2004) Chinese immigrants in Canada: Their changing composition and economic performance, CERIS Working Paper No. 30, Joint Centre of Excellence for Research on Immigration and Settlement
Bibliographic record
Abstract
Using landing records and tax data, this paper examines both the changing composition of the Chinese immigrants in Canada in the past two decades and their levels of economic performance. Our research found that, in addition to a shift in origin, economic immigrants have been on the rise and other classes of immigrants have declined. This has been accompanied by a significant increase in their educational qualifications and proficiency in a Canadian official language. Yet, despite their increased human capital, Chinese immigrants still experience very different economic outcomes in the Canadian labour market compared to members of the general population of Canada. For one thing, they have much lower employment and self-employment income than the general population. Moreover, these earning differentials hold true for all age groups, both genders, and Chinese immigrants from all origins. While their levels of economic performance increases with length of residency in Canada, this study suggests that it would take more than 20 years for Chinese immigrants to close the earning gaps with the general population. Evidence also suggests that Canadian-specific educational credentials are indeed worth more than those acquired in the immigrants ’ country of origin, and are much better remunerated by Canadian employers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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".