Diversity and Concentration in Canadian Immigration
Bibliographic record
Abstract
Canada is a country of immigrants. With the exception of the Aboriginal population, everyone in Canada is an immigrant or can trace his or her roots to immigrants. There have been two major periods of large immigrant flows to Canada in the 20th century. The first occurred in the early 1900s and coincided with the opening of Western Canada. Those who arrived during this period were primarily European migrants, farmers who were attracted by the government’s offer of free land. The second took place from the 1950s onwards, following the 1930s Depression and the Second World War (Figure 1). Both the total number of immigrants and immigrants as a percentage of Canada’s population peaked in the early 1900s when Canada was a young country with a relatively low population. In 1913, when immigration was at its highest level, Canada received 400,870 immigrants or about 5.3 percent of the country’s population. After the Second World War, annual immigrant flows fluctuated, but levelled off between 200,000 and 250,000 annually after 1990, or less than 1 percent of Canada’s population. Debate continues about whether Canada should maintain or expand its population through immigration in the next few decades. Depending on which option is chosen, the annual level of immigration will either be maintained or expanded considerably. The capacity of the country to absorb an increased flow of immigrants is also the subject of considerable discussion.
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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 | 0.000 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".