Immigrant Economic and Social Outcomes in Canada: Research and Data Development at Statistics Canada
Bibliographic record
Abstract
The past 25 years has seen a more or less continuous deterioration in the economic outcomes for immigrants entering Canada. However, economic outcomes for second-generation Canadians (children of immigrants) are more positive, and in spite of the economic difficulties, after four years in Canada most immigrants entering in 2000 remained positive regarding their immigration decision, citing the freedom, safety, rights, security and prospects for the future as the aspects they appreciate most in Canada. This paper reviews what we know about the economic deterioration, and the possible reasons behind it, in particular based on the research conducted at Statistics Canada. It also outlines the data development undertaken by Statistics Canada and its policy department partners to support increased research of this topic. From 2002 to 2008, Statistics Canada released 64 research articles on the above topics, and others related to immigration. The research suggests that through the 1980s and 1990s three factors were associated with the deterioration in economic outcomes: (1) the changing mix of source regions and related issues such as language and school quality, (2) declining returns to foreign experience, and (3) the deterioration in economic outcomes for all new labour market entrants, of which immigrants are a special case. After 2000, the reasons appear to be different, and are associated more with the dramatic increase in the number of engineers and information technology (IT) workers entering Canada, and the IT economic downturn. Data also suggest that, by and large, Canadians continue to see immigration as an important part of the development of Canada and that they continue to support it. The paper reviews Statistics Canada research that indicates that economic outcomes for most second-generation Canadians remain very positive. Finally, there is a discussion of the interaction between immigration and social cohesion in Canada, and possible reasons as to why we have not seen the discontent with immigration policy in Canada that has been observed in some European countries.
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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 | 0.013 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.026 | 0.066 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".