Effects of Minimum Wage on Youth Employment and School Enrolment in Canada
Bibliographic record
Abstract
Based on the Public Use of Microdata of Survey of Labour and Income Dynamics, we examine the effects of changes to minimum wage on youth employment and school enrollment across Canada over the period 2005–2011. Using multinomial logistic model, our estimate confirms the postulated neoclassical model disemployment effects for low-skilled workers. Our result suggests that a 10 percent increase in the minimum wage is associated with approximately 3.96 percent decrease in youth employment. More interestingly, we found a positive relationship between minimum wage and school enrollment such that a 10 percent increase in minimum wage is associated with a 3.6 percent increase in school enrollment among youth of 16 to 19 years of age. In addition, estimating the transition probabilities among the possible employment-enrollment activities, we found no substantial evidence to support substitution and queuing hypotheses proposed in past literatures in Canada.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".