Projecting the future of Canada's population: assumptions, implications, and policy
Bibliographic record
Abstract
After considering the assumptions for fertility, mortality and international migration, this paper looks at implications of the evolving demographics for population growth, labour force, retirement, and population distribution. With the help of policies favouring gender equity and supporting families of various types, fertility in Canada could avoid the particularly low levels seen in some countries, and remain at levels closer to 1.6 births per woman. The prognosis in terms of both risk factors and treatment suggests further reductions in mortality toward a life expectancy of 85. On immigration, there are political interests for levels as high as 270,000 per year, while levels of 150,000 correspond to the long term post-war average. The future will see slower population growth, and due to migration more than natural increase. International migration of some 225,000 per year can enable Canada to avoid population decline, and sustain the size of the labour force, but all scenarios show much change in the relative size of the retired compared to the labour force population. According to the ratio of persons aged 20-64 to that aged 65 and over, there were seven persons at labour force ages per person at retirement age in 1951, compared to five in 2001 and probably less than 2.5 in 2051. Growth that is due to migration more so than natural increase will accentuate the urbanization trend and the unevenness of the population distribution over space. Past projections have under-projected the mortality improvements and their impact on the relative size of the population at older age groups. Policies regarding fertility, mortality and migration could be aimed at avoiding population decline and reducing the effect of aging, but there is lack of an institutional basis for policy that would seek to endogenize population.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".