Antecedents of Underemployment: Job Search of Skilled Immigrants in Canada
Bibliographic record
Abstract
We investigate factors that skilled immigrants can improve in order to have better job search outcomes, in particular to avoid underemployment. We test an unfolding model which considers barriers faced by skilled immigrants during their job search (language and cultural barriers, and the lack of social support in the receiving country), job search constructs and job search outcomes (including underemployment). We collected data through an online questionnaire and obtained 357 usable responses from skilled immigrants in Canada. The hypotheses were tested with partial least squares (PLS). Language fluency and cultural knowledge were positively related to both job search clarity and job search self‐efficacy. Social support was only related to job search self‐efficacy. Job search clarity was related to job search intensity. Job search intensity was related to the number of interviews, which in turn, was related to the number of job offers. Finally, the number of job offers was negatively related to underemployment. Our paper contributes to the understanding of the job search of skilled immigrants by examining factors that can help them overcome obstacles and obtain better job search outcomes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 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".