Residential Segregation and Socioeconomic Integration of Visible Minorities in Canada
Bibliographic record
Abstract
Using Census data this paper tests the validity of the spatial assimilation model for the visible minorities in the seven largest Metropolitan Areas of Canada. It shows that residential segregation levels for the four largest visible minority groups remain relatively high during the period 1981-2001. Even while there is assimilation of earlier immigrants the large number of new immigrants in recent years have kept the segregation levels high in the cities. It is found that segregation levels have little relation to the absolute size of the minority group or its city proportion, a rather surprising finding. Further, there seems to be no significant relationship between segregation indices and measures of socioeconomic achievement such as education, occupation or income. Visible minority immigrants have much higher level of educational attainment than the other groups. However they are under- represented in managerial occupations and have significantly lower incomes. The Chinese and South Asians seem to do better than the Blacks and much better than the Filipinos. Many visible minority neighbourhoods in Canada are not situated in the city core and do not show the urban blight often associated with Black neighbourhoods in the United States, and raises the question that some amount of spatial concentration and social integration can go together. Some credit for this may be attributable to the Multiculturalism policies of Canadian government.
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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 | 0.000 | 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".