Exploration of the Role of Education in Intergenerational Income Mobility in Canada: Evidence from the Longitudinal and International Study of Adults
Bibliographic record
Abstract
Canadian children experience a high level of intergenerational income mobility compared with US children. Moreover, their physical and mental health outcomes, school readiness, and post-secondary attendance are all less tightly associated with parental outcomes than in the United States. In this article, we investigate the role played by children’s education in the intergenerational transmission of income in Canada. Existing research has produced macro-level estimates of mobility to draw comparisons over time and across places and has studied the micro-level mechanisms that underlie the relationship between parents’ and children’s outcomes. However, evidence on the extent to which the different factors investigated drive the broader numbers is still limited. To remedy this, we exploit the Longitudinal and International Study of Adults, a rich panel of integrated survey and administrative data covering 1982–2013. We estimate that the education level of children accounts for 40.5–50.1 percent of the correlation between their income and their parents’, similar to the United States. Moreover, we discuss evidence suggesting that the greater mobility of Canadian children is linked not only to their lower returns to education but also to the weaker association between their education and their parents’ income. Finally, we find that almost half of the effect linked to education is associated with the skills respondents use at work, such as reading or communication.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".