Training ‘expendable’ workers: temporary foreign workers in nursing
Bibliographic record
Abstract
The purpose of this article is to explore the experiences of Temporary Foreign Workers in health care in Alberta, Canada. In 2007–2008, one of the regional health authorities in the province responded to a shortage of workers by recruiting 510 health-care workers internationally; most were trained as Registered Nurses (RNs) in the Philippines. However, the Association of RNs required them to complete an assessment, and in many cases, to complete further training leading to an examination before they could actually work as RNs in the province. Furthermore, economic recession and restructuring of the health authority meant that many of the short-term contracts were not renewed, despite initial promises made by recruiters. This article looks at the assessment of foreign credentials and processes that followed as a part of the vocational education and training system that is often ignored. Drawing on social closure theories, we look at the experiences of foreign workers whose positions are extremely precarious in terms of employment and residency status. Our analysis suggests that the use of temporary workers to address ‘short term’ labour demand has implications for the workers themselves as well as larger political, social and economic implications that need to be acknowledged.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.014 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| 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".