Summary Of: The Initial Destinations and Redistribution of Canada's Major Immigrant Groups: Changes over the Past Two Decades
Bibliographic record
Abstract
This article summarizes findings from the research paper entitled: The Initial Destinations and Redistribution of Canada's Major Immigrant Groups: Changes over the Past Two Decades. In 1981, about 58% of immigrants who had come to Canada in the previous 10 years lived in Toronto, Vancouver, and Montreal; by 2001, this had increased to 74% (Statistics Canada 2003), triggering debate on the merits of a more 'balanced geographic distribution of immigrants' (Citizenship and Immigration Canada-CIC 2001). Policies aimed at directing immigrants away from major gateway cities in many western countries have focused on the choice of initial destination, and little effort has been made to affect subsequent mobility. But such policies will work only if other, non-gateway regions, can keep immigrants or maintain balanced in- and out-migration. To this end, this study examines how Canada's major immigrant groups arriving over the past two decades have altered their geographic concentration through time, comparing immigrants arriving in the 1970s, 1980s, and 1990s, in the concentration levels of their initial destinations, and in their subsequent geographic dispersal. It pays attention to the dispersal pattern of groups whose initial settlements were influenced by government policies and questions the role of pre-existing immigrant communities in geographic distribution.
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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 | 0.004 | 0.011 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".