Boys’ perspectives on girls’ marriage and school dropout: a qualitative study revisiting a structural intervention in Southern India
Bibliographic record
Abstract
Girls' education has for many decades been central to the global development agenda, due to its positive impact on girls' health and wellbeing. In this paper, the authors revisit boys' attitudes, behaviours and norms related to girls' education, following the Samata intervention to prevent girls' school dropouts in Northern-Karnataka, South India. Data were collected from 20 boys in intervention villages before and after the intervention, and analysis was undertaken using a thematic-framework approach. Findings suggest that while boys did hold some attitudes and beliefs that supported girls' education and delayed-marriage, these remained within the framework of gender-inequitable norms concerning girls' marriageability, respectability/family-honour. Participants criticised peers who sought to jeopardise girls' respectability by teasing and community gossip about girls-boys' communication in public. Boys who rejected prevailing norms of masculinity were subjected to gossip, ridicule and violence by the community. Boys' attitudes and beliefs supported girls' education but were conditional on the maintenance of gendered hierarchies at household and interpersonal levels. Social norms concerning girls' honour, respectability and the role of boys as protectors/aggressors appeared to influence boys' response to girls' school dropouts. Future interventions aiming to address girls' education and marriage must invest time and resources to ensure that intervention components targeting boys are relevant, appropriate and effective.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".