Not Everything is Black and Red: The Geographies of Canadian Economic Change
Bibliographic record
Abstract
Canada experienced the strongest economic growth of all G7 countries in 2022. However, economic development is not evenly distributed across the nation. Unlike global cities, economically declining municipalities are often overlooked, contributing to social, cultural, and political repercussions. What are the geographies of regional economic change in Canada? And what demographic and spatial characteristics are associated with economic decline? This study examines the spatial distribution of economic change across Canadian cities and regions from 1981 to 2021, while accounting for municipal boundary adjustments between census periods. The findings of our spatial analyses reveal distinct, complex patterns of socio-economic change, influenced by peripherality at various spatial scales. For instance, cities further from the American border were often found to have experienced undesirable trends in educational attainment and average income, while also experiencing an improvement in unemployment rates. These observations were confirmed through statistical analyses, with stagnation in educational attainment and income trends occurring in rural, peripheral, and demographically shrinking municipalities. Conversely, there is a positive relationship between trends in unemployment rates and population size. The diversity of geographies of economic change demonstrates the need for targeted interventions to mitigate the unique manifestations of decline within communities.
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".