A Strategic Assessment of Unsafe Abortion in Malawi
Bibliographic record
Abstract
As part of efforts to achieve Millennium Development Goal 5 – to reduce maternal mortality by 75% and achieve universal access to reproductive health by 2015 – the Malawi Ministry of Health conducted a strategic assessment of unsafe abortion in Malawi. This paper describes the findings of the assessment, including a human rights-based review of Malawi's laws, policies and international agreements relating to sexual and reproductive health and data from 485 in-depth interviews about sexual and reproductive health, maternal mortality and unsafe abortion, conducted with Malawians from all parts of the country and social strata. Consensus recommendations to address the issue of unsafe abortion were developed by a broad base of local and international stakeholders during a national dissemination meeting. Malawi's restrictive abortion law, inaccessibility of safe abortion services, particularly for poor and young women, and lack of adequate family planning, youth-friendly and post-abortion care services were the most important barriers. The consensus reached was that to make abortion safe in Malawi, there were four areas for urgent action – abortion law reform; sexuality education and family planning; adolescent sexual and reproductive health services; and post-abortion care services.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".