Youth Migration in the Context Of Rural Brain Drain: Longitudinal Evidence From Canada
Bibliographic record
Abstract
Population growth in many major cities is partly driven by migration from rural areas, which constrains these communities’ development. Despite this concern, research that longitudinally examines the patterns and predictors of youth outmigration to urban areas, as well as return migration to rural areas, is very limited in Canada. To address this void, we longitudinally link Canada’s Youth in Transition Survey, Cohort A, and the Programme for International Student Assessment reading scores, measured at age 15, to individuals’ tax filer information through age 30 via the T1 Family File to examine the characteristics and extent of rural Canada’s youth out- and return migration. Our analysis points to two important findings: (a) the ‘leavers’ are more educated with higher levels of employability and income than the ‘stayers’ and (b) the ‘returners’ tend to come back to rural areas as a result of economic constraints in urban areas. Based on these findings, we provide several recommendations for policymakers and future research. Keywords: Brain drain, out-migration, Programme for International Student Assessment, return migration, T1 Family File
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".