Employers´ paradoxical views about temporary foreign migrant workers´ health: a qualitative study in rural farms in Southern Ontario
Bibliographic record
Abstract
BACKGROUND: The province of Ontario hosts nearly a half of Canada's temporary foreign migrant farm workers (MFWs). Despite the essential role played by MFWs in the economic prosperity of the region, a growing body of research suggests that the workers' occupational safety and health are substandard, and often neglected by employers. This study thus explores farm owners' perceptions about MFWs occupational safety and general health, and their attitudes towards health promotion for their employees. METHODS: Using modified grounded theory approach, we collected data through in-depth individual interviews with farm owners employing MFWs in southern Ontario, Canada. Data were analyzed following three steps (open, axial, and selective coding) to identify thematic patterns and relationships. Nine employers or their representatives were interviewed. RESULTS: Four major overarching categories were identified: employers' dependence on MFWs; their fragmented view of occupational safety and health; their blurring of the boundaries between the work and personal lives of the MFWs on their farms; and their reluctance to implement health promotion programs. The interaction of these categories suggests the complex social processes through which employers come to hold these paradoxical attitudes towards workers' safety and health. There is a fundamental contradiction between what employers considered public versus personal. Despite employers' preference to separate MFWs' workplace safety from personal health issues, due to the fact that workers live within their employers' property, workers' private life becomes public making their personal health a business-related concern. Farmers' conflicting views, combined with a lack of support from governing bodies, hold back timely implementation of health promotion activities in the workplace. CONCLUSIONS: In order to address the needs of MFWs in a more integrated manner, an ecological view of health, which includes the social and psychological determinants of health, by employers is necessary. Employers and other stakeholders should work collaboratively to find a common ground, harnessing expertise and resources to develop more community-based approaches. Further research and continuous dialogue are needed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".