Can Skills Training Programs Increase Employment for Young Women? : The Case of Liberia
Why this work is in the frame
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Bibliographic record
Abstract
Young people age 15 to 29 make up about \n a quarter of the world's population, yet they \n constitute nearly half of the world's unemployed. The \n World Bank is helping to increase viable employment \n opportunities for youth. In many countries, restrictive \n gender norms make it harder for girls to access training and \n employment opportunities. To ensure that girls and young \n women are included in this agenda, the Bank launched the \n Adolescent Girls Initiative (AGI) in 2008. The program is \n being piloted in eight low-income countries- including some \n of the toughest environments for girls. Each intervention is \n tailored to the country context, and includes an impact \n evaluation to build the evidence base to help adolescent \n girls and young women succeed in the labor market. The first \n AGI pilot- the Economic Empowerment of Adolescent Girls \n (EPAG) and young women project was launched in Liberia in \n late 2009. Preliminary results from the midline survey show \n that EPAG has been very successful in achieving its primary \n objectives- increasing employment and earnings among young \n women. The magnitude of the results is impressive when \n compared to findings from other youth training programs in \n developing countries. It is expected that successful \n economic empowerment programs like EPAG can also indirectly \n bring about positive behavioral changes and provide \n spillover benefits for the families and communities of trainees.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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