Tracking immigrant professionals' experience in Manitoba's labour market
Bibliographic record
Abstract
Our project aims to improve immigrant integration programs by exploring the immigration and settlement process from the perspective of professionals and trades people who are clients of Winnipeg’s Success Skills Centre, an agency that offers employment assistance services to immigrant professionals and skilled workers. We make three observations on the integration experience of immigrant professionals and trades people in the Manitoba labour market. First, recent immigrants to Manitoba through the Provincial Nominee Program (PNP) have been educated and skilled, yet their labour market participation has often been restricted to general labour and entry-level employment. Second, immigration policy sets a minimum amount of money that an adult immigrant has to bring with him or her, resulting in a demand/supply mismatch in the labour market. Finally, employment has not been a fair or effective stepping-stone to integration in the case of visible minority immigrants. Our research indicates that a strict labour market definition of success fails to capture the expectations and real life goals of new immigrants. Key Words: immigration, professional immigrants, workforce, integration, Manitoba
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".