Job-Education Match & Tenure Among Young Canadians: Evidence from the 1997 & 2014 Labour Force Survey
Bibliographic record
Abstract
In response to the growing supply of postsecondary education graduates and the persistence of overqualification in the Canadian labour market, this study investigates the relationship between the levels of job-education match and tenure among young workers, 25 to 34 years of age, relative to the remaining workforce ages 35 to 64, using a job analysis (JA) approach based on skill levels defined by the National Occupational Classification (NOC) 2011 and education credentials defined by Statistics Canada. Using the 1997 and 2014 Labour Force Survey (LFS) files, a significant negative relationship is observed between length of tenure and overqualified workers, and a significant positive relationship with underqualified workers, in addition to significant differences in the effect that being over/underqualified has on tenure based on respondents’ age and survey year. Implications for individual, organizational, and societal stakeholders involved in the school-to-work transition are discussed.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".