Educational Selectivity of Out-migration in Canada: 1976-1981 to 1996-2001
Bibliographic record
Abstract
The major objective of this paper is to show that migrants are positively selected whether they are driven by economic factors or by non-economic factors, and whether they are motivated by pull factors or push factors. Using “five-year migration data” from the 1981 to 2001 censuses of Canada, we find that the education gradient of out-migration is apparent in every region, with the highly educated being more mobile than the less educated. However, the pattern is most pronounced in the Atlantic region, Quebec, and Manitoba/Saskatchewan, the regions experiencing poorer economic conditions and persistent net losses through migration. The three high-income provinces, Ontario, Alberta, and British Columbia not only experience lower overall net losses, but are also less likely to lose their better educated persons—even during bad economic times. Quebec emerges as a special case where economic as well as linguistic-political factors play an important role in governing the out-migration patterns of the better educated, particularly those belonging to the non-Francophone group.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| 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) | 0.003 | 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".