Education–job match among recent Canadian university graduates
Bibliographic record
Abstract
This study uses data from the 2005 Follow-up of Canadian Graduates – Class of 2000 – to look at the determinants of education–job match among university graduates. The question of education–job match is relevant given the substantial investment society puts into its postsecondary institutions and the role devoted to human capital in economic development. We find that 35.1% of graduates are in a job that is not closely related to their education 5 years after graduation. The education–job match strongly depends upon education characteristics, with fields that focus on providing specific skills for the job market (such as ‘Health sciences’ and ‘Education’) being associated with the highest likelihood of obtaining an education–job match. In addition, the level of education, good grades and time devoted to studying strongly affect the match. Employment characteristics also affect the match, but to a mixed extent. One of our main findings is that predetermined characteristics (age, gender and family background) do not significantly affect the match. However, immigrants are significantly disadvantaged even if they hold Canadian degrees.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".