Paving the way for universal family planning coverage in Ethiopia: an analysis of wealth related inequality
Bibliographic record
Abstract
BACKGROUND: Family planning plays a significant role in reducing maternal and child mortality and ultimately in achieving national and international development goals. It also has an important role in reducing new pediatric HIV infections by preventing unwanted pregnancies among HIV positive women. Investing in family planning is one of the smart investments for development as population dynamics have a fundamental influence on the pillars of sustainable development, including that of a sustainable environment. OBJECTIVE: To identify and quantify wealth related differences in family planning use between poor and rich Ethiopian women based on the Demographic and Health Survey asset based wealth quintiles. METHODS: The proportion of women who used contraceptives during implementation of the 2011 and 2005 Ethiopia Demographic and Health Surveys was calculated across wealth quintiles. Data were stratified for place of residence to analyze and determine inequalities in family planning use separately for rural and urban women. Socioeconomic inequalities according to wealth were measured using the slope index of inequality and the relative index of inequality. RESULT: The absolute difference of contraceptive prevalence between poorest and richest women was over 25.3 percentage points (95% CI = 18.9-31.7) in 2011. Contraceptive use was more than twice (RII: 2.6, 95% CI = 2.0 - 3.3) as prevalent among the richest compared with the poorest. CONCLUSION: Despite efforts to provide contraceptives for free at all public health facilities, wealth based inequalities still prevail in Ethiopia. People at lower socioeconomic strata should be empowered more to avoid the root causes of inequality and to achieve national Health Sector Development Program Goals.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".