Strengthening integrated sexual reproductive health and rights and HIV services programs to achieve sustainable development goals 3 and 5 in Africa
Bibliographic record
Abstract
Each year, over 200 million women globally cannot prevent pregnancy through modern contraceptive methods, with 70-80% of these women residing in sub-Saharan Africa. Consequently, almost 50% of pregnancies are unintended and 35 million unsafe abortions occur annually in the region. Further, sub-Saharan Africa has the highest burden globally of Human Immune-Deficiency Virus (HIV) infection, and over 57% of those affected are women. Women with a positive HIV status in sub-Saharan Africa experience higher rates of unintended pregnancy and unsafe abortion practices. In this commentary, we propose strategies to strengthen integrated sexual and reproductive health and rights (SRHR) and HIV services programs to improve the sexual and reproductive health of girls and women and to work towards achieving SDGs 3 and 5 in sub-Saharan Africa. We suggest a focus on capacity building, strengthening intersectoral collaborations, and improving governance and financial investment.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.022 | 0.028 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".