Changing Income Inequality and Immigration in Canada 1980-1995
Bibliographic record
Abstract
While there is a general consensus that income inequality has increased in most developed countries over the last two decades, the analytical focus has been at the national scale. However, these increases in inequality have not been uniform across different segments of society, either in terms of social group or geographic region. In particular, the high levels of immigration to metropolitan Canada have contributed to growing inequality. Using micro-level data on household income from the 1981, 1986, 1991 and 1996 censuses, this paper identifies the role of immigration and its differential impact on metropolitan and non-metropolitan areas. The impacts accelerated during the first half of the 1990s when immigration remained high yet the economy slowed. The evidence suggests that the overall impact of immigration is a relatively short-run phenomenon as recent immigrants take time to adjust to the labour market. If recent immigrants are excluded, inequality is still increasing, but at a slower rate, especially in the largest metropolitan areas.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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 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".