Does sex composition of offspring relate to fertility in urban areas? The case of Ouagadougou, Burkina Faso
Bibliographic record
Abstract
With the onset of the demographic transition in sub-Saharan Africa, couples' desired number of children and the sex composition of offspring may become conflicted, with potential effects on future fertility. While intuitively expected, this effect has not been observed in studies in sub-Saharan Africa, where the level of fertility is higher than in other African regions. In this study, the hypothesis of a conflicted situation was examined by assessing the effect of sex composition of offspring on women's intentions regarding additional children and their use of modern contraceptives. A mixed-method analysis was performed using quantitative data regarding 2567 women aged 35-49 years drawn from a 2012 Demtrend retrospective longitudinal population survey, supplemented by qualitative data collected through 23 in-depth interviews of men and women in Ouagadougou. Results showed that the absence of one sex (boy or girl) in the existing offspring was associated with additional demand for children and lower contraceptive use. These results suggest that a desire for a combination of both girls and boys may be the driving factor contributing to larger family size; that is, continued fertility may not be determined by son preference, but rather by overall composition of offspring, when existing children are all girls or all boys. This could explain the stalling of the fertility decline observed in recent years in Ouagadougou.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".