Post-Secondary Attendance by Parental Income: Comparing the U.S. and Canada
Bibliographic record
Abstract
This paper makes three contributions to the literature on educational attainment gaps by family income.First, we conduct a parallel empirical analysis of the effects of parental income on postsecondary (PS) attendance for recent high school cohorts in both the U.S. and Canada using data from the 1997 Cohort of the National Longitudinal Survey of Youth and Youth in Transition Survey.We estimate substantially smaller PS attendance gaps by parental income in Canada relative to the U.S., even after controlling for family background and adolescent cognitive achievement.Second, we develop an intergenerational schooling choice model that sheds light on the role of four potentially important determinants of the family income -PS attendance gap: (i) borrowing constraints, (ii) a 'consumption value' of attending PS school, (iii) the earnings structure, and (iv) tuition policies and the structure of financial aid.Third, we document Canada -U.S. differences in financial returns to PS schooling, tuition policy, and financial aid, discussing the extent to which these differences contribute to the stronger family income -attendance relationship in the U.S. Most notably, we document the dependence of both non-repayable financial aid and government student loan access on parental income in both countries.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".