Three essays on internal migration
Bibliographic record
Abstract
This dissertation is composed of three essays on intemal migration.The first essay entitled "Internal Migratíon, Self-selection and Eantings of Canadian Immigrants" investigates the post-arrival human capital investment behavior of immigrants, migration particularly, and its effect on individual earnings, compared with Canadian-born using the up-to-date longitudinal datasets-the Longitudinal Survey of Immigrant to Canada(LSIC) and the Survey of Labor and Income Dynamics (SLID).The double self-selectivity of migration and labor force participation are considered in the wage and wage growth models.The investment in internal migration activity is analyzed by employing the endogenous switching model.This study finds that migration behavior has a significant positive efîect on immigrants'early career wage development in Canada.Both migration and labor force participation selection bias are found to significantly affect the wages of immigrants and native-bom.The second essay entitl ed"Immigrant and Canadian-born Fømily Migr:ation and the Labor Supply Consequences of Women and Men" investigates the family migration behavior of immigrants and Canadian-bom and the consequences of labor supply for men and women.Even though immigrant families (in which both spouses are immigrants) have the lowest average migration rate compared with native families (in which both spouses are native-bom) and mixed families (in which one spouse is immigrant and one spouse is native-bom), the regression results show that immigrant families are not significantly less mobile than the other two family types after controlling for VI Jobless experience
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".