Effectiveness of a community-based intervention in changing knowledge of and attitudes towards early marriage in The Gambia
Bibliographic record
Abstract
A study was conducted to assess the effects of a multi-component community-based project intervention on changing knowledge of, and attitudes towards early marriage for girls in The Gambia. The study involved a cross-sectional household survey of 201 male and female parents and 296 adolescent boys and girls aged 10-19. It also included two community-based focus group discussions and six key informant interviews. The study compared the project baseline and midline data in the analysis of the survey data. The findings show a significant increase from a baseline of (44.8%) to (70.7%) at midline among the parents who have the view that the girl needs to come of age (18 years) before going into marriage. At both baseline and midline, there is a fear that girls may break their virginity by indulging in premarital sex if they do not marry early. However, there was a significant decrease from (51.7%) at baseline to (10%) (p-value <0.001) in the proportion of parents who think girls must marry early to avoid premarital sex. The findings show between (2%) and (7%) increase from baseline to midline on the view among adolescent boys and girls that girls have the right to choose who to marry. Findings from the focus group discussions and key informant interviews directly linked the changes in knowledge of attitudes towards early marriage among parents and adolescents to the project intervention.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".