Poverty in Canada: An Exploratory Spatial Data Analysis
Bibliographic record
Abstract
A spatial understanding of poverty is crucial in developing appropriate anti-poverty strategies, which should vary across space in light of Canada‟s diverse social geography. By employing exploratory spatial data analysis techniques, including global and local cluster analyses, and inferential spatial regression, this study examines the spatial nature and determinants of poverty across census divisions for the years 1991, 1996, 2001 and 2006. Throughout the 1990s, Canadian poverty was defined by an east-west cleavage, with high poverty in the east and low poverty rates in the west. By 2006 this cleavage was replaced by an emergent urban-rural divide, indicating a new and troubling concentration of poverty in Canada's cities. Poverty rates in both urban and rural Canada are particularly driven by such variables as median household income, female-headed lone-parent families, and, in cities, large immigrant populations. These results point to the importance of defining both people- and place-based antipoverty policies, as well as an increasingly worrisome situation for Canada's urban poor.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.021 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".