Feature Story: Help Wanted: Researchers seek to uncover the experiences of temporary workers in Saskatchewan
Bibliographic record
Abstract
Saskatchewan has come to depend greatly on temporary foreign workers. Since 2005, the number of migrant workers has risen over 300 per cent in Saskatchewan compared to the national growth rate of 146 per cent. In 2014, approximately 11,000 were working in Saskatchewan with temporary work permits. With this growth, questions emerge as to how well this program is working in the province. Dr. Andrew Stevens aims to find out. Stevens is an Associate Professor in the Faculty of Business and an adjunct in the Department of Sociology at the U of R. He will share some of his latest research at the Faculty of Business Administration’s research seminar April 20 at 11:00 a.m. at the Education Building (boardroom 560). His talk is titled Migrant workers and the maintenance of prairie capitalism in Saskatchewan.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.029 | 0.006 |
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".