Family size preferences among women in a union in Nigeria and associated factors
Bibliographic record
Abstract
 Nigeria’s population is currently estimated at 216million and the country will be the third most populous in the world in 2050. A major driver of the high population growth is persistent high fertility. This study examined women’s fertility preferences, which was measured with ideal family size (IFS) and the associated factors. Data were obtained from the 2018 Nigeria Demographic and Health Survey. The analysis consisted of a weighted sample of 13, 673 women in union, aged 15–49 years whose first marriage took place within 10 years before the survey. Descriptive and multinomial logistic regression analyses were conducted. The proportion of respondents whose IFS was 5+ was 65%. Slightly above one-quarter had IFS of four children, and 11% had IFS of 0 – 3. IFS of 5+ was significantly associated with women resident in the Northern and Southeast regions, rural residents, Muslims, women who had no education, women working in agriculture, sales/service jobs, those who participated in one or two out of four household decisions, justified wife beating, have 5+ siblings, experienced child death, and married before age 20. Efforts to achieve the target reduction in total fertility rate in Nigeria should be multi-sectoral targeting these subpopulations of women.  
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".