Brain Drain: Why Do Some Post-Secondary Graduates Choose to Work in the United States?
Bibliographic record
Abstract
In this study, we examine the phenomenon of the brain drain in Canada, specifically the loss of certain post-secondary graduates to the United States. Our analysis comprises three components: a descriptive analysis of the differences between graduates who stayed in Canada and those who moved to the United States; a multivariate analysis, to identify the determinant factors of the decision to move from Canada to the United States and the decision to return to Canada afterwards; and analysis to explain the wage differentials between stayers and movers. Using the data for the last three cohorts from the National Graduates Survey, we observe that the brain drain remains relatively marginal, affecting 2% of new graduates at most. We also note a slight decrease in the brain drain for the Class of 2005 compared with the Class of 2000 in the first two years after graduation. In addition, we identify a strong movement to return to Canada (some 48% of those who left between 2000 and 2005) or a strong intention to do so (61% of the graduates of 2000 still living in the United States in 2005). Striking differences emerge in connection with certain factors, however, including level of education and field of study. For example, PhDs are by far the most likely to move to the United States. That also holds true for graduates in the fields of mathematics, computer and information sciences and architecture, engineering and related technologies. The wage differences are also high, in the order of 27% to 40% higher for graduates working in the United States, of which only one third can be explained by a variety of observable factors. Finally, we find that the graduates of 2000 who returned to Canada after a stay in the United States earned, in 2005, up to 18% more on average than those who never left Canada, all other things being equal. Canada thus benefits from the brain drain when it is not permanent. Whatever the case, we do not believe that at current levels, the brain drain of post-secondary graduates to the United States requires specific intervention on the part of public policymakers. However, the phenomenon should be monitored on an ongoing basis, as it may evolve in the future.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".