Lifetime interprovincial migration in Canada: looking beyond short‐run fluctuations
Bibliographic record
Abstract
This article studies the lifetime interprovincial migration of the Canada‐born elderly (aged 60 and over), based on the data of the 1996 population census. The outcomes of the lifetime migration are found to be highly consistent with the human capital investment theory: there were substantial net transfers of migrants from the ‘have not’ provinces to the ‘have’ provinces, and the migrants moving in the ‘right’ direction, on average, achieved long‐term income improvements. However, the long‐term income improvements attributable to lifetime migration, both directly and indirectly via educational improvement, were in general not large enough to compensate for the disadvantages of being born in the ‘have not’ provinces and to francophone parents. The lifetime migration is also found to be highly selective by mother tongue and to have aggravated somewhat the spatial polarisation between Francophones and non‐Francophones.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".