Demand-Driven Youth Training Programs: Experimental Evidence from Mongolia
Bibliographic record
Abstract
Abstract The effectiveness of a demand-driven vocational-training program for disadvantaged youth in Ulaanbaatar, the capital city of Mongolia is assessed through a randomized controlled trial. Mongolia, a transitional country whose economic structure shifted from a Communist, centrally planned economy to a free-market economy over a relatively short period, offers a new setting in which to test the effectiveness of market-based active-labor-market policies. Results show short-term positive impacts on self-employment and skills match, while positive but uncertain effects emerge for employment and earnings. Substantial heterogeneity emerges as relatively older, richer, and better-educated individuals drive these positive effects. A second intervention, in which participants were randomly assigned to receive newsletters with information on market returns to vocational training, shows statistically meaningful effects on the length of exposure to the program (i.e., number of training days attended). These positive impacts, however, do not lead to higher employment or greater earnings.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".