Intersections on the road to skills’ transferability: The role of international training, gender, and visible minority status in shaping immigrant engineers’ career attainment in Canada
Bibliographic record
Abstract
This paper focuses on the engineering profession in Canada, a regulated field with a large proportion of internationally trained professionals. Using Canadian census data, this study addresses two main questions. First, I ask whether immigrant engineers who were trained abroad are at increased disadvantage in gaining access (1) to employment in general, (2) to the engineering field, and (3) to professional and managerial employment within the field. Second, I ask how immigration status and the origin of training intersect with gender and visible minority status to shape immigrant engineers' occupational outcomes. The results reveal that immigrant engineers who were trained abroad are at increased risk of occupational mismatch and this risk is two-fold and intersectional. First, they are at a disadvantage to enter the engineering field. Second, those employed in the engineering field are more likely to occupy technical positions. These forms of disadvantage intensify and diversify for women and racial/ethnic minority immigrants. The paper concludes with a discussion of immigrants' skills transferability in regulated fields from an intersectional perspective.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".