Bibliographic record
Abstract
The economic assimilation of immigrants is a key concern for economists and policy makers. The topic has been widely explored in terms of earnings assimilation of immigrants. Using the 1999 Survey of Financial Security, this study attempts to look at the issue from the wealth perspective. Among married families, immigrants have higher wealth than their native-born counterparts from the 40th to 90th percentiles of the distribution, with the wealth gap ranging between $20, 000 and $78, 000. Among single families, immigrants have higher wealth from the 55th to 95th percentiles, with the wealth gap ranging between $14, 000 and $145, 000. At the bottom of the distribution, however, evidence suggests that immigrants have lower wealth, although the gap is generally below $10, 000. Various decomposition results indicate that the age of the major income recipient (and of the spouse for married families) as well as factors affecting permanent income explain a significant portion of the wealth gap in cases where immigrant families have higher wealth than the native-born. At the bottom of the wealth distribution, however, the wealth gap cannot be explained by the age of the major income recipient, permanent income factors, or family size (or lone-parent status), suggesting that low-wealth immigrant families may behave differently than low-wealth Canadian-born families in their wealth accumulation process. The wealth gap is also studied from a cohort perspective. Not surprisingly, recent immigrants have lower wealth than comparable Canadian-born families, and immigrants who arrived before 1976 have higher wealth. While immigrants who arrived in Canada between 1976 and 1985 are widely believed to initially have had more of an earnings disadvantage than their predecessors with respect to the Canadian-born, this study finds that, over the upper segment of the distribution, the wealth of this cohort is not significantly different from that of comparable Canadian-born families. But over the lower portion of the distribution, the cohort has lower wealth.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".