Long‐Term Contribution of Immigration to Population Renewal in Canada: A Simulation
Bibliographic record
Abstract
We analyze the direct and indirect demographic contribution of immigration to the foreign‐origin composition of the Canadian population according to various projection scenarios over a century, from 2006 to 2106. More specifically, we use Statistics Canada's Demosim microsimulation model to assess the long‐term sensitivity to immigration levels and the frequency of mixed unions of the share of immigrants in Canada and of persons who have at least one ancestor who arrived after 2006. The results of the simulations show that the population renewal process through immigration happens at a fast pace in a high immigration and low fertility country such as Canada. Under the scenarios developed, immigrants who entered after 2006 and their descendants could form the majority of the population by 2058 at the earliest and by 2079 at the latest and could represent between 62 percent and 88 percent in 2106. They also show that mixed unions are a key element of the speed at which the changes are likely to occur in the long run.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".