Skilled immigrant labour: country of origin and the occupational locations of male engineers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Do high skill immigrant workers find employment corresponding to their training? Using unpublished data from the 1996 census, we examine the occupational locations of men age 30-54 who have a university degree with a major in engineering. We focus on three groups: Canadian born, foreign born who immigrated before age 19 and the foreign-born arriving after age 27, arguing that the first two are most likely to be educated in Canada whereas the last group is not. We find birth place differences in the percentages who are working in managerial, engineering, technical and all other occupations, with differences being most pronounced for those immigrating after age 27. Multinomial logit analysis confirms that these differences cannot be attributed to differences in measured human capital stock. Accreditation requirements are one likely explanation, particularly for those who have received training outside Canada.
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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 | 0.000 | 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 it