The Impact of Disaster on the Reproductive Health of Women and Girls in Nigeria
Bibliographic record
Abstract
The last two decades has witnessed an increase frequency and severity of both natural and man-made disasters in Nigeria. Women and girls are more affected by the impact of disasters, which due to their prior poor economic and social status limit their survival skills. The response to disaster in affected communities in Nigeria put more premiums on issues like shelter, food, water and sanitation, human security with less attention on reproductive health and social issues. Disaster and displacement expose women to sexual violence, exploitation, trafficking and abuse, leading to higher rates of unintended pregnancies, risky abortions, and sexually transmitted infections (STIs) as well as other latent issues. This paper assesses the impact of inaction and neglect of reproductive health and other social issues in disaster management. It is our conclusion that the emergency situation provides a possibility and opportunity to enhance knowledge and provide sexual and reproductive health services. Working with traditional authorities, local and national partners can facilitate the implementation of sexual and reproductive health services that also deal with related cultural norms and practices.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".