Interregional Migration and Public Policy in Canada
Bibliographic record
Abstract
Given Canada's vast geography and uneven distribution of economic activity, almost all Canadians have at one time or another faced the question of whether an interprovincial move would make them better off. Using a unique dataset based on income tax records, authors Kathleen Day and Stanley Winer examine the factors influencing the decision to migrate within Canada, paying special attention to the role of regional variation in the generosity of public policies including unemployment insurance, taxation, and public expenditure. The influence of extraordinary events such as the election of a separatist government in Quebec and the closure of the east coast cod fishery is also considered. They look at why we ought to be concerned about public policies that interfere with market-based incentives to move, provide a wealth of information on interregional differences in public policies and market conditions, and examine what other researchers have discovered about fiscally induced migration, culminating in a discussion of the likely impact of various policy changes on migration and provincial unemployment rates. The authors' assessment of the lessons to be learned from their own and past research on policy-induced migration in Canada will be of interest to students of migration and policy makers alike.
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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 | 0.002 | 0.008 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".