Direct and Indirect Effects of Subsidized Dual Apprenticeships
Bibliographic record
Abstract
Abstract Public interventions in the apprenticeship market often aim to increase demand or returns. We set up a double-sided experiment with youth and firms to analyse a subsidized dual apprenticeship program. This intervention seeks to relax financial constraints for youth by offering a wage subsidy and to make apprenticeship more attractive by providing vocational training in technical skills that complements on-the-job training. We document a large increase in youth participation in apprenticeship, yet the inflow of apprentices induces little crowding out of traditional apprentices in firms. The intervention leads to an increase in youth demand for apprenticeship, enabling firms to fill open apprenticeship positions. The subsidy compensates apprentices for low wages but does not alleviate financial constraints. Consistent with the dual training component contributing to an increase in youth demand for apprenticeship, youth perform more complex tasks and have higher earnings 4 years after the start of the experiment.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".