Gender gaps in the path to adulthood for young females and males in six African countries from the 1990s to the 2010s
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In this paper, we study on a comparative basis the school-to-work transition of young women and young men in six countries in sub-Saharan Africa, and we examine how this has evolved over recent years, based on the data collected by Demographic and Health Surveys. We examine educational attainments and the nature of early jobs young people are able to obtain, as well as considering their relationship to marriage and fertility outcomes, factors which are likely to be particularly relevant for young women. A pooled regression analysis shows that educational levels have increased substantially and gender gaps have narrowed in most countries. Access to better jobs has improved much more slowly with unchanging gender gaps in most countries, so that agriculture is still the dominant sector of employment for most young men and women. We model correlates of key educational outcomes and access to different types of jobs those controlling for individual- and household-level characteristics, including marital status, presence of children and wealth. Attaining a high level of education is unsurprisingly critical for access to the best jobs and is also associated with young women delaying marriage and childbearing.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it