Contraception coverage and methods used among women in South Africa: A national household survey
Bibliographic record
Abstract
BACKGROUND: Globally, family planning services are being strengthened and the range of contraceptive choices expanded. Data on contraceptive coverage and service gaps could help to shape these initiatives. OBJECTIVE: To assess contraception coverage in South Africa (SA) and identify underserved populations and aspects of programming that require strengthening. METHODS: Data from a 2012 SA household survey assessed contraception coverage among 6 296 women aged 15 - 49 years and identified underserved populations. RESULTS: Two-thirds had an unintended pregnancy in the past 5 years, a quarter of which were contraceptive failures. Most knew of injectable (92.0%) and oral contraception (89.9%), but fewer of intrauterine devices (56.1%) and emergency contraception (47.3%). Contraceptive prevalence was 49.1%, and 41.8% women used modern non-barrier methods. About half had ever used injectable contraception. Contraception was lower in black Africans and younger women, who used a limited range of methods. CONCLUSION: Contraception coverage is higher than many previous estimates. Rates of unintended pregnancy, contraceptive failure and knowledge gaps, however, demonstrate high levels of unmet need, especially among black Africans and young women.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".