A protocol for a controlled, pre-post intervention study to change attitudes toward child marriage in Southwestern Nigeria using targeted radio programming
Bibliographic record
Abstract
BACKGROUND: Child marriage hinders progress toward population health and development goals. Cost effective interventions that address the root causes of child marriage are needed to speed progress toward ending the practice. Nigeria is home to the largest number of married girls in Africa and many of these girls are members of the Hausa ethnic group, making efforts to tackle this issue particularly urgent among this population. METHODS: Radio programs have the potential to inform large numbers of people about the harms of child marriage and change their support for the practice at low cost. We will develop a series of radio programs that address gender inequitable attitudes that motivate child marriage among Hausa communities in Ibadan, Nigeria. The content of the series will be based on input from the Hausa community. A baseline survey that measures knowledge of and support for child marriage will be conducted among randomly selected samples of Hausa adults in two cities: Ibadan, which will serve as the intervention site, and Akure, the control site. The radio programs will then air on Hausa-language stations in Ibadan over a three-month period, with the aim of informing persons of the potential harms of child marriage and reducing their support for the practice. A follow-up survey with the same individuals surveyed at baseline will be conducted in both cities. We will measure the impact of this intervention by comparing changes in these outcomes over time in the intervention site (Ibadan) with changes in the same outcomes in the control site (Akure). CONCLUSION: This study will investigate whether a series of targeted radio programs can reduce support for child marriage. The intervention is readily scalable and cost-effective and, if it effectively shifts attitudes toward child marriage, could represent a promising way of addressing child marriage in Nigeria.
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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 | 0.043 | 0.025 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.067 | 0.010 |
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".