Provincial Returns to Education for 21 to 35 year-olds: Results from the 1991-2006 Canadian Analytic Censuses Files
Bibliographic record
Abstract
This paper examines the evolution of the returns to education and experience from 1990 to 2005 in Canada and across the provinces. The focus is on the earnings of young adults, age 21 to 35 at the times of the Censuses, classified by very detailed education groups, age and gender. Returns to higher education are very different across provinces and are particularly high in the western part of the nation. Over time, they are quite stable, but they are increasing for females in 2005 relative to 2000 in particular Bachelor’s degree and higher degrees. This is surprising given the very important increase in the supply of well educated females since 1991. These returns can explain partially why so many young women turned to higher education over time. It is also surprising that males have not followed suit, given that the returns are just as high for them as for women. Yet, the returns for university education are much higher than the returns for college or CEGE. Also, returns for trade degrees are much higher for males than for females. The male-female gap in higher education will certainly help to reduce the wage gap between genders, however, public policy must be concerned by the difference between male and female participation in higher education.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.015 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".