Medical repatriation of migrant farm workers in Ontario: a descriptive analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Approximately 40 000 migrant farm workers are employed annually in Canada through temporary foreign worker programs. Workers experiencing health conditions that prevent ongoing work are normally repatriated to their home country, which raises concerns about human rights and health equity. In this study, we present data on the reasons for medical repatriation of migrant farm workers in Ontario. METHODS: In this retrospective descriptive study, we examined medical repatriation data from Foreign Agricultural Resource Management Services, a non-profit corporation managing the contracts of more than 15 000 migrant farm workers in Ontario annually. We extracted repatriation and demographic data for workers from 2001-2011. Physician volunteers used a validated system to code the reported reasons for medical repatriation. We conducted descriptive analyses of the dominant reasons for repatriation and rates of repatriation. RESULTS: During 2001-2011, 787 repatriations occurred among 170 315 migrant farm workers arriving in Ontario (4.62 repatriations per 1000 workers). More than two-thirds of repatriated workers were aged 30-49 years. Migrant farm workers were most frequently repatriated for medical or surgical reasons (41.3%) and external injuries including poisoning (25.5%). INTERPRETATION: This study provides quantitative health data related to a unique and vulnerable occupational group. Our findings reinforce existing knowledge regarding occupational hazards and health conditions among migrant farm workers. Medical repatriation of migrant farm workers merits further examination as a global health equity concern.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it