Correlates of school dropout and absenteeism among adolescent girls from marginalized community in north Karnataka, south India
Bibliographic record
Abstract
Secondary education among lower caste adolescent girls living in rural Karnataka, South India, is characterized by high rates of school drop-out and absenteeism. A cross-sectional baseline survey (N=2275) was conducted in 2014 as part of a cluster-randomized control trial among adolescent girls (13-14 year) and their families from marginalized communities in two districts of north Karnataka. Bivariate and multivariate logistic regression models were used. Overall, 8.7% girls reported secondary school dropout and 8.1% reported frequent absenteeism (past month). In adjusted analyses, economic factors (household poverty; girls' work-related migration), social norms and practices (child marriage; value of girls' education), and school-related factors (poor learning environment and bullying/harassment at school) were associated with an increased odds of school dropout and absenteeism. Interventions aiming to increase secondary school retention among marginalized girls may require a multi-level approach, with synergistic components that address social, structural and economic determinants of school absenteeism and dropout.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".