Young Women’s Access to and Use of Contraceptives: The Role of Providers’ Restrictions in Urban Senegal
Bibliographic record
Abstract
CONTEXT: Contraceptive prevalence is very low in Senegal, particularly among young women. Greater knowledge is needed about the barriers young women face to using contraceptives, including barriers imposed by health providers. METHODS: Survey data collected in 2011 for the evaluation of the Urban Reproductive Health Initiative in Senegal were used to examine contraceptive use, method mix, unmet need and method sources among urban women aged 15-29 who were either currently married or unmarried but sexually active. Data from a sample of family planning providers were used to examine the prevalence of contraceptive eligibility restrictions based on age and marital status, and differences in such restrictions by method, facility type and provider characteristics. RESULTS: Modern contraceptive prevalence was 20% among young married women and 27% among young sexually active unmarried women; the levels of unmet need for contraception-mostly for spacing-were 19% and 11%, respectively. Providers were most likely to set minimum age restrictions for the pill and the injectable-two of the methods most often used by young women in urban Senegal. The median minimum age for contraceptive provision was typically 18. Restrictions based on marital status were less common than those based on age. CONCLUSIONS: Training and education programs for health providers should aim to remove unnecessary barriers to contraceptive access.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".