Health, social and legal supports for migrant agricultural workers in France, Italy, Spain, Germany, Canada, Australia and New Zealand: a scoping review
Bibliographic record
Abstract
Introduction: We carried out a scoping review to examine what previous literature can teach us about practices and possibilities for support services for migrant agricultural workers. Methods: Following guidelines for scoping reviews as outlined by Arksey and O'Malley (2005) and further refined by Levac et. al (2010) we conducted searches of several databases and two additional searches to capture regions of focus and more current literature. We used a thematic analysis to generate our themes. Results: Our analysis yielded four key themes: (1) political, economic and legal factors; (2) living and working conditions; (3) facilitators/barriers to navigating services and supports and; (4) potential and existing strategies for social support for migrant agricultural workers. The first two themes pointed more to structural and material conditions that both posed barriers for this population to access supports, but also illustrated vulnerabilities that pointed to the need for a variety of services and protections. Under the third, we highlighted the ways that the design of services and supports, or their degree of accessibility, could shape the level of help available to this population. Lastly, potential and existing strategies for social support discussed in the literature included an emphasis on mental health and wellbeing, occupational health and safety training and documentation, and policy reforms to secure the status and address the precarity of this workforce. Discussion: While research on social support and service provision for migrant agricultural workers is still in its infancy, a strength of this body of work is its attention to macro-level issues that advocate for strategies that address root factors that shape this group's health. Further research is required to expand our understanding of social support roles and possibilities across other domains and sectors for this population.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".