The changing face of Canada: the uneven geographies of population and social change
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it