Low‐Income Dynamics in Canadian Communities: A Place‐Based Approach
Bibliographic record
Abstract
ABSTRACT Canadian poverty rates have persisted at disappointingly high levels despite almost 15 years of continuous economic growth. The problem is exacerbated by some communities and neighborhoods having exceedingly high poverty, including very high rates for vulnerable demographic groups, such as aboriginals and recent immigrants. We investigate low‐income rates (poverty rates) for 2,400 Canadian “communities” over the 1981–2001 period. By focusing on communities, we fill a void in the related Canadian literature, which tends to focus on individuals, case studies, or more aggregate measures, such as provinces. Our approach allows us to assess the role of place‐based policies. Particular attention is given to communities with differing shares of aboriginal Canadians and recent immigrants. One novel feature is our analysis of both “short‐term” and “long‐term” causes of differential community poverty rates. The results suggest that community low‐income rates are more affected by initial economic conditions in the short term, with certain demographic factors becoming relatively more important in the long run.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.013 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".