Age‐at‐arrival differences in home‐ownership attainment among immigrants and their foreign‐born offspring in Canada
Bibliographic record
Abstract
Abstract This paper asks whether age at arrival matters when it comes to home‐ownership attainment among immigrants, paying particular attention to householders' self‐identification as a visible minority. Combining methods that were developed separately in the immigrant housing and the immigrant offspring literatures, this study shows the importance of recognising generational groups based on age at arrival, while also accounting for the interacting effects of current age (or birth cohorts) and arrival cohorts. The paper advocates a (quasi‐)longitudinal approach to studying home‐ownership attainment among immigrants and their foreign‐born offspring. Analysis of data from the Canadian Census reveals that foreign‐born householders who immigrated as adults in the 1970s and the 1980s are more likely to be home‐owners than their counterparts who immigrated at a younger age when they self‐identify as South Asian or White, but not always so when they self‐identify as Chinese or as ‘other visible minority’. The same bifurcated pattern recurs between householders who immigrated at secondary‐school age and those who were younger upon arrival. Age at arrival therefore emerges as a variable of significance to help explain differences in immigrant housing outcomes, and should be taken into account in future studies of immigrant home‐ownership attainment. Copyright © 2009 John Wiley & Sons, Ltd.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".