The changing face of Canada: the uneven geographies of population and social change
Bibliographic record
Abstract
This paper attempts to convey a sense of the increasing importance of the population question for the future of Canada and its social geographies. This future will be shaped as much by changes in population processes and living conditions as by economic and political factors. Specifically, four transformations are rippling through the country's social fabric and urban landscapes: slow growth and the demographic transition modifications to family forms and living arrangements; increasing ethnocultural diversity; and the shifting relationships among households, labour markets and the welfare state. There is increasing unevenness of population growth, juxtaposing localized growth and widespread decline, massive social changes, the concentration of immigration and new sources of diversity in metropolitan areas, and fundamental shifts in social attitudes concerning family, work and gender relations. Deepening contrasts in living environments and economic wellbeing flow from these trends, and the varied challenges they pose for private actors, governments and service‐providers. Questions relating to the country's future population geographies and social structures are complex, analytically difficult, and politically charged, but are too important to ignore.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.015 | 0.011 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".