The Homeownership Hierarchies of Canada and the United States: The Housing Patterns of White and Non-White Immigrants of the past Thirty Years
Bibliographic record
Abstract
In this paper two gaps in North American immigrant homeownership research are addressed. The first concerns the lack of studies (especially in Canada) that identify changes in homeownership rates by skin color over time, and the second relates to the shortage of comparative research between Canada and the United States on this topic. In this paper the homeownership levels and attainment rates of Black, Chinese, Filipino, White, and South Asian immigrants are compared in Canada and the United States for 1970/1971–2000/2001. For the most part, greater similarities than differences are found between the two countries. Both Canadian and U.S. Chinese and White immigrants have the highest adjusted homeownership rates of all groups, at times even exceeding comparably positioned native-born households. Black immigrants, on the other hand, tend to have the lowest ownership rates of all groups, particularly in the United States, with Filipinos and South Asians situated between these extremes. Most of these differences stem from disparities that exist at arrival, however, and not from differential advancement into homeownership.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".