remains limited. Using an Urdu translation of the Early Years Development Instrument (EDI), this study assessed the developmental health and vulnerability of 9,372 kindergarten-aged children ( Mean age = 6.2; SD = 1.1; 53.9 % female) in 397 schools in Karachi, Pakistan. We also examined differences in vulnerability in physical, social-emotional and cognitive domains based on the children’s gender, family income, and ethnic background. Results from logistic regression analyses revealed that 10 % of children were vulnerable in each developmental domain, and 28 % were vulnerable in one or more domains. Boys, children from low-income families, and children with ethnic minority backgrounds were more likely to be vulnerable in any of the domains. The findings highlight that children in our study who experienced social disadvantages were more likely to be developmentally vulnerable, which may negatively impact their further development and success in school. Our findings underscore the need for universal and targeted interventions to reduce childhood vulnerability in Pakistan. This includes supporting at-risk subgroups of children and promoting equity from an early stage in life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".